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Electronic Information Technology and Smart Agriculture (ICEITSA), International Conference on

作者： Xian Zhang Pengju Tang Taiguo Qu Yiwen Liu School of Computer Science and Engineering Huaihua University Huaihua China College of Computer Science and Electronic Engineering Hunan University Changsha China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application Hunan Province Universities Huaihua China

ISBN: (纸本)9781665413015

To reduce the upgrade and maintenance cost of embedded devices effectively, according to the requirement of a remote firmware update of embedded devices, this paper proposed a remote online firmware upgrade technology based on ZigBee. Combined with the requirement of remote online firmware upgrade application of the tower top amplifier, this paper analyzes and designs the system requirements, ZigBee module selection, and design the software, fault analysis, and other aspects. Designed Experiments to test the ZigBee connection success rate under the device startup state and normal operation state, the relationship between transmission firmware size and transmission success rate, system CPU resource consumption, transmission distance, transmission rate, and other performance indicators. The experimental results show that the remote online firmware upgrade technology of embedded devices based on ZigBee can better meet the performance requirements of all aspects of the system. The results show that this scheme has the advantages of simplicity, low cost, and high reliability and has a broad application prospect.

关键词： Performance evaluation Costs Codes Poles and towers Zigbee Maintenance engineering Software

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Research on Crop Disaster Stress Risk Mapping System Based on Agriculture Big data

Research on Crop Disaster Stress Risk Mapping System Based o...

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Electronic Information Technology and Smart Agriculture (ICEITSA), International Conference on

作者： Chunqiao Mi Xiaoning Peng Ling Peng Changhua Zhao Xiaowu Deng School of Computer Science and Engineering Huaihua University Huaihua Hunan China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture Huaihua University Huaihua Hunan China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application Hunan Province Universities Huaihua University Huaihua Hunan China

ISBN: (纸本)9781665413015

At present, the research on crop disaster risk is mostly carried out from the perspective of numerical simulation in one factor aspect, and there is a lack of information system practice that can integrate disaster spatio-temporal analysis technologies such as environment characteristic information extraction, geographic data scale transformation, spatial analysis and map visualization. Based on agriculture big data and highlighting the spatial characteristics of crop disasters, in this study a method of crop disaster risk mapping is designed and a prototype system is implemented, which function is composed of agriculture big data cleaning, scale conversion, multi-source data fusion, feature information extraction, risk probability prediction and map visualization. A specific application of the system is also demonstrated by taking the production of thematic map of wind-induced lodging risk probability distribution during maize jointing and tasseling stage as an example, which shows great help for avoiding maize lodging risk in agriculture practice. The research results have a good role in improving the technical level of agriculture disaster mapping and analysis, and improving the efficiency and effect of disaster prevention and reduction in agriculture production. It has important academic significance for promoting the application of big data in agriculture disaster management and establishing a new perspective of crop disaster mapping, and has important practice application value for optimizing the fine zoning of crop planting area and strengthening the accurate management of agriculture disaster risk.

关键词： Crops data visualization Prototypes Production Big data Information retrieval Agriculture

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Performance Analysis of Full-Duplex NOMA Assisted Satellite-Terrestrial Systems with Hardware Impairments and Imperfect CSI

Performance Analysis of Full-Duplex NOMA Assisted Satellite-...

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International Conference on Information, Communication and Networks (ICICN)

作者： Jinlong Zhao Mingming Huo Wanwei Tang Xinwei Yue School of Artificial Intelligence Gansu University of Political Science and Law Lanzhou China School of Electronic and Information Engineering Beihang university Beijing China Archives Center Lanzhou University of Technology Lanzhou China Key Lab of Intelligent Data Information Processing and Control of Hebei Province Tangshan University Tangshan China School of Information and Communication Engineering Beijing Information Science and Technology University Beijing China

ISBN: (纸本)9781665490832

In this paper, we investigate the satellite-terrestrial system employing non-orthogonal multiple access (NOMA) scheme, where a full-duplex (FD) decode-and-forward (DF) relaying assists the user in weak channel condition. The effects of hardware impairments, imperfect channel state information (CSI) and imperfect interference cancellation on system performance are considered. For this setting, we derive the closed-form expressions of the exact and asymptotic outage probabilities as well as delay-limited sum throughput for NOMA users. Numerical results are provided to demonstrate the correctness of theoretical analysis and the superiority of adopting FD NOMA scheme in the proposed system.

关键词： NOMA Interference cancellation Satellites System performance Full-duplex system Probability Throughput

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Statistical Movement Classification based on Gram-Schmidt Transform

Statistical Movement Classification based on Gram-Schmidt Tr...

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Electronic Information Technology and Smart Agriculture (ICEITSA), International Conference on

作者： Changhua Zhao Chunqiao Mi Yuanquan Shi School of Computer Science and Engineering Huaihua University Huaihua Hunan P. R. China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application Hunan Province Universities Huaihua Hunan P. R. China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua Hunan P. R. China

ISBN: (纸本)9781665413015

In this work, a technique for automatic classification of finger motion signals was introduced by using Gram-Schmidt orthonormalization. Because the motion signal has nonlinear and non-stationary processing characteristics, the Gram-Schmidt orthonormalization method is used to analyze the motion signal. By batch processing the high correlation between variables, the classification results are obtained. At the same time, combined with the idea of partial least squares, a new identity measure is proposed to select the best parameters. Finally, SVM is used to classify the movement types of the research objects. According to the test sample records of two finger motion signals (thumb and pinky), the average accuracy is 96.65%. The average accuracy of data activation (thumb and pinky) was 100%. Experiments show that the operation speed of Gram-Schmidt classification method is significantly improved, and it has better interpretability and prediction ability.

关键词： Support vector machines Dimensionality reduction Thumb Transforms Predictive models Time measurement Stability analysis

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A modified iterative algorithm for solving split equality problems

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2021年第3期83卷 45-54页

作者： Fu, Yuanmin Zhu, Li-Jun Wei, Haicheng School of Mathematics and Information Science North Minzu University Yinchuan750021 China The Key Laboratory of Intelligent Information and Big Data Processing of NingXia Province North Minzu University Yinchuan750021 China Health Big Data Research Institute of North Minzu University Yinchuan750021 China Advanced Intelligent Perception Control Technology Innovative Team of NingXia North Minzu University Yinchuan750021 China

In this paper, we investigate the split equality problems in Hilbert spaces. We propose an iterative algorithm with self-adaptive step-size for solving split equality prob-lems. Convergent analysis of the suggested algorithm is proved under some suitable conditions. © 2021, Politechnica University of Bucharest. All rights reserved.

关键词： Iterative methods

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Research on Improved Multiple Users Detection Algorithm in Pattern Division Multiple Access System

SSRN

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SSRN 2022年

作者： Tang, Wanwei Wang, Lixia Wang, Zedai Han, Guofeng Zhao, Jinlong Yue, Xinwei The Key Laboratory of Intelligent Data Information Processing and Control of Hebei Province Tangshan University Tangshan063000 China The School of Engineering Hong Kong University of Science and Technology Hong Kong999077 Hong Kong The Guofeng Han is with the Tangshan employment service center Tangshan human resources and Social Security Bureau Tangshan063000 China The School of Electronic and Information Engineering Beihang University Beijing100191 China The School of Information and Communication Engineering Beijing Information Science and Technology University Beijing100101 China

Receiver detection algorithm has always been a research hotspot in communication system and the key point to determine the performance of 5G system. Both industry and academia have been committed to finding detection algorithms with lower complexity and higher detection performance. This paper will study how to solve the problems of low detection performance and high complexity of classical algorithms. Taking Pattern Division Multiple Access (PDMA) as an example, this paper improves the existing receiver detection algorithms such as Minimum Mean Square Error-Serial Interference Cancellation(MMSE-SIC), Message Passing Algorithm (MPA) and Expectation Propagation Algorithm (EPA), and puts forward corresponding improved algorithms with specific formulas, i.e. Enhanced-MMSE-SIC, Turbo-like MPA (MPA-Turbo) and Turbo-like EPA with hybrid parallel interference cancellation (EPA-Turbo-PIC). Link-level simulation results and analysis show that the proposed improved algorithms have performance advantages over the corresponding traditional algorithms. © 2022, The Authors. All rights reserved.

关键词： Mean square error

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Automatic Fault Diagnosis of Smart Water Meter Based on BP Neural Network

Automatic Fault Diagnosis of Smart Water Meter Based on BP N...

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2020国际计算机前沿大会

作者： Jing Lin Chunqiao Mi School of Computer Science and Engineering Huaihua University Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province

The smart water meter in water supply network can directly affect water production and usage when faults occur. The traditional method of fault detection is inefficient with time lagging, which is not helpful for modernization of water supply system. The capability of automatic fault diagnosis of smart water meter is an important means to improve the service quality of water supply. In this paper, an automatic fault diagnosis method for the smart device is proposed based on BP neural network. And it was applied on Google Tensorflow platform. Fault symptom vectors were constructed using water meter status data and were used to train the neural network model. In order to improve the learning convergence speed and fault classification effect of the network, a method of weighted symptom was also employed. Experimental results show that it has good performance with a general fault diagnosis accuracy of 98.82%.

关键词： Automaticfaultdiagnosis Smartwatermeter BPneuralnetwork Tensorflow

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Design and Implementation of Log data Analysis Management System Based on Hadoop

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Journal of Information Hiding and Privacy Protection 2020年第2期2卷 59-65页

作者： Dunhong Yao Yu Chen School of Computer Science and Engineering Huaihua UniversityHuaihua418000China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua418000China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua418000China School of Computer Science and Engineering Yulin Normal UniversityYulin537000China

With the rapid development of the Internet,many enterprises have launched their network *** users browse,search,and click the products of these platforms,most platforms will keep records of these network behaviors,these records are often heterogeneous,and it is called log *** effectively to analyze and manage these heterogeneous log data,so that enterprises can grasp the behavior characteristics of their platform users in time,to realize targeted recommendation of users,increase the sales volume of enterprises’products,and accelerate the development of ***,we follow the process of big data collection,storage,analysis,and visualization to design the system,then,we adopt HDFS storage technology,Yarn resource management technology,and gink load balancing technology to build a Hadoop cluster to process the log data,and adopt MapReduce processing technology and data warehouse hive technology analyze the log data to obtain the ***,the obtained results are displayed visually,and a log data analysis system is successfully *** has been proved by practice that the system effectively realizes the collection,analysis and visualization of log data,and can accurately realize the recommendation of products by *** system is stable and effective.

关键词： Log data Hadoop data analysis data visualization

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A Study on the Differences of Attitude Learning and Learning Behavior Sequences for University Computer MOOC+ SPOC Course

A Study on the Differences of Attitude Learning and Learning...

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International Conference on Computer Science & Education (ICCSE)

作者： Zhao Changhua Mi Chunqiao School of Computer Science and Engineering Huaihua University Huaihua P. R. China Key Laboratory of Wuling-Mountain Health Big Data Intelligent Processing and Application in Hunan Province Universities Huaihua P. R. China Key Laboratory of Intelligent Control Technology for Wuling-Mountain Ecological Agriculture in Hunan Province Huaihua P. R. China

ISBN: (数字)9781728172675

ISBN: (纸本)9781728172682

The outbreak of COVID-19 make University Computer MOOC+SPOC course face opportunities and challenges. There are some problems in MOOC+SPOC course teaching, such as learners' curiosity decreasing, lack of accomplishment and etc. In order to deal with these problems, this study explores the correlation and differences in the learning behavior sequences of learners with different attitudes to high happiness, medium happiness, and low happiness. Through the learners' comments on University Computer MOOC+SPOC course, the learner's attitude information is tapped. By analyzing learning behavior sequences, this study finds out the degree of learning behavior change of learners with different attitudes. The result of this study can improve the existing University Computer MOOC+SPOC instructional design and promote the learning mode to move towards intelligent personalized adaptive learning.

关键词： Interviews Electronic learning data analysis Encoding Correlation

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An extragradient algorithm for fixed point problems and pseudomonotone equilibrium problems

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2020年第4期82卷 89-96页

作者： Yao, Zhangsong Liou, Yeong-Cheng Zhu, Li-Jun School of Information Engineering Nanjing Xiaozhuang University Nanjing211171 China Department of Healthcare Administration and Medical Informatics Research Center of Nonlinear Analysis and Optimization Kaohsiung Medical University Department of Medical Research Kaohsiung Medical University Hospital Kaohsiung807 Taiwan The Key Laboratory of Intelligent Information and Big Data Processing of NingXia Province and Health Big Data Research Institute Advanced Intelligent Perception and Control Technology Innovative Team of NingXia North Minzu University Yinchuan750021 China

Iterative methods for solving fixed point problems and pseudomonotone equilibrium problems have been considered. An extragradient algorithm has been presnted for finding a common element of the fixed points of pseudocontractive operators and the solutions of pseudomonotone equilibrium problems in Hilbert spaces. Weak convergence result of the suggested algorithm is proved. © 2020, Politechnica University of Bucharest. All rights reserved.

关键词： Iterative methods

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