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Two-Way Neural Network Performance PredictionModel Based onKnowledge Evolution and Individual Similarity

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Computer Modeling in Engineering & Sciences 2024年第2期138卷 1183-1206页

作者： Xinzheng Wang Bing Guo Yan Shen College of Computer Science Sichuan UniversityChengdu610065China School of information Science and Engineering Guilin University of TechnologyGuilin541004China School of Control Engineering Chengdu University of Information TechnologyChengdu610225China

Predicting students’academic achievements is an essential issue in education,which can benefit many stakeholders,for instance,students,teachers,managers,*** with online courses such asMOOCs,students’academicrelateddata in the face-to-face physical teaching environment is usually sparsity,and the sample size is *** makes building models to predict students’performance accurately in such an environment even *** paper proposes a Two-WayNeuralNetwork(TWNN)model based on the bidirectional recurrentneural network and graph neural network to predict students’next semester’s course performance using only theirprevious course *** experiments on a real dataset show that our model performs better thanthe baselines in many indicators.

关键词： Computer education performance prediction deep learning

Non-destructive method of small sample sets for the maize moisture content measurement during filling based on NIRS

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International Journal of Agricultural and Biological Engineering 2024年第4期17卷 236-244页

作者： Tiemin Ma Guangyue Zhang Xue Wang Shujuan Yi Changyuan Wang College of information and Electrical Engineering Heilongjiang Bayi Agricultural UniversityDaqing 163319HeilongjiangChina Daqing Center of Inspection and Testing for Agricultural Products and Processed Products Ministry of Agriculture Daqing 163319HeilongjiangChina Heilongjiang Province Research Center of Ecological Rice Seedling Raising Device and Whole course Mechanized Engineering technology Daqing 163319HeilongjiangChina College of Engineering Heilongjiang Bayi Agricultural UniversityDaqing 163319HeilongjiangChina

In maize breeding,limitations on sampling quantity and associated costs for measuring maize grain moisture during filling are imposed by factors like the planting area of new varieties,maize plant density,effective experimental spikes,and other ***,the conventional method of detecting moisture content in maize grains is slow,damages seeds,and necessitates many sample sets,particularly for high moisture content ***,a strong demand exists for a non-destructive quantitative analysis model of maize moisture content using a small sample set during grain *** Bayes-Merged-Bootstrap(BMB)sample optimization method,which built upon the Bayes-Bootstrap sampling method and the concept of merging,was proposed.A critical concern in dealing with small samples is the relationship between data distribution,minimum sample value,and sample size,which has been thoroughly *** to the Bayes-Bootstrap sample selection method,the BMB method offers distinct advantages in the optimized selection of small samples for non-destructive *** quantitative analysis model for maize grain moisture content was established based on the support vector machine *** demonstrate that when the optimal resampling size is 1000 times or more than the original sample size using the BMB method,the model exhibits strong predictive capabilities,with a determination coefficient(R2)>0.989 and a relative prediction determination(RPD)>*** results of the 3 varieties experiment demonstrate the generality of the ***,it can be applied effectively in practical maize breeding and determining grain moisture content during maize machine harvesting.

关键词： near-infrared spectroscopy moisture content quantitative analysis small samples optimized maize grain during the filling stage

Signal space transform and multidimensional information joint processing for moving target

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Chinese Journal of Acoustics 2024年第1期43卷 23-48页

作者： SHI Yunjia PIAO Shengchun GUO Junyuan ZHANG Liu Acoustic Science and technology Laboratory Harbin Engineering UniversityHarbin 150001 Key Laboratory of Marine information Acquisition and Security(Harbin Engineering University) Ministry of Industry and Information TechnologyHarbin 150001 College of Underwater Acoustic Engineering Harbin Engineering UniversityHarbin 150001

A signal space transform method for detection of line spectrum signals radiated by moving target is *** time-frequency analysis and beamforming processing,a three-dimensional(3D)time-frequency-azimuth signal space is obtained in the array coordinate *** certain target course angle,this 3D signal space is transformed to the time-frequency-relative bearing spectrum signal space in the target coordinate *** theoretical derivation,simulation,and experimental data processing are *** findings demonstrate that the method is capable of converting the target line spectrum signal 3D trajectory to a 2D trajectory on the corresponding slice in the transformed signal space and signal processing gain of multi-dimensional information joint processing is obtained easier than in 3D signal space.

关键词： system. moving transformed

Research on Site Planning of Mobile Communication Network

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Computers, Materials & Continua 2024年第8期80卷 3243-3261页

作者： Jiahan He Guangjun Liang Meng Li KefanYao Bixia Wang Lu Li Department of Computer information and Cyber Security Jiangsu Police InstituteNanjing210000China Engineering Research Center of Electronic Data Forensics Analysis Nanjing210000China Key Laboratory of Digital Forensics Department of Public Security of Jiangsu ProvinceNanjing210000China Basic course Teaching and Research Department Jiangsu Police InstituteNanjing210000China Communication and Signal College Nanjing Railway Vocational and TechnicalNanjing210000China

In this paper,considering the cost of base station,coverage,call quality,and other practical factors,a multi-objective optimal site planning scheme is ***,based on practical needs,mathematical modeling methods were used to establish mathematical expressions for the three sub-objectives of cost objectives,coverage objectives,and quality ***,a multi-objective optimization model was established by combining threshold and traffic volume *** order to reduce the time complexity of optimization,a non-dominated sorting genetic algorithm(NSGA)is used to solve the multi-objective optimization problem of site ***,a strategy for clustering and optimizing weak coverage areas was *** order to avoid redundant neighborhood retrieval during cluster expansion,the Fast Density-Based Spatial Clustering of Applications with Noise(FDBSCAN)clustering method was *** different sub-objectives as the main objectives,this paper obtained the distribution map of weak coverage areas before and after the establishment of new base stations,as well as relevant site planning maps,and provided three planning schemes for different main *** simulation results show that the traffic coverage of the three station planning schemes is above 90%.The change in the main optimization objective will result in a significant difference between the cost of the three solutions and the coverage of weak coverage points.

关键词： Siting of station multi-objective optimization genetic algorithm NSGA general greed FDBSCAN cluster

Reform and Practice of the course“Introduction to Computer Science”in Universities Based on the Cultivation of Computational Thinking and Systematic Abilities

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Journal of Contemporary Educational Research 2024年第7期8卷 197-203页

作者： Kun Zhang Zhengjie Deng Qi Peng Jinyang Zhou Fuyun Li School of information Science and technology Hainan Normal UniversityHaikou 571158Hainan ProvinceChina

Introduction to Computer Science,as one of the fundamental courses in computer-related majors,plays an important role in the cultivation of computer ***,traditional teaching models and content can no longer fully meet the needs of modern information technology *** response to these issues,this article introduces the concept of computational creative thinking,optimizes course content,adopts exploratory teaching methods,and innovates course assessment methods,aiming to comprehensively enhance students’computational thinking and innovative *** continuously improving and promoting this teaching model,it will undoubtedly promote computer education in universities to a new level.

关键词： Introduction to Computer Science Curriculum reform Computational thinking Practice

Identification of banana leaf disease based on KVA and GR-ARNet

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Journal of Integrative Agriculture 2024年第10期23卷 3554-3575页

作者： Jinsheng Deng Weiqi Huang Guoxiong Zhou Yahui Hu Liujun Li Yanfeng Wang College of Electronic information and Physics Central South University of Forestry and TechnologyChangsha 410004China Plant Protection Research Institute Hunan Academy of Agricultural SciencesChangsha 410125China Department of Soil and Water Systems College of Agricultural&Life SciencesUniversity of IdahoMoscow 83844USA College of Systems Engineering National University of Defense TechnologyChangsha 410073China

Banana is a significant crop,and three banana leaf diseases,including Sigatoka,Cordana and Pestalotiopsis,have the potential to have a serious impact on banana *** studies are insufficient to provide a reliable method for accurately identifying banana leaf ***,this paper proposes a novel method to identify banana leaf ***,a new algorithm called K-scale VisuShrink algorithm(KVA)is proposed to denoise banana leaf *** proposed algorithm introduces a new decomposition scale K based on the semi-soft and middle course thresholds,the ideal threshold solution is obtained and substituted with the newly established threshold function to obtain a less noisy banana leaf ***,this paper proposes a novel network for image identification called Ghost ResNeSt-Attention RReLU-Swish Net(GR-ARNet)based on *** this,the Ghost Module is implemented to improve the network's effectiveness in extracting deep feature information on banana leaf diseases and the identification speed;the ResNeSt Module adjusts the weight of each channel,increasing the ability of banana disease feature extraction and effectively reducing the error rate of similar disease identification;the model's computational speed is increased using the hybrid activation function of RReLU and *** model achieves an average accuracy of 96.98%and a precision of 89.31%applied to 13,021 images,demonstrating that the proposed method can effectively identify banana leaf diseases.

关键词： banana leaf diseases image denoising Ghost Module Res Ne St Module Convolutional Neural Networks GR-ARNet

Mitigating Urban Heat Island Effects: A Review of Innovative Pavement Technologies and Integrated Solutions

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Structural Durability & health Monitoring 2024年第5期18卷 525-551页

作者： S.F.Ismael A.H.Alias N.A.Haron B.B.Zaidan Abdulrahman M.Abdulghani Department of Civil Engineering Faculty of EngineeringUniversiti Putra MalaysiaSerdang43400Malaysia Central Region Heavy Civil DivisionGranite ConstructionWoodlandsTexas77381USA SP Jain School of Global Management LidcombeSydneyNSW2141Australia Department of Communication technology and Network Faculty of Computer Science and Information TechnologyUniversiti Putra MalaysiaSerdang43400Malaysia

In this review paper,we present a thorough investigation into the role of pavement technologies in advancing urban *** analysis traverses the historical evolution of these technologies,meticulously evaluating their socio-economic and environmental impacts,with a particular emphasis on their role in mitigating the urban heat island *** evaluation of pavement types and variables inﬂuencing pavement performance to be used in the multi-criteria decision-making(MCDM)framework to choose the optimal pavement application are at the heart of our *** serves to assess a spectrum of pavement options,revealing insights into the most effective and sustainable *** highlighting both the existing challenges and potential innovative solutions within theﬁeld,this paper aims to offer a directional compass for future urban planning and infrastructural *** review not only synthesizes the current state of knowledge but also aims to chart a course for future exploration,emphasizing the critical need for innovative and environmentally sensitive pavement tech-nologies in the creation of resilient and sustainable urban environments.

关键词： Pavement sustainability urban heat island environmental impact of pavements innovative pavement solutions economic and social implications sustainable development in urban areas

The Teaching Reform of“Automatic Control Theory”course

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IJLAI Transactions on Science and Engineering

IJLAI Transactions on Science and Engineering 2024年第3期2卷 19-25页

作者： Rui Yang School of Electronics and Electrical Engineering Zhengzhou University of Science and Technology Zhengzhou450064 China Henan Intelligent information processing and control engineering technology Research Center Zhengzhou 450064 China

Modern control theory course is a compulsory course for automation *** is based on automatic control theory course and plays an important role in teaching *** view of the problems in the teaching of modern control theory,such as abstract content and weak mathematical foundation,this paper puts forward some reform suggestions from the aspects of teaching method,mathematical foundation,and the difference and connection with the course of automatic control theory,in order to improve students’learning interest and teaching *** on the analysis of the teaching status of automatic control theory in School of Electronic and Electrical Engineering of Zhengzhou University of Science and technology,combined with the reform needs of ideological and political needs,teaching methods,assessment and evaluation,this paper puts forward a multi-dimensional curriculum reform with“moral education as the center”and“case type”+“online and offline hybrid”+“ideological and political”*** results have been obtained through practice.

关键词： Automatic control theory Weak mathematical foundation Learning interest Teaching quality

The EM algorithm for ML Estimators under nonlinear inequalities restrictions on the parameters

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Applied Mathematics(A Journal of Chinese Universities) 2019年第4期34卷 393-402页

作者： SHEN Qi-xia MIAO Peng LIANG Yin-shuang Department of Basic course Zhengzhou University of Science and TechnologyZhengzhou 450064China information Engineering School of Zhengzhou Institute of technology Zhengzhou 450044China

One of the most powerful algorithms for obtaining maximum likelihood estimates for many incomplete-data problems is the EM ***,when the parameters satisfy a set of nonlinear restrictions,It is difficult to apply the EM algorithm *** this paper,we propose an asymptotic maximum likelihood estimation procedure under a set of nonlinear inequalities restrictions on the parameters,in which the EM algorithm can be *** this kind of estimation problem is a stochastic optimization problem in the *** make use of methods in stochastic optimization to overcome the difficulty caused by nonlinearity in the given constraints.

关键词： Linear regression Maximum likelihood estimation Nonlinear constraints Asymptotic properties