Evolutionary Algorithm Based Feature Subset Selection for Students Academic Performance Analysis

Educational Data Mining(EDM)is an emergent discipline that concen-trates on the design of self-learning and adaptive approaches.Higher education institutions have started to utilize analytical tools to improve students’grades and retention.Prediction of students’performance is a difficult process owing to the massive quantity of educational data.Therefore,Artificial Intelligence(AI)techniques can be used for educational data mining in a big data environ-ment.At the same time,in EDM,the feature selection process becomes necessary in creation of feature subsets.Since the feature selection performance affects the predictive performance of any model,it is important to elaborately investigate the outcome of students’performance model related to the feature selection techni-ques.With this motivation,this paper presents a new Metaheuristic Optimiza-tion-based Feature Subset Selection with an Optimal Deep Learning model(MOFSS-ODL)for predicting students’performance.In addition,the proposed model uses an isolation forest-based outlier detection approach to eliminate the existence of outliers.Besides,the Chaotic Monarch Butterfly Optimization Algo-rithm(CBOA)is used for the selection of highly related features with low com-plexity and high performance.Then,a sailfish optimizer with stacked sparse autoencoder(SFO-SSAE)approach is utilized for the classification of educational data.The MOFSS-ODL model is tested against a benchmark student’s perfor-mance data set from the UCI repository.A wide-ranging simulation analysis por-trayed the improved predictive performance of the MOFSS-ODL technique over recent approaches in terms of different measures.Compared to other methods,experimental results prove that the proposed(MOFSS-ODL)classification model does a great job of predicting students’academic progress,with an accuracy of 96.49%.

Configuration Synthesis and Grasping Performance Analysis of Multi-Loop Coupling Capture Mechanism for Launch and Recovery of Torpedo-Shaped Autonomous Underwater Vehicle

Research of capture mechanisms with strong capture adaptability and stable grasp is important to solve the problem of launch and recovery of torpedo-shaped autonomous underwater vehicles(AUVs).A multi-loop coupling capture mechanism with strong adaptability and high retraction rate has been proposed for the launch and recovery of torpedo-shaped AUVs with different morphological features.Firstly,the principle of capturing motion retraction is described based on the appearance characteristics of torpedo-shaped AUVs,and the configuration synthesis of the capture mechanism is carried out using the method of constrained chain synthesis.Secondly,the screw theory is employed to analyze the degree of freedom(DoF)of the capture mechanism.Then,the 3D model of the capture mechanism is established,and the kinematics and dynamics simulations are carried out.Combined with the capture orientation requirements of the capture mechanism,the statics and vibration characteristics analyses are carried out.Furthermore,considering the capture process and the underwater working environment,the motion characteristics and hydraulics characteristics of the capture mechanism are analyzed.Finally,a principle prototype is developed and the torpedo-shaped AUVs capture experiment is completed.The work provides technical reserves for the research and development of AUV capture special equipment.

The Impact of Sleep Patterns on Academic Performance and Social Integration among Medical Students

Introduction: The impact of sleep on student life is crucial, particularly for those in demanding fields such as medicine. This study examines the relationships between sleep patterns, academic performance, and social integration among medical students, who often face irregular sleep cycles and sleep deprivation due to rigorous academic demands. Aim: This study aims to assess how sleep issues affect academic achievement and social relationships among medical students. Method: Data were collected from 215 medical students through surveys and academic records. Quantitative data provided insights into sleep quality and academic performance, while qualitative interviews explored the effects of sleep on social interactions. Results: The findings revealed a significant correlation between sleep quality and academic performance, with students reporting better sleep hygiene achieving higher grades. Qualitative data indicated that poor sleep negatively impacts social interactions, leading to feelings of isolation and reduced social participation. Conclusions: The study highlights the importance of promoting good sleep practices in medical schools to enhance academic success and social well-being. Interventions aimed at improving sleep quality may help reduce burnout and improve overall well-being among medical students. Future research should focus on longitudinal studies to better understand the long-term effects of sleep on academic and social outcomes in this population.

Performance Analysis and Optimization of Energy Harvesting Modulation for Multi-User Integrated Data and Energy Transfer

Integrated data and energy transfer(IDET)enables the electromagnetic waves to transmit wireless energy at the same time of data delivery for lowpower devices.In this paper,an energy harvesting modulation(EHM)assisted multi-user IDET system is studied,where all the received signals at the users are exploited for energy harvesting without the degradation of wireless data transfer(WDT)performance.The joint IDET performance is then analysed theoretically by conceiving a practical time-dependent wireless channel.With the aid of the AO based algorithm,the average effective data rate among users are maximized by ensuring the BER and the wireless energy transfer(WET)performance.Simulation results validate and evaluate the IDET performance of the EHM assisted system,which also demonstrates that the optimal number of user clusters and IDET time slots should be allocated,in order to improve the WET and WDT performance.

An Analysis of the Requesting Performance by an EFL Student and Its Pedagogical Implications

The present study investigated one Chinese college learner's requesting performance by analyzing the DCT data produced in four different situations.The results indicated that the learner favored the indirect strategy in all four situations,and was able to produce longer requests with a large portion of external modification.However,the learner lacked sufficient knowledge and ability to control over a wide range of internal modification,relied heavily on external modification,produced lengthy grounders,and failed to show enough sensitivity to imposition variation.

Python Server Page Performance Analysis and Modeling

Today, in the field of computer networks, new services have been developed on the Internet or intranets, including the mail server, database management, sounds, videos and the web server itself Apache. The number of solutions for this server is therefore growing continuously, these services are becoming more and more complex and expensive, without being able to fulfill the needs of the users. The absence of benchmarks for websites with dynamic content is the major obstacle to research in this area. These users place high demands on the speed of access to information on the Internet. This is why the performance of the web server is critically important. Several factors influence performance, such as server execution speed, network saturation on the internet or intranet, increased response time, and throughputs. By measuring these factors, we propose a performance evaluation strategy for servers that allows us to determine the actual performance of different servers in terms of user satisfaction. Furthermore, we identified performance characteristics such as throughput, resource utilization, and response time of a system through measurement and modeling by simulation. Finally, we present a simple queue model of an Apache web server, which reasonably represents the behavior of a saturated web server using the Simulink model in Matlab (Matrix Laboratory) and also incorporates sporadic incoming traffic. We obtain server performance metrics such as average response time and throughput through simulations. Compared to other models, our model is conceptually straightforward. The model has been validated through measurements and simulations during the tests that we conducted.

Video Games and School Performances of Dakar High School Students

The triptych (Smartphones, Video games, adolescents) has imposed itself on the collective consciousness in the form of questioning to the point of becoming a social phenomenon. It thus raises concerns about the uses that adolescents make of it and the effects on their academic performance, which we proposed to study among middle school students from the Dakar academy inspection. Where appropriate, we used mixed methods with the collection techniques of questionnaire survey, semi-structured interviews respectively with middle school students, adults (parents, supervisors, teachers, etc.), participant observation and literature review. Concretely, before accessibility to video games, the middle school students were more idle and well-behaved, watched a lot of TV, played with their brothers and sisters or did household chores. The majority of young people had good, very good or excellent conduct and their averages were fair, fairly good or good. With access to a diverse digital environment, middle school students have passionately turned to video games. As a result, their learning time, concentration and submission to parental injunctions have declined significantly. This situation negatively affected their academic performance and encouraged bad behavior.

Current Status of Key Competencies among Medical Students: A Latent Profile Analysis

The purpose of this study was to understand the overall level of key competencies of medical students and explore the potential profile of key competencies, promoting quality education, and improving the quality talent cultivation in medical colleges. A stratified random sampling method selected 734 medical students from four medical colleges in Chongqing Province of China. A general information questionnaire and a key competencies survey questionnaire were used to conduct the survey. The overall score and scores of each dimension of key competencies were analyzed. Latent profile analysis was conducted to classify the key competencies of medical students and compare the distribution differences of demographic variables among different categories. The results showed that 26% of medical students have never heard of the concept of key competencies, and 59% of them are not familiar with the content related to key competencies. The score of key competencies is 3.66 ± 0.60, with the highest score in the dimension of responsibility and the lowest score in the dimension of humanistic accomplishment. The latent profile analysis classified them into three categories: “low key competencies group (14.71%)”, “medium key competencies group (36.79%)”, and “high key competencies group (48.50%)”. The R3STEP regression analysis results showed statistically significant differences in educational level and whether they served as student cadres among different key competencies categories of medical students. This paper discusses three different potential key competencies categories among medical students, and the overall level of key competencies is relatively good. However, medical students lack a comprehensive and systematic understanding of key competencies. Humanistic accomplishment, healthy living, and practical innovation are the three dimensions with lower scores and should be given more attention. Medical colleges should integrate the concept of key competencies into teaching and implement it in medical practice to cultivate more high-quality medical talents for society.

An Investigation on the Influence of Middle School Students'Grammar Learning Self-efficacy on Their Learning Performance

In middleschool English teaching,grammar instruction has always been an important and challenging aspect.Due to the strong influence of grammar explanation in Chinese,learning English grammar may be affected by negative transfer from their native language,which could pose certain obstacles to English acquisition.Self-efficacy,as a major emotional factor influencing learners'internal regulation strategies,has attracted wide attention from researchers both domestically and internationally for its impact on learning performance.High self-efficacy helps learners develop a more positive mindset towards learning,thereby contributing to improved learning performance.Therefore,this study focuses on investigating the relationship between grammatical self-efficacy and learning performance of English grammar among middle school students.This research contributes to a complementary understanding of grammatical self-efficacy among educators,enhancing their teaching skills,and effectively guiding students to learn English grammar with a more positive and healthy mindset,presenting a future grammar instruction in middle school English teaching.

Optimization and Performance Analysis of Intelligent Video AI Dynamic

In today’s information age,video data,as an important carrier of information,is growing explosively in terms of production volume.The quick and accurate extraction of useful information from massive video data has become a focus of research in the field of computer vision.AI dynamic recognition technology has become one of the key technologies to address this issue due to its powerful data processing capabilities and intelligent recognition functions.Based on this,this paper first elaborates on the development of intelligent video AI dynamic recognition technology,then proposes several optimization strategies for intelligent video AI dynamic recognition technology,and finally analyzes the performance of intelligent video AI dynamic recognition technology for reference.

Performance analysis of U-vertical direct-expansion ground-source heat pump

The performance of a direct-expansion ground-source heat pump（DX GSHP）system is theoretically analyzed.Compared with the conventional ground-source heat pump（GSHP）,the DX GSHP has a lower condensing temperature in the cooling mode and a higher evaporating temperature in the heating mode,and the ground heat exchanger（GHE）in the DX GSHP has a low thermal resistance.Therefore,the coefficient of performance（COP）of the DX GSHP is higher than that of the GSHP.In addition,the system performance of the DX GSHP system is higher than that of the conventional GSHP system because there are no secondary solution loops and water circulating pumps in the DX GSHP system.The experimental energy performance of the DX GSHP system is also investigated based on the actual operational data.The tested DX GSHP system is installed in Xiangtan,China.The U-vertical GHE of the DX GSHP is buried in a water well.The length and the outside nominal diameter of the GHE are 42 m and 12.7 mm,respectively.The experimental results show that the maximum（COP）and the average COP of the DX GSHP system in the heating mode are 5.95 and 4.72,respectively.

SIMULATION AND PERFORMANCE ANALYSIS OF NETWORK ON CHIP ARCHITECTURES

The network on chip（NoC）is used as a solution for the communication problems in a complex system on chip（SoC）design.To further enhance performances,the NoC architectures,a high level modeling and an evaluation method based on OPNET are proposed to analyze their performances on different injection rates and traffic patterns.Simulation results for general NoC in terms of the average latency and the throughput are analyzed and used as a guideline to make appropriate choices for a given application.Finally,a MPEG4 decoder is mapped on different NoC architectures.Results prove the effectiveness of the evaluation method.

A FLEXIBLE SIMULATION TOOL FOR PERFORMANCE ANALYSIS

This paper presents RTSS simulation software with the capability for graphical model building and animation display. The RTSS simulation software consists of three separated parts: the simulation kernel, the model building program and the result post processing program. The RTSS may run in the client/server mode. The main features of the RTSS software are more modular, more flexible and easier to upgrade. RTSS is built on object oriented technology, so it has more flexibility. The RTSS model of a system is an open queueing network. For modeling various data acquisition systems, communication networks and flexible manufacturing systems at different abstraction levels, RTSS has proven to be an extremely useful tool for performance analysis.

Performance analysis in 3G/ad hoc integrated network

An analytical approach to evaluate the performance of the 3G/ad hoc integrated network is presented. A channel model capturing both path loss and shadowing is applied to the analysis so as to characterize power falloff vs. distance. The 3G/ad hoc integrated network scenario model is introduced briefly. Based on this model, several performances of the 3G/ ad hoc integrated network in terms of outage probability, call dropping probability and new call blocking probability are evaluated. The corresponding performance formulae are deduced in accordance with the analytical models. Meanwhile, the formula of the 3G/ad hoc integrated network capacity is deduced on the basis of the formula of the outage probability. It is observed from extensive simulation and numerical analysis that the 3G/ad hoc integrated network remarkably outperforms the 3G network with regards to the network performance. This derived evaluation approach can be applied into planning and optimization of the 3G/ad hoc network.

On Students' Self-Evaluation and Class Performance——An Empirical Study in College English Class

This paper aims to demonstrate whether students'self-evaluations influence their class performance.A questionnaire is designed and data is collected from 30 sophomore students in English class.The data analysis shows that students who have positive self-evaluation perform better and get higher class performance scores than students who have negative self-evaluation.

A Stacking Machine Learning Model for Student Performance Prediction Based on Class Activities in E-Learning

After the spread of COVID-19,e-learning systems have become crucial tools in educational systems worldwide,spanning all levels of education.This widespread use of e-learning platforms has resulted in the accumulation of vast amounts of valuable data,making it an attractive resource for predicting student performance.In this study,we aimed to predict student performance based on the analysis of data collected from the OULAD and Deeds datasets.The stacking method was employed for modeling in this research.The proposed model utilized weak learners,including nearest neighbor,decision tree,random forest,enhanced gradient,simple Bayes,and logistic regression algorithms.After a trial-and-error process,the logistic regression algorithm was selected as the final learner for the proposed model.The results of experiments with the above algorithms are reported separately for the pass and fail classes.The findings indicate that the accuracy of the proposed model on the OULAD dataset reached 98%.Overall,the proposed method improved accuracy by 4%on the OULAD dataset.

Application of Formative Assessment to Improve Art Students’Oral Eng lish Performance

This paper focuses on the advantages of formative assessment and explores a better application of it in English class to facilitate art students’learning and further improve their oral English performance.

Power Allocation and Performance Analysis of the Collaborative NOMA Assisted Relaying Systems in 5G

Serving multiple cell-edge mobile terminals poses multifaceted challenges due to the increased transmission power and interferences, which could be overcome by relay communications. With the recent advancement of 5G technologies, non-orthogonal multiple access(NOMA) has been used at relay node to transmit multiple messages simultaneously to multiple cell-edge users. In this paper, a Collaborative NOMA Assisted Relaying(CNAR) system for 5G is proposed by enabling the collaboration of source-relay(S-R) and relay-destination(R-D) NOMA links. The relay node of the CNAR decodes the message for itself from S-R NOMA signal and transmits the remaining messages to the multiple cell-edge users in R-D link. A simplified-CNAR(S-CNAR) system is then developed to reduce the relay complexity. The outage probabilities for both systems are analyzed by considering outage behaviors in S-R and R-D links separately. To guarantee the data rate, the optimal power allocation among NOMA users is achieved by minimizing the outage probability. The ergodic sum capacity in high SNR regime is also approximated. Our mathematical analysis and simulation results show that CNAR system outperforms existing transmission strategies and S-CNAR reaches similar performance with much lower complexity.

Feasibility and Path Analysis of Integrating Innovation and Entrepreneurship Education into“One-Stop”Student Communities

The“one-stop”student community provides new support for innovation and entrepreneurship education in universities.Integrating innovation and entrepreneurship education into the“one-stop”student community work enriches course materials,integrates teacher resources,improves students’participation in innovation and entrepreneurship,and solves problems such as low student participation,lack of course resources,insufficient teacher resources,and single evaluation methods in traditional classrooms.Through various means such as exploring course resources,innovating management models,and strengthening team construction,the role of“one-stop”student communities in innovation and entrepreneurship education has been fully utilized,promoting the development of innovation and entrepreneurship education.

Vibration Performance Analysis of a Mining Vehicle with Bounce and Pitch Tuned Hydraulically Interconnected Suspension

The current investigations primarily focus on using advanced suspensions to overcome the tradeo design of ride comfort and handling performance for mining vehicles. It is generally realized by adjusting spring sti ness or damping parameters through active control methods. However, some drawbacks regarding control complexity and uncertain reliability are inevitable for these advanced suspensions. Herein, a novel passive hydraulically interconnected suspension(HIS) system is proposed to achieve an improved ride-handling compromise of mining vehicles. A lumped-mass vehicle model involved with a mechanical–hydraulic coupled system is developed by applying the free-body diagram method. The transfer matrix method is used to derive the impedance of the hydraulic system, and the impedance is integrated to form the equation of motions for a mechanical–hydraulic coupled system. The modal analysis method is employed to obtain the free vibration transmissibilities and force vibration responses under di erent road excitations. A series of frequency characteristic analyses are presented to evaluate the isolation vibration performance between the mining vehicles with the proposed HIS and the conventional suspension. The analysis results prove that the proposed HIS system can e ectively suppress the pitch motion of sprung mass to guarantee the handling performance, and favorably provide soft bounce sti ness to improve the ride comfort. The distribution of dynamic forces between the front and rear wheels is more reasonable, and the vibration decay rate of sprung mass is increased e ectively. This research proposes a new suspension design method that can achieve the enhanced cooperative control of bounce and pitch motion modes to improve the ride comfort and handling performance of mining vehicles as an e ective passive suspension system.