Efficient Intelligent E-Learning Behavior-Based Analytics of Student’s Performance Using Deep Forest Model

E-learning behavior data indicates several students’activities on the e-learning platform such as the number of accesses to a set of resources and number of participants in lectures.This article proposes a new analytics systemto support academic evaluation for students via e-learning activities to overcome the challenges faced by traditional learning environments.The proposed e-learning analytics system includes a new deep forest model.It consists of multistage cascade random forests with minimal hyperparameters compared to traditional deep neural networks.The developed forest model can analyze each student’s activities during the use of an e-learning platform to give accurate expectations of the student’s performance before ending the semester and/or the final exam.Experiments have been conducted on the Open University Learning Analytics Dataset(OULAD)of 32,593 students.Our proposed deep model showed a competitive accuracy score of 98.0%compared to artificial intelligence-based models,such as ConvolutionalNeuralNetwork(CNN)and Long Short-TermMemory(LSTM)in previous studies.That allows academic advisors to support expected failed students significantly and improve their academic level at the right time.Consequently,the proposed analytics system can enhance the quality of educational services for students in an innovative e-learning framework.

An attention-based teacher-student model for multivariate short-term landslide displacement prediction incorporating weather forecast data

Predicting the displacement of landslide is of utmost practical importance as the landslide can pose serious threats to both human life and property.However,traditional methods have the limitation of random selection in sliding window selection and seldom incorporate weather forecast data for displacement prediction,while a single structural model cannot handle input sequences of different lengths at the same time.In order to solve these limitations,in this study,a new approach is proposed that utilizes weather forecast data and incorporates the maximum information coefficient(MIC),long short-term memory network(LSTM),and attention mechanism to establish a teacher-student coupling model with parallel structure for short-term landslide displacement prediction.Through MIC,a suitable input sequence length is selected for the LSTM model.To investigate the influence of rainfall on landslides during different seasons,a parallel teacher-student coupling model is developed that is able to learn sequential information from various time series of different lengths.The teacher model learns sequence information from rainfall intensity time series while incorporating reliable short-term weather forecast data from platforms such as China Meteorological Administration(CMA)and Reliable Prognosis(https://rp5.ru)to improve the model’s expression capability,and the student model learns sequence information from other time series.An attention module is then designed to integrate different sequence information to derive a context vector,representing seasonal temporal attention mode.Finally,the predicted displacement is obtained through a linear layer.The proposed method demonstrates superior prediction accuracies,surpassing those of the support vector machine(SVM),LSTM,recurrent neural network(RNN),temporal convolutional network(TCN),and LSTM-Attention models.It achieves a mean absolute error(MAE)of 0.072 mm,root mean square error(RMSE)of 0.096 mm,and pearson correlation coefficients(PCCS)of 0.85.Additionally,it exhibits enhanced prediction stability and interpretability,rendering it an indispensable tool for landslide disaster prevention and mitigation.

Preceptors'experiences in guiding nursing students to use research findings and to implement evidence-based practice

Objective:Evidence-based practices(EBPs)have been taught to students by identifying the best evidence/evidence from research results.However,the experiences of Indonesian nurse preceptors in helping students implement research findings have not been explored thoroughly.This study aimed to explore Indonesian nurse preceptors in guiding nursing students to use research findings.Methods:This study used interpretive phenomenology analysis that involves 9 nurse preceptors from hospitals in West Kalimantan,Indonesia.Semi-structured in-depth interviews were recorded and then transcribed verbatim.Results:Three themes were generated during the analysis:“types of student supervision,”“issues during supervision,”and“the need for research literacy and supervision.”Conclusions:Nurse preceptors need support to supervise the nursing students to use research findings.In addition to upgrading nursing skills,nurse preceptors must receive training in research and its utilization.Developing an appropriate strategy to assist students in using research findings will enhance the promotion of evidence-based nursing practices on a daily basis.

Synergistic effect of carbon nanotube and encapsulated carbon layer enabling high-performance SnS_2-based anode for lithium storage

Tin disulfide(SnS_(2)),due to large interlayer spacing and high theoretical capacity,is regarded as a prospective anode material for lithium-ion batteries.Nevertheless,the poor electron conductivity of SnS_(2) and huge volumetric change during the lithiation/delithiation process lead to a rapid capacity decay of the battery,hindering its commercialization.To address these issues,herein,SnS_(2) is in-situ grown on the surface of carbon nanotubes(CNT)and then encapsulated with a layer of porous amorphous carbon(CNT/SnS_(2)@C)by simple solvothermal and further carbonization treatment.The synergistic effect of CNT and porous carbon layer not only enhances the electrical co nductivity of SnS_(2) but also limits the huge volumetric change to avoid the pulverization and detachment of SnS_(2).Density functional theo ry calculations show that CNT/SnS_(2)@C has high Li^(+)adsorption and lithium storage capacity achieving high reaction kinetics.Consequently,cells with the CNT/SnS_(2)@C anode exhibit a high lithium storage capacity of 837mAh/g after 100 cycles at 0.1 A/g and retaining a capacity of 529.8 mAh/g under 1.0 A/g after 1000 cycles.This study provides a fundamental understanding of the electrochemical processes and beneficial guidance to design high-performance SnS_(2)-based anodes for LIBs.

High-temperature BaTiO_(3) -based ceramic capacitors by entropy engineering design

High-performance BaTiO_(3)(BTO)-based dielectric ceramics have great potential for high-power energy storagedevices. However, its poor temperature reliability and stability due to its low Curie temperature impedes the development ofmost electronic applications. Herein, a series of BTO-based ceramics are designed and prepared on the basis of entropyengineering. Owing to the incorporation of Bi(Mg_(0.5)Ti_(0.5))O_(3), relaxation behavior and low dielectric loss at high temperatureshave been achieved. Moreover, the high-entropy strategy also promotes lattice distortion, grain refinement and excellentresistance, which together increase the breakdown field strength. These simultaneous effects result in outstanding energystorage performance, ultimately achieving stable energy density (U_(e)) of 5.76 J·cm^(−3) and efficiency ( η) of 89%. Mostimportantly, the outstanding temperature stability makes high-entropy BTO-based ceramics realize a significant energystorage density of 4.90 0.14 J·cm^(−3) with the efficiency above 89%, spanning a wide temperature range of 25–250 ℃, aswell as cycling reliability with negligible performance deterioration after 3 105 cycles at 300 kV∙cm^(−1) and 200 ℃. Thisresearch presents an effective method for designing temperature-stable and reliable dielectrics with comprehensive energystorage performance.

Promoting Ethical Sensitivity in Nursing Education:A Systematic Review of Case Study-Based Health Education

Introduction: Nursing ethical sensitivity refers to a nurse’s capacity for thoughtful consideration of ethical issues when faced with dilemmas. In the nursing domain, ethical dilemmas arise when nurses face challenges in making sound ethical decisions during clinical practice. These challenges may stem from conflicts between personal values and professional responsibilities. Methodology: Articles downloaded from Pub Med, CNKI, and Google Scholar were reviewed. Results: After rigorous screening, a meticulous analysis was conducted, encompassing 10 articles and involving a substantial cohort of 2863 participants. Existing literature revealed variations in the ethical dilemmas faced by nurses across different departments. The ethical sensitivity of nurses also varies, with higher ethical sensitivity correlating with stronger empathetic abilities. Zhen et al. classified the causes of ethical dilemmas into four main categories: (1) Ethical dilemmas arising from personal reasons of nursing students;(2) Ethical dilemmas stemming from the actions of teachers;(3) Ethical dilemmas triggered by patients;(4) Ethical dilemmas resulting from miscellaneous reasons. Conclusion: According to literature findings, nursing ethical sensitivity was positively linked to the nurse’s ethical decision-making ability. A case study-oriented teaching program has proven effective in enhancing ethical sensitivity among nursing students.

A Feature Learning-Based Model for Analyzing Students’ Performance in Supportive Learning

Supportive learning plays a substantial role in providing a quality edu-cation system.The evaluation of students’performance impacts their deeper insight into the subject knowledge.Specifically,it is essential to maintain the baseline foundation for building a broader understanding of their careers.This research concentrates on establishing the students’knowledge relationship even in reduced samples.Here,Synthetic Minority Oversampling TEchnique(SMOTE)technique is used for pre-processing the missing value in the provided input dataset to enhance the prediction accuracy.When the initial processing is not done substantially,it leads to misleading prediction accuracy.This research concentrates on modelling an efficient classifier model to predict students’perfor-mance.Generally,the online available student dataset comprises a lesser amount of sample,and k-fold cross-validation is performed to balance the dataset.Then,the relationship among the students’performance(features)is measured using the auto-encoder.The stacked Long Short Term Memory(s-LSTM)is used to learn the previous feedback connection.The stacked model handles the provided data and the data sequence for understanding the long-term dependencies.The simula-tion is done in the MATLAB 2020a environment,and the proposed model shows a better trade-off than the existing approaches.Some evaluation metrics like pre-diction accuracy,sensitivity,specificity,AUROC,F1-score and recall are evalu-ated using the proposed model.The performance of the s?LSTM model is compared with existing approaches.The proposed model gives 89% accuracy,83% precision,86%recall,and 87%F-score.The proposed model outperforms the existing systems in terms of the earlier metrics.

Ensemble Deep Learning Framework for Situational Aspects-Based Annotation and Classification of International Student’s Tweets during COVID-19

As the COVID-19 pandemic swept the globe,social media plat-forms became an essential source of information and communication for many.International students,particularly,turned to Twitter to express their struggles and hardships during this difficult time.To better understand the sentiments and experiences of these international students,we developed the Situational Aspect-Based Annotation and Classification(SABAC)text mining framework.This framework uses a three-layer approach,combining baseline Deep Learning(DL)models with Machine Learning(ML)models as meta-classifiers to accurately predict the sentiments and aspects expressed in tweets from our collected Student-COVID-19 dataset.Using the pro-posed aspect2class annotation algorithm,we labeled bulk unlabeled tweets according to their contained aspect terms.However,we also recognized the challenges of reducing data’s high dimensionality and sparsity to improve performance and annotation on unlabeled datasets.To address this issue,we proposed the Volatile Stopwords Filtering(VSF)technique to reduce sparsity and enhance classifier performance.The resulting Student-COVID Twitter dataset achieved a sophisticated accuracy of 93.21%when using the random forest as a meta-classifier.Through testing on three benchmark datasets,we found that the SABAC ensemble framework performed exceptionally well.Our findings showed that international students during the pandemic faced various issues,including stress,uncertainty,health concerns,financial stress,and difficulties with online classes and returning to school.By analyzing and summarizing these annotated tweets,decision-makers can better understand and address the real-time problems international students face during the ongoing pandemic.

HIV Counseling and Testing Uptake,Knowledge and Attitude and Influencing Factors among Student Nurses and Midwives in The Gambia:An Institutional-based Cross-sectional Study

HIV counseling and testing(HCT)has become paramount in the prevention and control of HIV/AIDS worldwide.However,the uptake of HCT has been very slow globally,especially in sub-Saharan Africa.Student nurses formed the largest group undergoing health care training in the country compared to doctors and other health cadres.According to WHO,they are part of the most vulnerable group to HIV infection,judging by the fact that they interact more with patients/clients than other healthcare professionals.This study aimed to determine the prevalence of HCT uptake,knowledge,and attitude and evaluate influencing factors among student nurses and midwives in public nursing schools.An institutional-based cross-sectional study design was employed to collect data from 305 randomly selected nursing students and midwives using a validated and reliable self-administered questionnaire.Descriptive statistics(percentages,mean and standard deviation)and inferential statistics(chi square,logistics regression,one-way ANOVA and independent samples t-test)were used for data analysis using SPSS version 25.0.A p-value<0.05 was considered for statistical significance.Out of the 305 students recruited for the study,60.98%were females,with a mean age of 25.5 years old.About 58.4%of the participants had tested for HIV in the past.About 95.7%acknowledged the importance of HCT in the prevention and control of HIV/AIDS.HCT uptake among student nurses and midwives was influenced by factors ranging from an individual that are interpersonal challenges(such as concerns of friends),perceived susceptibility to the disease,lack of confidentiality,stigma and discrimination from health service providers.Therefore,these barriers can be addressed through an organized targeted health education intervention and advocacy programs across health training institutions in the Gambia and beyond.

The Effect of Inquiry-Based Learning Strategy on EFL Tenth-Grade Students’ Reading Comprehension

This study examined the potential effect of Inquiry-Based Learning Strategy(IBL)on the tenth-grade students’reading comprehension.Two groups and a quasi-experimental design were used.Two complete sections of grade 10 students from a public Secondary School for Girls in Irbid was randomly assigned by the researcher.The experimental group of 30 students was chosen first,and then the control group of 30 students.A pre-post reading comprehension test was designed before and after the study in order to fulfill its goals.Additionally,the experimental group was taught using the IBL strategy,whereas the control group was taught using the traditional teaching methods recommended in the tenth-grade Teacher’s Book.According to the findings,there were significant statistical differences favoring the experimental group over the control group.In light of the findings,the researcher recommended employing the IBL strategy to students with various levels and EFL skills.

扩展目标跟踪Student’s t逆Wishart平滑算法

脉冲干扰和离群量测信息等因素通常会导致异常的厚尾噪声,这使得以高斯假设为前提的扩展目标跟踪(ETT)估计器的性能急剧降低,针对该问题该文提出一种基于扩展目标随机矩阵模型(RMM)的Student’s t逆Wishart平滑(StIWS)算法。首先,将目标的运动状态以及过程噪声和量测噪声建模为Student’s t分布以表征异常噪声对扩展目标概率分布的影响,将目标扩展状态建模为服从逆Wishart分布的随机矩阵。然后,在Student’s t贝叶斯平滑框架下,详细推导了能在扩展目标的多重特征动态演变的过程中有效估计目标状态的StIWS算法。最后,通过扩展目标跟踪的仿真实验结果和真实场景实验结果验证了所提算法的有效性。

Corpus-based Study on the use of "really" in Chinese Students' Writing

This corpus-based study aims to explore if the high frequently used word "really" is at a risk of overused,underused or misused in the writing of Chinese learners.Then draw attention on English learning and teaching and raise learners' awareness of the structural and collocation complexity of words.

Consideration on Vocational Students' Participation in Class:With Special Reference to Task-based Approach and Traditional Method

This paper covers an experimental study on vocational students' participation in the class under task-based approach and traditional grammar-translation teaching method.As vocational colleges in China have developed rapidly,teachers are still exploring and experimenting with different teaching approaches in order to find the suitable one(s).Using the theory of task-based approach,the grammartranslation method,the author conducts an experiment by recording.The following key issue has been addressed and some conclusive results have been made.The paper intends to find an answer to the following question:Under which teaching approach can students participate in the class more actively? Based on the above research work,the following result has been reached:Task-based approach can promote students' mastering of vocabulary and grammar,and students participate in the class more actively.The author would like to share her experiences with others in pedagogical studies of teaching vocational college students English.

Correlates of Condom-use Self-efficacy on the EPPM-based Integrated Model among Chinese College Students

Objective To explore the predictors of condom-use self-efficacy in Chinese college students according to the extended parallel process model （EPPM）-based integrated model. Methods A total of 3,082 college students were anonymously surveyed through self-administered questionnaires in Guangzhou and Harbin, China. A structural equation model was applied to assess the integrated model. Results Among the participants, 2,387 （46.7%） were male, 2,586 （53.3%） were female, and the average age was 18.6 years. The final integrated model was acceptable. Apart from the direct effect （r = 0.23）, perceived severity had two indirect effects on condom-use self-efficacy through the attitude to HIV education （r = 0.40） and intention to engage in premarital sex （r = -0.16）, respectively. However, the perceived susceptibility mediated through the intention to engage in premarital sex （intent-to-premarital-sex） had a poor indirect impact on condom-use self-efficacy （total effect was -0.06）. Furthermore, attitude toward HIV health education （r = 0.49） and intent-to-premarital-sex （r = -0.32） had a strong direct effect on condom-use self-efficacy. In addition, male students perceived higher susceptibility, stronger intent-to-premarital-sex, and lower condom-use self-efficacy than female students. Conclusion The integrated model may be used to assess the determinants of condom-use self-efficacy among Chinese college students. Future research should focus on raising the severity perception, HIV-risk-reduction motivation, and the premarital abstinence intention among college students. Furthermore, considering the gender differences observed in the present survey, single-sex HIV education is required in school-based HIV/sex intervention.

First-principles study of moderate phonon-mediated pairing in high-pressure monoclinic phase of BiS_(2)-based superconductors

Isotope effect on superconductive transition temperature(T_c)is an essential indicator to examine whether the mechanism of superconductors is conventional.Unconventional isotope effect of BiS_(2)-based superconductors has been previously reported in ambient-pressure tetragonal phase.However,to comprehensively ascertain the nature of superconductivity,the investigation of BiS_(2)-based system in high-pressure structure is highly desirable.In this work,we carried out the first-principles calculations of phonon spectra and superconductivity in high-pressure monoclinic phase of LaO_(0.5)F_(0.5)BiS_(2)with ^(32)S and ^(34)S,and observed that the corresponding isotope coefficient is 0.13≤α≤0.20.This value is much greater than that of BiS_(2)-based superconductors in ambient-pressure phase,but slightly smaller than that of conventional MgB_2.Taking into account the calculated T_(c) lower than experimental results,we finally conclude that the moderate phonon-mediated pairing plays a significant role in forming superconductivity of BiS_(2)-based system in high-pressure phase,moreover,the cooperative multiple paring interactions should also be considered.

Fuzzy-Based Sentiment Analysis System for Analyzing Student Feedback and Satisfaction

The feedback collection and analysis has remained an important subject matter for long.The traditional techniques for student feedback analysis are based on questionnaire-based data collection and analysis.However,the student expresses their feedback opinions on online social media sites,which need to be analyzed.This study aims at the development of fuzzy-based sentiment analysis system for analyzing student feedback and satisfaction by assigning proper sentiment score to opinion words and polarity shifters present in the input reviews.Our technique computes the sentiment score of student feedback reviews and then applies a fuzzy-logic module to analyze and quantify student’s satisfaction at the fine-grained level.The experimental results reveal that the proposed work has outperformed the baseline studies as well as state-of-the-art machine learning classifiers.

Rational design of MoS_(2)-based catalysts toward lignin hydrodeoxygenation:Interplay of structure,catalysis,and stability

The MoS_(2)-based materials are a vital class of heterogeneous catalysts for the hydrodeoxygenation of lignin and its model compounds to produce value-added chemicals especially because of their unique selectivity to aromatics.The rational design of MoS_(2)-based catalyst greatly depends on the comprehensive understanding of its structure-activity relationship.However,an intensive summary and critical analysis are still scarce to date.In this review,we attempt to provide an in-depth understanding of the interplay of structure,catalysis,and stability of MoS_(2)-based catalysts for lignin hydrodeoxygenation.The recognition of intrinsic active sites on MoS_(2) structure was firstly discussed,followed by the illustration of MoS_(2)-catalyzed hydrodeoxygenation structural models.Afterward,based on the studies on the MoS_(2)-catalyzed lignin model compounds hydrodeoxygenation,the current active site modification strategies including structural modification of monometallic MoS_(2) catalysts and collaborative modification were summarized and emphatically discussed,which aims to elucidate the structure-activity relationship at the atomic-level.The deactivation mechanism and stabilization strategies were also illustrated to provide instructive suggestion for the rational design of efficient and stable MoS_(2)-based catalysts.Finally,the real lignin depolymerization over MoS_(2)-based catalysts was summarized to point out the advantages and difficulties.This review attempts to highlight the remaining challenges and provide some perspectives for the future development of MoS_(2)-based catalysts for lignin hydrodeoxygenation.

Frequency and associated factors of accommodation and non-strabismic binocular vision dysfunction among medical university students

AIM:To investigate the frequency and associated factors of accommodation and non-strabismic binocular vision dysfunction among medical university students.METHODS:Totally 158 student volunteers underwent routine vision examination in the optometry clinic of Guangxi Medical University.Their data were used to identify the different types of accommodation and nonstrabismic binocular vision dysfunction and to determine their frequency.Correlation analysis and logistic regression were used to examine the factors associated with these abnormalities.RESULTS:The results showed that 36.71%of the subjects had accommodation and non-strabismic binocular vision issues,with 8.86%being attributed to accommodation dysfunction and 27.85%to binocular abnormalities.Convergence insufficiency(CI)was the most common abnormality,accounting for 13.29%.Those with these abnormalities experienced higher levels of eyestrain(χ2=69.518,P<0.001).The linear correlations were observed between the difference of binocular spherical equivalent(SE)and the index of horizontal esotropia at a distance(r=0.231,P=0.004)and the asthenopia survey scale(ASS)score(r=0.346,P<0.001).Furthermore,the right eye's SE was inversely correlated with the convergence of positive and negative fusion images at close range(r=-0.321,P<0.001),the convergence of negative fusion images at close range(r=-0.294,P<0.001),the vergence facility(VF;r=-0.234,P=0.003),and the set of negative fusion images at far range(r=-0.237,P=0.003).Logistic regression analysis indicated that gender,age,and the difference in right and binocular SE did not influence the emergence of these abnormalities.CONCLUSION:Binocular vision abnormalities are more prevalent than accommodation dysfunction,with CI being the most frequent type.Greater binocular refractive disparity leads to more severe eyestrain symptoms.

Ferroelectricity of hafnium oxide-based materials:Current status and future prospects from physical mechanisms to device applications

The finding of the robust ferroelectricity in HfO_(2)-based thin films is fantastic from the view point of both the fundamentals and the applications.In this review article,the current research status of the future prospects for the ferroelectric HfO_(2)-based thin films and devices are presented from fundamentals to applications.The related issues are discussed,which include:1)The ferroelectric characteristics observed in HfO_(2)-based films and devices associated with the factors of dopant,strain,interface,thickness,defect,fabrication condition,and more;2)physical understanding on the observed ferroelectric behaviors by the density functional theory(DFT)-based theory calculations;3)the characterizations of microscopic and macroscopic features by transmission electron microscopes-based and electrical properties-based techniques;4)modeling and simulations,5)the performance optimizations,and 6)the applications of some ferroelectric-based devices such as ferroelectric random access memory,ferroelectric-based field effect transistors,and the ferroelectric tunnel junction for the novel information processing systems.

Attitude of nursing students towards Internet-based nursing services for the aged

Objective To investigate the attitude,willingness,and motivation of third-year undergraduate nursing students from a university of Chinese medicine toward Internet-based nursing services for the aged(IBNSA),providing a reference for its development and related nursing education.Methods This study was conducted from March to April 2019.Using a self-designed questionnaire,this cross-sectional study comprised 508 third-year undergraduate nursing students from a university of Chinese medicine.The questionnaire was divided into two parts.The first part contained the general information of nursing students.The second part investigated nursing students’attitudes,willingness,and motivation towards IBNSA(a total of seven questions).Results Of the 508 nursing students,314(61.81%)expressed support for the IBNSA,44(8.66%)expressed disapproval.Regarding career choice,279(54.92%)were willing to choose IBNSA,51(10.04%)were unwilling.The top three motivations for choosing IBNSA as a nursing student career were increased income,high autonomy and flexibility,and good job prospects.On the contrary,the top three reasons not to choose this option were safety concerns,lack of time and energy,and unwillingness to undertake elderly care.Experience with community activities or a part-time job,experience with elderly care,willing to choose the nursing profession,willing to engage in nursing care after graduation,and willing to engage in nursing for elderly patients after graduation were significantly associated with the motivation of nursing students to participate in IBNSA(P<0.05).Conclusion The majority of nursing students have a positive attitude towards IBNSA and are willing to choose it as their future career.Nurses’and patients’safety guarantees and salary distribution were critical factors influencing their choice.Nursing schools should pay attention to the concerns of nursing students,constantly improve the management system of IBNSA,strengthen safety education,and provide professional knowledge and skills to improve the quality of personnel training.