A study on service quality evaluation of digital libraries in China based on tetra-class model

Purpose: This study intends to evaluate the service quality of academic digital libraries(DLs)in China. By utilizing tetra-class model which concentrates on categorizing services according to their contributions to user satisfaction, this paper attempts to visually categorize the specific DL service elements to reveal their present performances, and then further explain the categorizing variations among different groups of users to discover the user preference.Design/methodology/approach: This paper carries out a survey to evaluate user experience on 27 typical DL services summarized from our investigations of representative Chinese university DLs. Based on the five-point Likert-type scale evaluation, the users’ attitudes toward specific service element are divided into negative and positive dimensions. Afterwards,a correspondence analysis is applied to calculate the contributions to satisfaction and dissatisfaction of each service element based on tetra-class model. As a result, the DL service elements of Chinese academic libraries are classified into four categories(i.e. Basic, Secondary,Plus, and Key). Finally, we compared the categorizing variations.Findings: The results show that the DL service elements of Chinese academic libraries are all distributed in Basic and Key services regarding information retrieval and informationorganizing; 80% of the interaction services elements are Plus services, while 50% of the Secondary services are information-providing services. The results also reveal that service categorization is obviously influenced by the users’ education background, especially their disciplines. Furthermore, the users who are older, more highly-educated, or studying in higher reputation universities are more likely to evaluate DL services as either critical or useless.Research limitations: Tetra-class model cannot reveal the interplay among the DL service elements. In addition, the user segmentation in our studies is limited to the sample structure.Practical implications: This empirical study focuses on the evaluation of DL services of academic libraries in China, the analyses of their current performances could provide useful reference for the assessment of other types of Chinese DLs. Moreover, the consideration of user characteristics(gender, age, and education background, etc.) in the DL evaluation would help librarians improve DL services to meet the users’ various needs in teaching and doing scientific research.Originality/value: Different from the frequently-used factor analysis which focuses on the relationship among factors and user satisfaction, this paper tries to use and compare element distributions of different user segments while focusing on various service objectives. Factor analysis shows some flaws as used to measure the element with selected indicators, for it ignores the fact that the indicators which measure the same factor would have different degrees of impacts on user satisfaction. However, the tetra-class model can better visually analyze the performance of each DL service element from its contributions to satisfaction and dissatisfaction, which would help librarians to better understand users’ need and offer DL services more efficiently.

将Flipped Class Model引入高校网球教学的SWOT分析

将Flipped Class Model引入到高校网球课教学,有助于激发学生对高校网球项目课学习的积极性,增强学生网球项目课学习的自主性,加强师生间的交流。运用SWOT态势分析法,将Flipped Class Model引入到高校网球教学,将会促进教师教学能力提高、教学过程中教师和学生角色转换、学生学习习惯改变等。

Two-Bubble Class Model for Churn-Turbulent Regime in a Bubble Column Slurry Reactor of Fischer-Tropsch Synthesis

A model for a bubble column slurry reactor is developed based on the experiment of Rhenpreussen Koppers demonstration plant for slurry phase Fischer-Tropsch synthesis reported by Koelble et al. This model is applicable to the operation in the churn-turbulent regime and incorporates the information on the bubble size. The axial dispersion model is adopted to describe the flow characteristics of the Fischer-Tropsch slurry reactor. With the model developed, simulations are performed to identify the steady state behavior of a Fischer-Tropsch slurry reactor of commercial size. Predictions of the two-bubble class model is compared with that of the conventional single- bubble class model. The results show that under a variety of conditions, the two-bubble class model gives results different from those for the single-bubble class model.

“FlippedClass Model”模式在教学中的运用实践与思考

本文通过"FlippedClass Model"在《现代轿车的新功能》中的实践,论述了"FlippedClass Model"体现教师为主导,学生为主体辩证统一的理念,符合独立性与依赖性相统一的心理发展的实际,适应学生的个别差异,有利于挖掘学生的创造潜能,培养学生的创新意识。

“Flipped Class Model”在《现代机床》中的实践与思考

翻转课堂通过对知识传授和知识内化的颠倒安排,改变了传统教学中的师生角色,并对课堂时间的使用进行了重新规划,实现了对传统教学模式的革新。文中尝试将"Flipped Class Model"用于现代机械创新产品分析与设计教学中,并以《现代机床》为例分析说明,以期为我国的机械课程教学改革提供借鉴。

“Flipped Class Model”在《现代机床》中的实践与思考

翻转课堂通过对知识传授和知识内化的颠倒安排,改变了传统教学中的师生角色,并对课堂时间的使用进行了重新规划,实现了对传统教学模式的革新。本文尝试将"Flipped Class Model"用于现代机械创新产品分析与设计教学中,并以《现代机床》为例分析说明,以期为我国的机械课程教学改革提供借鉴。

Accounting for Heterogeneity in Stop Frequency Models of Work Tours Using Latent Class Poisson Models

Stop frequency models, as one of the elements of activity based models, represent an important part of travel behavior. Unobserved heterogeneity across the travelers should be taken into consideration to prevent biasedness and inconsistency in the estimated parameters in the stop frequency models. Additionally, previous studies on the stop frequency have mostly been done in larger metropolitan areas and less attention has been paid to the areas with less population. This study addresses these gaps by using 2012 travel data from a medium sized U.S. urban area using the work tour for the case study. Stop in the work tour were classified into three groups of outbound leg, work based subtour, and inbound leg of the commutes. Latent Class Poisson Regression Models were used to analyze the data. The results indicate the presence of heterogeneity across the commuters. Using latent class models significantly improves the predictive power of the models compared to regular one class Poisson regression models. In contrast to one class Poisson models, gender becomes insignificant in predicting the number of tours when unobserved heterogeneity is accounted for. The commuters are associated with increased stops on their work based subtour when the employment density of service-related occupations increases in their work zone, but employment density of retail employment does not significantly contribute to the stop making likelihood of the commuters. Additionally, an increase in the number of work tours was associated with fewer stops on the inbound leg of the commute. The results of this study suggest the consideration of unobserved heterogeneity in the stop frequency models and help transportation agencies and policy makers make better inferences from such models.

Examining unobserved factors associated with red light running in Vietnam:A latent class model analysis

Red-light running(RLR)is a crucial violation that causes traffic accidents and injuries.Understanding factors that affect RLR is very significant to reduce the potential of this violation.Current studies have paid considerable attention to the observable factors,but not to unobservable factors.This study aims to examine the effects of observable and unobservable factors on RLR.This study uses a latent class model(LCM)to assign individuals into two classes—red-light-respectful and red-light-disrespectful road users—by surveying 751 respondents who use private transportation modes.This study incorporates psychological determinants into the LCM to account for unobservable factors.The contribution of this study is the in-depth investigation into law-respectful and law-disrespectful behaviours and intentional and unintentional violators.Such a study has not yet been conducted in the existing literature.In addition,a comprehensive comparison of the LCM and a traditional ordered probit model was conducted.Overall,the results suggest that the LCM is superior to the model that does not consider latent classes.Our estimation results are in alignment with previous studies on RLR:males,younger drivers/riders,less educated road users and motorcyclists are more likely to run red lights.An analysis of the latent variables shows that surrounding conditions—the behaviour of other violators,the absence of traffic police,and long waiting times—increase the possibility of violations.Based on these results,we provide suggestions to policymakers and traffic engineers:the implementation of enforcement cameras and penalties for violators are critical countermeasures to minimize the potential of RLR.

A Model Structured in Classes for the Study of Student Population Evolution

This paper presents an application of a metapopulation model structured in classes for the study of population evolution of a network of schools.The global dynamics are considered in two parts,the local,where the evolution for each grade in a cycle is accounted,and the metapopulation or the movement of students between schools.Simulation of the model is presented.

A Comparison of Statistics for Assessing Model Invariance in Latent Class Analysis

Latent class analysis (LCA) is a widely used statistical technique for identifying subgroups in the population based upon multiple indicator variables. It has a number of advantages over other unsupervised grouping procedures such as cluster analysis, including stronger theoretical underpinnings, more clearly defined measures of model fit, and the ability to conduct confirmatory analyses. In addition, it is possible to ascertain whether an LCA solution is equally applicable to multiple known groups, using invariance assessment techniques. This study compared the effectiveness of multiple statistics for detecting group LCA invariance, including a chi-square difference test, a bootstrap likelihood ratio test, and several information indices. Results of the simulation study found that the bootstrap likelihood ratio test was the optimal invariance assessment statistic. In addition to the simulation, LCA group invariance assessment was demonstrated in an application with the Youth Risk Behavior Survey (YRBS). Implications of the simulation results for practice are discussed.

Universality Class in Abelian Sandpile Models with Stochastic Toppling Rules

We present a stochastic critical slope sandpile model, where the amount of grains that fall in an overturning event is stochastic variable. The model is local, conservative, and Abelian. We apply the moment analysis to evaluate critical exponents and finite size scaling method to consistently test the obtained results. Numerical results show that this model, Oslo model, and one-dimensional Abelian Manna model have the same critical behavior although the three models have different stochastic toppling rules, which provides evidences suggesting that Abelian sandpile models with different stochastic toppling rules are in the same universality class.

Optimizing Movement of Students from Hostels to Lecture Rooms in a Potential World Class University Using Transportation Model

Transportation issue is one of the significant zones of utilization of Linear Programming Model. In this paper, transportation model is utilized to decide an ideal answer for the transportation issue in a run of the mill world class university utilizing Covenant University as a contextual analysis. Covenant University is a potential world class University. The quick development of Covenant University Campus over the most recent fourteen years affects its transportation framework. This paper particularly takes a gander at streamlining the time spent by the students moving from their lodgings to lecture rooms. Google guide was utilized to figure the separation and time between every cause and every goal. North-west corner technique, Least Cost strategy and Vogel’s estimation technique were utilized to decide the underlying fundamental plausible arrangement (initial feasible solution) and MODI strategy was utilized to locate the ideal arrangement (optimal solution). The last outcome demonstrates that the development of understudies from hostel to lecture rooms can be streamlined if the total time spent is decreased.

A lattice Bhatnagar-Gross-Krook model for a class of the generalized Burgers equations

A new lattice Bhatnagar-Gross-Krook （LBGK） model for a class of the generalized Burgers equations is proposed. It is a general LBGK model for nonlinear Burgers equations with source term in arbitrary dimensional space. The linear stability of the model is also studied. The model is numerically tested for three problems in different dimensional space, and the numerical results are compared with either analytic solutions or numerical results obtained by other methods. Satisfactory results are obtained by the numerical simulations.

Modeling Crash Risk at Rail-Highway Grade Crossings by Track Class

The Federal Railroad Administration (FRA)’s Web Based Accident Prediction System (WBAPS) is used by federal, state and local agencies to get a preliminary idea on safety at a rail-highway grade crossing. It is an interactive and user-friendly tool used to make funding decisions. WBAPS is almost three decades old and involves a three-step approach making it difficult to interpret the contribution of the variables included in the model. It also does not directly account for regional/local developments and technological advancements pertaining to signals and signs implemented at rail-highway grade crossings. Further, characteristics of a rail-highway grade crossing vary by track class which is not explicitly considered by WBAPS. This research, therefore, examines and develops a method and models to estimate crashes at rail-highway grade crossings by track class using regional/local level data. The method and models developed for each track class as well as considering all track classes together are based on data for the state of North Carolina. Linear, as well as count models based on Poisson and Negative Binomial (NB) distributions, was tested for applicability. Negative binomial models were found to be the best fit for the data used in this research. Models for each track class have better goodness of fit statistics compared to the model considering data for all track classes together. This is primarily because traffic, design, and operational characteristics at rail-highway grade crossings are different for each track class. The findings from statistical models in this research are supported by model validation.

A Survey Research on Agricultural College Undergraduates' Attitudes towards In-class and Out-of-class Activities Based on the Mixed Teaching Model

In order to study the effects of in-class and out-of-class activities of college English based on the mixed teaching model on the fostering of students' English learning and application ability,the attitudes of 215 freshmen of Agricultural College,Yanbian University towards inclass and out-of-class activities and their participation and completion of tasks were investigated by a questionnaire. The results show that a series of in-class and out-of-class activities could help improve the students' language competence as well as non-language competence such as learning strategies,emotional attitudes,and cultural awareness. The implementation and effect of school online courses were inferior to classroom teaching,but they provide reference and experience for future mixed teaching.

基于潜类别增长模型分析老年帕金森病患者用药依从性轨迹及影响因素

目的:利用潜类别增长模型(latent class growth model,LCGM)分析老年帕金森病患者用药依从性轨迹,并验证其影响因素。方法:对124例原发性老年帕金森病患者进行12个月随访调查,调查工具包括一般资料调查表和Morisky用药依从性量表。通过潜类别增长模型识别患者用药依从性轨迹,采用有序多分类Logistic回归分析用药依从性轨迹的影响因素。结果:老年帕金森病患者用药依从性分为“高-持续型”“中-下降型”和“低-下降型”3种类型,且该3种类型文化程度、工作状态、用药种类、智力状态比较,差异有统计学意义(P<0.05)。有序多分类Logistic回归显示,工作状态、用药种类、智力状态是患者用药依从性轨迹的影响因素(P<0.05)。结论:老年帕金森患者用药依从性分为3种轨迹,工作状态、用药种类和智力状态是用药依从性轨迹类别的影响因素。