Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- a...Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- and Q-factors is possible, this may lead to model error. Accordingly, loading estimates resulting from R-factor analysis of sample data drawn from a population based on a combination of R- and Q-factors will be biased. It was shown in a simulation study that a large amount of Q-factor variance induces an increase in the variation of R-factor loading estimates beyond the chance level. Tests of the multivariate kurtosis of observed variables are proposed as an indicator of possible Q-factor variance in observed variables as a prerequisite for R-factor analysis.展开更多
The horizontal continuous casting process,the initial step in TP2 copper tubular processing,directly determines the microstructure and properties of copper tubular.However,the process parameters of the continuous cast...The horizontal continuous casting process,the initial step in TP2 copper tubular processing,directly determines the microstructure and properties of copper tubular.However,the process parameters of the continuous casting characterize time variation,multiple disturbances and strong coupling.As a consequence,their influence on a casting billet is difficult to be determined.Due to the above issues,the common factor and special factor analysis of the factor analysis model were used in this study,and the casting experiment and billet metallographic experiment were carried out to diagnose and analyze the reason of the microstructure inhomogeneity.The multiple process parameters were studied and classified using common factor analysis,2 the cast billets with abnormal microstructures were identified by GT^(2) statistics,and the most important factors affecting the microstructural homogeneity were found by special factor analysis.The calculated and experimental results show that the principal parameters influencing the inhomogeneity of solidified microstructure are the primary inlet water pressure and the primary outlet water temperature.According to the consequence of the above investigation,the inhomogeneity of the copper billet microstructure can be effectively improved when the process parameters are controlled and adjusted.展开更多
Multicollinearity in factor analysis has negative effects, including unreliable factor structure, inconsistent loadings, inflated standard errors, reduced discriminant validity, and difficulties in interpreting factor...Multicollinearity in factor analysis has negative effects, including unreliable factor structure, inconsistent loadings, inflated standard errors, reduced discriminant validity, and difficulties in interpreting factors. It also leads to reduced stability, hindered factor replication, misinterpretation of factor importance, increased parameter estimation instability, reduced power to detect the true factor structure, compromised model fit indices, and biased factor loadings. Multicollinearity introduces uncertainty, complexity, and limited generalizability, hampering factor analysis. To address multicollinearity, researchers can examine the correlation matrix to identify variables with high correlation coefficients. The Variance Inflation Factor (VIF) measures the inflation of regression coefficients due to multicollinearity. Tolerance, the reciprocal of VIF, indicates the proportion of variance in a predictor variable not shared with others. Eigenvalues help assess multicollinearity, with values greater than 1 suggesting the retention of factors. Principal Component Analysis (PCA) reduces dimensionality and identifies highly correlated variables. Other diagnostic measures include the condition number and Cook’s distance. Researchers can center or standardize data, perform variable filtering, use PCA instead of factor analysis, employ factor scores, merge correlated variables, or apply clustering techniques for the solution of the multicollinearity problem. Further research is needed to explore different types of multicollinearity, assess method effectiveness, and investigate the relationship with other factor analysis issues.展开更多
This pioneering research represents a unique and singular study conducted within the United States, with a specific focus on non-technical graduate students pursuing degrees in business analytics. The primary impetus ...This pioneering research represents a unique and singular study conducted within the United States, with a specific focus on non-technical graduate students pursuing degrees in business analytics. The primary impetus behind this study stems from the escalating demand for data-driven professionals, the diverse academic backgrounds of students, the imperative for adaptable pedagogical methods, the ever-evolving landscape of curriculum designs, and the overarching commitment to fostering educational equity. To investigate these multifaceted dynamics, we employed a data collection method that included the distribution of an online survey on platforms such as LinkedIn. Our survey reached and engaged 74 graduate students actively pursuing degrees in Business Analytics within the United States. This comprehensive research is the first and only one of its kind conducted in this context, and it serves as a vanguard exploration into the challenges and influences that shape the learning journey of Python among non-technical graduate Business Analytics students. The analytical insights derived from this research underscore the pivotal role of hands-on learning strategies, exemplified by practice exercises and assignments. Moreover, the study highlights the positive and constructive influence of collaboration and peer support in the process of learning Python. These invaluable findings significantly augment the existing body of knowledge in the field of business analytics. Furthermore, they offer an essential resource for educators and institutions seeking to optimize the educational experiences of non-technical students as they acquire essential Python skills.展开更多
Affective exercise experience as an emerging theoretical concept has great potential to provide a more nuanced understanding of individual factors that influence exercise behavior.However,concerning the Affective Exer...Affective exercise experience as an emerging theoretical concept has great potential to provide a more nuanced understanding of individual factors that influence exercise behavior.However,concerning the Affective Exercise Experiences(AFFEXX)questionnaire,it has not been examined yet whether the structural score of the AFFEXX is a useful index to predict physical activity(refers to any bodily movement produced by skeletal muscles that requires energy expenditure).Furthermore,there is currently a gap in knowledge regarding the psychological mechanisms that can explain the relationship between affective exercise experiences and the level of physical activity(PA).In order to adress these gaps in the literature,we conducted two studies among Chinese collge students that aimed(i)to investigated whether the total score of the three AFFEXX-C constructs(antecedent appraisals,core affective exercise experiences,and attraction-antipathy towards exercise)is a relaible indicator that can be utilized in research and pratical settings and(ii)to evalute the specific psychological mechanisms that can explain the relationship between affective exercise experience and PA.In Study 1,we recruited 801 voluntary Chinese college students for bifactor and correlational analyses.In Study 2,875 Chinese college students were enrolled to verify our findings from Study 1 and to explore the aforementioned mechanism.Results from the bifactor analyses supported our hypothesis that the total scores of the three AFFEXX-C constructs can be used among Chinese college students to establish a link with PA.Additionally,our results suggested that core affective exercise experiences and attraction-antipathy mediated the relationship between antecedent appraisals and the level of moderate-to-vigorous intensity PA.Therefore,measuring affective exercise experiences using the AFFEXX-C,specifically the total scores of each individual construct may be a useful approach to predict future PA levels.展开更多
The interception probability of a single missile is the basis for combat plan design and weapon performance evaluation,while its influencing factors are complex and mutually coupled.Existing calculation methods have v...The interception probability of a single missile is the basis for combat plan design and weapon performance evaluation,while its influencing factors are complex and mutually coupled.Existing calculation methods have very limited analysis of the influence mechanism of influencing factors,and none of them has analyzed the influence of the guidance law.This paper considers the influencing factors of both the interceptor and the target more comprehensively.Interceptor parameters include speed,guidance law,guidance error,fuze error,and fragment killing ability,while target performance includes speed,maneuverability,and vulnerability.In this paper,an interception model is established,Monte Carlo simulation is carried out,and the influence mechanism of each factor is analyzed based on the model and simulation results.Finally,this paper proposes a classification-regression neural network to quickly estimate the interception probability based on the value of influencing factors.The proposed method reduces the interference of invalid interception data to valid data,so its prediction accuracy is significantly better than that of pure regression neural networks.展开更多
Accurate and real-time passenger flow prediction of rail transit is an important part of intelligent transportation systems(ITS).According to previous studies,it is found that the prediction effect of a single model i...Accurate and real-time passenger flow prediction of rail transit is an important part of intelligent transportation systems(ITS).According to previous studies,it is found that the prediction effect of a single model is not good for datasets with large changes in passenger flow characteristics and the deep learning model with added influencing factors has better prediction accuracy.In order to provide persuasive passenger flow forecast data for ITS,a deep learning model considering the influencing factors is proposed in this paper.In view of the lack of objective analysis on the selection of influencing factors by predecessors,this paper uses analytic hierarchy processes(AHP)and one-way ANOVA analysis to scientifically select the factor of time characteristics,which classifies and gives weight to the hourly passenger flow through Duncan test.Then,combining the time weight,BILSTM based model considering the hourly travel characteristics factors is proposed.The model performance is verified through the inbound passenger flow of Ningbo rail transit.The proposed model is compared with many current mainstream deep learning algorithms,the effectiveness of the BILSTM model considering influencing factors is validated.Through comparison and analysis with various evaluation indicators and other deep learning models,the results show that the R2 score of the BILSTM model considering influencing factors reaches 0.968,and the MAE value of the BILSTM model without adding influencing factors decreases by 45.61%.展开更多
Factor analysis of annual dynamics from 1879 to 2017 was carried out by the method of identification of stable regularities:maximum,minimum and average air temperature of Central England according to HadCET.The sample...Factor analysis of annual dynamics from 1879 to 2017 was carried out by the method of identification of stable regularities:maximum,minimum and average air temperature of Central England according to HadCET.The sample capacity was 139 rows.In factor analysis,time is excluded,and it acts only as a system-forming factor that ensures the relationship between the three parameters of climate and weather.Therefore,the adequacy of the dynamics models is taken into account in the diagonal cells of the correlation matrix.In addition to time,different lists of objects are possible in factor analysis.The coefficient of correlation variation,that is,a measure of the functional relationship between the parameters of the system(annual weather at the weather station in Central England)is 0.8230 for trends,0.8603 taking into account the annual dynamics of the four-membered model obtained from the computational capabilities of the software environment CurveExpert-1.40,and 0.9578 for the full up to the error of measurement wavelet analysis of the dynamics of the values of three factors.In all three methods of factor analysis,the meteorological parameter«average Annual temperature»was in the first place as the influencing variable,the«Maximum temperature»was in the second place,and the«Minimum temperature»was in the third place.As the dependent measure in these areas there are three kinds of temperature.The comparison shows that among the binary relations between the three temperatures,the average temperature on the maximum air temperature in the surface layer of the atmosphere has the greatest influence on the correlation coefficient 0.9765.At the same time,all six equations refer to strong connections,so there is a high quantum certainty between the three types of temperature.But when predicting the most meaningful essence showed the maximum temperature.展开更多
In this study,the Five Facet Mindfulness Questionnaire which was adapted from the short form of the Five Facet Mindfulness Questionnaire was evaluated and this scale into neutrosophic form was converted and the result...In this study,the Five Facet Mindfulness Questionnaire which was adapted from the short form of the Five Facet Mindfulness Questionnaire was evaluated and this scale into neutrosophic form was converted and the results of the scale were compared for proposing new type confirmatory analysis procedure as well as developing neutrosophic scales.The exploratory factor analysis was used in the analysis of the data.Besides,test results were analyzed for Kaiser–Meyer–Olkin and Bartlett values,common factor variance values,scree plot graphs,and the principal component analysis results.The sample of the study consists of 194 students in mathematics departments at Bitlis Eren University and Igdır University in Turkey by convenience sampling method.A convenience sampling is a kind˘of non-probability sampling procedure in which the sample is obtained from a group of individuals easily accessible or reachable.The convenience sampling method was chosen in this study because the study aims to examine the structure of the measurement tool rather than the psychological characteristics of a particular population.First of all,it is observed that if any classical scale can be converted into a neutrosophic one.It is observed that the sub-dimensions of a neutrosophic scale as agree,disagree,and undecided might not have a similar factor structure to the classical one.Interestingly,in the factor analysis of the neutrosophic scale,both classical and the agreement part of the neutrosophic scales have the same factors,implying that the one-dimensional classical scale measures the agreement degree of the participants.When the factor analysis was conducted to disagreement and vagueness dimensions,it seemed that some factors were eliminated and even some new factors emerged,indicating that in human cognition those three dimensions can be taken as independent of each other,just as assumed by neutrosophic logic.The another important implication of the factor analysis is that the neutrosophic forms of any questionnaire can be used for the validity of the classical ones.Loads of items or their accumulation into factors are compared to the classical scale and the three-dimensional neutrosophic scale in the factor,so that the corresponding ones in the same factors and the items or factors that do not correspond to each other are eliminated.It is very similar to the Sieve of Eratosthenes,which is an ancient algorithm for finding prime numbers up to any given limit where each prime is taken as an independent base or dimension and multiples of the selected primes in a given interval are eliminated until there are only prime numbers left.Finally,the reliability of three independent dimensions of the neutrosophic forms of any questionnaire can also be used to check whether the measurement This work is licensed under a Creative Commons Attribution 4.0 International License,which permits unrestricted use,distribution,and reproduction in any medium,provided the original work is properly cited.954 CMES,2021,vol.129,no.2 tool is reliable.Low-reliability results in any dimensions may imply that the scale has some problems in terms of meaning,language,or other factors.展开更多
Objectives:To establish long-term outcome of surgical pulmonary valve replacement(PVR)in congenital heart disease(CHD)and to identify risk factors for overall mortality,operative mortality,and repetitive PVR.Methods:T...Objectives:To establish long-term outcome of surgical pulmonary valve replacement(PVR)in congenital heart disease(CHD)and to identify risk factors for overall mortality,operative mortality,and repetitive PVR.Methods:This is a retrospective study of 375 surgical PVR in 293 patients who underwent surgical PVR for CHD between January 2000 and May 2020.We only included patients with index PVR with previous open-heart surgery regardless of the number of PVRs.The previous surgical history of patients who underwent PVR during the study period was also included.Patients who underwent the Rastelli operation,and those who underwent single PVR without previous open-heart surgery were excluded.Results:The median age of the patients at the time of surgical PVR was 14.9 years(Interquartile range,IQR,11.0–22.0).The median follow-up duration was 10.5 years(IQR,5.5–14.8 years).There were 3 patients with operative mortality(1.0%)and 15 patients with overall mortality(5.1%).The survival rate was 95.1%over 20 years follow-up period.Multivariate analysis demonstrated that more than 3 times of previous open-heart surgeries before surgical PVR,older age at the first operation,longer cardiopulmonary bypass(CPB)time and longer intensive care unit(ICU)stay were predictors for overall mortality.Patients who underwent surgical PVR after more than 3 times of previous open-heart surgeries had significantly higher mortality than those who underwent open-heart surgeries less than 3 times(P<0.001).Age younger than 10 years,male,multiple valve problems and longer ICU stay were significant predictors for repetitive PVR by multivariate analysis.Conclusions:Though surgical PVR has excellent long-term outcome,it should be performed with caution for those who previously underwent multiple open-heart surgeries,especially if patient received more than 3 times of open-heart surgeries.展开更多
The purpose of this study was to explore the quality of the Tibetan native hulless barley variety in depth and to evaluate the characteristics of its processing quality using ratio analysis.For this study,10 native ba...The purpose of this study was to explore the quality of the Tibetan native hulless barley variety in depth and to evaluate the characteristics of its processing quality using ratio analysis.For this study,10 native barley varieties were chosen with the detection of 24 quality indexes in order to build a system of comprehensive evaluation.The results of the factor analysis indicated that seven common factors with an eigenvalue greater than 1 were extracted,cumulatively accounting for 96.21%of the total variance.The first common factor,including ASP,GLU,SER,GLY,ARG,TYR and CYS contents,accounted for 33.82% of the variance.The second common factor,including ash,the total starch,soluble fiber,VB_(3),Cu,Mn,Na and beta-glucan contents,accounted for 19.46%of the variance.The third common factor,including the total dietary fiber,α-VE,K,Zn and glutelin.The fourth common factor,including B,Ba and prolamin,explained the barley starch character of the rheological property.The fifth common factor included crude fiber.The sixth and the seventh common factors did not account for a substantial amount of variance.According to the comprehensive evaluation model,the score consequence was as the following:Zangqing25>Pengnaigabu>Lhasa changhei>2004Qing21>Lhasa duanbai>Liangamu>Zhikonggaxia>lianmubai>Jiangreejiu>Longzihei.展开更多
Taking a total of 13 areas in Heilongjiang commodity grain base as the research objects,9 indices are selected,which are regional GDP(X1),per capita GDP(X2),total value of tertiary industry(X3),financial revenue(X4),u...Taking a total of 13 areas in Heilongjiang commodity grain base as the research objects,9 indices are selected,which are regional GDP(X1),per capita GDP(X2),total value of tertiary industry(X3),financial revenue(X4),urban fixed assets investment(X5),average salary(X6),gross industrial output value(X7),total output value of farming,forestry,husbandry and fishing(X8),and retail sales of social consumer goods(X9).Based on this,evaluation index system of regional economy is established.According to the 2006-2008 Heilongjiang Statistical Yearbook,average values within 3 years are used as analytical data.Factor Analysis Method is adopted to establish regression model and to carry out comprehensive analysis.Result shows that Heilongjiang commodity grain base has extremely uneven regional economic development in different areas.According to the score order and actual situation,the 13 areas are divided into 4 types.The first and second types are Harbin and Daqing,respectively.The third type is Qiqihaer,Suihua,Mudanjiang and Jiamusi.And the forth type is Jixi,Shuangyashan,Heihe,Yichun,Qitaihe,Hegang and Daxinganling.Suggestions for the development of these areas are put forward.展开更多
Women entrepreneurship is now a rapidly growing socio-economic phenomenon in developing country like Bangladesh.Women entrepreneurs’development in the SME sector is one of the most important challenge.The research ai...Women entrepreneurship is now a rapidly growing socio-economic phenomenon in developing country like Bangladesh.Women entrepreneurs’development in the SME sector is one of the most important challenge.The research aims to analyze the factors related to the development of women entrepreneurship in Small and Medium Enterprises(SMEs)sector of Bangladesh.The analysis is based on recent theoretical ideas that have been supported by empirical research findings.Both descriptive and inferential statistics were used in this research.To analyze the factors we have interviewed 232 women entrepreneurs of SME businesses.The main tool of research was a structured questionnaire.This study illustrates an analytical framework based on institutional theory,which focuses on three kinds of factors:regulative,normative,and cognitive.Regulative factors refer to different rules and regulations of the Government that facilitate women entrepreneurship development of SMEs sector in Bangladesh.Normative and cognitive factors include norms,rules,regulation,and values of society.This study provides suggestions on how to overcome barriers and also many significant policy implications to improve women entrepreneurship in SMEs sector of Bangladesh.展开更多
<b><span style="font-family:Verdana;">Objective:</span></b><span style="font-family:Verdana;"> Despite efforts in describing the impact of shiftwork </span><s...<b><span style="font-family:Verdana;">Objective:</span></b><span style="font-family:Verdana;"> Despite efforts in describing the impact of shiftwork </span><span style="font-family:Verdana;">on</span><span style="font-family:""><span style="font-family:Verdana;"> the performance of health care workers, the perception of ambulance service staff is largely unexplored. This study attempted to develop the Perception of Effects of Shiftwork Questionnaire (PESQ) using a factor analysis approach to determine the underlying dimensions. </span><b><span style="font-family:Verdana;">Methods:</span></b><span style="font-family:Verdana;"> A 16-item Likert scale research inst</span><span style="font-family:Verdana;">rument, designed to gather information about the perceived effects of</span><span style="font-family:Verdana;"> shiftwork</span></span><span style="font-family:Verdana;"> on</span><span style="font-family:""><span style="font-family:Verdana;"> the respondents’ health, social relationships, and career quality, was floated to 375 ambulance services personnel in Saudi Arabia during March and April 2021. </span><b><span style="font-family:Verdana;">Results:</span></b><span style="font-family:Verdana;"> Based on factor analysis, the questionnaire has three dimensions with varying reliability, namely “perceived effects on social relationship” (</span><i><span style="font-family:Verdana;">α</span></i><span style="font-family:Verdana;"> = 0.815), perceived effects on health (</span><i><span style="font-family:Verdana;">α</span></i><span style="font-family:Verdana;"> = 0.787) and “perceived </span><span><span style="font-family:Verdana;">effects on career quality” (</span><i><span style="font-family:Verdana;">α</span></i><span style="font-family:Verdana;"> = 0.602). Over-all, the research instrument had an acceptable internal consistency (</span><i><span style="font-family:Verdana;">α</span></i><span style="font-family:Verdana;"> = 0.829). </span><b><span style="font-family:Verdana;">Conclusion:</span></b><span style="font-family:Verdana;"> The three-dimension model was analyzed simultaneously using parallel analysis</span></span><span style="font-family:Verdana;"> and confirms that the three-factor model is the most ideal for the research instrument. Further research, however, is recommended to improve the internal consistency of the items which measure the perceived effects on career quality.展开更多
Over the past years,there has been an expanding intrigued in building refurbishment projects because of the alter in financial conditions and the accentuation on sustainable development.Increasing demand for building ...Over the past years,there has been an expanding intrigued in building refurbishment projects because of the alter in financial conditions and the accentuation on sustainable development.Increasing demand for building refurbishment projects will lead to an increase in organizational interactions in the construction works as building refurbishment works involve interactions among many different organizations and it can cause Inter-Organizational conflict(IOC)among organizations involved in projects.This paper adopted an Exploratory Factor Analysis(EFA)approach to analyses IOC in building refurbishment projects.For this study,a fivepoint Likert Scale was adopted to ensure the instruments of the study are reliable.The researcher ultimately sent questionnaires as a web-link and email invitation to 1050 construction firms and 733 architectural firms.The questionnaire sent to managers and professionals from construction and architectural firms in Malaysia.Finally,one-hundred-seventy-nine(179)refurbishment projects formed a database for this paper.The finding of this paper shows the IOC factors that contribute to the improve the performance of building refurbishment project can be conflict during the construction stage,conflict between the client and the consultant,task expectations,basic responsibilities,final duration,project’s goals,conflict between the client and the contractor,final cost,final quality,standards of behaviors,conflict between the contractor and the consultant,interference and conflict during the design stage.展开更多
Confirmatory factor analysis (CFA) refers to the FA procedure with some loadings constrained to be zeros. A difficulty in CFA is that the constraint must be specified by users in a subjective manner. For dealing with ...Confirmatory factor analysis (CFA) refers to the FA procedure with some loadings constrained to be zeros. A difficulty in CFA is that the constraint must be specified by users in a subjective manner. For dealing with this difficulty, we propose a computational method, in which the best CFA solution is obtained optimally without relying on users’ judgements. The method consists of the procedures at lower (L) and higher (H) levels: at the L level, for a fixed number of zero loadings, it is determined both which loadings are to be zeros and what values are to be given to the remaining nonzero parameters;at the H level, the procedure at the L level is performed over the different numbers of zero loadings, to provide the best solution. In the L level procedure, Kiers’ (1994) simplimax rotation fulfills a key role: the CFA solution under the constraint computationally specified by that rotation is used for initializing the parameters of a new FA procedure called simplimax FA. The task at the H level can be easily performed using information criteria. The usefulness of the proposed method is demonstrated numerically.展开更多
Dissolved oxygen(DO)is an important indicator of aquaculture,and its accurate forecasting can effectively improve the quality of aquatic products.In this paper,a new DO hybrid forecasting model is proposed that includ...Dissolved oxygen(DO)is an important indicator of aquaculture,and its accurate forecasting can effectively improve the quality of aquatic products.In this paper,a new DO hybrid forecasting model is proposed that includes three stages:multi-factor analysis,adaptive decomposition,and an optimizationbased ensemble.First,considering the complex factors affecting DO,the grey relational(GR)degree method is used to screen out the environmental factors most closely related to DO.The consideration of multiple factors makes model fusion more effective.Second,the series of DO,water temperature,salinity,and oxygen saturation are decomposed adaptively into sub-series by means of the empirical wavelet transform(EWT)method.Then,five benchmark models are utilized to forecast the sub-series of EWT decomposition.The ensemble weights of these five sub-forecasting models are calculated by particle swarm optimization and gravitational search algorithm(PSOGSA).Finally,a multi-factor ensemble model for DO is obtained by weighted allocation.The performance of the proposed model is verified by timeseries data collected by the pacific islands ocean observing system(PacIOOS)from the WQB04 station at Hilo.The evaluation indicators involved in the experiment include the Nash–Sutcliffe efficiency(NSE),Kling–Gupta efficiency(KGE),mean absolute percent error(MAPE),standard deviation of error(SDE),and coefficient of determination(R^(2)).Example analysis demonstrates that:①The proposed model can obtain excellent DO forecasting results;②the proposed model is superior to other comparison models;and③the forecasting model can be used to analyze the trend of DO and enable managers to make better management decisions.展开更多
Learning style,aiming at language learner,is a hot issue of second language acquisition.The article first reviews the various definitions of learning style.From the perspective of cognition,three influence factors of ...Learning style,aiming at language learner,is a hot issue of second language acquisition.The article first reviews the various definitions of learning style.From the perspective of cognition,three influence factors of Chinese students' learning styles are analyzed.Suggestions are proposed for teachers to help students develop learning styles.展开更多
文摘Effects of performing an R-factor analysis of observed variables based on population models comprising R- and Q-factors were investigated. Although R-factor analysis of data based on a population model comprising R- and Q-factors is possible, this may lead to model error. Accordingly, loading estimates resulting from R-factor analysis of sample data drawn from a population based on a combination of R- and Q-factors will be biased. It was shown in a simulation study that a large amount of Q-factor variance induces an increase in the variation of R-factor loading estimates beyond the chance level. Tests of the multivariate kurtosis of observed variables are proposed as an indicator of possible Q-factor variance in observed variables as a prerequisite for R-factor analysis.
基金This work is financially supported by Basic Scientific Project of Liaoning Provincial Department of Education(LJKMZ20220591)Science and Technology Plan Project of Changzhou,China(CQ20220057).
文摘The horizontal continuous casting process,the initial step in TP2 copper tubular processing,directly determines the microstructure and properties of copper tubular.However,the process parameters of the continuous casting characterize time variation,multiple disturbances and strong coupling.As a consequence,their influence on a casting billet is difficult to be determined.Due to the above issues,the common factor and special factor analysis of the factor analysis model were used in this study,and the casting experiment and billet metallographic experiment were carried out to diagnose and analyze the reason of the microstructure inhomogeneity.The multiple process parameters were studied and classified using common factor analysis,2 the cast billets with abnormal microstructures were identified by GT^(2) statistics,and the most important factors affecting the microstructural homogeneity were found by special factor analysis.The calculated and experimental results show that the principal parameters influencing the inhomogeneity of solidified microstructure are the primary inlet water pressure and the primary outlet water temperature.According to the consequence of the above investigation,the inhomogeneity of the copper billet microstructure can be effectively improved when the process parameters are controlled and adjusted.
文摘Multicollinearity in factor analysis has negative effects, including unreliable factor structure, inconsistent loadings, inflated standard errors, reduced discriminant validity, and difficulties in interpreting factors. It also leads to reduced stability, hindered factor replication, misinterpretation of factor importance, increased parameter estimation instability, reduced power to detect the true factor structure, compromised model fit indices, and biased factor loadings. Multicollinearity introduces uncertainty, complexity, and limited generalizability, hampering factor analysis. To address multicollinearity, researchers can examine the correlation matrix to identify variables with high correlation coefficients. The Variance Inflation Factor (VIF) measures the inflation of regression coefficients due to multicollinearity. Tolerance, the reciprocal of VIF, indicates the proportion of variance in a predictor variable not shared with others. Eigenvalues help assess multicollinearity, with values greater than 1 suggesting the retention of factors. Principal Component Analysis (PCA) reduces dimensionality and identifies highly correlated variables. Other diagnostic measures include the condition number and Cook’s distance. Researchers can center or standardize data, perform variable filtering, use PCA instead of factor analysis, employ factor scores, merge correlated variables, or apply clustering techniques for the solution of the multicollinearity problem. Further research is needed to explore different types of multicollinearity, assess method effectiveness, and investigate the relationship with other factor analysis issues.
文摘This pioneering research represents a unique and singular study conducted within the United States, with a specific focus on non-technical graduate students pursuing degrees in business analytics. The primary impetus behind this study stems from the escalating demand for data-driven professionals, the diverse academic backgrounds of students, the imperative for adaptable pedagogical methods, the ever-evolving landscape of curriculum designs, and the overarching commitment to fostering educational equity. To investigate these multifaceted dynamics, we employed a data collection method that included the distribution of an online survey on platforms such as LinkedIn. Our survey reached and engaged 74 graduate students actively pursuing degrees in Business Analytics within the United States. This comprehensive research is the first and only one of its kind conducted in this context, and it serves as a vanguard exploration into the challenges and influences that shape the learning journey of Python among non-technical graduate Business Analytics students. The analytical insights derived from this research underscore the pivotal role of hands-on learning strategies, exemplified by practice exercises and assignments. Moreover, the study highlights the positive and constructive influence of collaboration and peer support in the process of learning Python. These invaluable findings significantly augment the existing body of knowledge in the field of business analytics. Furthermore, they offer an essential resource for educators and institutions seeking to optimize the educational experiences of non-technical students as they acquire essential Python skills.
基金This study was supported by the Start-Up Research Grant of Shenzhen University[20200807163056003]the Start-Up Research Grant[Peacock Plan:20191105534C]。
文摘Affective exercise experience as an emerging theoretical concept has great potential to provide a more nuanced understanding of individual factors that influence exercise behavior.However,concerning the Affective Exercise Experiences(AFFEXX)questionnaire,it has not been examined yet whether the structural score of the AFFEXX is a useful index to predict physical activity(refers to any bodily movement produced by skeletal muscles that requires energy expenditure).Furthermore,there is currently a gap in knowledge regarding the psychological mechanisms that can explain the relationship between affective exercise experiences and the level of physical activity(PA).In order to adress these gaps in the literature,we conducted two studies among Chinese collge students that aimed(i)to investigated whether the total score of the three AFFEXX-C constructs(antecedent appraisals,core affective exercise experiences,and attraction-antipathy towards exercise)is a relaible indicator that can be utilized in research and pratical settings and(ii)to evalute the specific psychological mechanisms that can explain the relationship between affective exercise experience and PA.In Study 1,we recruited 801 voluntary Chinese college students for bifactor and correlational analyses.In Study 2,875 Chinese college students were enrolled to verify our findings from Study 1 and to explore the aforementioned mechanism.Results from the bifactor analyses supported our hypothesis that the total scores of the three AFFEXX-C constructs can be used among Chinese college students to establish a link with PA.Additionally,our results suggested that core affective exercise experiences and attraction-antipathy mediated the relationship between antecedent appraisals and the level of moderate-to-vigorous intensity PA.Therefore,measuring affective exercise experiences using the AFFEXX-C,specifically the total scores of each individual construct may be a useful approach to predict future PA levels.
基金supported by the Foundation Strengthening Program Technology Field Foundation(2020-JCJQ-JJ-132)。
文摘The interception probability of a single missile is the basis for combat plan design and weapon performance evaluation,while its influencing factors are complex and mutually coupled.Existing calculation methods have very limited analysis of the influence mechanism of influencing factors,and none of them has analyzed the influence of the guidance law.This paper considers the influencing factors of both the interceptor and the target more comprehensively.Interceptor parameters include speed,guidance law,guidance error,fuze error,and fragment killing ability,while target performance includes speed,maneuverability,and vulnerability.In this paper,an interception model is established,Monte Carlo simulation is carried out,and the influence mechanism of each factor is analyzed based on the model and simulation results.Finally,this paper proposes a classification-regression neural network to quickly estimate the interception probability based on the value of influencing factors.The proposed method reduces the interference of invalid interception data to valid data,so its prediction accuracy is significantly better than that of pure regression neural networks.
基金supported by the Program of Humanities and Social Science of Education Ministry of China(Grant No.20YJA630008)the Ningbo Natural Science Foundation of China(Grant No.202003N4142)+1 种基金the Natural Science Foundation of Zhejiang Province,China(Grant No.LY20G010004)the K.C.Wong Magna Fund in Ningbo University,China.
文摘Accurate and real-time passenger flow prediction of rail transit is an important part of intelligent transportation systems(ITS).According to previous studies,it is found that the prediction effect of a single model is not good for datasets with large changes in passenger flow characteristics and the deep learning model with added influencing factors has better prediction accuracy.In order to provide persuasive passenger flow forecast data for ITS,a deep learning model considering the influencing factors is proposed in this paper.In view of the lack of objective analysis on the selection of influencing factors by predecessors,this paper uses analytic hierarchy processes(AHP)and one-way ANOVA analysis to scientifically select the factor of time characteristics,which classifies and gives weight to the hourly passenger flow through Duncan test.Then,combining the time weight,BILSTM based model considering the hourly travel characteristics factors is proposed.The model performance is verified through the inbound passenger flow of Ningbo rail transit.The proposed model is compared with many current mainstream deep learning algorithms,the effectiveness of the BILSTM model considering influencing factors is validated.Through comparison and analysis with various evaluation indicators and other deep learning models,the results show that the R2 score of the BILSTM model considering influencing factors reaches 0.968,and the MAE value of the BILSTM model without adding influencing factors decreases by 45.61%.
文摘Factor analysis of annual dynamics from 1879 to 2017 was carried out by the method of identification of stable regularities:maximum,minimum and average air temperature of Central England according to HadCET.The sample capacity was 139 rows.In factor analysis,time is excluded,and it acts only as a system-forming factor that ensures the relationship between the three parameters of climate and weather.Therefore,the adequacy of the dynamics models is taken into account in the diagonal cells of the correlation matrix.In addition to time,different lists of objects are possible in factor analysis.The coefficient of correlation variation,that is,a measure of the functional relationship between the parameters of the system(annual weather at the weather station in Central England)is 0.8230 for trends,0.8603 taking into account the annual dynamics of the four-membered model obtained from the computational capabilities of the software environment CurveExpert-1.40,and 0.9578 for the full up to the error of measurement wavelet analysis of the dynamics of the values of three factors.In all three methods of factor analysis,the meteorological parameter«average Annual temperature»was in the first place as the influencing variable,the«Maximum temperature»was in the second place,and the«Minimum temperature»was in the third place.As the dependent measure in these areas there are three kinds of temperature.The comparison shows that among the binary relations between the three temperatures,the average temperature on the maximum air temperature in the surface layer of the atmosphere has the greatest influence on the correlation coefficient 0.9765.At the same time,all six equations refer to strong connections,so there is a high quantum certainty between the three types of temperature.But when predicting the most meaningful essence showed the maximum temperature.
文摘In this study,the Five Facet Mindfulness Questionnaire which was adapted from the short form of the Five Facet Mindfulness Questionnaire was evaluated and this scale into neutrosophic form was converted and the results of the scale were compared for proposing new type confirmatory analysis procedure as well as developing neutrosophic scales.The exploratory factor analysis was used in the analysis of the data.Besides,test results were analyzed for Kaiser–Meyer–Olkin and Bartlett values,common factor variance values,scree plot graphs,and the principal component analysis results.The sample of the study consists of 194 students in mathematics departments at Bitlis Eren University and Igdır University in Turkey by convenience sampling method.A convenience sampling is a kind˘of non-probability sampling procedure in which the sample is obtained from a group of individuals easily accessible or reachable.The convenience sampling method was chosen in this study because the study aims to examine the structure of the measurement tool rather than the psychological characteristics of a particular population.First of all,it is observed that if any classical scale can be converted into a neutrosophic one.It is observed that the sub-dimensions of a neutrosophic scale as agree,disagree,and undecided might not have a similar factor structure to the classical one.Interestingly,in the factor analysis of the neutrosophic scale,both classical and the agreement part of the neutrosophic scales have the same factors,implying that the one-dimensional classical scale measures the agreement degree of the participants.When the factor analysis was conducted to disagreement and vagueness dimensions,it seemed that some factors were eliminated and even some new factors emerged,indicating that in human cognition those three dimensions can be taken as independent of each other,just as assumed by neutrosophic logic.The another important implication of the factor analysis is that the neutrosophic forms of any questionnaire can be used for the validity of the classical ones.Loads of items or their accumulation into factors are compared to the classical scale and the three-dimensional neutrosophic scale in the factor,so that the corresponding ones in the same factors and the items or factors that do not correspond to each other are eliminated.It is very similar to the Sieve of Eratosthenes,which is an ancient algorithm for finding prime numbers up to any given limit where each prime is taken as an independent base or dimension and multiples of the selected primes in a given interval are eliminated until there are only prime numbers left.Finally,the reliability of three independent dimensions of the neutrosophic forms of any questionnaire can also be used to check whether the measurement This work is licensed under a Creative Commons Attribution 4.0 International License,which permits unrestricted use,distribution,and reproduction in any medium,provided the original work is properly cited.954 CMES,2021,vol.129,no.2 tool is reliable.Low-reliability results in any dimensions may imply that the scale has some problems in terms of meaning,language,or other factors.
文摘Objectives:To establish long-term outcome of surgical pulmonary valve replacement(PVR)in congenital heart disease(CHD)and to identify risk factors for overall mortality,operative mortality,and repetitive PVR.Methods:This is a retrospective study of 375 surgical PVR in 293 patients who underwent surgical PVR for CHD between January 2000 and May 2020.We only included patients with index PVR with previous open-heart surgery regardless of the number of PVRs.The previous surgical history of patients who underwent PVR during the study period was also included.Patients who underwent the Rastelli operation,and those who underwent single PVR without previous open-heart surgery were excluded.Results:The median age of the patients at the time of surgical PVR was 14.9 years(Interquartile range,IQR,11.0–22.0).The median follow-up duration was 10.5 years(IQR,5.5–14.8 years).There were 3 patients with operative mortality(1.0%)and 15 patients with overall mortality(5.1%).The survival rate was 95.1%over 20 years follow-up period.Multivariate analysis demonstrated that more than 3 times of previous open-heart surgeries before surgical PVR,older age at the first operation,longer cardiopulmonary bypass(CPB)time and longer intensive care unit(ICU)stay were predictors for overall mortality.Patients who underwent surgical PVR after more than 3 times of previous open-heart surgeries had significantly higher mortality than those who underwent open-heart surgeries less than 3 times(P<0.001).Age younger than 10 years,male,multiple valve problems and longer ICU stay were significant predictors for repetitive PVR by multivariate analysis.Conclusions:Though surgical PVR has excellent long-term outcome,it should be performed with caution for those who previously underwent multiple open-heart surgeries,especially if patient received more than 3 times of open-heart surgeries.
基金Supported by Chnia Agriculture Research Systemthe Scientific Research Fund of the Key Technology and Research and Development of Barley Characteristic Agricultural Products Processing(XZ201901NA04)Development and Industrialization Application of Xizang Highland Barley Baijiu(XZ202001ZY0017N)。
文摘The purpose of this study was to explore the quality of the Tibetan native hulless barley variety in depth and to evaluate the characteristics of its processing quality using ratio analysis.For this study,10 native barley varieties were chosen with the detection of 24 quality indexes in order to build a system of comprehensive evaluation.The results of the factor analysis indicated that seven common factors with an eigenvalue greater than 1 were extracted,cumulatively accounting for 96.21%of the total variance.The first common factor,including ASP,GLU,SER,GLY,ARG,TYR and CYS contents,accounted for 33.82% of the variance.The second common factor,including ash,the total starch,soluble fiber,VB_(3),Cu,Mn,Na and beta-glucan contents,accounted for 19.46%of the variance.The third common factor,including the total dietary fiber,α-VE,K,Zn and glutelin.The fourth common factor,including B,Ba and prolamin,explained the barley starch character of the rheological property.The fifth common factor included crude fiber.The sixth and the seventh common factors did not account for a substantial amount of variance.According to the comprehensive evaluation model,the score consequence was as the following:Zangqing25>Pengnaigabu>Lhasa changhei>2004Qing21>Lhasa duanbai>Liangamu>Zhikonggaxia>lianmubai>Jiangreejiu>Longzihei.
基金Supported by the Research Fund of Heilongjiang Science & Technology Department(GB08D101-2)
文摘Taking a total of 13 areas in Heilongjiang commodity grain base as the research objects,9 indices are selected,which are regional GDP(X1),per capita GDP(X2),total value of tertiary industry(X3),financial revenue(X4),urban fixed assets investment(X5),average salary(X6),gross industrial output value(X7),total output value of farming,forestry,husbandry and fishing(X8),and retail sales of social consumer goods(X9).Based on this,evaluation index system of regional economy is established.According to the 2006-2008 Heilongjiang Statistical Yearbook,average values within 3 years are used as analytical data.Factor Analysis Method is adopted to establish regression model and to carry out comprehensive analysis.Result shows that Heilongjiang commodity grain base has extremely uneven regional economic development in different areas.According to the score order and actual situation,the 13 areas are divided into 4 types.The first and second types are Harbin and Daqing,respectively.The third type is Qiqihaer,Suihua,Mudanjiang and Jiamusi.And the forth type is Jixi,Shuangyashan,Heihe,Yichun,Qitaihe,Hegang and Daxinganling.Suggestions for the development of these areas are put forward.
文摘Women entrepreneurship is now a rapidly growing socio-economic phenomenon in developing country like Bangladesh.Women entrepreneurs’development in the SME sector is one of the most important challenge.The research aims to analyze the factors related to the development of women entrepreneurship in Small and Medium Enterprises(SMEs)sector of Bangladesh.The analysis is based on recent theoretical ideas that have been supported by empirical research findings.Both descriptive and inferential statistics were used in this research.To analyze the factors we have interviewed 232 women entrepreneurs of SME businesses.The main tool of research was a structured questionnaire.This study illustrates an analytical framework based on institutional theory,which focuses on three kinds of factors:regulative,normative,and cognitive.Regulative factors refer to different rules and regulations of the Government that facilitate women entrepreneurship development of SMEs sector in Bangladesh.Normative and cognitive factors include norms,rules,regulation,and values of society.This study provides suggestions on how to overcome barriers and also many significant policy implications to improve women entrepreneurship in SMEs sector of Bangladesh.
文摘<b><span style="font-family:Verdana;">Objective:</span></b><span style="font-family:Verdana;"> Despite efforts in describing the impact of shiftwork </span><span style="font-family:Verdana;">on</span><span style="font-family:""><span style="font-family:Verdana;"> the performance of health care workers, the perception of ambulance service staff is largely unexplored. This study attempted to develop the Perception of Effects of Shiftwork Questionnaire (PESQ) using a factor analysis approach to determine the underlying dimensions. </span><b><span style="font-family:Verdana;">Methods:</span></b><span style="font-family:Verdana;"> A 16-item Likert scale research inst</span><span style="font-family:Verdana;">rument, designed to gather information about the perceived effects of</span><span style="font-family:Verdana;"> shiftwork</span></span><span style="font-family:Verdana;"> on</span><span style="font-family:""><span style="font-family:Verdana;"> the respondents’ health, social relationships, and career quality, was floated to 375 ambulance services personnel in Saudi Arabia during March and April 2021. </span><b><span style="font-family:Verdana;">Results:</span></b><span style="font-family:Verdana;"> Based on factor analysis, the questionnaire has three dimensions with varying reliability, namely “perceived effects on social relationship” (</span><i><span style="font-family:Verdana;">α</span></i><span style="font-family:Verdana;"> = 0.815), perceived effects on health (</span><i><span style="font-family:Verdana;">α</span></i><span style="font-family:Verdana;"> = 0.787) and “perceived </span><span><span style="font-family:Verdana;">effects on career quality” (</span><i><span style="font-family:Verdana;">α</span></i><span style="font-family:Verdana;"> = 0.602). Over-all, the research instrument had an acceptable internal consistency (</span><i><span style="font-family:Verdana;">α</span></i><span style="font-family:Verdana;"> = 0.829). </span><b><span style="font-family:Verdana;">Conclusion:</span></b><span style="font-family:Verdana;"> The three-dimension model was analyzed simultaneously using parallel analysis</span></span><span style="font-family:Verdana;"> and confirms that the three-factor model is the most ideal for the research instrument. Further research, however, is recommended to improve the internal consistency of the items which measure the perceived effects on career quality.
基金the Exploratory Research Grant Scheme(ERGS)of Universiti Teknologi MARA(UiTM)Malaysia(No.ERGS/1/2013/SSl11/UITM/01/01)High-Level Talents Introduction Funding of Haixi Research Institute,the Chinese Academy of Sciences(No.19Q3671boa).
文摘Over the past years,there has been an expanding intrigued in building refurbishment projects because of the alter in financial conditions and the accentuation on sustainable development.Increasing demand for building refurbishment projects will lead to an increase in organizational interactions in the construction works as building refurbishment works involve interactions among many different organizations and it can cause Inter-Organizational conflict(IOC)among organizations involved in projects.This paper adopted an Exploratory Factor Analysis(EFA)approach to analyses IOC in building refurbishment projects.For this study,a fivepoint Likert Scale was adopted to ensure the instruments of the study are reliable.The researcher ultimately sent questionnaires as a web-link and email invitation to 1050 construction firms and 733 architectural firms.The questionnaire sent to managers and professionals from construction and architectural firms in Malaysia.Finally,one-hundred-seventy-nine(179)refurbishment projects formed a database for this paper.The finding of this paper shows the IOC factors that contribute to the improve the performance of building refurbishment project can be conflict during the construction stage,conflict between the client and the consultant,task expectations,basic responsibilities,final duration,project’s goals,conflict between the client and the contractor,final cost,final quality,standards of behaviors,conflict between the contractor and the consultant,interference and conflict during the design stage.
文摘Confirmatory factor analysis (CFA) refers to the FA procedure with some loadings constrained to be zeros. A difficulty in CFA is that the constraint must be specified by users in a subjective manner. For dealing with this difficulty, we propose a computational method, in which the best CFA solution is obtained optimally without relying on users’ judgements. The method consists of the procedures at lower (L) and higher (H) levels: at the L level, for a fixed number of zero loadings, it is determined both which loadings are to be zeros and what values are to be given to the remaining nonzero parameters;at the H level, the procedure at the L level is performed over the different numbers of zero loadings, to provide the best solution. In the L level procedure, Kiers’ (1994) simplimax rotation fulfills a key role: the CFA solution under the constraint computationally specified by that rotation is used for initializing the parameters of a new FA procedure called simplimax FA. The task at the H level can be easily performed using information criteria. The usefulness of the proposed method is demonstrated numerically.
基金the National Natural Science Foundation of China(61873283)the Changsha Science&Technology Project(KQ1707017)the innovation-driven project of the Central South University(2019CX005).
文摘Dissolved oxygen(DO)is an important indicator of aquaculture,and its accurate forecasting can effectively improve the quality of aquatic products.In this paper,a new DO hybrid forecasting model is proposed that includes three stages:multi-factor analysis,adaptive decomposition,and an optimizationbased ensemble.First,considering the complex factors affecting DO,the grey relational(GR)degree method is used to screen out the environmental factors most closely related to DO.The consideration of multiple factors makes model fusion more effective.Second,the series of DO,water temperature,salinity,and oxygen saturation are decomposed adaptively into sub-series by means of the empirical wavelet transform(EWT)method.Then,five benchmark models are utilized to forecast the sub-series of EWT decomposition.The ensemble weights of these five sub-forecasting models are calculated by particle swarm optimization and gravitational search algorithm(PSOGSA).Finally,a multi-factor ensemble model for DO is obtained by weighted allocation.The performance of the proposed model is verified by timeseries data collected by the pacific islands ocean observing system(PacIOOS)from the WQB04 station at Hilo.The evaluation indicators involved in the experiment include the Nash–Sutcliffe efficiency(NSE),Kling–Gupta efficiency(KGE),mean absolute percent error(MAPE),standard deviation of error(SDE),and coefficient of determination(R^(2)).Example analysis demonstrates that:①The proposed model can obtain excellent DO forecasting results;②the proposed model is superior to other comparison models;and③the forecasting model can be used to analyze the trend of DO and enable managers to make better management decisions.
文摘Learning style,aiming at language learner,is a hot issue of second language acquisition.The article first reviews the various definitions of learning style.From the perspective of cognition,three influence factors of Chinese students' learning styles are analyzed.Suggestions are proposed for teachers to help students develop learning styles.
