• Journal of Korean Neurosurgical Society
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• v.64 no.1
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• pp.125-135
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• 2021

Objective : This study aimed to validate the Korean version of the Repeatable Battery for the Assessment of Neuropsychological Status Update (K-RBANS). Methods : We performed a retrospective analysis of 283 psychiatric and neurosurgery patients. To investigate the convergent validity of the K-RBANS, correlation analyses were performed for other intelligence and neuropsychological test results. Confirmatory factor analysis was used to test a series of alternative plausible models of the K-RBANS. To analyze the various capabilities of the K-RBANS, we compared the area under the receiver operating characteristic (ROC) curves (AUC). Results : Significant correlations were observed, confirming the convergent validity of the K-RBANS among the Total Scale Index (TSI) and indices of the K-RBANS and indices of intelligence (r=0.47-0.81; p<0.001) and other neuropsychological tests at moderate and above significance (r=0.41-0.63; p<0.001). Additionally, the results testing the construct validity of the K-RBANS showed that the second-order factor structure model (model 2, similar to an original factor structure of RBANS), which includes a first-order factor comprising five index scores (immediate memory, visuospatial capacity, language, attention, delayed memory) and one higher-order factor (TSI), was statistically acceptable. The comparative fit index (CFI) (CFI, 0.949) values and the goodness of fit index (GFI) (GFI, 0.942) values higher than 0.90 indicated an excellent fit. The root mean squared error of approximation (RMSEA) (RMSEA, 0.082) was considered an acceptable fit. Additionally, the factor structure of model 2 was found to be better and more valid than the other model in χ2 values (Δχ2=7.69, p<0.05). In the ROC analysis, the AUCs of the TSI and five indices were 0.716-0.837, and the AUC of TSI (AUC, 0.837; 95% confidence interval, 0.760-0.896) was higher than the AUCs of the other indices. The sensitivity and specificity of TSI were 77.66% and 78.12%, respectively. Conclusion : The overall results of this study suggest that the K-RBANS may be used as a valid tool for the brief screening of neuropsychological patients in Korea.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.249-254
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• 2007

The main bodies of housing markets of today need to carry out a systematic and objective feasibility analysis even from the step of planning in order to succeed in a diverse and complex market environment. Therefore, it is meaningful to understand this housing market environment and propose a necessary model for the feasibility analysis of hosing business. In this vein, the aim of this study was to extract an actual and practical feasibility analysis factor and its importance for housing market, and then present and apply a feasibility analysis factor model to an on-site example, in order to verify the model's validity. For this, the investigator interviewed with and carried out a questionnaire survey of experts in housing development projects. Study findings are as follows:First, the feasibility analysis factor, derived in this study, could provide a ground to evaluate the feasibility of subject projects in the planning of development through an analysis index. Second, when feasibility is under the level of carrying out the projects, it is possible to reexamine the projects through extracting analysis factors of which points are under the standard and via a feedback process for improvable analysis factors. Therefore, the result of applying the feasibility analysis model of this study to actual housing development projects analytically shows that the model could provide a practical evaluation criterion to the person in charge of project development through an analysis index.

• Journal of Korea Technology Innovation Society
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• v.20 no.4
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• pp.1262-1287
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• 2017

Recently, forecasting for next-generation technologies have influenced the competitiveness of companies. However, in previous studies, only extract factors influencing the adoption of technology have been investigated. Also, there are few researches on the importance of each decision factors or the competition between technologies. In this research, Lotka-Volterra model is used to confirm the technological competition in the new technology choice timing when the competition is intensified due to the emergence of new technologies. For purpose of this study, estimate the LVC model based on the data of the past competition and then derived the factors affecting the technology of competition and substitution from the literature survey. After that, we confirmed the factor value between the past and the present technology competition. The difference between the factor values derived from the previous step is used to revise the model estimated from the past data base. At this stage, regression analysis is used to derive the importance of each factor and use it as the weight. Through the correction model, the competitiveness is identified through 1:1 comparison with competition candidate technology and existing dominant design technology. In this research, we quantitatively propose the possibility that a specific technology can become a dominant design in the next generation, based on the difference in factor values and importance. This results will help the company's R&D strategy and decision making.

• Journal of the Korea Institute of Building Construction
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• v.22 no.6
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• pp.619-630
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• 2022

The concrete mix design and compressive strength evaluation are used as basic data for the durability of sustainable structures. However, the recent diversification of mixing factors has created difficulties in calculating the correct mixing factor or setting the reference value concrete mixing design. The purpose of this study is to design a predictive model of bidirectional analysis that calculates the mixing elements of ternary concrete using deep learning, one of the artificial intelligence techniques. For the DNN-based predictive model for calculating the concrete mixing factor, performance evaluation and comparison were performed using a total of 8 models with the number of layers and the number of hidden neurons as variables. The combination calculation result was output. As a result of the model's performance evaluation, an average error rate of about 1.423% for the concrete compressive strength factor was achieved. and an average MAPE error of 8.22% for the prediction of the ternary concrete mixing factor was satisfied. Through comparing the performance evaluation for each structure of the DNN model, the DNN5L-2048 model showed the highest performance for all compounding factors. Using the learned DNN model, the prediction of the ternary concrete formulation table with the required compressive strength of 30 and 50 MPa was carried out. The verification process through the expansion of the data set for learning and a comparison between the actual concrete mix table and the DNN model output concrete mix table is necessary.

• Journal of the Korean Society of Clothing and Textiles
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• v.16 no.3 s.43
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• pp.181-195
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• 1992

The purposes of this study were to investigate 1) the effect of body exposure and color of a woman's suit on the perception of modesty, and 2) the effect of perceiver's sex and age on impression formed by the function of clothing variables. The instrument of this study consisted of a response scale and stimuli. Thirteen items of 7-point semantic differential scales were developed to measure the perceiver's impression on wearer's modesty. Stimuli were color pictures of a model wearing one of 8 types of suit constructed by a 2 $\times$ 2 $\times$ 2 factorial design. The manipulation of each level of the clothing variables were: color of the suit by black and red, leg exposure by varying skirt lengths to a Chanel-line and mini skirt, and neck exposure by shirt collar blouse and scarf. Two models, representing typical female college students living in Seoul, were selected to eliminate model effect. The sample include 384 subjects, consisting of 4 groups of male and female college students and middle aged men and women. Eight experimental groups were randomly assigned to one of eight stimuli based on between-subject design. One half of each group responded to model 1 and the other half to model 2 of same stimulus. Responses to the semantic differential scales were factor analyzed (pc model, Varimax rotation) to identify factors constructing impression of modesty. Two factors emerged regard­less of subgroups; Elegance and Extroversion factor. The first factor was found to be dominant, accounting for 60 percent of the total variance. The other accounted for just 11 percent. Multidimensional ANOVA (5-way, 3-way) was conducted to test the effect of the clothing variables against two factors identified from the factor analysis. Leg exposure was the most powerful variable affecting the impression of Elegance and Extroversion factor for all per. ceiver subgroups. Neck exposure had primary effect on the impression of Elegance, whereas it partially influenced that of Extroversion. Color of suit had only partial effect on the impression of Extroversion. Hypothesis I was partially supported from the findings above. The effect of perceiver's age and sex on impression by the function of clothing variables was tested by comparing the result between four subgroups. In forming an impression of the wearer's modesty, male college students were least affected by the manipulation of clothing variables, while middle aged males were affected most. In the female groups, there was no age difference and they fell between the male groups in the degree to which they were affected. Hypothesis II was supported only by age difference in two male groups, and by sex difference in two student groups.

• Journal of Industrial Convergence
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• v.20 no.11
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• pp.75-83
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• 2022

This study analyzes whether investor sentiment and liquidity explain the momentum phenomenon in the Korean stock market and whether it is a risk factor for the asset pricing model. The empirical analysis used the monthly returns of non-financial companies listed on the stock market during the period 2000-2021. As a result of the analysis, first, it was found that there is a momentum effect in Korea. This is the same result as the previous study, and since 2000, the momentum effect has been accepted as a general phenomenon in the Korean stock market. Second, if we look at the portfolio based on investor sentiment, investor sentiment is influencing momentum. In particular, when investor sentiment is negative, the return on the winner portfolio is high. Third, as a result of the analysis based on liquidity, the momentum effect disappears and a reversal effect appears. Fourth, it was found that investor sentiment and liquidity influence the momentum effect. This is a result of the strong momentum effect in the illiquid stock group with negative investor sentiment. Fifth, as a result of analyzing the effect of each factor on stock returns, it was found that both investor psychology and liquidity factors have a significant impact on returns. The estimated results provide evidence that the inclusion of these two factors in the Carhart four-factor model significantly increases the predictive power of the model. Therefore, it can be said that investor sentiment factors and liquidity factors are important factors in determining stock returns.

• Journal of Korean Academy of Nursing
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• v.45 no.3
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• pp.429-438
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• 2015

Purpose: This study was conducted to develop key performance indicators (KPIs) for home care nursing (HCN) based on a balanced scorecard, and to construct a performance prediction model of strategic objectives using the Bayesian Belief Network (BBN). Methods: This methodological study included four steps: establishment of KPIs, performance prediction modeling, development of a performance prediction model using BBN, and simulation of a suggested nursing management strategy. An HCN expert group and a staff group participated. The content validity index was analyzed using STATA 13.0, and BBN was analyzed using HUGIN 8.0. Results: We generated a list of KPIs composed of 4 perspectives, 10 strategic objectives, and 31 KPIs. In the validity test of the performance prediction model, the factor with the greatest variance for increasing profit was maximum cost reduction of HCN services. The factor with the smallest variance for increasing profit was a minimum image improvement for HCN. During sensitivity analysis, the probability of the expert group did not affect the sensitivity. Furthermore, simulation of a 10% image improvement predicted the most effective way to increase profit. Conclusion: KPIs of HCN can estimate financial and non-financial performance. The performance prediction model for HCN will be useful to improve performance.

• Computational Structural Engineering
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• v.6 no.4
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• pp.57-66
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• 1993

The p-version crack model based on integrals of Legendre polynomial and virtual crack extension method is proposed with its potential for application to stress intensity factor computations in linear elastic fracture mechanics. The main advantage of this model is that the data preparation effort is minimal because only a small number of elements are used and high accuracy and the rapid convergence can be achieved in the vicinity of crack tip. There are two important findings from this study. Firstly, the limit value, the strain energy of the exact solution, can be estimated with successive three p-version approximations by ascertaining that the approximations enter the asymptotic range. Secondly, the rate of convergence of p-version model is almost twice that of h-version model on the basis of uniform or quasiuniform mesh refinement for the cracked panel problem subjected to tension.

• Journal of Korean Society for Quality Management
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• v.31 no.1
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• pp.21-41
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• 2003

The purpose of this research is to identify if psychological temptation, site quality and sense of community influence user's flow and addiction and if causalities among flow, addiction, customer satisfaction and customer loyalty are different between Korean and Japanese online games. To perform our research, we use MCSF(Multi-group Confirmatory Factor Analysis) and MSEM(Multi-group Structural Equation Model). The empirical results of SEM(Structural Equation Model) including high-order factor analysis indicate that all of paths in our model are the same for both countries. Therefore, site quality and sense of community have impacts on the flow, while on the other hand, psychological temptation has impacts on the addiction. Customer satisfaction and loyalty are positively related not with the addiction but with the flow. In addition, customer loyalty is significantly influenced by the flow and the customer satisfaction. In Conclusion, the empirical results of MSEM(Multi-group Structural Equation Model) indicate sense of community to flow, flow to loyalty and customer satisfaction to loyalty are different between Korea and Japan. This indicates that companies to penetrate into Japa online game industry should have a concern with Japanese Social and Cultural features and to develop strategies which correspond with Japanese culture.

• International Journal of Highway Engineering
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• v.15 no.3
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• pp.93-101
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• 2013

PURPOSES : This study is to investigate the relationship of socioeconomic characteristics and road network structure with traffic growth patterns. The findings is to be used to tweak traffic forecast provided by traditional four step process using relevant socioeconomic and road network data. METHODS: Comprehensive statistical analysis is used to identify key explanatory variables using historical observations on traffic forecast, actual traffic counts and surrounding environments. Based on statistical results, a multiple regression model is developed to predict the effects of socioeconomic and road network attributes on traffic growth patterns. The validation of the proposed model is also performed using a different set of historical data. RESULTS : The statistical analysis results indicate that several socioeconomic characteristics and road network structure cleary affect the tendency of over- and under-estimation of road traffics. Among them, land use is a key factor which is revealed by a factor that traffic forecast for urban road tends to be under-estimated while rural road traffic prediction is generally over-estimated. The model application suggests that tweaking the traffic forecast using the proposed model can reduce the discrepancies between the predicted and actual traffic counts from 30.4% to 21.9%. CONCLUSIONS : Prediction of road traffic growth patterns based on surrounding socioeconomic and road network attributes can help develop the optimal strategy of road construction plan by enhancing reliability of traffic forecast as well as tendency of traffic growth.