• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.32 no.1
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• pp.64-77
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• 2022

Objectives: The purpose of this study is to objectify the level of case management performance and the factors influencing performance, to improve the case management performance at the Korea Worker's Compensation & Welfare Service (KWCWS) on the basis of the recognition of the objective realities of case management by job coordinators at the KWCWS, to develop a model of case management fit for the KWCWS, and to provide a basis for establishing guidelines for standardized case management. Methods: A total of 156 questionnaires were distributed to job coordinators at the KWCWS's headquarters, six regional headquarters, and 55 branches. One hundred forty-one questionnaires were collected and 126 were analyzed statistically using SPSS 21.0. Factor analysis and reliability analysis were conducted to verify the validity and reliability of the main measurement items in the research model. Frequency analysis was conducted for general characteristics of survey subjects. Frequency analysis or descriptive statistics were conducted to identify the level of independent variables (case manager's individual variables, job variables, institutional and organizational variables). Dependent variables (case management performance) and the degree of correlation were analyzed through correlation analysis between research variables. Multiple regression analysis and hierarchical regression analysis were conducted to examine the effect of independent variables on case management performance. Results: The results of the study showed that the level of overall performance in the five stages of case management was ordinary, with an average level of 3.45 on a 5-point scale. Levels of performance by step were institutional approach and intake (3.69), assessment (3.63), goal setting and intervention planning (3.46), implementation of intervention plan (3.32), and evaluation and termination (3.20), in that order. The explanatory power of case management performance (overall) by case managers with the KWCWS was case manager's institutional and organizational variables, job variables, and individual variables, in that order. At each stage of case management, the explanatory power of a case manager's institutional and organizational variables was found to be the greatest. The model changes at each stage of case management assume similar aspects statistically. In hierarchical regression analysis, it was institutional support that had a significant effect on case management performance (overall), and institutional support had the greatest effect. The results of multiple regression analysis in which all variables are input simultaneously showed that institutional support and expertise as well as self-efficacy had a positive effect. However, case management work experience, expertise (technology), and autonomy were found to have a negative effect during the stage of case management performance. Conclusions: As a result of the study, it was confirmed that raising the case manager's expertise and support from the institution and organization are important factors to improve the level of case management performance. The research also derived practical ways of reinforcement of case manager capacity, institutional and organizational support, operation of rehabilitation-case management teams, and occupational health-related aspects.

• Asia pacific journal of information systems
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• v.20 no.4
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• pp.53-79
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• 2010

The study was originated from recognition that project participants' satisfaction should be Improved to raise project performance and to make progress of a successful project since the above dissatisfaction was operated as a danger factor of the project. The study selected one large-scale sample project and attempted measuring characteristics of the project, participants' satisfaction and project performance with the whole project participants. The study analyzed correlations between individual level (team members) and group level (development team), and examined what effect a sub project manager under complicated hierarchical organization of the large-scale project, namely PL (project leader)'s leadership style had on each individual project participant's satisfaction and what effect project uncertainty in organization/technology environment had on project participants' satisfaction and project performance. The study verified that development team (group) had an effect on team member (individual)-level project participants' satisfaction by disclosing that there was a significant dispersion among groups within project participants' satisfaction by each individual. It is analyzed that it is necessary to make improvement through approach by each pertinent team to raise individual-level project participants' satisfaction. The study also verified PL's ideal leadership under strict methodology and hierarchical control of the large-scale project. Based on the verification of the hypotheses, the results of the analysis were produced as follows. First, the development team affects the satisfaction level that an individual has when he/she participates in a project. This suggests that the satisfaction with project participation should be improved at the team level. In addition, the project management style and leadership orientation of the manager of a sub project who is mostly affected by the team proved to have a direct influence on the satisfaction with project participation and project performances. Second, both the performance-oriented leadership and the relationship-oriented leadership of the PL of the development team were verified to have a significant effect on the satisfaction of the team members associated with project participation. In other words, when the team members recognize that the PL of the development team shows both the performance-oriented leadership and the relationship-oriented leadership, their satisfaction with project participation increases accordingly. Third, it was verified that the uncertainty of the organizational environment significantly affects the satisfaction level when the PL of the development team exerts a relationship-oriented and performance-oriented leadership. The higher the uncertainty of the organizational environment is, the more the satisfaction with project participation decreases whereas the relationship-oriented leadership has a more positive effect on the satisfaction than the performance-oriented leadership style. Fourth, when the PL of the development team exerts the relationship-related and performance-related leadership, the uncertainty of the technological environment has a significant influence on the satisfaction level. The higher the uncertainty of the technological environment is, the more the satisfaction with project participation decreases whereas the performance-oriented leadership has a more positive effect on the satisfaction than the relationship-oriented leadership style. The result of the research on the uncertainty of the project environment suggests that when the development team leader exerts a relationship-oriented and performance-oriented leadership style, the uncertainty of the organizational environment has a significant effect on the satisfaction with project participation; the higher the uncertainty of the organizational environment, the more the satisfaction level decreases, and the relationship-oriented leadership style affects the satisfaction level more positively than the performance-oriented leadership style. In addition, when the development team leader displays a relationship-oriented and performance-oriented leadership style, the uncertainty of the technological environment has a significant effect on the satisfaction with project participation; the higher the uncertainty of the technological environment. the more the satisfaction level decreases. The performance-oriented leadership style as well affects the satisfaction level more positively than the relationship-oriented leadership style. Based on the above results, the research provides the following implications when handling multiple concurrent projects. First, the satisfaction with the participation in the multiple concurrent projects needs to be enhanced at the team (group) level. Second. the manager of the project team, particularly the middle managers should have both a performance-oriented and relationship (task and human)-oriented attitude and exert a consolidated leadership in order to improve the satisfaction of team members with project participation and their performances. Third, as the uncertainty factor of the technological and organizational environment among the characteristics factors of the project has room for methodological improvement depending on one's effort even though there are some complications, we need to continuously prevent and control the risks resulting from the uncertainties of the technological and organizational environment of the project in order to enhance the satisfaction of project participation and project performances. Fourth, the performance (task)-oriented leadership is required when there is uncertainty in a technological environment while the relationship (human)-oriented leadership is required when there is uncertainty in an organizational environment. This research has the following limitations. First, this research intended to select one large-sized sample project and measure the project characteristics, the satisfaction of all the participants associated with project participation, and their performances. Therefore, it is inappropriate to generalize and apply the result of this result onto other numerous projects. Second, as this case study entailed a survey to measure the characteristics factors and performance of the project, since the result value was based on the perception of project team members, the data may have insufficient objectivity. Third, though this research targeted on all the project participants, some development teams did not provide sufficient data and questionnaires were collected from some specific development teams among the 23 development teams, causing a significant deviation in the response rate among the development teams. Therefore, we need to continuously conduct the follow-up researches making comparisons among the multiple projects, and centering on the characteristics factors of the project and its satisfaction level.

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.123-137
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• 2018

A nonlinear mixed effects model is mainly used to analyze repeated measurement data in various fields. A nonlinear mixed effects model consists of two stages: the first-stage individual-level model considers intra-individual variation and the second-stage population model considers inter-individual variation. The individual-level model, which is the first stage of the nonlinear mixed effects model, estimates the parameters of the nonlinear regression model. It is the same as the general nonlinear regression model, and usually estimates parameters using the least squares estimation method. However, the least squares estimation method may have a problem that the estimated value of the parameters and standard errors become extremely large if the assumed nonlinear function is not explicitly revealed by the data. In this paper, a new estimation method is proposed to solve this problem by introducing the ridge regression method recently proposed in the nonlinear regression model into the first-stage individual-level model of the nonlinear mixed effects model. The performance of the proposed estimator is compared with the performance with the standard estimator through a simulation study. The proposed methodology is also illustrated using quantitative high throughput screening data obtained from the US National Toxicology Program.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.10a
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• pp.199-202
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• 1996

Although numerous studies demonstrate that one technique outperforms the others for a given data set, there is often no way to tell a priori which of these techniques will be most effective to solve a specific problem. Alternatively, it has been suggested that a better approach to classification problem might be to integrate several different forecasting techniques by combining their results. The issues of interest are how to integrate different modeling techniques to increase the prediction performance. This paper proposes the post-model integration method, which means integration is performed after individual techniques produce their own outputs, by finding the best combination of the results of each method. To get the optimal or near optimal combination of different prediction techniques. Genetic Algorithms (GAs) are applied, which are particularly suitable for multi-parameter optimization problems with an objective function subject to numerous hard and soft constraints. This study applied three individual classification techniques (Discriminant analysis, Logit and Neural Networks) as base models to the corporate failure prediction context. Results of composite prediction were compared to the individual models. Preliminary results suggests that the use of integrated methods will offer improved performance in business classification problems.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.3
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• pp.163-173
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• 1997

Although numerous studies demonstrate that one technique outperforms the others for a given data set, it is hard to tell a priori which of these techniques will be the most effective to solve a specific problem. It has been suggested that the better approach to classification problem might be to integrate several different forecasting techniques by combining their results. The issues of interest are how to integrate different modeling techniques to increase the predictive performance. This paper proposes the post-model integration method, which tries to find the best combination of the results provided by individual techniques. To get the optimal or near optimal combination of different prediction techniques, Genetic Algorithms (GAs) are applied, which are particularly suitable for multi-parameter optimization problems with an object function subject to numerous hard and soft constraints. This study applies three individual classification techniques (Discriminant analysis, Logit model and Neural Networks) as base models for the corporate failure prediction. The results of composite predictions are compared with the individual models. Preliminary results suggests that the use of integrated methods improve the performance of business classification.

• STI Policy Review
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• v.6 no.2
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• pp.1-23
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• 2015

This study aims to contribute to the debate over the age-productivity relationships in scientific and technological research. For this purpose, we conducted an empirical experiment employing a time-series cross-section dataset derived from the KRI of the NRF containing data on individual researchers of fifty major universities in Korea covering the period of 2008-2013. This study has found that: (1) there exists an inverse U-shaped age-productivity relationship at the level of individual researchers; (2) the impact of the average age of a research group on the productivity of individual researchers varies across fields; (3) male and female researchers move along different age-productivity curves; and (4) the inverse U-shaped age-productivity relationship also holds at the level of organizations. The results suggest that the aging of researchers in Korea will soon reach the stage where serious losses in research productivity become a reality. Yet, it is not so clear whether the observed decline in the performance of older researchers is due to declining cognitive capability, which is an unavoidable result of aging, or to declining motivation, which results from an institutional system that discourages older researchers' research activities (such as reduced access to research opportunities or mandatory retirement). What is clear is that it is inevitable for the Korean science system to change the current seniority- and age-based organizational system into one of higher adaptability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.1
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• pp.196-212
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• 2014

Facial expression recognition is an important part in emotional interaction between human and machine. This paper proposes a facial expression recognition approach based on multi-classifier fusion with stacking algorithm. The kappa-error diagram is employed in base-level classifiers selection, which gains insights about which individual classifier has the better recognition performance and how diverse among them to help improve the recognition accuracy rate by fusing the complementary functions. In order to avoid the influence of the chance factor caused by guessing in algorithm evaluation and get more reliable awareness of algorithm performance, kappa and informedness besides accuracy are utilized as measure criteria in the comparison experiments. To verify the effectiveness of our approach, two public databases are used in the experiments. The experiment results show that compared with individual classifier and two other typical ensemble methods, our proposed stacked ensemble system does recognize facial expression more accurately with less standard deviation. It overcomes the individual classifier's bias and achieves more reliable recognition results.

• Nuclear Engineering and Technology
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• v.51 no.1
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• pp.293-302
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• 2019

Many researches have been done to develop and improve the performance of personal (individual) dosimeter response to cover a wide of neutron energy range (from thermal to fast). Depending on the individual category of the dosimeter, the semiconductor sensor has been used to simplify and lightweight. In this plan, it's very important to have a fairly accurate counting of doses rate in different energies. With a general design and single-sensor simulations, all optimal thicknesses have been extracted. The performance of the simulation scheme has been compared with the commercial and laboratory samples in the world. Due to the deviation of all dosimeters with a flat energy response, in this paper, has been used an idea of one semi-conductor sensor to have the flat energy-response in the entire neutron energy range. Finally, by analyzing of the sensors data as arrays for the first time, we have reached a nearly flat and acceptable energy-response. Also a comparison has been made between Lucite-PMMA ($H_5C_5O_2$) and polyethylene-PE ($CH_2$) as a radiator and $B_4C$ has been studied as absorbent. Moreover, in this paper, the effect of gamma dose in the dosimeter has been investigated and shown around the standard has not been exceeded.

• International journal of steel structures
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• v.18 no.5
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• pp.1508-1524
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• 2018

Hysteretic energy dissipating devices (HEDDs) have been increasingly applied to building construction to improve the seismic performance. The seismic responses of such damped structures are significantly affected by HEDD's structural properties. An accurate investigation on the propagation of HEDD's structural properties is required for reasonable evaluation of the seismic performance of a structure. This study aims to develop simplified methods that can estimate the collective uncertainty-propagation to the seismic response of damped structures employing HEDDs. To achieve this, three- and six-story steel moment-resisting frames were selected and the propagations of the individual HEDD's property-uncertainties were evaluated when they are subjected to various levels of seismic demand. Based on the result of individual uncertainty-propagations, a simplified method is proposed to evaluate the variation of seismic response collectively propagated by HEDD's property-uncertainties and is verified by comparing with the exact collective uncertainty-propagation calculated using the Monte Carlo simulation method. The proposed method, called as a modified SRSS method in this study, is established from a conventional square root of the sum of the squares (SRSS) method with the relative contributions of the individual HEDD's property-uncertainty propagations. This study shows that the modified SRSS method provides a better estimation than the conventional SRSS method and can significantly reduce computational time with reasonable accuracy compared with the Monte Carlo simulation method.

• 한국HCI학회:학술대회논문집
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• 2008.02b
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• pp.78-84
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• 2008

The traditional intelligent teachable system has mainly focused on knowledge and cognition. It has overlooked motivational aspects of learners. Motivation is an important factor in learning making learners to have interests in a given task and persist it. Although the systems include cognitive as well as motivational factors, the effects of ITS on interest are not equivalent depending on individual characteristics. This study is to investigate how influence learners' response patterns to their interests and also examined effects of individual characteristics on interest in teachable agent (TA). In this experiment, we used KORI which is a new type of ITS that learner teach computer agent based on the instructional method of learning by teaching'. In the beginning of experiments, metacognition, achievement goal orientation and self-efficacy were measured as individual characteristics. Then, participants were asked to use KORI at home during 10 days. After using KORI the level of interest were measured. The result showed that metacognition was positively related with interest, whereas performance goal orientation and mastery goal orientation were negatively related to interest. It suggests t hat different individual characteristics should be considered to promote learners' intrinsic motivation in TA.