• Proceedings of the Korean Statistical Society Conference
• /
• 2005.11a
• /
• pp.187-192
• /
• 2005

For the problem of variable selection in linear models, we consider the errors are correlated with V covariance matrix. Hocking's theorems on the effects of the overfitting and the undefitting in linear model are extended to the less than full rank and correlated error model, and to the ANCOVA model

• Journal of the Korea Safety Management & Science
• /
• v.1 no.1
• /
• pp.91-100
• /
• 1999

We propose a decision model to incorporates the values assigned by a group of experts on different factors in selecting robots. Using this model, SN ratio of taguchi method for each of subjective factors as well as values of weights are used in this comprehensive method for robot selection. A numerical example is presented to illustrate the model and to show a rank reversal when compared to a model that does not eliminate extreme values and eliminates the highest and lowest experts' values allocating the weights and the subjective factors.

• Proceedings of the Safety Management and Science Conference
• /
• 1999.11a
• /
• pp.537-540
• /
• 1999

We propose a decision model to incorporates the values assigned by a group of experts on different factors in selecting robots. Using this model, SN ratio of taguchi method for each of subjective factors as well as values of weights are used in this comprehensive method for robot selection. A numerical example is presented to illustrate the model and to show a rank reversal when compared to a model that does not eliminate extreme values and eliminates the highest and lowest experts' values allocating the weights and the subjective factors.

• Current Optics and Photonics
• /
• v.5 no.4
• /
• pp.431-443
• /
• 2021

Sparse unmixing has been proven to be an effective method for hyperspectral unmixing. Hyperspectral images contain rich spectral and spatial information. The means to make full use of spectral information, spatial information, and enhanced sparsity constraints are the main research directions to improve the accuracy of sparse unmixing. However, many algorithms only focus on one or two of these factors, because it is difficult to construct an unmixing model that considers all three factors. To address this issue, a novel algorithm called multiview-based spectral weighted and low-rank row-sparsity unmixing is proposed. A multiview data set is generated through spectral partitioning, and then spectral weighting is imposed on it to exploit the abundant spectral information. The row-sparsity approach, which controls the sparsity by the l_2,0 norm, outperforms the single-sparsity approach in many scenarios. Many algorithms use convex relaxation methods to solve the l_2,0 norm to avoid the NP-hard problem, but this will reduce sparsity and unmixing accuracy. In this paper, a row-hard-threshold function is introduced to solve the l_2,0 norm directly, which guarantees the sparsity of the results. The high spatial correlation of hyperspectral images is associated with low column rank; therefore, the low-rank constraint is adopted to utilize spatial information. Experiments with simulated and real data prove that the proposed algorithm can obtain better unmixing results.

• Journal of the Korean Data and Information Science Society
• /
• v.19 no.2
• /
• pp.487-496
• /
• 2008

Recently survival analysis becomes popular in a variety of fields so that a number of statistical packages are developed for analyzing the survival model. In this paper, several types of survival models are introduced and considered briefly. In addition, widely used three packages(SAS, SPSS, and STATA) for survival data are reviewed and their characteristics are investigated.

• Journal of the military operations research society of Korea
• /
• v.24 no.1
• /
• pp.157-175
• /
• 1998

This paper develops multiple objective manpower planning model in order to design and adjust manpower structure and flow when advance rate for officer's native is considered. The state transition in manpower structure is analyzed using Markov chains. Multiple objectives in the model are security of advance rate, satisfaction of rank's number of personnel, and stability of the number of recruit personnel for officer's native. Trade - off of these objectives is made to evaluate manpower structure and flow. Solutions of this model are obtained by LINGO package.

• IE interfaces
• /
• v.24 no.3
• /
• pp.220-230
• /
• 2011

The multi-reservoir operation problem for efficient utilization of water resources involves conflicting objectives, and the problem can be solved by varying weight coefficient on objective functions. Accordingly, decision makers need to choose appropriate weight coefficients balancing the trade-offs among multiple objectives. Although the appropriateness of the weight coefficients may depend on the total amount of water inflow, reservoir operating policy may not be changed to a certain degree for different hydrological conditions on inflow. Therefore, we propose to use fuzzy Data Envelopment Analysis (DEA) to rank the weight coefficients in consideration of the inflow variation. In this approach, we generate a set of Paretooptimal solutions by applying different weight coefficients on Coordinated Multi-reservoir Operating Model. Then, we rank the Pareto-optimal solutions or the corresponding weight coefficients by using Fuzzy DEA model. With the proposed approach, we can suggest the best weight coefficients that can produce the appropriate Pareto-optimal solution considering the uncertainty of inflow, whereas the general DEA model cannot pinpoint the best weight coefficients.

• Nuclear Engineering and Technology
• /
• v.25 no.1
• /
• pp.63-70
• /
• 1993

A simplified safety assessment is carried out on rock-cavern type disposal of LLW using the analytical repository source term (REPS) model. For reliable prediction of the leach rates for various radionuclides, degradation of concrete structures, corrosion rate of waste container, degree of corrosion on the container surface, and the characteristics of radionuclides are considered in the REPS model. The results of preliminary assessment show that Cs-137, Ni-63, and Sr-90 are dominant. For the parametric uncertainty and sensitivity analysis, Latin hypercube sampling technique and rank correlation technique are applied. The results of the potential public health impacts show that radiological dose to intruder in the worst case scenario will be negligible and that more attention should be given to near-field performance.

• Journal of the Korean Data and Information Science Society
• /
• v.25 no.6
• /
• pp.1591-1598
• /
• 2014

The reviews of the balance sheet of commercial banks showed that loan item constitutes the largest portion of bank's assets. Although the sector has highest rate of profit, it possesses the greatest risk. Identifying factors that can contribute in lifting-up the loan repayment rate of customers of Hawassa district commercial bank is the major goal of this study. A sample of 183 customers who took loan from October, 2005 to April, 2012 was taken from the bank record. Kaplan-Meier estimation method and univariate Cox proportional hazard model were applied to identify factors affecting bank loan repayment rate. The result from Kaplan-Meier survival estimation revealed that the loan repayment rate is significantly related with loan type, and previous loan experience, educational level and mode of repayment. The log-rank test indicates that the survival probability of loan customers is not statistically different in repaying the loan among groups classified by sex. Moreover, the univariate Cox proportional hazard model result portrayed that educational level, having previous loan experience, mode of repayment, collateral type and purpose of loan are significantly related with loan repayment rate of customers commercial bank. Hence, banks should design loan strategies giving special emphasis on the significant factors while they are giving loans to their customers.

• Journal of Sport and Applied Science
• /
• v.7 no.2
• /
• pp.53-60
• /
• 2023

Purpose: This study examines the role of leaders of sport organizations from the perspectives of rank-and-file volunteers. Specifically, the study explores which factors are important in leading volunteers and how rank-and-filers interact with their leaders. Research design, data, and methodology: This study reviews a comprehensive literature on volunteer and leadership theories which are trait theory, behavior theory, and contingency theory. Given the comprehension of prior structure of knowledge on leadership, the study provides a structure of knowledge on volunteer and leadership in sport context and discusses managerial implications for leaders in sport organization. Results: With an exploration of sport leadership, this study proposes a volunteer classification model which presents four-volunteer types: professional volunteer, company volunteer, general volunteer, and school volunteer. Furthermore, this study discussed managerial implications for sport organization leaders. Conclusions: Paid employees may be prepared to accept a job and its requirements mainly due to economic benefits. Volunteers, however, do not pursue economic benefits through their activity. Different types of motivation between paid employees and volunteers bring to surface how a leader influences volunteer effectively. A conceptual volunteer clarification model could be examined in real world situations. Insights for future studies were discussed.