• International Journal of Human Ecology
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• v.4 no.2
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• pp.77-87
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• 2003

This paper tried to construct statistical and econometric models on the basis of economic theory in order to discuss the issue of statistical efficiency and unbiasedness including the sample selection bias correcting problem. Comparative analytical tool were one stage Tobit of Maximum Likelihood estimation and Heckman's two-step Tobit of Ordinary Least Squares. The results showed that the adequacy of model for the analysis on demand and choice, we believe that there is no big difference in explanatory variables between the first selection model and the second linear probability model. Since the Lambda, the self- selectivity correction factor, in the Type II Tobit is not statistically significant, there is no self-selectivity in the Type II Tobit model, indicating that Type I Tobit model would give us better explanation in the demand for and choice which is less complicated statistical method rather than type II model.

• IE interfaces
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• v.22 no.1
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• pp.44-55
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• 2009

We propose a method for selection of input-output factors in DEA. It is designed to select better combinations of input-output factors that are well suited for evaluating substantial performance of DMUs. Several selected DEA models with different input-output factors combinations are evaluated, and the relationship between the computed efficiency scores and a single performance criterion of DMUs is investigated using decision tree. Based on the results of decision tree analysis, a relatively better DEA model can be chosen, which is expected to well represent the true performance of DMUs. We illustrate the effectiveness of the proposed method by applying it to the efficiency evaluation of 101 listed companies in steel and metal industry.

• Journal of the Korean Operations Research and Management Science Society
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• v.23 no.3
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• pp.75-90
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• 1998

The improper use of input and output factors in DEA has a critical and negative impact on the efficiency measurement and the discernment of decision making units(DMUs) : hence the proper selection Process of the factors should precede the actual applications of DEA. In this paper, we propose a new approach to selecting proper factors based on Tofallis' partial efficiency evaluation method(1996). With the approach, the factors aye clustered by measuring their respective partial efficiencies and analyzing the rank correlations of them. The method and procedure we propose in this paper are then applied to measure the efficiencies of the public libraries in Seoul District area, and the results show that the proposed approach can provide meaningful information to improve discernment of the DMUs while using less number of input factors (and less information). The proposed method can be effectively used in the situation where the number of the DMUs to be considered is relatively small compared to the number of available input and output factors, which usually lessens the power to identify the inefficient units in DEA.

• Journal of Communications and Networks
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• v.18 no.4
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• pp.649-657
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• 2016

In this paper, we investigate energy efficiency (EE) of the traditional co-located and the distributed massive multiple-input multiple-output (MIMO) systems. First, we derive an approximate EE expression for both the idealistic and the realistic power consumption models. Then an optimal energy-efficient remote access unit (RAU) selection algorithm based on the distance between the mobile stations (MSs) and the RAUs are developed to maximize the EE for the downlink distributed massive MIMO systems under the realistic power consumption model. Numerical results show that the EE of the distributed massive MIMO systems is larger than the co-located massive MIMO systems under both the idealistic and realistic power consumption models, and the optimal EE can be obtained by the developed energy-efficient RAU selection algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.673-694
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• 2021

In this paper, we intend to study the energy efficiency (EE) optimization for a simultaneous wireless information and power transfer (SWIPT)-based distributed antenna system (DAS). Firstly, a DAS-SWIPT model is formulated, whose goal is to maximize the EE of the system. Next, we propose an optimal resource allocation method by means of the Karush-Kuhn-Tucker condition as well as an ergodic method. Considering the complexity of the ergodic method, a suboptimal scheme with lower complexity is proposed by using an antenna selection scheme. Numerical results illustrate that our suboptimal method is able to achieve satisfactory performance of EE similar to an optimal one while reducing the calculation complexity.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2022.06a
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• pp.825-828
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• 2022

In this paper, we propose an efficient image size selection method for video-based point cloud compression. The current MPEG video-based point cloud compression reference encoding process configures a threshold on the size of images while converting point cloud data into images. Because the converted image is compressed and restored by the legacy video codec, the size of the image is one of the main components in influencing the compression efficiency. If the image size can be made smaller than the image size determined by the threshold, compression efficiency can be improved. Here, we studied how to improve the compression efficiency by selecting the best-fit image size generated during video-based point cloud compression. Experimental results show that the proposed method can reduce the encoding time by 6 percent without loss of coding performance compared to the test model 15.0 version of video-based point cloud encoder.

• Journal of Korea Technology Innovation Society
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• v.21 no.4
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• pp.1366-1385
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• 2018

Recently, government policy focuses on R&D subsidies for venture firms in the early and medium stage. However, due to the 'asymmetric information' on those firms, a concern about the possibility of adverse selection of government policy, that is, whether the R&D subsidies are offered to the less-growth potential venture firms is on the rise. Therefore, based on the "2015 venture firm's survey" data in Korea, we compared the managerial efficiency of venture firms in manufacturing sectors by dividing them into beneficiary and non-beneficiary groups at government R&D subsidies. We found that the beneficiary groups showed lower managerial efficiency than non-beneficiary groups, even if they are superior to non-beneficiary groups in technological performance. We also observed that the phenomenon involve 'low managerial efficiency in the beneficiary groups' is more relevant in mid-high tech. manufacturing sectors. Our findings provide an exploratory empirical evidence of the concern about adverse selection in the selection of R&D subsidies beneficiary groups. Therefore, the government should consider managerial performance as the key criteria for selecting R&D subsidies beneficiary groups, rather than depending on technological performance solely. Furthermore, the government should develop other complementary policies to support financial performance of the groups. Lastly, the government should make those policies attract venture firms with potential to achieve financial performance.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.39 no.2
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• pp.180-186
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• 1994

Lipoxygenase activity of soybean seeds of approximately 507 genotypes as well as its inheritance and selection efficiency in early breeding generation was measured in the Department of Agronomy, Seoul National University to facilitate breeding for low lipoxygenase activity of soybean. Average seed lipoxygenase activity of 507 cultivars and strains was 350 unit (unit: $\Delta$0.01 /min. /mg at 234nm) and ranged from 50 to 670 unit. There was no difference in mean lipoxygenase activity according to apparent seed characters such as seed coat and embryo color. But early mature soybean genotypes had fairly low lipoxygenase activity. Lipoxygenase activity was inherited quantitatively, in which additive effect was greater than dominant one and proportion of gene with positive effects was similar to that with negative ones. Estimated narrow- and broad-sense heritabilities were 0.78 and 0.86 for lipoxygenase activity, respectively. Heritability measured from selection in early breeding lines for high or low lipoxygenase activity was 64~76% or 54~62%, respectively. And selection for high lipoxygenase activity increased by 29.7~44.7%, whereas that for low ones decreased by 21.8~27.3%, respectively, when compared to random population. Clear effect in selecting of lipoxygenase activity was present in early generation.

• Journal of the Korean Solar Energy Society
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• v.39 no.2
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• pp.45-55
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• 2019

More than 76% of the detached houses in Korea are over 20 years old. These old detached houses have poor energy efficiency. According to the 2017 Housing Census (Statistics Korea), more than 50% of low-income families live in detached houses. Therefore, the improvement of energy efficiency in old detached houses is needed from the viewpoint of energy welfare. The general method of building energy modelling for the verification of energy efficiency is based on the construction year data of "Building Design Criteria for Energy Saving" due to the cost and time involved in collecting the thermal performance data of buildings. There is poor accuracy with the deterioration of long-term aging of building materials. Also, the selection of alternatives for energy performance improvement is based on the items to be applied, not a performance improvement goal. It is difficult to calculate energy performance that reflects variations in various parameters with dynamic energy simulations. In this study, the influence of long-term aging is used to accurately predict the energy performance of old detached houses. The building energy modelling method is called ENERGY#, which is a static analysis method based on ISO13790. Energy performance is evaluated by a combination of input variables including building orientation, insulation of walls and roof, thermal performance of windows and window/wall ratio, and infiltration rate. Finally, this study provides a way to determine alternatives that meet energy performance improvement goals.

• Journal of Intelligence and Information Systems
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• v.14 no.4
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• pp.179-200
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• 2008

We develop a feature selection method that can improve both the efficiency and the effectiveness of classification technique. In this research, we employ case-based reasoning as a classification technique. Basically, this research integrates the two existing feature selection methods, i.e., the univariate analysis and the LVF algorithm. First, we sift some predictive features from the whole set of features using the univariate analysis. Then, we generate all possible subsets of features from these predictive features and measure the inconsistency rate of each subset using the LVF algorithm. Finally, the subset having the lowest inconsistency rate is selected as the best subset of features. We measure the performances of our feature selection method using the data obtained from UCI Machine Learning Repository, and compare them with those of existing methods. The number of selected features and the accuracy of our feature selection method are so satisfactory that the improvements both in efficiency and effectiveness are achieved.