• Communications for Statistical Applications and Methods
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• v.27 no.5
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• pp.535-546
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• 2020

In genetic association studies, pleiotropy is a phenomenon where a variant or a genetic region affects multiple traits or diseases. There have been many studies identifying cross-phenotype genetic associations. But, most of statistical approaches for detection of pleiotropy are based on individual tests where a single variant association with multiple traits is tested one at a time. These approaches fail to account for relations among correlated variants. Recently, multivariate regularization methods have been proposed to detect pleiotropy in analysis of high-dimensional genomic data. However, they suffer a problem of tuning parameter selection, which often results in either too many false positives or too small true positives. In this article, we applied selection probability to multivariate regularization methods in order to identify pleiotropic variants associated with multiple phenotypes. Selection probability was applied to individual elastic-net, unified elastic-net and multi-response elastic-net regularization methods. In simulation studies, selection performance of three multivariate regularization methods was evaluated when the total number of phenotypes, the number of phenotypes associated with a variant, and correlations among phenotypes are different. We also applied the regularization methods to a wild bean dataset consisting of 169,028 variants and 17 phenotypes.

• Journal of Korea Water Resources Association
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• v.39 no.6 s.167
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• pp.495-502
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• 2006

The importance of the bandwidth selection has been more emphasized than the kernel function selection for nonparametric frequency analysis since the interpolation is more reliable than the extrapolation method. However, when the extrapolation method is being applied(i.e. recurrence interval more than the length of data or extreme probabilities such as $200{\sim}500$ years), the selection of the kernel function is as important as the selection of the bandwidth. So far, the existing kernel functions have difficulties for extreme value estimations because the values extrapolated by kernel functions are either too small or too big. This paper suggests a Modified Cauchy kernel function that is suitable for both interpolation and extrapolation as an improvement.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1204-1208
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• 2014

As required performance of UAV (Unmanned Aerial Vehicle) becomes more complex and complicated, required positioning accuracy is becoming more and more higher. GPS is a reliable world wide positioning providing system. Therefore, UAV generally acquires position information from GPS. But when GPS is not available such as too weak signal or too less GPS satellites environments, UAV needs alternative positioning system such as network positioning system. RSSI (Received Signal Strength Indicator) based positioning, which is one method of network positioning technologies, determines its position using RSSI measurements containing distance information from AP (Access Point)s. In that method, a selected AP's configuration has strong and tight relationship with its positioning errors. In this paper, for, we additionally account AP's configuration information by adopting DOP (Dilution of Precision) into AP selection procedures and provide more accurate RSSI based positioning results.

• International Journal of Internet, Broadcasting and Communication
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• v.9 no.1
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• pp.72-80
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• 2017

In this work, an efficient transmit antenna selection approach for the quadrature spatial modulation (QSM) systems is proposed. The conventional Euclidean distance antenna selection (EDAS)-based schemes in QSM have too high computational complexity for practical use. The proposed antenna selection algorithm is based on approximation of the EDAS decision metric employed for QSM. The elimination of imaginary parts in the decision metric enables decoupling of the approximated decision metric, which enormously reduces the complexity. The proposed method is also evaluated via simulations in terms of symbol error rate (SER) performance and compared with the conventional EDAS methods in QSM systems.

• Korean Journal of Computational Design and Engineering
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• v.3 no.4
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• pp.236-242
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• 1998

This paper presents a development of computer aided cutting tool selection techniques for rough and finish turning operations. The developed system,. which is one of important activities for computer aided operation planning, firstly implements operation sequencing. Then, from relations of the size of machined area, recommended finishing allowance and maximum depth of cut, a main machining method is selected, a number of cut is calculated, cutting tools including toolholders and inserts are selected, and values for cutting parameters are determined. A cutting tool selection procedure is proposed for toolholders and inserts of ISO code in rough cutting, and some important parameters such as holder style, tool approach angle, tool function and its direction are described in detail. In order to demonstrate the validity of the system a case study is performed.

• Journal of Korea Multimedia Society
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• v.21 no.11
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• pp.1288-1296
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• 2018

PBS(Pairwise Broadcast Synchronization) is a well-known synchronization scheme for WSN(Wireless Sensor Networks). As PBS needs the set of node-pairs for network-wide synchronization by over-hearing, GPA(Group-Wise Pair Selection Algorithm) was also proposed after PBS. However, GPA is complex and requires too many message transmissions, leading to much power consumption. Besides, GPA is not appropriate to topology change or mobile wireless sensor networks. So, we propose a new and energy-efficient pair-node selection algorithm for PBS. The proposed scheme's performance has been evaluated and compared with GPA by simulation. The results are shown to be better than GPA.

• Journal of Korean Library and Information Science Society
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• v.24
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• pp.243-274
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• 1996

The purpose of this study is to investigate the necessity, selection, organization and management of Must Books List in middle schools. A great book can change a person's life and future. Especially, reading in the juvenile period is important because of their intellectual curiosity and sensitivity. The results of the study were as follows: 1. The necessity of Must Books can be considered in two perspectives : One is the cultivation of emotion and sense of value and the other is the development of information abilities. 2. The general criteria for the selection of Must Books are whether a book is su n.0, pportive of learning activities, of extracurricular activities, and of activities for school festivals. And whether a book is contributing to the building of good characters of students or not should be considered, too. 3. The special attention should be given to such matters as the organizational and distributional ratio among subjects of the Must Books, the degree of difficulties, the ratio of books for both male and female students, the ratio of foreign books to domestics, the possibilities of further reading and the bibliographical matters. 4. The points to be duly considered for the management of Must Books List are the educational considerations, clearness of objectives, the elimination of commercialism and authoritarianism in the book selection. The Must Books List should be managed autonomously, depending on the characteristics of each school and be updated annually. However, the most important thing is that the teacher should be a good reader himself. 5. It is better to include short stories than the long one in the Must Book List. Students should be guided to read explanatory text first and then to move to the original text. And they should be exposed to books in various subjects and not to be too dependent on the Must Books List. They should be able to develop the problem solving ability through the reading of the Must Books. 6. Finally, the Must Books selection committee should be composed of both teacher librarian and subject teachers. It is desirable that books for the cultivation of emotion, for the establishment of sense of value, and for the development of information ability should be selected by consulting the various reading lists compiled by the Ministry of Education, the Board of Local Education and other authorities concerned.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.133-141
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• 2001

Since the computing environment changes very rapidly, the estimation of software effort is very difficult because it is not easy to collect a sufficient number of relevant cases from the historical data. If we pinpoint the cases, the number of cases becomes too small. However is we adopt too many cases, the relevance declines. So in this paper we attempt to balance the number of cases and relevance. Since many researches on software effort estimation showed that the neural network models perform at least as well as the other approaches, so we selected the neural network model as the basic estimator. We propose a search method that finds the right level of relevant cases for the neural network model. For the selected case set. eliminating the qualitative input factors with the same values can reduce the scale of the neural network model. Since there exists a multitude of combinations of case sets, we need to search for the optimal reduced neural network model and corresponding case, set. To find the quasi-optimal model from the hierarchy of reduced neural network models, we adopted the beam search technique and devised the Case-Set Selection Algorithm. This algorithm can be adopted in the case-adaptive software effort estimation systems.

• Bulletin of the Korean Chemical Society
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• v.10 no.3
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• pp.298-302
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• 1989

The strengths of two-photon transitions from the ground state to excited vibronic states in benzene are calculated by using the CNDO/2-U wave functions. The role of vibronic coupling in two-photon absorption process is discussed. The $A_{1{\bar{g}}}-A_{2g}^+$ two-photon transitions, which are forbidden by the identity-forbidden selection rule in single frequency two-photon absorption, are too weak to be experimentally observed even when two photons of different energies are used. It is because the transitions are forbidden also by the pseudo-parity selection rule which are applicable for alternant hydrocarbons such as benzene. It is also shown that the vibronic coupling is not very effective in altering the pseudo-parity property of the electronic state. The strength of the vibronically induced two-photon absorption is strongly affected by the presence of an electronic state from which two-photon absorption can borrow the intensity. It is pointed out that the pseudo-parity selection rule may be violated in such cases.

• Communications for Statistical Applications and Methods
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• v.30 no.6
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• pp.577-587
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• 2023

Conventional categorical data imputation techniques, such as mode imputation, often encounter issues related to overestimation. If the variable has too many categories, multinomial logistic regression imputation method may be impossible due to computational limitations. To rectify these limitations, we propose a two-stage imputation method. During the first stage, we utilize the Boruta variable selection method on the complete dataset to identify significant variables for the target categorical variable. Then, in the second stage, we use the important variables for the target categorical variable for logistic regression to impute missing data in binary variables, polytomous regression to impute missing data in categorical variables, and predictive mean matching to impute missing data in quantitative variables. Through analysis of both asymmetric and non-normal simulated and real data, we demonstrate that the two-stage imputation method outperforms imputation methods lacking variable selection, as evidenced by accuracy measures. During the analysis of real survey data, we also demonstrate that our suggested two-stage imputation method surpasses the current imputation approach in terms of accuracy.