• Korea Journal of Hospital Management
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• v.12 no.4
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• pp.1-21
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• 2007

The relaxation of the regulation in selection of medical institution allows patients to use their own judgement in choosing proper institution for their diseases. Since the change of the regulation, there should have been many changes in medical institution selection behavior. The analysis of the change in disease specific selection pattern is critical because there be an optimal selection criteria that ensure the efficient and effective utilization of medical resources. This study analysis the institution selection factors by comparing the choice among the cases of acute diseases, the cases of chronic diseases, inpatient services, outpatient services, and emergency medical service. The comparisons performed in terms of size, class and other characteristics of medical institutions. For the study the nationally surveyed database was used and the data were analyzed using logistic regression procedure. The results indicates that the primary care facilities were not properly utilized. This study speculates that the reason for the undesirable pattern of utilization is that the roles of primary care facilities in the healthcare delivery system was not clearly defined. Based on the results, the medical policy implications are discussed.

• Asian-Australasian Journal of Animal Sciences
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• v.27 no.12
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• pp.1678-1683
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• 2014

This study considers a problem of genomic selection (GS) for adjacent genetic markers of Yorkshire pigs which are typically correlated. The GS has been widely used to efficiently estimate target variables such as molecular breeding values using markers across the entire genome. Recently, GS has been applied to animals as well as plants, especially to pigs. For efficient selection of variables with specific traits in pig breeding, it is required that any such variable selection retains some properties: i) it produces a simple model by identifying insignificant variables; ii) it improves the accuracy of the prediction of future data; and iii) it is feasible to handle high-dimensional data in which the number of variables is larger than the number of observations. In this paper, we applied several variable selection methods including least absolute shrinkage and selection operator (LASSO), fused LASSO and elastic net to data with 47K single nucleotide polymorphisms and litter size for 519 observed sows. Based on experiments, we observed that the fused LASSO outperforms other approaches.

• Journal of Korea Multimedia Society
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• v.21 no.10
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• pp.1182-1194
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• 2018

The Dynamic Adaptive Streaming over HTTP(DASH) is envisioned to evolve to meet an increasing demand on providing seamless video streaming services in the near future. The DASH performance heavily depends on the client's adaptive quality selection algorithm that is not included in the standard. The existing conventional algorithms are basically based on a procedural algorithm that is not easy to capture and reflect all variations of dynamic network and traffic conditions in a variety of network environments. To solve this problem, this paper proposes a novel quality selection mechanism based on the Deep Q-Network(DQN) model, the DQN-based DASH Adaptive Bitrate(ABR) mechanism. The proposed mechanism adopts a new reward calculation method based on five major performance metrics to reflect the current conditions of networks and devices in real time. In addition, the size of the consecutive video segment to be downloaded is also considered as a major learning metric to reflect a variety of video encodings. Experimental results show that the proposed mechanism quickly selects a suitable video quality even in high error rate environments, significantly reducing frequency of quality changes compared to the existing algorithm and simultaneously improving average video quality during video playback.

• Architectural research
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• v.11 no.2
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• pp.19-26
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• 2009

The effect of rebirthing technique on the genetic algorithm (GA)-based size optimization is investigated. The GA mimics the principles of nature and it can gradually improve structural design through biological operations such as fitness, selection, crossover and mutation. However, premature optimum has been often detected in the generic GA with continuous design variable. Since then, the so-called rebirthing technique has been proposed to avoid this problem. However, the performance of the rebirthing technique has not been reported. Therefore, the size optimizations of spatial structures are tackled to investigate the performance of the rebirthing technique on the generic GA. From numerical results, it is well proved that the rebirthing technique is very effective to produce the optimum values regardless of the values of parameters used in the GA operations.

• Journal of the East Asian Society of Dietary Life
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• v.22 no.6
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• pp.895-902
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• 2012

This study was conducted to understand the Ramyun's selection attributes of Korean adults and examine differences in demographic characteristics and meal intake behavior among three groups of samples divided based on the Ramyun's selection attributes. Self-administered questionnaires were completed by 702 adults, and data were subjected to frequency analysis, chi-square analysis, factor analysis, reliability tests, cluster analysis, and discriminant analysis using SPSS. The results of the study were as follows. The Ramyun's selection attributes for Korean adults investigated were food quality (four variables), price (three variables), and company reliability (four variables). Cluster analysis resulted in the subjects being divided into three groups according to their Ramyun's selection attributes, a high-selection group, mid-selection group, and low-selection group. Three groups of samples classified by Ramyun's selection attributes differed based on demographic characteristics (gender and education level) and meal intake behavior (meal numbers, reason for meal, meal time, and meal size).

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4269-4292
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• 2014

Currently, increasing numbers of access points (AP) are being deployed in enterprise offices, campuses and municipal downtowns for flexible Internet connectivity, but most of these access points are idle or redundant most of the time, which causes significant energy waste. Therefore, with respect to power conservation, applying energy efficient strategies in WIFI networks is strongly advocated. One feasible method is dynamically managing network resources, particularly APs, by powering devices on or off. However, when an AP is powered on, the device is initialized through a long boot time, during which period clients cannot be associated with it; therefore, the network performance would be greatly impacted. In this paper, based on a global view of an entire WLAN, we propose an AP selection technology, known as Temporary Access Selection (TAS). The criterion of TAS is a fusion metric consisting of two evaluation indexes which are based on throughput and battery life, respectively. TAS is both service and clients' preference specific through balancing the data rate, battery life and packet size. TAS also works well independently in traditional WLANs in which no energy efficient strategy is deployed. Moreover, this paper demonstrates the feasibility and performance of TAS through experiments and simulations with Network Simulator version 3 (NS3).

• Journal of the Korean Operations Research and Management Science Society
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• v.16 no.2
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• pp.61-61
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• 1991

We propose a strategic R&D resource allocation and project selection model based on national R&D policy and objectives. First, contributions to R&D policy and objectives for each R&D area are evaluated by using analytical hierarchy process (AHP). Second, fuzzy Delphi are proposed to estimate R&D budget for each R&D area. Then, a project selection grid is also introduced to implement two-phased evaluation for R&D project selection. We also discuss how to improve the consistency in AHP and how to reduce the pairwise comparison in AHP. The proposed model enables the decision makers to allocate R&D budget, and to evaluate and select the R&D proposals based on both the contribution to national R&D policy and objectives, and the size of each R&D area concurrently

• Korean Management Science Review
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• v.16 no.2
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• pp.61-77
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• 1999

We propose a strategic R&D resource allocation and project selection model based on national R&D policy and objectives. First, contributions to R&D policy and objectives for each R&D area are evaluated by using analytical hierarchy process (AHP). Second, fuzzy Delphi are proposed to estimate R&D budget for each R&D area. Then, a project selection grid is also introduced to implement two-phased evaluation for R&D project selection. We also discuss how to improve the consistency in AHP and how to reduce the pairwise comparison in AHP. The proposed model enables the decision makers to allocate R&D budget, and to evaluate and select the R&D proposals based on both the contribution to national R&D policy and objectives, and the size of each R&D area concurrently.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.59 no.3
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• pp.189-195
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• 2023

This study quantitatively evaluated size selectivity for three netting shapes (T0; regular, T45, T90) and hanging ratio (35%, 70%) of T0 netting used for trawl codend. The size selectivity experiment was performed in a tank using a cube experimental model with a length of 50 cm on one side and 389 experimental individuals, jack mackerel (Trachurus japonicus). In the selectivity analysis, a selectivity curve was created based on the selection ratio using a logistic function, and the 25%, 50%, and 70% selection length and selection range (SR) were obtained. The T0 netting was 19.54 cm when the 50% selective length, which is a selectivity evaluation index, had a hanging ratio of 35%, a selection range of 0.51 cm, and 22.70 cm and 3.08 cm for the hanging ratio of 70%. The T45 netting was 24.34 cm and 2.13 cm, and the T90 netting was 23.51 cm and 2.84 cm. The results of the T45 netting and the T90 netting are similar, and the 50% selection length and selection range were relatively larger than the T0 netting. There was a significant difference in the correlation between the circumference of the inner circle of the mesh by the shape of the netting and the body girth of the experimental individual (Pearson test, r = 0.86, p < 0.05). There was no significant difference in the correlation between the selection ratio by the T0 netting, T45 netting, and T90 netting with a 70% hanging ratio (one-way ANOVA, p > 0.05). The results of this study showed that selectivity such as T45 netting and T90 netting appeared when the hanging ratio, which maximizes the area of T0 netting, was maintained at 70%.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.224-229
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• 2001

When a semiconductor package is assembled, various materials such as die attach adhesive, lead frame, EMC (Epoxy Molding Compound), and gold wire are used. For better preconditioning performance, the combination between the packaging materials by studying the compatibility of their properties as well as superior packaging material selection is important. But it is not an easy task to find proper packaging material sets, since a variety of factors like package design, substrate design, substrate size, substrate treatment, die size, die thickness, die passivation, and customer requirements should be considered. This research applies case-based reasoning(CBR) technique to solve this problem, utilizing prior cases that have been experienced. Our particular interests lie in building decision support model to aid the selection of proper die attach adhesive. The preliminary results show that this approach is promising.