• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.2
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• pp.408-427
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• 2011

Intensive computational complexity is an obstacle of enabling multiview video coding for real-time applications. In this paper, we present a fast macroblock (MB) mode selection algorithm for B frames which are based on the computational complexity analyses between the MB mode selection and reference frame selection. Three strategies are proposed to reduce the coding complexity jointly. First, the temporal correlation of MB modes between current MB and its temporal corresponding MBs is utilized to reduce computational complexity in determining the optimal MB mode. Secondly, Lagrangian cost of SKIP mode is compared with that of Inter $16{\times}16$ modes to early terminate the mode selection process. Thirdly, reference frame correlation among different Inter modes is exploited to reduce the number of reference frames. Experimental results show that the proposed algorithm can promote the encoding speed by 3.71~7.22 times with 0.08dB PSNR degradation and 2.03% bitrate increase on average compared with the joint multiview video model.

• Korea Journal of Hospital Management
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• v.23 no.4
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• pp.1-14
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• 2018

Purpose : Customers with loyalty are very important to hospitals for sustainable growth in their medical market. Individuals with loyalty are likely to visit same hospital repeatedly when they need medical services. This study was to identify factors associated with selection of specialty hospitals among customers with loyalty. Methods : The subjects of this study were 735 inpatients in 22 specialty hospitals in 6 designated fields(joints, spine, colorectal-anal, obstetrics and gynecology, ophthalmology, otolaryngology). Customer types classified as customers with high loyalty, neutral customers, and customers with low loyalty according to net promoter score(NPS). Factor analysis was conducted to classify 22 hospital selection factors into some similar properties. Logistic regression analysis was conducted to confirm the selection factors related to loyal customers. Findings : Most of specialty hospitals received high NPS of 8 points or higher in all the designated fields. Five factors associated with selection of specialty hospital are (1) hospital facilities and convenience, (2) trust in doctor and hospital, (3) rapidness of treatment, (4) hospital awareness, and (5) accessibility. As a result of logistic regression analysis, selection factors related to loyal customers were 'hospital facilities and convenience', 'trust in doctor and hospital' and 'rapidness of treatment'. Differences in the degree of importance of three selection factors by customer types appeared for each designated field. Practical Implications : This study confirms the high level of patient experience among inpatients of specialty hospitals. Factors associated with selection of hospital among inpatients with loyalty are 'facilities and convenience of hospitals', 'trust of doctor and hospital' and 'rapidness of treatment'. This study will be meaningful as basic data to systematically enhance the roles and functions of the health care system and to provide securing competitiveness according to designated fields in the management aspect of specialty hospitals.

• Journal of Information Technology Applications and Management
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• v.28 no.6
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• pp.97-116
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• 2021

Due to the decrease in the school-age population and government regulations, universities have made great efforts to secure their own competitiveness. In particular, the selection of universities with financial support based on the recent evaluation of the Ministry of Education has become a major concern enough to affect the existence of the university itself. This paper extracts three-year data from 124 major private universities nationwide, and quantitatively analyzes the variables of major universities selected as self-improvement universities, competency reinforcement universities, and universities with limited financial support. As a result of estimating the selection of self-powered universities using the ordered logit model by hierarchically inputting 12 variables, student competitiveness in the metropolitan area (1.318^**), Educational Restitution Rate (4.078^***), University operation expenditure index rate (1.088^***) values were found. Significant positive coefficient values were found in the admission enrollment rate (45.98^***) and the enrollment rate (13.25^***). As a result of analyzing the marginal effects, the increase in the rate of reduction of education costs has always been positive in the selection of self-powered universities, but it was observed that the rate of increase decreases in areas of increase of 150% or more. On the contrary, the probability of becoming a Em-powered university was negative in all sectors, but on the contrary, it was analyzed that marginal effects increased at the same time point. On the other hand, the employment rate of graduates was not able to find direct significance with the result of the selection of Self powered universities. Through this paper, it is expected that each university will analyze the possibility and shortcomings of the selection of Self powered universities in policy making, and in particular, the risk of dropout of selection for the vulnerable field can be predicted using marginal effects. It can be used as major research data for both university evaluators, university officials and students.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.30 no.3
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• pp.161-171
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• 1994

Mesh selection analysis for the trawl net were carried out at the Southern Korean Sea and the East China Sea during the 1992-1994 years by the training ship Seabada of the National Fisheries University of Pusan, using A type (51.2mm), B type (70.2mm), C type (77.6mm), D type (88.0mm) square mesh cod-ends. The fishing trials were made using bottom trawl of the trouser type cod-end with cover net. Selection curves and selection parameters were calculated by a logistic model for Sphyraena pinguis, Pampus argenteus, Trachurus japonicus, Pagrus major, Callanthias japonicus, Trichiurus lepturus. The results obtained are summarized as follows: 1. Red barracuda : Selection range and fifty percent selection length in the A type was 115.8mm, 292.8mm, respectively. 2. Harvest fish : Each selection range and fifty percent selection length in the B. C. and D type was 37.7mm, 113.8mm : 40.1mm, 131.7mm and 64.8mm, 148.6mm, respectively. Selection parameters of master curve were : slope, 3.81 : intercept, -6.4. Optimum mesh size was 89.3mm. 3. Horse mackerel : Each selection range and fifty percent selection length in the A, B, C and D type was 43.0mm, 148.3mm : 60.7mm, 183.2mm, 214.5mm and 91.4mm, 254.9mm, respectively. Selection parameters of master curve were : slope 2.30 : intercept, -6.4. Optimum mesh size was 66.8mm. 4. Red seabrem : Selection range and fifty percent selection length in the D type was 42.7mm, 203.4mm, respectively. 5. Yellowsail red bass : Selection range and fifty percent selection length in the A type was 84.0mm, 110.6mm, respectively. 6. Hair tail : Each selection range and fifty percent selection length in the A, B and C type was 59.7mm, 176.0mm : 100.9mm, 250.7mm and 178.6mm, 307.0mm, respectively. Selection parameters of master curve were : slope, 1.54 : intercept, -5.4. Optimum mesh size was 57.5mm.

• Journal of the Semiconductor & Display Technology
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• v.14 no.2
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• pp.9-16
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• 2015

In this paper, selection criterions on selection diversity are researched. The diversity is applied to the multiple antenna system based on wireless access in vehicular environment (WAVE) standard for rapid varying channel. Least squares (LS) based decision feedback equalizer (DFE) are used for channel equalization. Received signal is regenerated by means of the decision feedback path. In the selection diversity, the regenerated signal as well as the received signal is selected according to selection criterion. The decision feedback algorithm can follow the fast speed of WAVE fading channel. To control the tracking speed of the time-varying channel, simple low pass filter is used. Finally, the estimated channel value recovers the distorted payloads. Signal power before automatic gain control (AGC) in analog stage can be used as a selection criterion. In the digital stage, signal power after AGC, noise power after AGC, signal to noise ratio after AGC and cross-correlation method can be used as selection criterions. According to the simulation results, the performance of the selection diversity is improved in comparison with that of the combining diversity for the WAVE fading channel.

• Journal of Biosystems Engineering
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• v.40 no.4
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• pp.417-427
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• 2015

Purpose: This study investigated different band selection methods to classify spectrally similar data - obtained from aerial images of healthy citrus canopies and citrus greening disease (Huanglongbing or HLB) infected canopies - using small differences without unmixing endmember components and therefore without the need for an endmember library. However, large number of hyperspectral bands has high redundancy which had to be reduced through band selection. The objective, therefore, was to first select the best set of bands and then detect citrus Huanglongbing infected canopies using these bands in aerial hyperspectral images. Methods: The forward feature selection algorithm (FFSA) was chosen for band selection. The selected bands were used for identifying HLB infected pixels using various classifiers such as K nearest neighbor (KNN), support vector machine (SVM), naïve Bayesian classifier (NBC), and generalized local discriminant bases (LDB). All bands were also utilized to compare results. Results: It was determined that a few well-chosen bands yielded much better results than when all bands were chosen, and brought the classification results on par with standard hyperspectral classification techniques such as spectral angle mapper (SAM) and mixture tuned matched filtering (MTMF). Median detection accuracies ranged from 66-80%, which showed great potential toward rapid detection of the disease. Conclusions: Among the methods investigated, a support vector machine classifier combined with the forward feature selection algorithm yielded the best results.

• Journal of the Korean Operations Research and Management Science Society
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• v.41 no.3
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• pp.1-21
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• 2016

The Markowitz portfolio selection model uses estimators to deduce input parameters. However, the estimation errors of input parameters negatively influence the performance of portfolios. Therefore, this model cannot be reliably applied to real-world investments. To overcome this problem, we suggest an algorithm that can exclude stocks with large estimation error from the portfolio by applying a tracking signal to the Markowitz portfolio selection model. By calculating the tracking signal of each stock, we can monitor whether unexpected departures occur on the outcomes of the forecasts on rate of returns. Thereafter, unreliable stocks are removed. By using this approach, portfolios can comprise relatively reliable stocks that have comparatively small estimation errors. To evaluate the performance of the proposed approach, a 10-year investment experiment was conducted using historical stock returns data from 6 different stock markets around the world. Performance was assessed and compared by the Markowitz portfolio selection model with additional constraints and other benchmarks such as minimum variance portfolio and the index of each stock market. Results showed that a portfolio using the proposed approach exhibited a better Sharpe ratio and rate of return than other benchmarks.

• Structural Monitoring and Maintenance
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• v.4 no.1
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• pp.85-105
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• 2017

Monitoring is the most important part of the construction and operation of the embankment dams. Applied instruments in these dams should be determined based on dam requirements and specifications. Instruments selection considered as one of the most important steps of monitoring plan. Competent instruments selection for dams is very important, as inappropriate selection causes irreparable loss in critical condition. Lack of a systematic method for determining instruments has been considered as a problem for creating an efficient selection. Nowadays, decision making methods have been used widely in different sciences for optimal determination and selection. In this study, the Multi-Attribute Decision Making is applied by considering 9 criteria and categorisation of 8 groups of geotechnical instruments. Therefore, the Analytic Hierarchy Process and Multi-Criteria Optimisation and Compromise Solution methods are employed in order to determine the attributes' importance weights and to prioritise of instruments for embankment dams, respectively. This framework was applied for a rock fill with clay core dam. The results indicated that group decision making optimizes the selection and prioritisation of monitoring instruments for embankment dams, and selected instruments are reliable based on the dam specifications.

• Korean journal of food and cookery science
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• v.29 no.6
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• pp.637-645
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• 2013

The purpose of this study was to investigate the consumers' selection attributes of social enterprises type cafe by IPA(Importance-Performance Analysis). Data were collected through a self-administered questionnaire by 309 random consumers in several social enterprises type cafes in Seoul and Gyonggi area. The data was analyzed using SPSS windows(ver. 17.0) for descriptive analysis, t-test, one-way ANOVA and factor analysis. The importance of cafe's selection attributes were divided into five factors including 'promotion and menu', 'service quality and atmosphere', 'location', 'taste', and 'brand name'. The mean scores of importance and performance for cafe selection attributes were 4.01 and 3.68 out of 5, showing a significant difference between importance and performance. According to the IPA results of 17 selection attributes for social enterprises type cafe, the selection attributes with relatively low performance but high importance(II quadrant) was 'easy accessibility'. The factor to be improved through the IPA was accessibility factor, showing that the consumers had a low satisfaction compared to the significance of cafe's location.

• 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.