• Journal of the Korean Society for Aviation and Aeronautics
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• v.23 no.2
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• pp.32-39
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• 2015

Airport is not only a public facility but a place where multiple cultural and ethnic groups are visiting. It has been reported though several researches that the level of emotional labor is more heavier than any other job. The more complex our society become, the more frequently emotional labor has been focused. Emotional labor became recently the issue of integrated studies above. Considering the level of emotional labor of airport employees, this paper believes their emotional labor has not been focused compared to such as tourism and service industry. This paper tried to research empirically the impact of internal marketing on airport employees' customer-oriented attitude based on their emotional labor using SEM (Structural Equation Modeling). According to the SEM results, it was proven that 'Autonomy of Airport Employee', a latent variable of internal marketing has a significant negative effect on employees' outside emotion. The outside emotion has also a significant effect on their customer-oriented attitude. It could be concluded the effort to increase decision making authority of employees should be implemented to provide them with deeper customer oriented insight.

• Asian Journal of Business Environment
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• v.8 no.4
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• pp.29-35
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• 2018

Purpose - This study examined the relationship between dyadic relationship between leaders and followers (DRLF), distributive justice (DISJ), job satisfaction (JSTC), and organizational commitment (OGCM). Research design, data, and methodology - 200 sets of survey questionnaires were distributed to the employees at a municipal office in East Malaysia using purposive sampling technique. Only 60 percent or 115 questionnaires were returned to the researchers. The survey data were analysed using the SmartPLS due to its ability to deliver latent construct scores, handle small sample size problems and estimate relationship between many constructs in the hypothesized model. Results - The findings indicated that there is a significant correlated direct relationship between DRLF and DISJ and mediating relationship between DRLF, DISJ and personal outcomes, which are JSTC and OGCM. Conclusions - This study confirms that DISJ does act as an important mediating variable in the relationship between DRLF with JSTC and DRLF with OGCM. Other dimensions of personal outcomes, such as extra-role behaviour, job motivation and service quality should be considered in future study because they are found to be the important outcomes of the relationship between DRLF and DISJ. The importance of these issues need to be further advanced in future research.

• The Korean Journal of Applied Statistics
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• v.18 no.2
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• pp.381-393
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• 2005

As a promising technique for dimension reduction in regression analysis, Sliced Inverse Regression (SIR) and an associated chi-square test for dimensionality were introduced by Li (1991). However, Li's test needs assumption of Normality for predictors and found to be heavily dependent on the number of slices. We will provide a unified asymptotic test for determining the dimensionality of the SIR model which is based on the probabilistic principal component analysis and free of normality assumption on predictors. Illustrative results with simulated and real examples will also be provided.

• Korean Journal of Bronchoesophagology
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• v.12 no.2
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• pp.35-41
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• 2006

Traumatic pseudoaneurysm of the intracavernous internal carotid artery(ICA) is extremely rare, but it is life threatening condition because of massive recurrent epistaxis. Unfortunately, the prompt diagnosis and treatment of this disease are frequently delayed due to its rarity and variable latent period, so this disease is regarded as a challenge to clinicians. Optimal therapy for this diseases demands rapid suspicion for it and is essential in order to give the best functional outcome with minimizing its morbidity and mortality. The authors present a case of male patient with traumatic pseudoaneurysm of intracavernous ICA accompanying severe epistaxis. This patient was a 37-year-old male with unilateral blindness and recurrent massive epistaxis after suffering trauma to head. Computed tomography, MRI and carotid artery angiogram showed pseudoaneurysm of intracavernous ICA with sphenoid bone fracture. The patient was effectively managed with occlusion of the pseudoaneurysmal circulation by endovascular interventional embolization technique utilizing mechanically detachable tungsten coils.

• 한국생물공학회:학술대회논문집
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• 2004.07a
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• pp.47-84
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• 2004

Principal Component Analysis나 Partial Least Squares와 같은 다변량 통계 기법은 변수간의 correlation structure로부터 공정의 variance를 설명할 수 있는 latent variable를 얻고 이를 이용하여 공정을 효과적으로 modeling할 수 있는 방법으로 최근 들어 많은 관심을 얻고 있다. 하지만 PLS는 공정이 stationary state에 있다고 가정하기 때문에, 생물학적 공정의 non-stationary and time-varying behavior를 설명하기에 부적절하다. 본 논문에서는 PLS 알고리즘의 혐기성 폐수처리 공정에의 적용에 있어, 이와 같은 문제를 해결하기 위해서 adaptive PLS 알고리즘을 사용함으로써 변화하는 공정의 특성에 대응하여 모델을 update하는 방법을 이용하였다. 하지만 실시간 데이터로부터 adaptive PLS 방법을 적용하는 데에는 많은 어려움이 존재하며, 특히 outlier나 abnormal disturbance에 모델이 부적절하게 adaptation하는 문제가 발생할 수 있다. 따라서 이의 해결을 위해 adaptive PLS를 적용하는데 있어 robustness를 향상시키기 위해 monitoring index를 이용하여 abnormal data에 weight를 주고 안정적인 모델의 update가 가능하게 하는 방법을 제안하였으며, 이를 적용하여 성공적으로 혐기성 폐수처리 공정의 Output을 예측하고 효과적으로 공정을 모니터링할 수 있었다. 만들어진 PLS 모델은 산업폐수를 처리하기 위한 industrial plan에서 측정된 실제 데이터에 적용하여 그 효용성을 입증하였으며, 그 결과는 mechanistic model을 적용하기 힘든 실공정에 비교적 쉽게 implementation할 수 있는 장점이 있다.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.9 no.3
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• pp.410-425
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• 1997

Buildings are mostly under part load conditions causing an inefficient system operation in terms of energy consumption. It is critical to operate building air-conditioning system with a scientific or optimal manner which minimizes energy consumption and maintains thermal comfort by matching building sensible and latent loads. Little research has been performed in developing general methodologies for the optimal operation of air-conditioning system. Based on this research motivation, system simulation program was developed by adopting various equipment operating strategies which are energy efficient especially for humidity control in summer. A numerical optimization technique was utilized to search optimal solution for multi-independent variables and then linked to the developed system simulation model within a mam program. The main goal of the study is to provide a systematic framework and guideline for the optimal operation of air-conditioning system focusing on air-side. For given cooling loads and ambient outdoor conditions the optimal operating strategies of a commercial building are determined by minimizing a constrained objective function by a nonlinear programming technique. Desired space setpoint conditions were found through evaluating the trade-offs between comfort and system power consumption. The results show that supply airflow rate and compressor fraction play main roles in the optimization process. It was found that variable setpoint optimization technique could produce lower indoor humidity level demanding less power consumption which will be benefits for building applications of humidity problem.

• Communications for Statistical Applications and Methods
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• v.27 no.3
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• pp.385-395
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• 2020

We present a new maximum likelihood approach to estimate demographic history using genomic data sampled from two populations. A demographic model such as an isolation-with-migration (IM) model explains the genetic divergence of two populations split away from their common ancestral population. The standard probability model for an IM model contains a latent variable called genealogy that represents gene-specific evolutionary paths and links the genetic data to the IM model. Under an IM model, a genealogy consists of two kinds of evolutionary paths of genetic data: vertical inheritance paths (coalescent events) through generations and horizontal paths (migration events) between populations. The computational complexity of the IM model inference is one of the major limitations to analyze genomic data. We propose a fast maximum likelihood approach to estimate IM models from genomic data. The first step analyzes genomic data and maximizes the likelihood of a coalescent tree that contains vertical paths of genealogy. The second step analyzes the estimated coalescent trees and finds the parameter values of an IM model, which maximizes the distribution of the coalescent trees after taking account of possible migration events. We evaluate the performance of the new method by analyses of simulated data and genomic data from two subspecies of common chimpanzees in Africa.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.59-60
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• 2000

The past few years have seen a dramatic increase in gene expression data on the basis of DNA microarrays or DNA chips. Going beyond a generic view on the genome, microarray data are able to distinguish between gene populations in different tissues of the same organism and in different states of cells belonging to the same tissue. This affords a cell-wide view of the metabolic and regulatory processes under different conditions, building an effective basis for new diagnoses and therapies of diseases. In this talk we present machine learning techniques for effective mining of DNA microarray data. A brief introduction to the research field of machine learning from the computer science and artificial intelligence point of view is followed by a review of recently-developed learning algorithms applied to the analysis of DNA chip gene expression data. Emphasis is put on graphical models, such as Bayesian networks, latent variable models, and generative topographic mapping. Finally, we report on our own results of applying these learning methods to two important problems: the identification of cell cycle-regulated genes and the discovery of cancer classes by gene expression monitoring. The data sets are provided by the competition CAMDA-2000, the Critical Assessment of Techniques for Microarray Data Mining.

• The Journal of Information Systems
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• v.26 no.3
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• pp.211-228
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• 2017

Purpose This study proposes a research model based on Expectation-Confirmation theory in order to investigate impacts of three variables(expectation confirmation, social interaction, and perceived usefulness) on continuous intention to uss SNS in MICE industry. Design/methodology/approach A survey approach was used in order to measure each latent variable in the research model. A total of 140 responses were collected from actual users of SNS in MICE industry. A structural equation modeling with SmartPLS 2.0 was conducted in order to analyze each relationship in the proposed research model. Findings The results indicated the expectation confirmation had a positive impact on the perceived usefulness, social interaction, and satisfaction. Second, perceived usefulness had a significant positive impact on satisfaction and continuous intention to use SNS in MICE industry. Thrid, social interaction had a positive influence on both satisfaction and continuous intention to use SNS in MICE industry. Finally, the relationship between satisfaction and continuous intention in SNS of MICE industry was fully supported.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.7 s.238
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• pp.814-819
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• 2005

The phase change heat transfer has been applied to the processes of machines as well as of manufacturing. The cycle in a heat exchanger includes the phase change phenomena of coolant for air conditioning, the solidification in casting process makes use of the characteristics of phase change of metal, and the welding also proceeds with melting and solidification. To predict the phase change processes, the experimental and numerical approaches are available. In the case of numerical analysis, the Enthalpy method is most widely applied to the phase change problem, comparing to the other numerical methods, i.e. the Equivalent Specific Heat method and the Temperature Recovery method. It's because that the Enthalpy method is accurate and straightforward. The Enthalpy method does not include any correction step while the correction of final temperature field is inevitable in the Equivalent Specific Heat method and the Temperature Recovery method. When the temperature field is to be used in the calculation, however, there must be converting process from enthalpy to temperature in the calculation scheme of Enthalpy method. In this study, an improved method for the Equivalent Specific Heat method is introduced whose method dose not include the correction steps and takes temperature as an independent variable so that the converting between enthalpy and temperature does not need any more. The improved method is applied to the solidification process of pure metal to see the differences of conventional and improved methods.