• 응용통계연구
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• 제21권6호
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• pp.1007-1014
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• 2008

Usability evaluation(UE) experiments are conducted to provide UE practitioners with guidelines for better outcomes. In UE research, significant quantities of empirical results have been accumulated in the past decades. While those results have been anticipated to integrate for producing generalized guidelines, traditional meta-analysis has limitations to combine UE empirical results that often show considerable heterogeneity. In this study, a new data mining method called weighted bi-clustering(WBC) was proposed to partition heterogeneous studies into homogeneous subsets. We applied the WBC to UE empirical results and identified two homogeneous subsets, each of which can be meta-analyzed. In addition, interactions between experimental conditions and UE methods were hypothesized based on the resulting partition and some interactions were confirmed via statistical tests.

• 한국항공우주학회지
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• 제49권2호
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• pp.85-93
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• 2021

본 논문에서는 반경험적 해석도구를 이용하여 일반적인 형상의 꼬리날개 조종 유도무기의 공력 특성을 예측하고 그 결과를 보정하는 연구를 수행하였다. 반경험적 해석도구의 공력 특성 예측 결과를 풍동시험 결과와 비교하여 오차 원인을 확인하였으며, 반경험적 해석도구의 주요 오차 요인은 주날개-꼬리날개 간 간섭 성분임을 확인하였다. 반경험적 해석 결과를 풍동시험 결과와 전산해석 결과를 이용하여 보정하였으며, 보정된 데이터가 풍동시험 결과와 잘 일치함을 확인하였다. 본 연구를 통해 일반적인 꼬리날개 조종 유도무기의 공력 특성을 반경험적 해석도구를 이용하여 예측할 때 날개 간 간섭 성분 보정이 필요함을 확인하였다.

• 한국정보시스템학회지:정보시스템연구
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• 제27권1호
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• pp.171-191
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• 2018

Purpose Corporate technology leakage is not only monetary loss, but also has a negative impact on the corporate image and further deteriorates sustainable growth. In particular, since SMEs are highly dependent on core technologies compared to large corporations, loss of technology leakage threatens corporate survival. Therefore, it is important for SMEs to "prevent and protect technology leakage". With the recent development of data analysis technology and the opening of public data, it has become possible to discover and proactively detect companies with a high probability of technology leakage based on actual company data. In this study, we try to construct profiles of enterprises with and without technology leakage experience through profiling analysis using data mining techniques. Furthermore, based on this, we propose a classification model that distinguishes companies that are likely to leak technology. Design/methodology/approach This study tries to develop the empirical model for prevention and protection of technology leakage through profiling method which analyzes each SME from the viewpoint of individual. Based on the previous research, we tried to classify many characteristics of SMEs into six categories and to identify the factors influencing the technology leakage of SMEs from the enterprise point of view. Specifically, we divided the 29 SME characteristics into the following six categories: 'firm characteristics', 'organizational characteristics', 'technical characteristics', 'relational characteristics', 'financial characteristics', and 'enterprise core competencies'. Each characteristic was extracted from the questionnaire data of 'Survey of Small and Medium Enterprises Technology' carried out annually by the Government of the Republic of Korea. Since the number of SMEs with experience of technology leakage in questionnaire data was significantly smaller than the other, we made a 1: 1 correspondence with each sample through mixed sampling. We conducted profiling of companies with and without technology leakage experience using decision-tree technique for research data, and derived meaningful variables that can distinguish the two. Then, empirical model for prevention and protection of technology leakage was developed through discriminant analysis and logistic regression analysis. Findings Profiling analysis shows that technology novelty, enterprise technology group, number of intellectual property registrations, product life cycle, technology development infrastructure level(absence of dedicated organization), enterprise core competency(design) and enterprise core competency(process design) help us find SME's technology leakage. We developed the two empirical model for prevention and protection of technology leakage in SMEs using discriminant analysis and logistic regression analysis, and each hit ratio is 65%(discriminant analysis) and 67%(logistic regression analysis).

• International Journal of Naval Architecture and Ocean Engineering
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• 제7권2호
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• pp.301-314
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• 2015

Aiming at accurately distinguishing modeless component and natural vibration mode terms from data series of nonlinear and non-stationary processes, such as Vortex-Induced Vibration (VIV), a new empirical mode decomposition method has been developed in this paper. The key innovation related to this technique concerns the method to decompose modeless component from non-stationary process, characterized by a predetermined 'maximum intrinsic time window' and cubic spline. The introduction of conceptual modeless component eliminates the requirement of using spurious harmonics to represent nonlinear and non-stationary signals and then makes subsequent modal identification more accurate and meaningful. It neither slacks the vibration power of natural modes nor aggrandizes spurious energy of modeless component. The scale of the maximum intrinsic time window has been well designed, avoiding energy aliasing in data processing. Finally, it has been applied to analyze data series of vortex-induced vibration processes. Taking advantage of this newly introduced empirical decomposition method and mode identification technique, the vibration analysis about vortex-induced vibration becomes more meaningful.

• 한국조리학회지
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• 제23권3호
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• pp.111-122
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• 2017

The purpose of this study was to examine the market segments of Chinese dining-out customers based on their lifestyle. This study focused on the selection and consumption behavior of dining-out customers. The subjects of this study were 20 years old or older diners in Luoyang, China, and the data were collected for 11 days from April 5, 2016. 400 questionnaires were distributed, and 390 copies were collected. After excluding 9 inadequate questionnaires, 381 responses were used for data analysis by using IBM SPSS 23.0, and Data analysis included frequency analysis, cluster analysis, one-way ANOVA, and cross tabulation. The results of empirical analysis showed that there was a significant difference in selection attributes, consumption behavior and demographic characteristics in terms of lifestyle market segments.

• 한국환경과학회지
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• 제20권1호
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• pp.25-34
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• 2011

The new empirical static model was constructed on the basis of dimension analysis to predict the pressure drop according to the operating conditions. The empirical static model consists of the initial pressure drop term (${\Delta}P_{initial}$) and the dust mass number term($N_{dust}=\frac{{\omega}_0{\nu}_f}{P_{pulse}t}$), and two parameters (dust deposit resistance and exponent of dust mass number) have been estimated from experimental data. The optimum injection distance was identified in the 64 experimental data at the fixed filtration velocity and pulse pressure. The dust deposit resistance ($K_d$), one of the empirical static model parameters got the minimum value at d=0.11m, at which the total pressure drop was minimized. The exponent of dust mass number was interpreted as the elasticity of pressure drop to the dust mass number. The elasticity of the unimodal behavior had also a maximum value at d=0.11m, at which the pressure drop increased most rapidly with the dust mass number. Additionally, the correlation coefficient for the new empirical static model was 0.914.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 1998년도 가을 학술발표회 논문집
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• pp.439-446
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• 1998

One of the most important roles in the nonlinear dynamic structural analysis is to select a proper ground excitation, which dominates the response of a structure. Because of the lack of recorded accelerograms in Korea, a stochastic model of ground excitation with various dynamic properties rather than recorded accelerograms is necessarily required. If all information is not available at site, the information from other sites with similar features can be used by the procedure of seismic hazard analysis. Eliopoulos and Wen identified the parameters of the ground motion model by the empirical relations or expressions developed by Trifunac and Lee. Because the relations used in the parameter identification are largely empirical, it is required to apply the artificial neural networks instead of the empirical model. Additionally, neural networks have the advantage of the empirical model that it can continuously re-train the new recorded data, so that it can adapt to the change of the enormous data. Based on the redefined traditional processes, three neural-networks-based models (FAS_NN, PSD_NN and INT_NN) are proposed to individually substitute the Fourier amplitude spectrum, the parameter identification of power spectral density function and intensity function. The paper describes the first half of the research for the development of Neural-Networks-based model for the generation of an Artificial earthquake and a Response Spectrum(NNARS).

• 유통과학연구
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• 제14권11호
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• pp.129-138
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• 2016

Purpose - The ICT(information and communications technologies) development is affecting consumer behaviors on selecting channel or distribution system. This study aims to advance our knowledge about the factors influencing omni-channel behaviors. This study considers the positive brand experience as the moderating variable into the relationship between omini-channel use intention and consumer brand relation. Also, the effect of positive brand experience on consumer-brand relation is researched. Research design, data, and methodology - This study conducted an empirical test with the subject as customers who purchase goods or service through on-off cross channel simultaneously. The research model is developed from prior literatures about influencing variables on channel selection. The structure of this study is designed to identify causal relationships between the variables. 268 survey data from the questionnaire survey which is conducted to target customers who use online and offline channels, is used for empirical analysis. This study validates generality with descriptive statistics and data reliability with Cronbach's alpha value. The exploratory factor analysis is used for value purification. Then, the confirmatory factor analysis is conducted for structural equation modeling. Finally, the execute structural equation modeling is analyzed to confirm the hypotheses Results - First, the two causal influences between perceived performance risk and the propensity of omni-channel and between price consciousness and the propensity of omni-channel are verified through the empirical test. Second, the result identifies that the propensity of omni-channel is influenced on consumer-brand relationship. Third, the AMOS analysis proves that the moderating variable, positive brand experience, has significant positive impact on consumer-brand relationship. This significant relationship is highly supported by the regression analysis between brand experience and propensity of omni-channel because it results that positive brand experience has positive impact on the propensity of omni-channel. All hypotheses are verified to be true. Conclusions - Based on the empirical result, this study confirms that perceived performance risk and price consciousness are the important factors influencing propensity of omni-channel. According to the additional analysis, the moderating variable and positive brand experience plays important role between the propensity of omni-channel and consumer-brand relationship. Furthermore, positive brand experience influences more on consumer-brand relationship than non-positive brand experience.

• 한국항해항만학회지
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• 제27권2호
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• pp.163-170
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• 2003

본 연구는 한중정기항로에서 국적선사 활성화 방안에 관한 실증연구이다. 본 연구를 위하여 한중항로의 국적정기선사, 중국적 정기선사, 3국적 정기선사 등의 종사자에 실문지 500매를 배포하여 290매 회수하였으며, 한중정기항로 국적선사 활성화 요인과 물동량 증대효과의 관련성을 검증하기 위하여 먼저, 설문문항의 신뢰성(Reliability)은 크론바하 알파(Cronbach's Alpha)에 의한 내적 일관성 검사법을 통하여 검정하였고, 독립변수의 구성타당성(Construct Validity)을 검정하기 위해서 변수들이 선형결합이라는 가정 하에 요인을 추출하는 주성분 법(Principal Components)을 이용한 요인분석(Factor Analysis)을 실시하였다. 그리고 연구가설을 검증하기 위하여 다변량 회귀분석(Multiple Regression Analysis)을 실시하였다.

• 유통과학연구
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• 제12권10호
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• pp.67-74
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• 2014

Purpose - This study analyzed how image affects customer trust and satisfaction in the online shopping mall market, which is becoming more competitive; future implications for customer management in online shopping malls were presented. Consumers visit and prefer a few shopping mall sites instead of many sites. Consumers do not visit sites that cannot provide trust and satisfaction. Therefore, establishing trust and satisfaction with differentiated image is essential for survival and growth. Specifically analyzing company image, shop image, and brand image, I studied how symbolic image, functional image, and empirical image affect satisfaction mediated by trust in the online shopping malls of hypermarket retailers. Research design, data, and methodology - To investigate the relationship between image and satisfaction of big box retailers' shopping malls in the online market, the study is based on analyzed data from questionnaires involving advanced research. From May 1st to 20th in the year 2014, a questionnaire survey targeting university students using big box retailers' shopping malls in Seoul was conducted. A total of 282 questionnaires were conducted, and 276 questionnaires were used for empirical analysis, excluding invalid data. Using the SPSS 21.0 statistics package, factor analysis and regression analysis were implemented, and effects of image on trust and satisfaction were presented. Results - First, symbolic image can affect satisfaction with only trust. Among 3 image factors, symbolic image exerts the most influence on trust; trust is important in coupling the medium to satisfaction. Second, functional image and empirical image affect satisfaction directly and indirectly with trust. Conclusions - As I classified the image of hyper market retailers' online shopping malls into symbolic, functional, and empirical image, I analyzed the effects of image on trust and satisfaction empirically. The results of the study and strategic implications are as follows. First, symbolic image can affect satisfaction with only trust. Among 3 image factors, symbolic image exerts the most influence on trust; trust is important in coupling the medium to satisfaction. The establishment of a distinctive symbolic image, such as the online shopping mall's loyalty, level of awareness, and special service, is needed. With the establishment of symbolic image, trust and satisfaction could be improved. Second, functional image and empirical image affect satisfaction directly and indirectly with trust. Especially, as functional image affects trust more than empirical image, setting and implementing a strategy for empirical image based on the right price, service, and convenience could raise trust and satisfaction. Empirical image affects trust and satisfaction substantially. Even though empirical image's influence on trust is lower than that of other three image factors, empirical image's influence on satisfaction is higher than symbolic image. Therefore, it requires a strategy for providing joyful use, and information research functions and distinctive use experience are important to improve satisfaction. This study analyzed image characteristics of hyper-market retailers' online shopping malls in the fast-growing online market; future strategic implications were presented.