• Journal of the Korean Society of Food Science and Nutrition
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• v.41 no.11
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• pp.1639-1644
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• 2012

This study analyzed the Importance-Performance Analysis of selective attributes of Home Meal Replacement (HMR). This study was conducted using a primary field survey on department stores and wholesale markets in Seoul and Gyeonggi province. A total of 201 out of 234 questionnaires were analyzed. First, the highest intake frequency was 1~3 times a month (100 respondents: 48%), the most common purchasing place was wholesale market (148 respondents: 73.6%), and the most cited reason for preference was convenience (115 respondents: 57.2%). According to the IPA results, selective attributes with low satisfaction and high importance in the second quadrant were 'quality', 'health', 'hygiene', 'origin of food', and 'safety'. These results suggest that the microbiological and sensory qualities of HMR production should be improved to meet consumer's expectations.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.33-51
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• 2022

This study analyzes newly listed companies on KOSDAQ from 2011 to 2020 for both firms having experience in attracting venture investment before listing (VI) and those without having experience in attracting venture investment (NVI) by examining differences between two groups (VI and NVI) with respect to both the level of listing performance and that of firm performance (growth) after the listing. This paper conducts descriptive statistics, mean difference, and multiple regression analysis. Independent variables for regression models include VC investment, firm age at the time of listing, firm type, firm location, firm size, the age of VC, the level of expertise of VC, and the level of fitness of VC with investment company. Throughout this paper, results suggest that listing performance and post-listed growth are better for VI than NVI. VC investment shows a negative effect on the listing period and a positive effect on the sales growth rate. Also, the amount of VC investment has negative effects on the listing period and positive effects on the market capitalization at the time of IPO and on sales growth among growth indicators. Our evidence also implies a significantly positive effect on growth after listing for firms which belong to R&D specialized industries. In addition, it is statistically significant for several years that the firm age has a positive effect on the market capitalization growth rate. This shows that market seems to put the utmost importance on a long-term stability of management capability. Finally, among the VC characteristics such as the age of VC, the level of expertise of VC, and the level of fitness of VC with investment company, we point out that a higher market capitalization tends to be observed at the time of IPO when the level of expertise of anchor VC is high. Our paper differs from prior research in that we reexamine the venture ecosystem under the outbreak of coronavirus disease 2019 which stimulates the degradation of the business environment. In addition, we introduce more effective variables such as VC investment amount when examining the effect of firm type. It enables us to indirectly evaluate the validity of technology exception policy. Although our findings suggest that related policies such as the technology special listing system or the injection of funds into the venture ecosystem are still helpful, those related systems should be updated in a more timely fashion in order to support growth power of firms due to the rapid technological development. Furthermore, industry specialization is essential to achieve regional development, and the growth of the recovery market is also urgent.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.273-283
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• 2020

Because of climate change, the occurrence of localized and heavy rainfall is increasing. It is important to predict floods in urban areas that have suffered inundation in the past. For flood prediction, not only numerical analysis models but also machine learning-based models can be applied. The LSTM (Long Short-Term Memory) neural network used in this study is appropriate for sequence data, but it demands a lot of data. However, rainfall that causes flooding does not appear every year in a single urban basin, meaning it is difficult to collect enough data for deep learning. Therefore, in addition to the rainfall observed in the study area, the observed rainfall in another urban basin was applied in the predictive model. The LSTM neural network was used for predicting the total overflow, and the result of the SWMM (Storm Water Management Model) was applied as target data. The prediction of the inundation map was performed by using logistic regression; the independent variable was the total overflow and the dependent variable was the presence or absence of flooding in each grid. The dependent variable of logistic regression was collected through the simulation results of a two-dimensional flood model. The input data of the two-dimensional flood model were the overflow at each manhole calculated by the SWMM. According to the LSTM neural network parameters, the prediction results of total overflow were compared. Four predictive models were used in this study depending on the parameter of the LSTM. The average RMSE (Root Mean Square Error) for verification and testing was 1.4279 ㎥/s, 1.0079 ㎥/s for the four LSTM models. The minimum RMSE of the verification and testing was calculated as 1.1655 ㎥/s and 0.8797 ㎥/s. It was confirmed that the total overflow can be predicted similarly to the SWMM simulation results. The prediction of inundation extent was performed by linking the logistic regression with the results of the LSTM neural network, and the maximum area fitness was 97.33 % when more than 0.5 m depth was considered. The methodology presented in this study would be helpful in improving urban flood response based on deep learning methodology.

• The Journal of Korean Philosophical History
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• no.28
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• pp.363-386
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• 2010

The purpose of this study is to examine the relationship between theory of Confucian moral cultivation and meditation. Recently our community is more interested in 'a disease of mind'. A view of world, life, values which derived from the distorted perception of 'a disease of mind' can not be treated by psychiatric methods. In this sense, 'a disease of mind' is different from psychiatric illness. In this reason, alternative therapies applying philosophy, literature, arts, and humanities are attracting attention. Meditation is also one of them. In general, Meditation has been developed in Buddhism, but its method is closely related with Confucianism. Buddhist meditation has a pessimistic view of the reality in human life, but that of Confucian philosophy has laid stress on the reality and ego in human life. At this point, the Confucian meditation could provide a clue of solution for us in treatment of a disease of human mind. So Confucian moral cultivation and meditation have a great significance for the treatment of this disease as a methodology. In general, mental healing or psychotherapy has been proceeded by way of dialogue. 'Talking Cure' was conceived to let clients themselves recognize their current situation and find out the problem: "what happened and what's wrong" in their minds. But it does not have a high possibility of successful cure for subjects who are in the state of frustration, confusion, and lost of value. And also it is very difficult to apply to special institutions such as correctional institutions and military soldier who are targeted by current application of Humanities therapy. On this sense, it seems to be valuable to apply Confucian cultivation of mind and meditation which have emphasized the importance of mind-control for this. This study tries to examine theoretically how to relate the Confucian cultivation of mind with meditation, and to suggest a model of Humanities therapy that could be applied by Toe-gye's 『The Method on Preservation of Human mind(活人心方)』. Although Confucian cultivation of mind could present a meaningful theory for curing the disease of mind, it is very difficult to put the theory into practice. It is because Confucian cultivation of mind in itself is a kind of instruction that you need to do in all of your life, and essentially it is difficult to expect a temporary effect by performance or practice. So a cure model of Confucian cultivation of mind will be suggested on this assumption and limitations. This model is attempted on the main purpose of Humanities therapy in accordance with the development of a Korean model.

• Journal of Distribution Research
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• v.15 no.1
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• pp.1-24
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• 2010

I. Introduction The industry of domestic discount store was reorganized with 2 bigs and 1 middle, and then Home Plus took over Home Ever in 2008. In present, Oct, 2008, E-Mart has 118 outlets, Home Plus 112 outlets, and Lotte Mart 60 stores. With total number of 403 outlets, they are getting closer to a saturation point. We know that the industry of discount store has been getting through the mature stage in retail life cycle. There are many efforts to maintain existing customers rather than to get new customers. These competitions in this industry lead firms to acknowledge 'store loyalty' to be the first strategic tool for their sustainable competitiveness. In other words, the strategic goal of discount store is to boost up the repurchase rate of customers throughout increasing store loyalty. If owners of retail shops can figure out main factors for store loyalty, they can easily make more efficient and effective retail strategies which bring about more sales and profits. In this practical sense, there are many papers which are focusing on the antecedents of store loyalty. Many researchers have been inspecting causal relationships between antecedents and store loyalty; store characteristics, store image, atmosphere in store, sales promotion in store, service quality, customer characteristics, crowding, switching cost, trust, satisfaction, commitment, etc., In recent times, many academic researchers and practitioners have been interested in 'dual path model for service loyalty'. There are two paths in store loyalty. First path has an emphasis on symbolic and emotional dimension of service brand, and second path focuses on quality of product and service. We will call the former an extrinsic path and call the latter an intrinsic path. This means that consumers' cognitive path for store loyalty is not single but dual. Existing studies for dual path model are as follows; First, in extrinsic path, some papers in domestic settings show that there is 'store personality-identification-loyalty' path. Second, service quality has an effect on loyalty, which is a behavioral variable, in the mediation of customer satisfaction. But, it's very difficult to find out an empirical paper applied to domestic discount store based on this mediating model. The domestic research for store loyalty concentrates on not only intrinsic path but also extrinsic path. Relatively, an attention for intrinsic path is scarce. And then, we acknowledge that there should be a need for integrating extrinsic and intrinsic path. Also, in terms of retail industry, this study is meaningful because retailers want to achieve their competitiveness by using store loyalty. And so, the purpose of this paper is to integrate and complement two existing paths into one specific model, dual path model. This model includes both intrinsic and extrinsic path for store loyalty. With this research, we would expect to understand the full process of forming customers' store loyalty which had not been clearly explained. In other words, we propose the dual path model for discount store loyalty which has been originated from store personality and service quality. This model is composed of extrinsic path, discount store personality$\rightarrow$store identification$\rightarrow$store loyalty, and intrinsic path, service quality of discount store$\rightarrow$customer satisfaction$\rightarrow$store loyalty. II. Research Model Dual path model integrates intrinsic path and extrinsic path into one specific model. Intrinsic path put an emphasis on quality characteristics and extrinsic path focuses on brand characteristics. Intrinsic path is based on information processing perspective, and extrinsic path emphasizes symbolic and emotional dimension of brand. This model is composed of extrinsic path, discount store personality$\rightarrow$store identification$\rightarrow$store loyalty, and intrinsic path, service quality of discount store$\rightarrow$customer satisfaction$\rightarrow$store loyalty. Hypotheses are as follows; Hypothesis 1: Service quality perceived by customers in discount store has an positive effect on customer satisfaction Hypothesis 2: Store personality perceived by customers in discount store has an positive effect on store identification Hypothesis 3: Customer satisfaction in discount store has an positive effect on store loyalty. Hypothesis 4: Store identification has an positive effect on store loyalty. III. Results and Implications We examined consumers who patronize discount stores for samples of this study. With the structural equation model(SEM) analysis, we empirically tested the validity and fitness of the dual path model for store loyalty in discount stores. As results, the fitness indices of this model were well fitted to data obtained. In an intrinsic path, service quality(SQ) is positively related to customer satisfaction(CS), customer satisfaction(CS) has very significantly positive effect on store loyalty(SL). Also, in an extrinsic path, the store personality(SP) is positively related to store identification(SI), it shows significant effect on store loyalty. Table 1 shows the results as follows; There are some theoretical and practical implications. First, Many studies on discount store loyalty have been executed from various perspectives. But there has been no integrative view on this issue. And so, this research was theoretically designed to integrate various and controversial arguments into one systematic model. We empirically tested dual path model forming store loyalty, and brought up a systematic and integrative framework for future studies. We want to expect creative and aggressive research activities. Second, a few established papers are focused on the relationship between antecedents and store loyalty; store characteristics, atmosphere, sales promotion in store, service quality, trust, commitment, etc., There has been some limits in understanding thoroughly the formation process of store loyalty with a singular path, intrinsic or extrinsic. Beyond these limits in single path, we could propose the new path for store loyalty. This is meaningful. Third, discount store firms make and execute marketing strategies for increasing store loyalty. This research provides real practitioners with reference framework needed for actual strategy formation. Because this paper shows integrated and systematic path for store loyalty. A special feature of this study is to represent 6 sub dimensions of service quality in intrinsic path and 4 sub dimensions of store personality in extrinsic path. Marketers can make more analytic marketing planning with concrete sub dimensions of service quality and store personality. When marketers of discount stores make strategic planning like MPR, Ads, campaign, sales promotion, they can use many items which are more competitive than competitors.

• Journal of the Korean Society for Library and Information Science
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• v.46 no.1
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• pp.163-181
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• 2012

We investigated how useful video tags were in summarizing video speech and how valuable positional information was for speech summarization. Furthermore, we examined the similarity among sentences selected for a speech summary to reduce its redundancy. Based on such analysis results, we then designed and evaluated a method for automatically summarizing speech transcripts using a modified Maximum Marginal Relevance model. This model did not only reduce redundancy but it also enabled the use of social tags, title words, and sentence positional information. Finally, we compared the proposed method to the Extractor system in which key sentences of a video speech were chosen using the frequency and location information of speech content words. Results showed that the precision and recall rates of the proposed method were higher than those of the Extractor system, although there was no significant difference in the recall rates.

• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.961-970
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• 2012

To evaluate companies that participated in the defense R&D project, 27 variables are chosen through literature survey, feature analysis of defense R&D and interviews with military experts. 17 variables are selected after factor analysis which is applied to reduce the number of variables and to detect structure in the relationships among variables, that is to classify variables using Likert-type scales. And then 17 variables are prioritized by AHP (analytic hierarchy process) method. It is shown that communication skill & cooperation strategy, level of technology, possession of needs technology have high priorities. However, protection plan of technology leakage, expertise of subcontractors, software development plan have low priorities.

• Journal of Digital Convergence
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• v.10 no.3
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• pp.191-196
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• 2012

The importance of hi-tech communications technology including mobile or ubiquitous system and the related business field is currently expanding. In terms of wellness for enhancing quality of individual life, ICT technology became a requirement, not an option. The first purpose of this study is to identify factors that influence user's perceived usefulness & perceived ease of use related to the acceptance of TAM focused on ubiquitous fitness service through multiple regression analysis, thereby discovering important factors influencing consumer behavior. In conjunction with the result, the second purpose of this study has also its implication on the u-Healthcare system development using QFD. That is, this research is to propose the possibility of combining the external variables of TAM to u-Healthcare system service characteristics with user requirement reflected by using QFD method. Based on these results, the suitable system may be constructed and developed.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.5
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• pp.1138-1149
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• 1993

A new mode synthesis method using Lagrange multipliers and substructure hybrid interface modes is presented. Substruture governing equations of motion are derived using Lagrange equations and the constraints of geometric compatibility between the substructures are treated with Lagrange multipliers. Fixed, free, and loaded interface modes can be employed for the modal bases of each substructure. In cases of the fixed and loaded interface modes, two successive modal transformation relations are used. Compared with the conventional mode synthesis methods, the suggested method does not construct the equations of motion of the coupled structure and the final characteristic equation becomes a polynomial. Only modal parameters of each substructure and geometric compatibility conditions are needed. The suggested method is applied to a simple lumped mass model and parametric study is performed.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.43-55
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• 2016

This study estimated land prices using instance-based learning. A k-nearest neighbor method was utilized among various instance-based learning methods, and the 10 distance metrics including Euclidean distance were calculated in k-nearest neighbor estimation. One distance metric prediction which shows the best predictive performance would be normally chosen as final estimate out of 10 distance metric predictions. In contrast to this practice, an ensemble technique which combines multiple predictions to obtain better performance was applied in this study. We applied the gradient boosting algorithm, a sort of residual-fitting model to our data in ensemble combining. Sales price data of farm lands in Haenam-gun, Jeolla Province were used to demonstrate advantages of instance-based learning as well as an ensemble technique. The result showed that the ensemble prediction was more accurate than previous 10 distance metric predictions.