• Journal of Gastric Cancer
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• v.21 no.4
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• pp.368-378
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• 2021

Purpose: When patients with early gastric cancer (EGC) undergo non-curative endoscopic submucosal dissection requiring gastrectomy (NC-ESD-RG), additional medical resources and expenses are required for surgery. To reduce this burden, predictive model for NC-ESD-RG is required. Materials and Methods: Data from 2,997 patients undergoing ESD for 3,127 forceps biopsy-proven differentiated-type EGCs (2,345 and 782 in training and validation sets, respectively) were reviewed. Using the training set, the logistic stepwise regression analysis determined the independent predictors of NC-ESD-RG (NC-ESD other than cases with lateral resection margin involvement or piecemeal resection as the only non-curative factor). Using these predictors, a risk-scoring system for predicting NC-ESD-RG was developed. Performance of the predictive model was examined internally with the validation set. Results: Rate of NC-ESD-RG was 17.3%. Independent pre-ESD predictors for NC-ESD-RG included moderately differentiated or papillary EGC, large tumor size, proximal tumor location, lesion at greater curvature, elevated or depressed morphology, and presence of ulcers. A risk-score was assigned to each predictor of NC-ESD-RG. The area under the receiver operating characteristic curve for predicting NC-ESD-RG was 0.672 in both training and validation sets. A risk-score of 5 points was the optimal cut-off value for predicting NC-ESD-RG, and the overall accuracy was 72.7%. As the total risk score increased, the predicted risk for NC-ESD-RG increased from 3.8% to 72.6%. Conclusions: We developed and validated a risk-scoring system for predicting NC-ESD-RG based on pre-ESD variables. Our risk-scoring system can facilitate informed consent and decision-making for preoperative treatment selection between ESD and surgery in patients with EGC.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.287-298
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• 2023

The purpose of this study is to analyze the compensation law for Special Mission Executors enacted to compensate for sacrifices for the state based on the policy framework proposed by Gilbert and Terrell and to present the limitations and development directions of the compensation policy. In particular, this study presents the characteristics of each dimension of the policy through the bases of social allocation, the types of social provisions, the strategies for the delivery, and the ways to finance. Through the analysis, We deduce problems of the compensation law for Special Mission Executors. Representative limitations of the compensation policy can be summarized as follows. Due to extreme selectivism, the limitations are the narrow selection criteria of the targets, the benefits which are not out of proportional to contributions, delayed benefits and the decrease in the size of public resources. These limitations suggest that the compensation policy for Special Mission Executors does not contain the significance of the Patriots and Veterans Affairs Policy. The value the Patriots and Veterans Affairs can be considered as a means for repaying the contributions who sacrificed for the nation. Therefore, the government needs to make efforts to develop a policy with the true significance of the Patriots and Veterans Affairs.

• Korea Trade Review
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• v.43 no.2
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• pp.159-180
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• 2018

The purpose of this study is to contribute to the efficient selection of SMEs' trade settlement system through the empirical analysis of determinants of the payment method of SMEs in Korea. In the previous study, external factors, internal factors, settlement characteristics, transaction goods, transaction amount factors and risk management factors were used. Questionnaires were excluded from analysis, and the number of validated samples collected was 155. To conduct the study, all empirical analyses were verified at the significance level p <.005. Statistical analysis was performed using the SPSSWIN 18.0 program. Analysis results found the payment method used in the company was based on the year of establishment, export items, transaction area, type of transaction, and size of company. Empirical analysis showed that factors influencing the choice of the letter of credit are external factors, internal factors, the risk management factors, and the transaction amounts, etc. Results of this study are as follows: First, the effects of external factors, internal factors, settlement characteristics, and transaction amounts were significant. Hypothesis testing of collections trading methods has not been adopted in all areas presented. In order to utilize the research results, we conducted the study and comparison of the payment method of the income.

• Journal of agriculture & life science
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• v.50 no.5
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• pp.51-60
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• 2016

This study was selected drought tolerant plants, by observing the physiological characteristics and biochemical materials from the 9 kinds of the Compositae plants. After selecting plants of the similar size, and then drought stress was induced by the irrigation stopping. Survival rates, chlorophyll values, relative water content(RWC), excised-leaf water loss(ELWL), proline, reducing sugar were measured after 30 days of stopping irrigation. The species that had high rates of survival were Ainsliaea acerifolia Sch. Bip, Aster koraiensis, Aster scaber, Dendranthema zawadskii(S), however other 5 species were dead. The remaining factors have been determined based on plant species showed a higher survival rate. However, chlorophyll content showed high values in A. acerifolia, A.altaicus var. uchiyamae, A. koraiensis, and will have been determined that has no correlation with survival rates, except for A. acerifolia and A. koraiensis. On the other hand, A. scaber, A. acerifolia, A. koraiensis were determined to be relatively high drought tolerant plants in RWC, ELWL, proline, reducing sugar, it showed a similar correlation with survival rate. As a result of 9 kinds of the Compositae plants A. scaber, A. acerifolia, A. koraiensis were considered relatively higher drought tolerant plants.

• Journal of Industrial Convergence
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• v.21 no.8
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• pp.97-110
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• 2023

This study presents a systematic literature review aimed at integrating and analyzing the research findings regarding the components of various self-care intervention programs conducted for individuals with chronic obstructive pulmonary disease (COPD) both domestically and internationally. The paper selection criteria were established based on materials from PubMed, CINAHL, EMBASE, /MEDLINE, RISS, DBpia, KISS, and KMbase databases, covering the period from January 1, 2000, to September 30, 2022. The inclusion criteria included controlled pre-post experimental study designs. A total of 23 studies were included in this systematic review. The intervention-related factors examined included the sample size, type of intervention mediator, intervention frequency, and duration. Additionally, factors associated with intervention effects, such as measurement tools and variables, were analyzed. The findings of the analysis support the notion that self-care intervention programs for COPD can contribute to the prevention of symptom exacerbation and hospital readmissions among patients. Consequently, the development of a tailored self-care intervention program specifically designed for COPD patients in South Korea is warranted, considering aspects such as patient accessibility, convenience, and motivation for long-term sustainability.

• Korean Journal of Construction Engineering and Management
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• v.10 no.2
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• pp.65-74
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• 2009

It is expected that the number of apartment complexes in Korea that are over 20 years old will rapidly increase to more than 3,500,000. Consequently, the remodeling of these buildings is being revitalized throughout the country. Among the requirements for such remodeling, the expansion of parking lots has considerable weight. When enlarging a parking lot, the access route from an underground floor to the main building (i.e., the means of entry into the main building) determines the possibility of vertical enlargement for elevators, the size of the parking lot, the construction period, and construction expenses, etc. When enlarging an underground parking lot of an apartment complex, the access between the main building and the parking lot, as well as the inhabitants' requirements for entering the main building, are generally determined based on the designer's experience, rather than on the exact estimation of the peculiarity of the complex. In order to resolve such a problem, when enlarging an underground parking lot, a systematic and rational method is needed for selecting the means of entry into the main building. In this study, a selection model is derived for the method of selecting an access route into the main building when constructing an underground parking lot, in order to provide a reasonable decision-making process. A research method was investigated for determining the access route into the main building when enlarging a parking lot. On the basis of research carried out through in-depth interviews with experts, the characteristics for each means of entry into the main building were analyzed and the factors affecting the selection of the access route were deduced. The affecting factors selected were construction efficiency, convenience efficiency and economic efficiency. Weight values were then estimated for the selected affecting factors by applying the AHP method. Results showed that convenience efficiency, which gained the highest value, is the most important factor in selecting the means of entry into the main building. The most suitable means of entry into the main building was also suggested after estimating the applicability of the site by selecting complexes with remodeling possibility. This study will be applied as a reference for selecting the means of entry into the main building when constructing an underground parking lot particularly for older apartment complexes.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.9 no.5
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• pp.83-94
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• 2014

Before economical crisis in 1997, domestic company focused on increasing the size of outward experience which including organization. The result of increasing outward experience without substance was economical crisis, so after that time, many companies have been changing their focus from insourcing to strengthen the core competence to secure global market. This is becoming a cause of following that companies are reducing their outward experience. Especially, to process tasks more effectively and to cope with rapid change of business environment, such as incoming raw material from overseas/high raising of salary/rising property prices, many companies decided outsourcing method. At most of hypothesis, the result was that outsourcing can affect positively to the business. First, introducing of outsourcing during focusing on core competence can be positive effect for company performance such as business management /productivity /procurement /administration /product competitiveness /technology. Second, the result that analyzed based on a point of view of population statics after outsourcing was positive effect at the most of research. Third, result of effectiveness for every outsourcing type classified by 4M was also can be positive at the most of research. Fourth, the characteristic of population statics can be positive effect at the most of category when select outsourcing companies. Research result of outsourcing was various based on the goal of outsourcing. It is revealed by investigation of domestic/overseas treatise that there are opposite two opinions. In this research, there is no consistent result that the outsourcing can give effects on business performance, but most of hypothesis indicates that outsourcing can give positive effect on the business performance.In this research, based on the outsourcing intensity, mutual relation was analyzed. The assumption of the reason of outsourcing is economical and organizational. First, sampling numbers of research was too small so it is too difficult to get significant business performance result. (Sampling : 150, Replied : 106, Rate of Reply : 71%) Second, tried to compare significant differences of outsourcing methods which were divided based on 4M, but the there is gaps between the number of Cell and too difficult to make replier understand. Third, it is tried to find the degrees of effect that the point of view of popular statics can effect on business performances and selection of outsourced companies.

• Journal of Intelligence and Information Systems
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• v.23 no.1
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• pp.127-141
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• 2017

Advances in Internet technologies and the proliferation of mobile devices enabled consumers to approach a wide range of goods and services, while causing an adverse effect that they have hard time reaching their congenial items even if they devote much time to searching for them. Accordingly, businesses are using the recommender systems to provide tools for consumers to find the desired items more easily. Association Rule Mining (ARM) technology is advantageous to recommender systems in that ARM provides intuitive form of a rule with interestingness measures (support, confidence, and lift) describing the relationship between items. Given an item, its relevant items can be distinguished with the help of the measures that show the strength of relationship between items. Based on the strength, the most pertinent items can be chosen among other items and exposed to a given item's web page. However, the diversity of the measures may confuse which items are more recommendable. Given two rules, for example, one rule's support and confidence may not be concurrently superior to the other rule's. Such discrepancy of the measures in distinguishing one rule's superiority from other rules may cause difficulty in selecting proper items for recommendation. In addition, in an online environment where a web page or mobile screen can provide a limited number of recommendations that attract consumer interest, the prudent selection of items to be included in the list of recommendations is very important. The exposure of items of little interest may lead consumers to ignore the recommendations. Then, such consumers will possibly not pay attention to other forms of marketing activities. Therefore, the measures should be aligned with the probability of consumer's acceptance of recommendations. For this reason, this study proposes a model-based approach to combine those measures into one unified measure that can consistently determine the ranking of recommended items. A regression model was designed to describe how well the measures (independent variables; i.e., support, confidence, and lift) explain consumer's acceptance of recommendations (dependent variables, hit rate of recommended items). The model is intuitive to understand and easy to use in that the equation consists of the commonly used measures for ARM and can be used in the estimation of hit rates. The experiment using transaction data from one of the Korea's largest online shopping malls was conducted to show that the proposed model can improve the hit rates of recommendations. From the top of the list to 13th place, recommended items in the higher rakings from the proposed model show the higher hit rates than those from the competitive model's. The result shows that the proposed model's performance is superior to the competitive model's in online recommendation environment. In a web page, consumers are provided around ten recommendations with which the proposed model outperforms. Moreover, a mobile device cannot expose many items simultaneously due to its limited screen size. Therefore, the result shows that the newly devised recommendation technique is suitable for the mobile recommender systems. While this study has been conducted to cover the cross-selling in online shopping malls that handle merchandise, the proposed method can be expected to be applied in various situations under which association rules apply. For example, this model can be applied to medical diagnostic systems that predict candidate diseases from a patient's symptoms. To increase the efficiency of the model, additional variables will need to be considered for the elaboration of the model in future studies. For example, price can be a good candidate for an explanatory variable because it has a major impact on consumer purchase decisions. If the prices of recommended items are much higher than the items in which a consumer is interested, the consumer may hesitate to accept the recommendations.

• Journal of Intelligence and Information Systems
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• v.20 no.4
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• pp.1-23
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• 2014

Market forecasting aims to estimate the sales volume of a product or service that is sold to consumers for a specific selling period. From the perspective of the enterprise, accurate market forecasting assists in determining the timing of new product introduction, product design, and establishing production plans and marketing strategies that enable a more efficient decision-making process. Moreover, accurate market forecasting enables governments to efficiently establish a national budget organization. This study aims to generate a market growth curve for ICT (information and communication technology) goods using past time series data; categorize products showing similar growth patterns; understand markets in the industry; and forecast the future outlook of such products. This study suggests the useful and meaningful process (or methodology) to identify the market growth pattern with quantitative growth model and data mining algorithm. The study employs the following methodology. At the first stage, past time series data are collected based on the target products or services of categorized industry. The data, such as the volume of sales and domestic consumption for a specific product or service, are collected from the relevant government ministry, the National Statistical Office, and other relevant government organizations. For collected data that may not be analyzed due to the lack of past data and the alteration of code names, data pre-processing work should be performed. At the second stage of this process, an optimal model for market forecasting should be selected. This model can be varied on the basis of the characteristics of each categorized industry. As this study is focused on the ICT industry, which has more frequent new technology appearances resulting in changes of the market structure, Logistic model, Gompertz model, and Bass model are selected. A hybrid model that combines different models can also be considered. The hybrid model considered for use in this study analyzes the size of the market potential through the Logistic and Gompertz models, and then the figures are used for the Bass model. The third stage of this process is to evaluate which model most accurately explains the data. In order to do this, the parameter should be estimated on the basis of the collected past time series data to generate the models' predictive value and calculate the root-mean squared error (RMSE). The model that shows the lowest average RMSE value for every product type is considered as the best model. At the fourth stage of this process, based on the estimated parameter value generated by the best model, a market growth pattern map is constructed with self-organizing map algorithm. A self-organizing map is learning with market pattern parameters for all products or services as input data, and the products or services are organized into an $N{\times}N$ map. The number of clusters increase from 2 to M, depending on the characteristics of the nodes on the map. The clusters are divided into zones, and the clusters with the ability to provide the most meaningful explanation are selected. Based on the final selection of clusters, the boundaries between the nodes are selected and, ultimately, the market growth pattern map is completed. The last step is to determine the final characteristics of the clusters as well as the market growth curve. The average of the market growth pattern parameters in the clusters is taken to be a representative figure. Using this figure, a growth curve is drawn for each cluster, and their characteristics are analyzed. Also, taking into consideration the product types in each cluster, their characteristics can be qualitatively generated. We expect that the process and system that this paper suggests can be used as a tool for forecasting demand in the ICT and other industries.

• Journal of Korean Society of Transportation
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• v.18 no.1
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• pp.75-85
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• 2000

In existing models in optimization, the crisp data improve has been used in the objective or constraints to derive the optimal solution, Besides, the subjective environments are eliminated because the complex and uncertain circumstances were regarded as Probable ambiguity, In other words those optimal solutions in the existing models could be the complete satisfactory solutions to the objective functions in the Process of application for industrial engineering methods to minimize risks of decision-making. As a result of those, decision-makers in location Problems couldn't face appropriately with the variation of demand as well as other variables and couldn't Provide the chance of wide selection because of the insufficient information. So under the circumstance. it has been to develop the model for the location and size decision problems of logistics facility in the use of the fuzzy theory in the intention of making the most reasonable decision in the Point of subjective view under ambiguous circumstances, in the foundation of the existing decision-making problems which must satisfy the constraints to optimize the objective function in strictly given conditions in this study. Introducing the Process used in this study after the establishment of a general mixed integer Programming(MIP) model based upon the result of existing studies to decide the location and size simultaneously, a fuzzy mixed integer Programming(FMIP) model has been developed in the use of fuzzy theory. And the general linear Programming software, LINDO 6.01 has been used to simulate, to evaluate the developed model with the examples and to judge of the appropriateness and adaptability of the model(FMIP) in the real world.