• Proceedings of the Korea Inteligent Information System Society Conference
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• 2005.11a
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• pp.241-250
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• 2005

New product development (NPD) is defined as the transformation of a market opportunity and a set of assumptions about product technology into a product available for sale. Managers charged with project selection decisions in the NPD process, such as go/no-go choices and specific resource allocation decisions, are faced with a complicated problem. Therefore, the ability to develop new successful products has identifies as a major determinant in sustaining a firm's competitive advantage. The purpose of this study is to develop a new evaluation model for NPD project selection in the high -tech industry using support vector machines (SYM). The evaluation model is developed through two phases. In the first phase, binary (go/no-go) classification prediction model, i.e. SVM for high-tech NPD project selection is developed. In the second phase. using the predicted output value of SVM, feasibility grade is calculated for the final NPD project decision making. In this study, the feasibility grades are also divided as three level grades. We assume that the frequency of NPD project cases is symmetrically determined according to the feasibility grades and misclassification errors are partially minimized by the multiple grades. However, the horizon of grade level can be changed by firms' NPD strategy. Our proposed feasibility grade method is more reasonable in NPD decision problems by considering particularly risk factor of NPD in viewpoints of future NPD success probability. In our empirical study using Korean NPD cases, the SVM significantly outperformed ANN and logistic regression as benchmark models in hit ratio. And the feasibility grades generated from the predicted output value of SVM showed that they can offer a useful guideline for NPD project selection.

• Journal of Nutrition and Health
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• v.52 no.6
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• pp.593-603
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• 2019

Purpose: Previous studies have highlighted that the nutritional behaviors among South Korean workers are far from ideal. This study examined the organizational influences affecting the eating practices of office workers in South Korea. Methods: We conducted in-depth interviews with 22 office workers at 12 companies in South Korea. The interviewer inquired about the employees' daily routines on food and beverage intake. The various factors that influence their food choices in their work environments were also explored. The interviews were transcribed and then analyzed using a content analysis. Results: A framework analysis revealed 7 key recurring themes, and these were grouped under three levels: team-, company-, and corporate group-levels. First, team dinners are core social events for all the workers and they tend to include high-caloric food and alcoholic beverages. The frequency of team meals and the food associated with them depend on various team characteristics such as gender composition, the nature of a team's work and the team leaders' emphasis on group meals. Second, the company's policies and practices regarding budget allocation for team meals and subsidies for cafeteria meals affect the workers' food intake practices. In addition, the physical environment of the worksite cafeterias can influence the choices of foods. Third, various corporate group policies that were not designed to target food intake had additional positive effects on the workers' eating behaviors. Conclusion: This study provides important insights into the broader organizational influences on the food consumption of employees in their workplace. These insights can be used to design and implement more effective intervention strategies for improving the nutritional behaviors of office workers.

• Publications of The Korean Astronomical Society
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• v.18 no.1
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• pp.97-110
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• 2003

WRC-03 was held between 9 June and 4 July 2003 in Geneva, Switzerland. Over 2,200 delegates from 138 ITU Member States attended the Conference. The delegates considered some 2,500 proposals, and over 900 numbered documents related to 50 agenda items. The final output of the Conference consists of 527 pages of new and revised text of the Radio Regulations. This paper provides some details about the outcome of the radio astronomy related issues at the WRC-03 Conference. It is divided into two part: a) Agenda item1.8.2 and b) Agenda item 1.32, related to radio astronomy. Relevant extracts from the Final Acts of WRC-03 are given in the Appendix. Agenda item 1.8.2 was one of the most controversial Agenda Items at WRC-03. Studies were carried out within ITU-R TG 1/7 for the last three years; the results of these studies are summarized in Recommendation ITU-R SM.1633. The Conference adopted a new footnote (5.347A), that calls for the application of Resolution 739 (WRC-03) in the 1452-1492 MHz, 1525-1559 MHz, 1613.8-1626.5 MHz, 2655-2670 MHz, 2670-2690 MHz and 21.4-22.0 GHz bands. Agenda item 1.32 is to consider technical and reglatory provisions concerning the band 37.5-43.5 GHz, in accordance with Resolutions 128 (Rev.WRC-2000) and 84 (WRC-2000). WRC-03 reviewed and adjusted the New footnotes 5.551H and 5.551I cover the protection of radio astronomy observations in the 42.5-43.5 GHz band from unwanted emissions by non-geostationary (5.551H) and geostationary (5.551I) FSS and BSS systems, respectively.

• Journal of Navigation and Port Research
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• v.45 no.6
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• pp.360-365
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• 2021

LTE-maritime, which was built as part of the Korean e-Navigation project, has been providing a service that meets the goal of establishing a network up to 100km from the coast since J anuary 31, 2021. To provide appropriate communication services for LTE-maritime from the perspective of real users, additional performance analysis of LTE-maritime is required considering service implementation, and efficient use of spectrum resources. This paper presents the requirement of transmission speed according to the e-Navigation service scenario, and available transmission speed based on LTE modulation coding scheme (MCS) according to sea-specific ship distribution scenario and frequency resource allocation, and is cross-analyzed with results of the sea test.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.74-86
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• 2019

As many existing research fields are matured academically, researchers have encountered numbers of academic, social and other problems that cannot be addressed by internal knowledge and methodologies of existing disciplines. Earlier, pioneers of researchers thus are following a new paradigm that breaks the boundaries between the prior disciplines, fuses them and seeks new approaches. Moreover, developed countries including Korea are actively supporting and fostering the convergence research at the national level. Nevertheless, there is insufficient research to analyze convergence trends in national R&D support projects and what kind of content the projects mainly deal with. This study, therefore, collected and preprocessed the research proposal data of National Research Foundation of Korea, transforming the proposal documents to term-frequency matrices. Based on the matrices, this study derived detailed research topics through Latent Dirichlet Allocation, a kind of topic modeling algorithm. Next, this study identified the research topics each proposal mainly deals with, visualized the convergence relationships, and quantitatively analyze them. Specifically, this study analyzed the centralities of the detailed research topics to derive clues about the convergence of the near future, in addition to visualizing the convergence relationship and analyzing time-varying number of research proposals per each topic. The results of this study can provide specific insights on the research direction to researchers and monitor domestic convergence R&D trends by year.

• Journal of the Korean Society of Radiology
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• v.16 no.3
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• pp.343-349
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• 2022

We intend to use topic modeling to identify radiation-themed papers published from 1989 to 2022 and analyze the relevance and weight between topics. This study analyzed topics derived from national subjects for 717 papers published until recently in 2022 to contribute to the revitalization of research in the field of radiation. Through text mining, overall research trends on the subject distribution of the study were analyzed, and five topics were derived through topic modeling. First, among the papers to be analyzed, a total of 1,675 words were frequency-analyzed through the preprocessing process of key words in a total of 717 papers centered on keywords. Second, as a result of analyzing topics based on the association of constituent words for five topics, it was found that studies focused on minimizing dose in the range that does not degrade image quality in the fields of radiation, image, CT clinical. In addition, it was found that various studies were mainly conducted in the MRI, and the study of ultrasound in various areas of disease analysis was actively attempted.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.5
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• pp.37-48
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• 2022

With development of Digital Technology, social issues are communicated through digital-based platform such as SNS and form public opinion. This study attempted to analyze big data from Twitter, a world-renowned social network service, and find out the public opinion. After collecting Twitter data based on 14 keywords for 1 year in 2021, analyzed the term-frequency and relationship among keyword documents with pearson correlation coefficient using Data-mining Technology. Furthermore, the 6 main topics that on the center of information security field in 2021 were derived through topic modeling using the LDA(Latent Dirichlet Allocation) technique. These results are expected to be used as basic data especially finding key agenda when establishing strategies for the next step related industries or establishing government policies.

• The Korean Journal of Applied Statistics
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• v.35 no.6
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• pp.739-754
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• 2022

Usually, text data consists of many variables, and some of them are closely correlated. Such multi-collinearity often results in inefficient or inaccurate statistical analysis. For supervised learning, one can select features by examining the relationship between target variables and explanatory variables. On the other hand, for unsupervised learning, since target variables are absent, one cannot use such a feature selection procedure as in supervised learning. In this study, we propose a word selection procedure that employs topic models to find latent topics. We substitute topics for the target variables and select terms which show high relevance for each topic. Applying the procedure to real data, we found that the proposed word selection procedure can give clear topic interpretation by removing high-frequency words prevalent in various topics. In addition, we observed that, by applying the selected variables to the classifiers such as naïve Bayes classifiers and support vector machines, the proposed feature selection procedure gives results comparable to those obtained by using class label information.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6D
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• pp.927-933
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• 2006

The Variable Message Signs (VMS) are useful way to reduce the socio-economic costs due to the traffic congestions and delays by providing the information on traffic condition to drivers. This study provided a methodology to determine the locations of VMS's in terms of the minimization of the delay by applying the genetic algorithm. The optimal number of VMS's was also derived by the economic analysis based on the cost and the benefit. The simulation considered the variation of traffic volume, the frequency and duration of the incident, and the traffic conversion in order to reflect the real situation. I've made a scenario to consider traffic volume and incident, and it can undergo through changing different traffic volume and incident in time and days and seasons. And I've comprised two kinds of result, one is based on empirical studies, the other is based on Genetic Algorithm about optimal allocation VMS. This result of using optimal location VMS, reduce total travel time rather than preceding study based on normal location VMS and we can estimate optimal location VMS each one.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.6
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• pp.65-78
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• 2023

In recent times, the frequency and intensity of natural disasters, such as heavy rains and typhoons, have been increasing due to the impacts of climate change. This has led to a rise in social and economic damages. Rural areas, in particular, possess limited disaster response capabilities due to their underdeveloped infrastructure and are highly vulnerable to flooding. Therefore, it is crucial to establish preventative and responsive measures. In this study, an Inventory-Based Flood Loss Estimation (IB-FLE) method utilizing high-resolution spatial information was developed for estimating flood-related losses in rural areas. Additionally, the developed approach was applied to a study area and compared with the Multidimensional Flood Damage Analysis (MD-FDA) method. Compared to the MD-FDA, the IB-FLE enables faster and more accurate estimation of flood damages and allows for the assessment of individual building and agricultural land losses using up-to-date information. The findings of this study are expected to contribute to the rational allocation of budgets for rural flood damage prevention and recovery, as well as enhancing disaster response capabilities.