• Information Systems Review
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• v.13 no.2
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• pp.1-16
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• 2011

Recently, many companies have started to manage and support CoPs formally at the organizational level because of strategic usability of CoP. These companies are also seeking ways to motivate CoP members to actively participate in their groups. Accordingly, this paper proposes one way of increasing CoP activities by rearranging CoP members. In practice, active CoP members often lead their groups. Therefore, rearranging members can, eventually, be one method to motivate more individuals to participate in CoP activities. This paper first suggests a new approach in order to improve knowledge sharing activities at the organizational level based on rearranging members of current CoPs. Second, a mathematical model is presented which maximizes total BLS (Balanced Level Score) of company A with several constraints. Then a real world problem is changed to a popular problem, VRP to solve this problem. Third, the solution program was developed to find a meaningful solution.

• Journal of Veterinary Clinics
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• v.33 no.5
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• pp.278-285
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• 2016

Epidemiological studies have shown the association between transportation of live animals and the potential transmission of infectious disease between premises. This finding was also observed in the 2014-2015 foot-and-mouth disease (FMD) outbreak in Korea. Furthermore, slaughterhouses played a key role in the global spread of the FMD virus during the epidemic. In this context, in-depth knowledge of the structure of direct and indirect contact between slaughterhouses is paramount for understanding the dynamics of FMD transmission. But the social network structure of vehicle movements to slaughterhouses in Korea remains unclear. Hence, the aim of this study was to configure a social network topology of vehicle movements between slaughterhouses for a better understanding of how they are potentially connected, and to explore whether FMD outbreaks can be explained by the network properties constructed in the study. We created five monthly directed networks based on the frequency and chronology of on- and off-slaughterhouse vehicle movements. For the monthly network, a node represented a slaughterhouse, and an edge (or link) denoted vehicle movement between two slaughterhouses. Movement data were retrieved from the national Korean Animal Health Integrated System (KAHIS) database, which tracks the routes of individual vehicle movements using a global positioning system (GPS). Electronic registration of livestock movements has been a mandatory requirement since 2013 to ensure traceability of such movements. For each of the five studied networks, the network structures were characterized by small-world properties, with a short mean distance, a high clustering coefficient, and a short diameter. In addition, a strongly connected component was observed in each of the created networks, and this giant component included 94.4% to 100% of all network nodes. The characteristic hub-and-spoke type of structure was not identified. Such a structural vulnerability in the network suggests that once an infectious disease (such as FMD) is introduced in a random slaughterhouse within the cohesive component, it can spread to every other slaughterhouse in the component. From an epidemiological perspective, for disease management, empirically derived small-world networks could inform decision-makers on the higher potential for a large FMD epidemic within the livestock industry, and could provide insights into the rapid-transmission dynamics of the disease across long distances, despite a standstill of animal movements during the epidemic, given a single incursion of infection in any slaughterhouse in the country.

• Journal of the Korea Convergence Society
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• v.10 no.3
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• pp.1-6
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• 2019

In modern society, lifestyle and individuality are important, and personalized lifestyle and patterns are emerging. The number of people with articulation diseases is increasing due to wrong living habits. In addition, as the number of households increases, there is a case where emergency care is not received at the appropriate time. We need information that can be managed by ourselves through accurate analysis according to the individual's condition for health and disease management, and care appropriate to the emergency situation. It is effectively used for classification and prediction of data using CNN in deep learning. CNN differs in accuracy and processing time according to the data features. Therefore, it is necessary to improve processing speed and accuracy for real-time healthcare. In this paper, we propose motion monitoring using Mask R-CNN for articulation disease management. The proposed method uses Mask R-CNN which is superior in accuracy and processing time than CNN. After the user's motion is learned in the neural network, if the user's motion is different from the learned data, the control method can be fed back to the user, the emergency situation can be informed to the guardian, and appropriate methods can be taken according to the situation.

• Korean Journal of Remote Sensing
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• v.34 no.6_2
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• pp.1283-1298
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• 2018

KOPRI(Korea Polar Research Institute) have researhed Arctic sea ice by using satellite remote sensing data since 2017 as a mission of KOPRI. The title of the reseach is "Development of Satellite Observation and Analysis for Arctc sea-ice". This project has three major aims; 1) development of prototype satellite data archive/manage system for Arctic sea ice monitoring, 2) development of sea ice remote sensing data processing and analysis technique, and 3) development of international satellite observing network for Arcitc. This reseach will give us that 1) deveolpment of sea ice observing system for northern sea route, 2) development of optimal remote sensing data processing technique for sea ice and selected satelite sensors, 3) development of international satellite onbservation network. I hope that this letter of introducton KOPRI satellite program for Arctic will help to understand Arctic remote sensing and will introduce you to step into the Arctic remote sensing, which Iis like a blue ocean of remote sensing.

• The Journal of Society for e-Business Studies
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• v.26 no.4
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• pp.81-93
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• 2021

Through processors, wholesale markets, intermediate sellers, and retailers, agricultural products have been distributed in a multi-level customary manner for a long time as they are easy to deteriorate and no not have a standardized system of size and quality. However, with the advancement of Internet networks and logistic services during the 2000s that facilitated the development of offline markets, and the rise of the non-contact purchase preference in direct response to COVID-19, previous offline consumers flowed into the online market to purchase agricultural goods. In other words, the volume of online agricultural transactions exploded since the pandemic. Against this social backdrop, this study focused on the difference in distribution costs as a result of converting from conventional offline distribution channels to online channels, and analyzed the reduced distribution costs through a case study of garlic sales on the online platform "H" shopping mall. The analysis found that considerable economic effects occurred, some of the effects being an approximate 39% decrease in distribution cost when comparing direct online transactions of the online shopping mall with other more traditional means, a reduced distribution cost rate of approximately 28%p, and increased profit for farmers.

• International Area Studies Review
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• v.15 no.1
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• pp.447-466
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• 2011

This paper examined the supply chain management Integration factors and environmental performance in Korean industry. Focusing on SCM Integration, GreenSCM practice, and environmental performance factors, purpose of this study is finding linkage between SCM Integration factors with new environmental practice factors and environmental performance. Based on the analysis of eighty-eight cases, the following results were found. First, We found External environmental collaboration factors and Internal environmental monitoring factors within Green Supply Chain Practices. Second, SCM Integration have a positively significant influence on environmental performance. Third, Internal environmental monitoring factors have a positively significant influence on Environmental performance but External environmental collaboration factors doesn't. This study suggests that only with high level of Integration firms may have good result on entire supply chain environmental performance. Finally, our empirical evidence shows that company should be prepared for new environmental trade regulation with Green Supply chain management integration.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.6
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• pp.689-693
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• 2023

Domestic bridges with a service life of more than 30 years are expected to account for approximately 54% of all bridges within the next 10 years. As bridges rapidly deteriorate, it is necessary to establish an appropriate maintenance plan. Recent domestic and international research have focused on the integration of BIM to digitize bridge maintenance information and then enhance accessibility and usability of the information. Accordingly, this study developed a BIM-FEM interoperability algorithm for bridge decks to convert maintenance information into data and efficiently manage the history of maintenance. After creating an initial crack BIM based on an exterior damage map, bridge specification and damage information were linked to a numerical analysis that performs damage analysis considering damage scenarios and design loads. The spread of cracks obtained from the analysis results were updated into the BIM. Based on the damage spread information on the BIM, an automated technology was also developed to assess both the current and future condition ratings of the bridge deck. This approach can enable an efficient maintenance of the deck using the history data from bridge inspection and diagnosis as well as future information on cracks and defects. The expected early detection and prevention would ultimately improve the lifespan and safety of bridges.

• Journal of Korea Water Resources Association
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• v.56 no.5
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• pp.311-323
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• 2023

In order to reduce disaster damage by localized heavy rains, floods, and urban inundation, it is important to know in advance whether natural disasters occur. Currently, heavy rain watch and heavy rain warning by the criteria of the Korea Meteorological Administration are being issued in Korea. However, since this one criterion is applied to the whole country, we can not clearly recognize heavy rain damage for a specific region in advance. Therefore, in this paper, we tried to reset the current criteria for a special weather report which considers the regional characteristics and to predict the damage caused by rainfall after 1 hour. The study area was selected as Gyeonggi-province, where has more frequent heavy rain damage than other regions. Then, the rainfall inducing disaster or hazard-triggering rainfall was set by utilizing hourly rainfall and heavy rain damage data, considering the local characteristics. The heavy rain damage prediction model was developed by a decision tree model and a random forest model, which are machine learning technique and by rainfall inducing disaster and rainfall data. In addition, long short-term memory and deep neural network models were used for predicting rainfall after 1 hour. The predicted rainfall by a developed prediction model was applied to the trained classification model and we predicted whether the rain damage after 1 hour will be occurred or not and we called this as 1ST-Model. The 1ST-Model can be used for preventing and preparing heavy rain disaster and it is judged to be of great contribution in reducing damage caused by heavy rain.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.6
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• pp.89-104
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• 2022

Entrepreneurship by seniors who have accumulated skills and expertise in the industrial field is very important from a social point of view. This study aimed at seniors to find out the major start-up capabilities of seniors in an economic situation where instability factors and uncertainties are amplified due to the social structure of jobs that has changed due to COVID-19 during the 4th industrial revolution and the rapidly progressing high interest rates and global supply chain problems. The purpose of this study was to empirically verify how variables affect entrepreneurial intention. In addition, from the perspective of mindset, which is the individual psychological characteristic of pre-entrepreneurs, we tried to empirically verify whether growth mindset and fixed mindset have a significant effect on senior entrepreneurship intention. The psychological characteristics of founders were approached from the perspective of mindset, and an attempt was made to apply them to the field of entrepreneurship and to obtain practical implications. This study empirically analyzed the effects of growth mindset, fixed mindset, technical competency, network competency, and funding competency, which are components of mindset, on senior entrepreneurial intention, and verified the mediating effect of entrepreneurial efficacy. As a result of the empirical analysis, it was verified that growth mindset and technological competency had a positive (+) effect on entrepreneurial intention. In addition, it was verified that the mediating effect of entrepreneurial efficacy was significant in the influence of growth mindset and technological competency on entrepreneurial intention, and it was verified that growth mindset and technological competency are important variables in senior entrepreneurship. The study results provide the following policy implications. In order to activate senior entrepreneurship, first, to maximize the effect of founder education, programs such as customized entrepreneurship education that match the growth mindset characteristics, which are the psychological characteristics of founders, are needed. Second, it is required to expand the base of technology startups by expanding government support, such as expanding low-interest policy financing, for senior startups with technological capabilities and expertise. Third, it is necessary to provide institutional support for starting a business, such as providing a start-up program even before retirement, so that the expertise and technology accumulated by seniors can be linked to start-ups even after retirement.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.19-42
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• 2012

Consumer consumption patterns are shifting rapidly as buyers migrate from offline markets to e-commerce routes, such as shopping channels on TV and internet shopping malls. In the offline markets consumers go shopping, see the shopping items, and choose from them. Recently consumers tend towards buying at shopping sites free from time and place. However, as e-commerce markets continue to expand, customers are complaining that it is becoming a bigger hassle to shop online. In the online shopping, shoppers have very limited information on the products. The delivered products can be different from what they have wanted. This case results to purchase cancellation. Because these things happen frequently, they are likely to refer to the consumer reviews and companies should be concerned about consumer's voice. E-commerce is a very important marketing tool for suppliers. It can recommend products to customers and connect them directly with suppliers with just a click of a button. The recommender system is being studied in various ways. Some of the more prominent ones include recommendation based on best-seller and demographics, contents filtering, and collaborative filtering. However, these systems all share two weaknesses : they cannot recommend products to consumers on a personal level, and they cannot recommend products to new consumers with no buying history. To fix these problems, we can use the information which has been collected from the questionnaires about their demographics and preference ratings. But, consumers feel these questionnaires are a burden and are unlikely to provide correct information. This study investigates combining collaborative filtering with the centrality of social network analysis. This centrality measure provides the information to infer the preference of new consumers from the shopping history of existing and previous ones. While the past researches had focused on the existing consumers with similar shopping patterns, this study tried to improve the accuracy of recommendation with all shopping information, which included not only similar shopping patterns but also dissimilar ones. Data used in this study, Movie Lens' data, was made by Group Lens research Project Team at University of Minnesota to recommend movies with a collaborative filtering technique. This data was built from the questionnaires of 943 respondents which gave the information on the preference ratings on 1,684 movies. Total data of 100,000 was organized by time, with initial data of 50,000 being existing customers and the latter 50,000 being new customers. The proposed recommender system consists of three systems : [+] group recommender system, [-] group recommender system, and integrated recommender system. [+] group recommender system looks at customers with similar buying patterns as 'neighbors', whereas [-] group recommender system looks at customers with opposite buying patterns as 'contraries'. Integrated recommender system uses both of the aforementioned recommender systems to recommend movies that both recommender systems pick. The study of three systems allows us to find the most suitable recommender system that will optimize accuracy and customer satisfaction. Our analysis showed that integrated recommender system is the best solution among the three systems studied, followed by [-] group recommended system and [+] group recommender system. This result conforms to the intuition that the accuracy of recommendation can be improved using all the relevant information. We provided contour maps and graphs to easily compare the accuracy of each recommender system. Although we saw improvement on accuracy with the integrated recommender system, we must remember that this research is based on static data with no live customers. In other words, consumers did not see the movies actually recommended from the system. Also, this recommendation system may not work well with products other than movies. Thus, it is important to note that recommendation systems need particular calibration for specific product/customer types.