• Management & Information Systems Review
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• v.36 no.4
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• pp.33-51
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• 2017

With the advent of 'The Forth Industrial Revolution' and the growing demand for quality of life due to economic growth, needs for the quality of medical services are increasing. Artificial intelligence has been introduced in the medical field, but it is rarely used in chronic skin diseases that directly affect the quality of life. Also, atopic dermatitis, a representative disease among chronic skin diseases, has a disadvantage in that it is difficult to make an objective diagnosis of the severity of lesions. The aim of this study is to establish an intelligent severity recognition model of atopic dermatitis for improving the quality of patient's life. For this, the following steps were performed. First, image data of patients with atopic dermatitis were collected from the Catholic University of Korea Seoul Saint Mary's Hospital. Refinement and labeling were performed on the collected image data to obtain training and verification data that suitable for the objective intelligent atopic dermatitis severity recognition model. Second, learning and verification of various CNN algorithms are performed to select an image recognition algorithm that suitable for the objective intelligent atopic dermatitis severity recognition model. Experimental results showed that 'ResNet V1 101' and 'ResNet V2 50' were measured the highest performance with Erythema and Excoriation over 90% accuracy, and 'VGG-NET' was measured 89% accuracy lower than the two lesions due to lack of training data. The proposed methodology demonstrates that the image recognition algorithm has high performance not only in the field of object recognition but also in the medical field requiring expert knowledge. In addition, this study is expected to be highly applicable in the field of atopic dermatitis due to it uses image data of actual atopic dermatitis patients.

• Management & Information Systems Review
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• v.39 no.3
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• pp.1-16
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• 2020

The current tariff return system requires tax officials to calculate tax amount by themselves and pay the tax amount on their own responsibility. In other words, in principle, the duty and responsibility of reporting payment system are imposed only on the taxee who is required to calculate and pay the tax accurately. In case the tax payment system fails to fulfill the duty and responsibility, the additional tax is imposed on the taxee by collecting the tax shortfall and imposing the tax deduction on For this reason, item classifications, together with tariff assessments, are the most difficult and could pose a significant risk to entities if they are misclassified. For this reason, import reports are consigned to customs officials, who are customs experts, while paying a substantial fee. The purpose of this study is to classify HS items to be reported upon import declaration and to indicate HS codes to be recorded on import declaration. HS items were classified using the attached image in the case of item classification based on the case of the classification of items by the Korea Customs Service for classification of HS items. For image classification, CNN was used as a deep learning algorithm commonly used for image recognition and Vgg16, Vgg19, ResNet50 and Inception-V3 models were used among CNN models. To improve classification accuracy, two datasets were created. Dataset1 selected five types with the most HS code images, and Dataset2 was tested by dividing them into five types with 87 Chapter, the most among HS code 2 units. The classification accuracy was highest when HS item classification was performed by learning with dual database2, the corresponding model was Inception-V3, and the ResNet50 had the lowest classification accuracy. The study identified the possibility of HS item classification based on the first item image registered in the item classification determination case, and the second point of this study is that HS item classification, which has not been attempted before, was attempted through the CNN model.

• Management & Information Systems Review
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• v.36 no.5
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• pp.45-60
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• 2017

This study aims to elucidate the key improvements through the current state of customer support for smart home services based on the Internet of things and the evaluation of user's usage. Smart home services typically provide a wide range of value in terms of security, safety, manageability (electricity and water use), convenience, and remote management accessibility. In this study, we analyzed the current state of smart home service based on Internet of Samsung, SKT and LG U + companies in Korea. However, since LG U+ is the only company providing user reviews, there is a limit to generalization, but we are trying to figure out whether the customer value is conveyed properly or not, and in which part the customer support is focused to support the service. As a result of analyzing the results of the study, we found that the smart home service is commercialized and marketed in various forms. However, it is questionable whether the technological level and user satisfaction level are sufficiently satisfied. The results of this study are as follows. First, although each company provides usage guidance, they still ask many questions about joining products and using products. Second, there are many defects in the product itself, and it is found that the companies are not satisfied with the overall response. Third, the three companies are focusing on switches, outlets, sensors, and lamps. This is an individual intelligent product rather than an interlocking or linking level, and it can be seen that there are many parts that are not compatible with the concept of the original Internet of things. In conclusion, this study shows that there are still many areas to improve on the level of customer service provision of smart home service, in particular, the ease of use is low and the quality of products is not reliable. We would like to present the improvement of this in detail through this study and reflect the companies that provide it and the service providers.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.83-102
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• 2021

The government recently announced various policies for developing big-data and artificial intelligence fields to provide a great opportunity to the public with respect to disclosure of high-quality data within public institutions. KSURE(Korea Trade Insurance Corporation) is a major public institution for financial policy in Korea, and thus the company is strongly committed to backing export companies with various systems. Nevertheless, there are still fewer cases of realized business model based on big-data analyses. In this situation, this paper aims to develop a new business model which can be applied to an ex-ante prediction for the likelihood of the insurance accident of credit guarantee. We utilize internal data from KSURE which supports export companies in Korea and apply machine learning models. Then, we conduct performance comparison among the predictive models including Logistic Regression, Random Forest, XGBoost, LightGBM, and DNN(Deep Neural Network). For decades, many researchers have tried to find better models which can help to predict bankruptcy since the ex-ante prediction is crucial for corporate managers, investors, creditors, and other stakeholders. The development of the prediction for financial distress or bankruptcy was originated from Smith(1930), Fitzpatrick(1932), or Merwin(1942). One of the most famous models is the Altman's Z-score model(Altman, 1968) which was based on the multiple discriminant analysis. This model is widely used in both research and practice by this time. The author suggests the score model that utilizes five key financial ratios to predict the probability of bankruptcy in the next two years. Ohlson(1980) introduces logit model to complement some limitations of previous models. Furthermore, Elmer and Borowski(1988) develop and examine a rule-based, automated system which conducts the financial analysis of savings and loans. Since the 1980s, researchers in Korea have started to examine analyses on the prediction of financial distress or bankruptcy. Kim(1987) analyzes financial ratios and develops the prediction model. Also, Han et al.(1995, 1996, 1997, 2003, 2005, 2006) construct the prediction model using various techniques including artificial neural network. Yang(1996) introduces multiple discriminant analysis and logit model. Besides, Kim and Kim(2001) utilize artificial neural network techniques for ex-ante prediction of insolvent enterprises. After that, many scholars have been trying to predict financial distress or bankruptcy more precisely based on diverse models such as Random Forest or SVM. One major distinction of our research from the previous research is that we focus on examining the predicted probability of default for each sample case, not only on investigating the classification accuracy of each model for the entire sample. Most predictive models in this paper show that the level of the accuracy of classification is about 70% based on the entire sample. To be specific, LightGBM model shows the highest accuracy of 71.1% and Logit model indicates the lowest accuracy of 69%. However, we confirm that there are open to multiple interpretations. In the context of the business, we have to put more emphasis on efforts to minimize type 2 error which causes more harmful operating losses for the guaranty company. Thus, we also compare the classification accuracy by splitting predicted probability of the default into ten equal intervals. When we examine the classification accuracy for each interval, Logit model has the highest accuracy of 100% for 0~10% of the predicted probability of the default, however, Logit model has a relatively lower accuracy of 61.5% for 90~100% of the predicted probability of the default. On the other hand, Random Forest, XGBoost, LightGBM, and DNN indicate more desirable results since they indicate a higher level of accuracy for both 0~10% and 90~100% of the predicted probability of the default but have a lower level of accuracy around 50% of the predicted probability of the default. When it comes to the distribution of samples for each predicted probability of the default, both LightGBM and XGBoost models have a relatively large number of samples for both 0~10% and 90~100% of the predicted probability of the default. Although Random Forest model has an advantage with regard to the perspective of classification accuracy with small number of cases, LightGBM or XGBoost could become a more desirable model since they classify large number of cases into the two extreme intervals of the predicted probability of the default, even allowing for their relatively low classification accuracy. Considering the importance of type 2 error and total prediction accuracy, XGBoost and DNN show superior performance. Next, Random Forest and LightGBM show good results, but logistic regression shows the worst performance. However, each predictive model has a comparative advantage in terms of various evaluation standards. For instance, Random Forest model shows almost 100% accuracy for samples which are expected to have a high level of the probability of default. Collectively, we can construct more comprehensive ensemble models which contain multiple classification machine learning models and conduct majority voting for maximizing its overall performance.

• Journal of the Korean Institute of Landscape Architecture
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• v.40 no.4
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• pp.36-50
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• 2012

This study was carried out to find contradiction factors on laws for children's activity spaces and facilities and to suggest the rational options to control and manage those spaces and facilities by environmental and landscape planning methods. The results of this study are as follows: 1. The major laws related to the environmental safety for children's activity spaces are "Environmental Health Act (ERA)" for managing the environmental safety of children's activity spaces; "Safety Supervision Law of Children's Play Facilities(SSLCPF)" for the inspection and management for safety of children's play facilities; "Quality Management and Industrial Products Safety Management Law(QMIPSML)" for managing safety certification on children's play equipments. 2. The interior space such as "living room" by the Children's Welfare Law(CWL), "Children Park" by the Act on Urban Parks and Green Spaces(AUPGS), "classroom" on private educational institutes by the Act on Establishment and Operation Private Lesson and Training(AEOPLT) and "nursing room" of child care center smaller than $430m^2$ are needed to be managed as an activity space. 3. In order to reduce industrial burden in the production, establishment, construction, and operation and to minimize unwilling extra burden in the administration effort due to legally double regulate, it is necessary to mitigate the inspections on the equipment certificate from QMIPSML and overlapped or different factors and standards must be unified. With this study, the landscape domain could he enlarged from producing, import of play equipment and establishment, construction and operation of play facilities for a comprehensive range of activity spaces, and the landscape industry such as engineering industry, academic research, management, etc.

• Journal of Technology Innovation
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• v.25 no.3
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• pp.155-195
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• 2017

The goal of the present study is reviewing the literature on the scientific community and also on science, technology & society to increase interactions between innovation studies and social studies of science and technology. Up until now, various empirical studies on Korean scientists and engineers have been concentrated on researchers at universities, while they have paid inadequate attention to researchers at state-funded research institutes and private companies. In addition, these studies have tended to use concepts in Western academia to elucidate Korean cases. On the other hand, recent empirical researches on the effects of the evaluation systems in universities, PBS system, and the network of school ties suggest that these topics may reveal the unique characteristics of Korean scientific community. Empirical studies on the scientific community have also shown that Korean research institutes and researchers who are in charge of innovation in Korea have demonstrated a tendency to conform to the government's guidance due to long experiences of state-led R&D and nationalism. Research on science, technology and society has viewed the participation of citizens in science and technology as a way toward science and technology democracy, and tended to have a strong practical orientation. However, there has been a relatively small amount of research on how citizen participation influences the direction and content of technological innovation. Also, although, from the viewpoint of technological innovation, how participation of citizens in science and technology can contribute to knowledge production and innovation is a critical issue, relatively small numbers of case studies on this subject have been conducted. Therefore, as the scholars who have emphasized the democracy of science and technology have actually experimented with various ways of citizen participation, innovation researchers may have to design and implement citizen participation through which citizens' local knowledge can contribute to technological innovation.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.4
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• pp.1-24
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• 2021

The Korean government is currently expanding the business startup incubator support program and funds for new ventures with innovative technology in order to spread the second venture boom. However, despite the fact that entrepreneurial education and mentoring that entrepreneurs should have are important parts for the sustainable growth of the startup, some companies selected for government support programs are reluctant to participate in programs such as entrepreneurship education and mentoring for the sole purpose of funding commercialization. This research addressed the effects of entrepreneurial alertness with opportunity awareness as its medium and the small business mentoring service along with the number of times the mentoring has taken place, on the corporate performances. The results of empirical research are as follow: the first one is that scanning-search and evaluation-judgment can influence a company's performance (financial, non-financial) through opportunity recognition, with the exception of association-connection, which is a sub-factor of entrepreneurial alertness. Secondly, it was found to affect a company's financial and non-financial performance through opportunity recognition for financing mentoring, technical support mentoring, and management support mentoring. Thirdly, it was found that the number of mentoring also affects the financial and non-financial performance of a company through opportunity recognition. The implications of this study are that it should be revisited that program managers consider rooms that do not violate the startup founder's strategic decision-making opportunities when designing and operating the program as entrepreneurial alertness sub-factor association-connection does not affect corporate performance through opportunity recognition. This study also emphasizes the need for customized mentoring to meet the outcome goals of each startup, as it has been empirically clarified that the mentoring provided to the startup by the government's support is important. The contribution of this research is that entrepreneurial alertness and opportunity recognition that are treated as important components in research for entrepreneurship, and the factors of mentoring and mentoring frequency that are recognized as important elements in the practical aspect of startup business are clarified theoretically and empirically as an influential factor in corporate performance. And this study also provide a rationale for the startup business support agency supplying mentoring.

• Journal of Technology Innovation
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• v.31 no.1
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• pp.29-63
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• 2023

The purpose of this study is to analyze the process of changes in regional science and technology policies in Korea and to seek future development directions. In Korea, regional science and technology policies have been implemented since the introduction of the local autonomy system. Since then, it has been implemented in earnest with the establishment of a central government-level plan. The regional science and technology policies have been developed to this day by interacting with national science and technology policies and regional development policies. Nevertheless, due to the path dependence and lock-in effect in the accumulated process, the regional science and technology policies are still subordinate to central government policies. Thus, the establishment of an independent ecosystem for local science and technology is still insufficient. Furthermore, the gap between regions is deepening, such as the growing of aging population, population decline due to low birth rates, job losses due to the recession of local key industry, and the concentration of the youth population in the metropolitan area. The transformation path such as digital transformation and carbon neutrality paradigm is expected to further widen regional disparities. In order to address a comprehensive problem, the implementing system of regional science and technology policies need to be newly established. A framework for reinvention of regional science and technology policy needed in the era of grand societal challenges have to be developed.

• Journal of Navigation and Port Research
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• v.46 no.1
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• pp.1-10
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• 2022

This study aims to investigate changes in the demand for ship officers in response to changes in the shipping industry environment in which Maritime Autonomous Surface Ships (MASS) emerge according to the application of the fourth industrial revolution technology to ships, and it looks into changes in the skill of ship officer. It also analyzes and proposes a plan for nurturing ship officers accordingly. As a result of the degree of recognition and AHP analysis, this study suggests that a new training system is required because the current training and education system may cover the job competencies of emergency response, caution and danger navigation, general sailing, cargo handling, seaworthiness maintenance, emergency response, and ship maintenance and management, but tasks such as remote control, monitoring diagnosis, device management capability, and big data analysis require competency for unmanned and shore-based control. By evaluating the importance of change factors in the duties of ship officers in Maritime Autonomous Surface Ships, this study provides information on ship officer educational institutions' response strategies for nurturing ship officers and prioritization of resource allocation, etc. The importance of these factors was compared and evaluated to suggest changes in the duties of ship officers and methods of nurturing ship officers according to the introduction of Maritime Autonomous Surface Ships. It is expected that the findings of this study will be meaningful as it systematically derives the duties and competency factors of ship officers of Maritime Autonomous Surface Ships from a practical point of view and analyzed the perception level of each relevant expert to diagnose expert-level responses to the introduction of Maritime Autonomous Surface Ships.

• Journal of Agricultural Extension & Community Development
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• v.7 no.1
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• pp.155-166
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• 2000

When the marcher visited Korea in fall 1994, he was shocked to see high rise apartment buildings around the capitol region including Seoul and Suwon, resulting from rising demand of housing because of urban migration followed by second and third industrial development. After 6 years in March 2000, the researcher witnessed more apartment buildings and vinyl house complexes, one of the evidences of continued economic progress in Korea. Korea had to receive the rescue finance from International Monetary Fund (IMF) because of financial crisis in 1997. However, the sign of recovery was seen in a year, and the growth rate of Gross Domestic Products (GDP) in 1999 recorded as high as 10.7 percent. During this period, the Korean government has been working on restructuring of banks, enterprises, labour and public sectors. The major directions of government were; localization, reducing administrative manpower, limiting agricultural budgets, privatization of public enterprises, integration of agricultural organization, and easing of various regulations. Thus, the power of central government shifted to local government resulting in a power increase for city mayors and county chiefs. Agricultural extension services was one of targets of government restructuring, transferred to local governments from central government. At the same time, the number of extension offices was reduced by 64 percent, extension personnel reduced by 24 percent, and extension budgets reduced. During the process of restructuring, the basic direction of extension services was set by central Rural Development Administration Personnel management, technology development and supports were transferred to provincial Rural Development Administrations, and operational responsibilities transferred to city/county governments. Agricultural extension services at the local levels changed the name to Agricultural Technology Extension Center, established under jurisdiction of city mayor or county chief. The function of technology development works were added, at the same time reducing the number of educators for agriculture and rural life. As a result of observations of rural areas and agricultural extension services at various levels, functional responsibilities of extension were not well recognized throughout the central, provincial, and local levels. Central agricultural extension services should be more concerned about effective rural development by monitoring provincial and local level extension activities more throughly. At county level extension services, it may be desirable to add a research function to reflect local agricultural technological needs. Sometimes, adding administrative tasks for extension educators may be helpful far farmers. However, tasks such as inspection and investigation should be avoided, since it may hinder the effectiveness of extension educational activities. It appeared that major contents of the agricultural extension service in Korea were focused on saving agricultural materials, developing new agricultural technology, enhancing agricultural export, increasing production and establishing market oriented farming. However these kinds of efforts may lead to non-sustainable agriculture. It would be better to put more emphasis on sustainable agriculture in the future. Agricultural extension methods in Korea may be better classified into two approaches or functions; consultation function for advanced farmers and technology transfer or educational function for small farmers. Advanced farmers were more interested in technology and management information, while small farmers were more concerned about information for farm management directions and timely diffusion of agricultural technology information. Agricultural extension service should put more emphasis on small farmer groups and active participation of farmers in these groups. Providing information and moderate advice in selecting alternatives should be the major activities for consultation for advanced farmers, while problem solving processes may be the major educational function for small farmers. Systems such as internet and e-mail should be utilized for functions of information exchange. These activities may not be an easy task for decreased numbers of extension educators along with increased administrative tasks. It may be difficult to practice a one-to-one approach However group guidance may improve the task to a certain degree.