• The Korean Society of Law and Medicine
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• v.23 no.4
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• pp.29-74
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• 2022

As social disasters occur under the Disaster Management Act, which can damage the people's "life, body, and property" due to the rapid spread and spread of unexpected COVID-19 infectious diseases in 2020, information collected through inspection and reporting of infectious disease pathogens (Article 11), epidemiological investigation (Article 18), epidemiological investigation for vaccination (Article 29), artificial technology, and prevention policy Decision), (3) It was used as an important basis for decision-making in the context of an infectious disease crisis, such as promoting vaccination and understanding the current status of damage. In addition, medical policy decisions using infectious disease data contribute to quarantine policy decisions, information provision, drug development, and research technology development, and interest in the legal scope and limitations of using infectious disease data has increased worldwide. The use of infectious disease data can be classified for the purpose of spreading and blocking infectious diseases, prevention, management, and treatment of infectious diseases, and the use of information will be more widely made in the context of an infectious disease crisis. In particular, as the serious stage of the Disaster Management Act continues, the processing of personal identification information and sensitive information becomes an important issue. Information on "medical records, vaccination drugs, vaccination, underlying diseases, health rankings, long-term care recognition grades, pregnancy, etc." needs to be interpreted. In the case of "prevention, management, and treatment of infectious diseases", it is difficult to clearly define the concept of medical practicesThe types of actions are judged based on "legislative purposes, academic principles, expertise, and social norms," but the balance of legal interests should be based on the need for data use in quarantine policies and urgent judgment in public health crises. Specifically, the speed and degree of transmission of infectious diseases in a crisis, whether the purpose can be achieved without processing sensitive information, whether it unfairly violates the interests of third parties or information subjects, and the effectiveness of introducing quarantine policies through processing sensitive information can be used as major evaluation factors. On the other hand, the collection, provision, and use of infectious disease data for research purposes will be used through pseudonym processing under the Personal Information Protection Act, consent under the Bioethics Act and deliberation by the Institutional Bioethics Committee, and data provision deliberation committee. Therefore, the use of research purposes is recognized as long as procedural validity is secured as it is reviewed by the pseudonym processing and data review committee, the consent of the information subject, and the institutional bioethics review committee. However, the burden on research managers should be reduced by clarifying the pseudonymization or anonymization procedures, the introduction or consent procedures of the comprehensive consent system and the opt-out system should be clearly prepared, and the procedure for re-identifying or securing security that may arise from technological development should be clearly defined.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.205-225
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• 2018

Convolutional Neural Network (ConvNet) is one class of the powerful Deep Neural Network that can analyze and learn hierarchies of visual features. Originally, first neural network (Neocognitron) was introduced in the 80s. At that time, the neural network was not broadly used in both industry and academic field by cause of large-scale dataset shortage and low computational power. However, after a few decades later in 2012, Krizhevsky made a breakthrough on ILSVRC-12 visual recognition competition using Convolutional Neural Network. That breakthrough revived people interest in the neural network. The success of Convolutional Neural Network is achieved with two main factors. First of them is the emergence of advanced hardware (GPUs) for sufficient parallel computation. Second is the availability of large-scale datasets such as ImageNet (ILSVRC) dataset for training. Unfortunately, many new domains are bottlenecked by these factors. For most domains, it is difficult and requires lots of effort to gather large-scale dataset to train a ConvNet. Moreover, even if we have a large-scale dataset, training ConvNet from scratch is required expensive resource and time-consuming. These two obstacles can be solved by using transfer learning. Transfer learning is a method for transferring the knowledge from a source domain to new domain. There are two major Transfer learning cases. First one is ConvNet as fixed feature extractor, and the second one is Fine-tune the ConvNet on a new dataset. In the first case, using pre-trained ConvNet (such as on ImageNet) to compute feed-forward activations of the image into the ConvNet and extract activation features from specific layers. In the second case, replacing and retraining the ConvNet classifier on the new dataset, then fine-tune the weights of the pre-trained network with the backpropagation. In this paper, we focus on using multiple ConvNet layers as a fixed feature extractor only. However, applying features with high dimensional complexity that is directly extracted from multiple ConvNet layers is still a challenging problem. We observe that features extracted from multiple ConvNet layers address the different characteristics of the image which means better representation could be obtained by finding the optimal combination of multiple ConvNet layers. Based on that observation, we propose to employ multiple ConvNet layer representations for transfer learning instead of a single ConvNet layer representation. Overall, our primary pipeline has three steps. Firstly, images from target task are given as input to ConvNet, then that image will be feed-forwarded into pre-trained AlexNet, and the activation features from three fully connected convolutional layers are extracted. Secondly, activation features of three ConvNet layers are concatenated to obtain multiple ConvNet layers representation because it will gain more information about an image. When three fully connected layer features concatenated, the occurring image representation would have 9192 (4096+4096+1000) dimension features. However, features extracted from multiple ConvNet layers are redundant and noisy since they are extracted from the same ConvNet. Thus, a third step, we will use Principal Component Analysis (PCA) to select salient features before the training phase. When salient features are obtained, the classifier can classify image more accurately, and the performance of transfer learning can be improved. To evaluate proposed method, experiments are conducted in three standard datasets (Caltech-256, VOC07, and SUN397) to compare multiple ConvNet layer representations against single ConvNet layer representation by using PCA for feature selection and dimension reduction. Our experiments demonstrated the importance of feature selection for multiple ConvNet layer representation. Moreover, our proposed approach achieved 75.6% accuracy compared to 73.9% accuracy achieved by FC7 layer on the Caltech-256 dataset, 73.1% accuracy compared to 69.2% accuracy achieved by FC8 layer on the VOC07 dataset, 52.2% accuracy compared to 48.7% accuracy achieved by FC7 layer on the SUN397 dataset. We also showed that our proposed approach achieved superior performance, 2.8%, 2.1% and 3.1% accuracy improvement on Caltech-256, VOC07, and SUN397 dataset respectively compare to existing work.

• Korean small business review
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• v.32 no.2
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• pp.209-223
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• 2010

Korea's business is composed of a few large-sized enterprises (which can be abbreviated as LSE) and a majority of small-sized enterprises (SSE). Although there has been a growing recognition of the need for the development of medium-sized enterprises (MSE) which can serve as a link between SSE and LSE, as yet there has not yet been a consensus on the definition, characteristics and the function of the MSE in Korea. Nowadays, the world is being globalized, and Japan and China are in competition to ne a great economic power. While East Asia is experiencing rapid changes, promoting MSE which can secure flexibility and efficiency through covering up the limitation of LSE and SSE is needed in order to respond the global market which is being specialized. The features of MSE in Japan can be listed as follows. First, the MSE in Japan is developing the company through getting into niche markets which are hard for major companies to enter rather than developing markets in order to compete against major companies directly. While MSEs are endeavoring to build the business firmly in the domestic market, they can possess special and competitive technical skills through trials and errors; so that they can get a chance develop their business through independent business system rather than putting their effort to compete against major companies. Second, from the MSEs with competitive edge in the market, there are many contributions to the national exportation. Those MSEs produce in domestic and maintain the quality of high price products which need cutting-edge technology, while they relocate the low and middle priced goods to the country where manufacturing costs are low, so that they can maintain the price competitiveness. Third, the industrial structure in Japan is formed from dual structure between major companies and small sized companies. In other words, in Japan's industrial structure which are composed of subcontract structure, this dual structure has taken a major role of small sized companies' growth and manufacturing businesses' international competitive power. Forth, MSE in Japan adopt a strategy of putting their value on qualitative scale growth rather than quantitative scale growth. In this paper, the case of Japanese MSE is analyzed. Along with its long history of Industrialization, Japan has a corporate environment where the SSEs can develop as a MSE and later a LSE through a full-support system. Among its SSEs, there are a number of world class corporations equipped with a large domestic market, win-win cooperation with the LSEs and an independent technology development. It can also be observed that these SSEs develop into MSEs with sustainable growth potentials. This study will focus on the condition under which the MSEs of Japan have been developed, and how they have survived the competition between SSEs and LSEs. Through this study, this paper attempts to offer solutions to Korea's polarization between the SSE and LSE, while providing the basis for SSEs revitalization. In general, if both extremities phenomenon deepen between LSE and SSE, there are possible fears of occurring disutility in national economy by the monopolization of LSE. For that reason, enterprise group, which can make SSE or MSE compete LSE in some area and ease the monopoly and oligopoly problem, is needed. This awareness has been shared for ages long. Nevertheless, there is no legal definition for MSE in Japan, and there is no definition about the enterprise size or unified view of MSE between scholars, but it is defined differently by each of academical person or research institution and study meeting. For that reason, this paper will organize the definition of MSE in Japan, and then will propose the characteristics of the background which has made MSE secure competitiveness and sustainable growth in global market. This study focus on that because through this process, the positive change to the awareness of MSE can be proposed in Korea and to seek the policy direction for building institutional framework which can make SSE become MES. Through this way, the fundamentals for SSE to become MSE can be managed and some appropriate suggestions which will be able to make MSE enter the global market in the future can also be proposed. Due to these facts, this study is very important and well timed task. In a sense of this way, this study will examine the definition and role of MSE in Japan. after this examination, this study will deal with the status, special feature, and promotion policy for MSE. Through this analysis of MSE in Japan, the foundation which be able to set the desirable role model for MSE in Korea can be proposed. Also, the political implication which is needed to push ahead to contribute to creating employment and economic growth through sustainable growth of MSEs in economic system of Korea can be offered through this study. It has been found that Japan's MSE functions as an indispensable link among various industrial structures by holding a significant position in employment rate, production and value added. Although the MSEs took up less than 1% of the entire number of businesses with 2700 manufacturing firms and 7000 non-manufacturing firms, its employment ratios are about 15%, while taking about 25% of the manufacturing industry's exports. In industries such as machinery and electronics which is considered Japan's major industry, the MSEs showed a higher than average ratio of manufacturing exports and employment rate. It can be analyzed that behind Japan's advantageous industries, close and deeply knit MSEs exist. Although there are no clearly stated policies geared towards the MSEs by the Japanese government, various political measures exist such as the R&D Project and the inducement of cooperation between enterprises which gives room for MSEs to participate in the SSE policies. In relation to these findings, the following practical measures can be considered in order to revitalize Korea's MSEs: First, there is a need for a legal definition of MSE and the incentives to provide legal support for its growth. Second, if a law to support the MSEs is established, it could provide a powerful inducement for the SSE to grow as a MSE, rather than stay as a SSE. Third, there is a need for a strategy of MSEs to establish a stable base in the domestic market and then advance to the global market with the accumulated trial and error and competitiveness. Fourth, the SSE themselves need the spirit of entrepreneurship in order to make the leap to a MSE. Because if nothing is to be changed about the system on the firms that grew, and the parts of the past custom was left to be managed alone, confusion and absence of management can take place. No matter how much tax favors the government will give and no matter how much incentive there could be through the policies, there are limits for industries to higher the ability to propagate. And because of that it is a period where industries need their own innovative skills to reform their firms.

• The Korean Journal of Rehabilitation Nursing
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• v.2 no.2
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• pp.257-270
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• 1999

The purpose of this study is to investigate factors related to the intent of using home nursing of chronic disease patients who got out of a university hospital. For the purpose, the study selected 153 patients who were hospitalized and left K university hospital with diagnoses of cancer, hypertension, diabetes and cerebral vascular accident and ordered to be discharged and performed interviews with them and surveys on their medical records to obtain the following results. For this study a direct-interview survey and medical record review was conducted from June 28 to Aug. 30, 1998. The frequency and mean values were computed to find the characteristics of the study subjects, and $X^2$-test, t-test, factor analysis and multiple logistic regession analysis were applied for the analysis of the data. The following results were obtained. 1) When characteristics of the subjects were examined, men and women occupied for 58.8% and 41.2%, respectively. The subjects were 41.3 years old in aver age and had the monthly aver age earning of 0.99 million won or below, which was the most out of the total subjects at 34.6%. Among the total, 87.6% resided in cities and 12.4 in counties. The most left the hospital with diagnosis of cancer at 51.6%, followed by hyper tension at 24.2%, diabetes at 13.7% and cerebral vascular accident at 7.2%. 2) 93.5% of the selected patients had the intent of using home nursing and 6.5%, didn't. Among those patients having the intent, 85.6% had the intent of paying for home nursing and 14.4%, didn't. The subjects expected that the nursing would be paid 9,143 won in aver age and 47.7% of them preferred national authorities as the main servers. 86.3% of the subjects thought that home nursing business had the main advantage of making it possible to learn nursing methods at home and thereby contributing to improving the ability of patients and their facilities to solve health problems. 3) Relations between the intent of use and characteristics of the subjects such as demography-related social, home environment, disease and physical function characteristics did not show statistically significant differences among one another. Compared to those who had no intent of using home nursing, the group having the intent had more cases of male patients, the age of 39 or below, residence in cities, 5 family member s or more, no existence of home nursing servers, leaving the hospital from a non-hospitalized building, disease development for five months or below, hospitalization for ten days or more, non-hospitalization with in the recent one month, two times or over of hospitalization, leaving the hospital with no demand of special treatment, operation underwent, poor results of treatment, leaving the hospital with demand of rehabilitation services, physical disablement and high evaluation point of daily life. 4) Among those patients having the intent of using home nursing, 47.6% demanded technical nursing and 55.9%, supportive nursing. As technical nursing,' inject into a blood vessel ' and 'treat pustule and teach basic prevention methods occupied for 57.4%, respectively, topping the list. Among demands of supportive nursing, 'observe patients 'status and refer them to hospitals or community resources as available, if necessary' was the most with percent age point of 59.5. Regarding the intent of paying for home nursing, 39.2% of those patients wishing to use the nursing responded paying for technical services and 20.2, supportive services. In detail, 70.0% wanted to pay for a service stated as 'inject into a blood vessel', highest among the former services and 30.7%, a service referred to as 'teaching exercises needed to make the body of patients move', highest among the latter. When this was analyzed in terms of a relation between the need(the need for home nursing) and the demand(the intent of paying for home nursing), The rate of the need to the demand was found two or three times higher in technical nursing(0.82) than in supportive nursing(0.35). In aspects of tech ical nursing, muscle injection(1.26, the 1st rank) was highest in the rate while among aspects of supportive nursing, a service referred to as 'teach exercises needed for making patients move their bodies normally'(0.58, the 1st rank). 5) factors I(satisfaction with hospital services), II(recognition of disease state), III(economy) and IV(period of disease) occupied for 34.4, 13.8, 11.9 and 9.2 percents, respectively among factors related to the intent by the subjects of using home nursing, totaled 59.3%. In conclusion, most of chronic disease patients have the intent of using hospital-based home nursing and satisfaction with hospital services is a factor affecting the intent most. Thus a post-management system is needed to continue providing health management to those patients after they leave the hospital. Further, supportive services should be provided in order that those who are satisfied with hospital services return to their community and live their in dependent lives. Based on these results, the researcher would make the following recommendation. 1) Because home nursing becomes more and more needed due to a sharp increase in chronic disease patients and elderly people, related rules and regulations should be made and implemented. 2) Hospital nurses specializing in home nursing should be cultivated.

• Water for future
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• v.9 no.1
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• pp.38-42
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• 1976

Because of differences in thoughts and ideology, our country, Korea has been deprived of national unity for some thirty years of time and tide. To achieve peaceful unification, the cultivation of national strength is of paramount importance. This national strength is also essential if Korea is to take rightful place in the international societies and to have the confidence of these societies. However, national strength can never be achieved in a short time. The fundamental elements in economic development that are directly conducive to the cultivation of national strength can be said to lie in -a stable political system, -exertion of powerful leadership, -cultivation of a spirit of diligence, self-help and cooperation, -modernization of human brain power, and -establishment of a scientific and well planned economic policy and strong enforcement of this policy. Our country, Korea, has attained brilliant economic development in the past 15 years under the strong leadership of president Park Chung Hee. However, there are still many problems to be solved. A few of them are: -housing and home problems, -increasing demand for employment, -increasing demand for staple food and -the need to improve international balance of payment. Solution of the above mentioned problems requires step by step scientific development of each sector and region of our contry. As a spearhead project in regional development, the Saemaul Campaign or new village movement can be cited. The campaign is now spreading throughout the country like a grass fire. However, such campaigns need considerable encouragement and support and the means for the desired development must be provided if the regional and sectoral development program is to sucdceed. The construction of large multipurpose dams in major river basin plays significant role in all aspects of national, regional and sectoral development. It ensures that the water resource, for which there is no substitute, is retained and utilized for irrigation of agricultural areas, production of power for industry, provision of water for domestic and industrial uses and control of river water. Water is the very essence of life and we must conserve and utilize what we have for the betterment of our peoples and their heir. The regional and social impact of construction of a large dam is enormous. It is intended to, and does, dras tically improve the "without-project" socio-economic conditions. A good example of this is the Soyanggang multipurpose dam. This project will significantly contribute to our national strength by utilizing the stored water for the benefit of human life and relief of flood and drought damages. Annual average precipitation in Korea is 1160mm, a comparatively abundant amount. The catchment areas of the Han River, Keum River, and Youngsan River are $62,755\textrm{km}^2$, accounting for 64% of the national total. Approximately 62% of the national population inhabits in this area, and 67% of the national gross product comes from the area. The annual population growth rate of the country is currently estimated at 1.7%, and every year the population growth in urban area increases at a rising rate. The population of Seoul, Pusan, and Taegu, the three major cities in Korea, is equal to one third of our national total. According to the census conducted on October 1, 1975, the population in the urban areas has increased by 384,000, whereas that in rural areas has decreased by 59,000,000 in the past five years. The composition of population between urban and rural areas varied from 41%~59% in 1959 to 48%~52% in 1975. To mitigate this treand towards concentration of population in urban areas, employment opportunities must be provided in regional and rural areas. However, heavy and chemical industries, which mitigate production and employment problems at the same time, must have abundant water and energy. Also increase in staple food production cannot be attained without water. At this point in time, when water demand is rapidly growing, it is essential for the country to provide as much a reservoir capacity as possible to capture the monsoon rainfall, which concentarated in the rainy seaon from June to Septesmber, and conserve the water for year round use. The floods, which at one time we called "the devil" have now become a source of immense benefit to Korea. Let me explain the topographic condition in Korea. In northern and eastern areas we have high mountains and rugged country. Our rivers originate in these mountains and flow in a general southerly or westerly direction throught ancient plains. These plains were formed by progressive deposition of sediments from the mountains and provide our country with large areas of fertile land, emminently suited to settlement and irrigated agricultural development. It is, therefore, quite natural that these areas should become the polar point for our regional development program. Hower, we are fortunate in that we have an additional area or areas, which can be used for agricultural production and settlement of our peoples, particularly those peoples who may be displaced by the formation of our reservoirs. I am speaking of the tidelands along the western and southern coasts. The other day the Ministry of Agriculture and Fishery informed the public of a tideland reclamation of which 400,000 hectares will be used for growing rice as part of our national food self-sufficiency programme. Now, again, we arrive at the need for water, as without it we cannot realize this ambitious programme. And again we need those dams to provide it. As I mentioned before, dams not only provide us with essential water for agriculture, domestic and industrial use, but provide us with electrical energy, as it is generally extremely economical to use the water being release for the former purposes to drive turbines and generators. At the present time we have 13 hydro-electric power plants with an installed capacity of 711,000 kilowatts equal to 16% of our national total. There are about 110 potential dams ites in the country, which could yield about 2,300,000 kilowatts of hydro-electric power. There are about 54 sites suitable for pumped storage which could produce a further 38,600,000 kilowatts of power. All available if we carefully develop our water resources. To summarize, water resource development is essential to the regional development program and the welfare of our people, it must proceed hand-in-hand with other aspects of regional development such as land impovement, high way extension, development of our forests, erosion control, and develop ment of heavy and chemical industries. Through the successful implementation of such an integrated regional development program, we can look forward to a period of national strength, and due recognition of our country by the worlds societies.

• Journal of Korean Home Economics Education Association
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• v.18 no.3 s.41
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• pp.1-22
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• 2006

The purpose of this study is that I should look for a desirous directions about home economics by studying the requirements and perception of the high school parents who have finished the course of home economics. It was about 600 parents whom I have searched Seoul-Pusan, Ganwon. Ghynggi province, Choongcheong-Gyungsang province, Cheonla and Jeju province of 600, I chose only 560 as apparently suitable research. The questions include 61 requirements about home economics and one which we never fail to keep among the contents, whenever possible and one about the perception of home economics aims 11 about the perception of home economics courses and management. The collections were analyzed frequency, percent, mean. standard deviation t-test by using SAS program. The followings is the summary result of studying of it. 1. All the boys and girls learning together about the Idea of healthy lives and desirous human formulation and knowledge together are higher. 2. Among the teaching purposes of home economics, the item of the scientific principle and knowledge for improvements of home life shows 15.7% below average value. 3. The recognition degree about the quality of home economics is highly related with the real life, and about the system. we recognize lacking in periods and contents of home economics field and about guiding content, accomplishment and application qualities are higher regardless of sex. 4. The important term which we should emphasize in the subject of home economics is family part. 5. Among the needs of home economic requirement in freshman, in the middle unit, their growth and development are higher than anything else, representing 4.11, and by contrast the basic principle and actuality is 3.70, which is lowest among them. 6. In the case of second grade requirement of home economics content for parents in the middle unit young man and consuming life is 4.09 highest. 7. In the case of 3rd grade requirement of economics contents in the middle unit the choice of coming direction and job ethics is highest 4.16, and preparing meals and evaluation is lowest 3.50.

• Journal of the Korean Society of Food Science and Nutrition
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• v.34 no.2
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• pp.202-208
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• 2005

This study was conducted to examine the food habits, knowledge of nutrition and actual conditions of food ingestion of adolescent middle school students according to questionnaire answers. Questionnaires were completed by 524 students, divided into a healthy group (n=289) and an unhealthy group (n=235) according to clinical signs. Further questions were asked of the two groups in the areas of food habits, knowledge of nutrition and nutritional attitude. The results were as follows: Mean age of all subjects was 14, heights for male and female students were 162.0 em, and 157.2 cm, weights were 53.4 kg, and 49.4, respectively. Heights and weights of male students were greater than those of female students. The body mass index (BMI) for male and female students was 20.3 kg/$m^2$ and 20.0 kg/$m^2$, respectively, and all data were within normal ranges. There were no significant differences in mean age, height, weight, and BMI between the healthy and unhealthy groups. There was no significant difference in body image recognition between the two groups, although the ratio of dissatisfaction with their own body shape was significantly higher in the female unhealthy group (46.1%), than in the female healthy group (33.0%) (p<0.05). In the area of the struggle to control body weight during the previous year, the female unhealthy group (59.4%) was higher than the female healthy group (38.4%) (p<0.01). There was no significant difference in the scores between the two groups in the areas of knowledge of nutrition and the nutritional attitude. Meal frequency and meal patterns were showed that having breakfast less than 4x/week was significantly higher in the female unhealthy group (44.0%), than in the female healthy group (30.7%) (p<0.01). Meal frequency for suppers<4x/week showed that the female unhealthy group (18.8%) was also higher than the female healthy group (10.7%). Therefore, the unhealthy group exhibited a higher pattern of missing both breakfast and supper. The male unhealthy group (16.7%) dined out more frequently than the male healthy group (12.3%) (p<0.01), and female unhealthy group also indulged in snacking significantly more frequently than the female healthy group. The unhealthy group also ate only 1 item for meals more frequently than the healthy group and no significant difference. The conclusion of this study is that adolescent Korean middle school students, who showed a higher incidence of clinical symptoms, representing an unhealthy status, missed breakfast and supper, and dined out and indulged in snacking more frequently. Their quality of breakfast and satisfaction of body image were also lower than the healthy group. These results indicated that there is a high correlation between a Korean adolescent's health status, food habits and body image satisfaction. It is recommended that a more intense program of nutritional education and monitoring be introduce into the current Korean middle-school system in order to optimally support and maximize the health potential of the current population of Korean student.

• Journal of Intelligence and Information Systems
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• v.26 no.3
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• pp.71-90
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• 2020

Recently, the global insurance industry is rapidly developing digital transformation through the use of artificial intelligence technologies such as machine learning, natural language processing, and deep learning. As a result, more and more foreign insurers have achieved the success of artificial intelligence technology-based InsurTech and platform business, and Ping An Insurance Group Ltd., China's largest private company, is leading China's global fourth industrial revolution with remarkable achievements in InsurTech and Digital Platform as a result of its constant innovation, using 'finance and technology' and 'finance and ecosystem' as keywords for companies. In response, this study analyzed the InsurTech and platform business activities of Ping An Insurance Group Ltd. through the ser-M analysis model to provide strategic implications for revitalizing AI technology-based businesses of domestic insurers. The ser-M analysis model has been studied so that the vision and leadership of the CEO, the historical environment of the enterprise, the utilization of various resources, and the unique mechanism relationships can be interpreted in an integrated manner as a frame that can be interpreted in terms of the subject, environment, resource and mechanism. As a result of the case analysis, Ping An Insurance Group Ltd. has achieved cost reduction and customer service development by digitally innovating its entire business area such as sales, underwriting, claims, and loan service by utilizing core artificial intelligence technologies such as facial, voice, and facial expression recognition. In addition, "online data in China" and "the vast offline data and insights accumulated by the company" were combined with new technologies such as artificial intelligence and big data analysis to build a digital platform that integrates financial services and digital service businesses. Ping An Insurance Group Ltd. challenged constant innovation, and as of 2019, sales reached $155 billion, ranking seventh among all companies in the Global 2000 rankings selected by Forbes Magazine. Analyzing the background of the success of Ping An Insurance Group Ltd. from the perspective of ser-M, founder Mammingz quickly captured the development of digital technology, market competition and changes in population structure in the era of the fourth industrial revolution, and established a new vision and displayed an agile leadership of digital technology-focused. Based on the strong leadership led by the founder in response to environmental changes, the company has successfully led InsurTech and Platform Business through innovation of internal resources such as investment in artificial intelligence technology, securing excellent professionals, and strengthening big data capabilities, combining external absorption capabilities, and strategic alliances among various industries. Through this success story analysis of Ping An Insurance Group Ltd., the following implications can be given to domestic insurance companies that are preparing for digital transformation. First, CEOs of domestic companies also need to recognize the paradigm shift in industry due to the change in digital technology and quickly arm themselves with digital technology-oriented leadership to spearhead the digital transformation of enterprises. Second, the Korean government should urgently overhaul related laws and systems to further promote the use of data between different industries and provide drastic support such as deregulation, tax benefits and platform provision to help the domestic insurance industry secure global competitiveness. Third, Korean companies also need to make bolder investments in the development of artificial intelligence technology so that systematic securing of internal and external data, training of technical personnel, and patent applications can be expanded, and digital platforms should be quickly established so that diverse customer experiences can be integrated through learned artificial intelligence technology. Finally, since there may be limitations to generalization through a single case of an overseas insurance company, I hope that in the future, more extensive research will be conducted on various management strategies related to artificial intelligence technology by analyzing cases of multiple industries or multiple companies or conducting empirical research.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.35-48
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• 2014

According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

• Journal of Intelligence and Information Systems
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• v.18 no.2
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• pp.29-45
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• 2012

Bond rating is regarded as an important event for measuring financial risk of companies and for determining the investment returns of investors. As a result, it has been a popular research topic for researchers to predict companies' credit ratings by applying statistical and machine learning techniques. The statistical techniques, including multiple regression, multiple discriminant analysis (MDA), logistic models (LOGIT), and probit analysis, have been traditionally used in bond rating. However, one major drawback is that it should be based on strict assumptions. Such strict assumptions include linearity, normality, independence among predictor variables and pre-existing functional forms relating the criterion variablesand the predictor variables. Those strict assumptions of traditional statistics have limited their application to the real world. Machine learning techniques also used in bond rating prediction models include decision trees (DT), neural networks (NN), and Support Vector Machine (SVM). Especially, SVM is recognized as a new and promising classification and regression analysis method. SVM learns a separating hyperplane that can maximize the margin between two categories. SVM is simple enough to be analyzed mathematical, and leads to high performance in practical applications. SVM implements the structuralrisk minimization principle and searches to minimize an upper bound of the generalization error. In addition, the solution of SVM may be a global optimum and thus, overfitting is unlikely to occur with SVM. In addition, SVM does not require too many data sample for training since it builds prediction models by only using some representative sample near the boundaries called support vectors. A number of experimental researches have indicated that SVM has been successfully applied in a variety of pattern recognition fields. However, there are three major drawbacks that can be potential causes for degrading SVM's performance. First, SVM is originally proposed for solving binary-class classification problems. Methods for combining SVMs for multi-class classification such as One-Against-One, One-Against-All have been proposed, but they do not improve the performance in multi-class classification problem as much as SVM for binary-class classification. Second, approximation algorithms (e.g. decomposition methods, sequential minimal optimization algorithm) could be used for effective multi-class computation to reduce computation time, but it could deteriorate classification performance. Third, the difficulty in multi-class prediction problems is in data imbalance problem that can occur when the number of instances in one class greatly outnumbers the number of instances in the other class. Such data sets often cause a default classifier to be built due to skewed boundary and thus the reduction in the classification accuracy of such a classifier. SVM ensemble learning is one of machine learning methods to cope with the above drawbacks. Ensemble learning is a method for improving the performance of classification and prediction algorithms. AdaBoost is one of the widely used ensemble learning techniques. It constructs a composite classifier by sequentially training classifiers while increasing weight on the misclassified observations through iterations. The observations that are incorrectly predicted by previous classifiers are chosen more often than examples that are correctly predicted. Thus Boosting attempts to produce new classifiers that are better able to predict examples for which the current ensemble's performance is poor. In this way, it can reinforce the training of the misclassified observations of the minority class. This paper proposes a multiclass Geometric Mean-based Boosting (MGM-Boost) to resolve multiclass prediction problem. Since MGM-Boost introduces the notion of geometric mean into AdaBoost, it can perform learning process considering the geometric mean-based accuracy and errors of multiclass. This study applies MGM-Boost to the real-world bond rating case for Korean companies to examine the feasibility of MGM-Boost. 10-fold cross validations for threetimes with different random seeds are performed in order to ensure that the comparison among three different classifiers does not happen by chance. For each of 10-fold cross validation, the entire data set is first partitioned into tenequal-sized sets, and then each set is in turn used as the test set while the classifier trains on the other nine sets. That is, cross-validated folds have been tested independently of each algorithm. Through these steps, we have obtained the results for classifiers on each of the 30 experiments. In the comparison of arithmetic mean-based prediction accuracy between individual classifiers, MGM-Boost (52.95%) shows higher prediction accuracy than both AdaBoost (51.69%) and SVM (49.47%). MGM-Boost (28.12%) also shows the higher prediction accuracy than AdaBoost (24.65%) and SVM (15.42%)in terms of geometric mean-based prediction accuracy. T-test is used to examine whether the performance of each classifiers for 30 folds is significantly different. The results indicate that performance of MGM-Boost is significantly different from AdaBoost and SVM classifiers at 1% level. These results mean that MGM-Boost can provide robust and stable solutions to multi-classproblems such as bond rating.