• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.79-96
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• 2012

As the pace of competition dramatically accelerates and the complexity of change grows, a variety of research have been conducted to improve firms' short-term performance and to enhance firms' long-term survival. In particular, researchers and practitioners have paid their attention to identify promising technologies that lead competitive advantage to a firm. Discovery of promising technology depends on how a firm evaluates the value of technologies, thus many evaluating methods have been proposed. Experts' opinion based approaches have been widely accepted to predict the value of technologies. Whereas this approach provides in-depth analysis and ensures validity of analysis results, it is usually cost-and time-ineffective and is limited to qualitative evaluation. Considerable studies attempt to forecast the value of technology by using patent information to overcome the limitation of experts' opinion based approach. Patent based technology evaluation has served as a valuable assessment approach of the technological forecasting because it contains a full and practical description of technology with uniform structure. Furthermore, it provides information that is not divulged in any other sources. Although patent information based approach has contributed to our understanding of prediction of promising technologies, it has some limitations because prediction has been made based on the past patent information, and the interpretations of patent analyses are not consistent. In order to fill this gap, this study proposes a technology forecasting methodology by integrating patent information approach and artificial intelligence method. The methodology consists of three modules : evaluation of technologies promising, implementation of technologies value prediction model, and recommendation of promising technologies. In the first module, technologies promising is evaluated from three different and complementary dimensions; impact, fusion, and diffusion perspectives. The impact of technologies refers to their influence on future technologies development and improvement, and is also clearly associated with their monetary value. The fusion of technologies denotes the extent to which a technology fuses different technologies, and represents the breadth of search underlying the technology. The fusion of technologies can be calculated based on technology or patent, thus this study measures two types of fusion index; fusion index per technology and fusion index per patent. Finally, the diffusion of technologies denotes their degree of applicability across scientific and technological fields. In the same vein, diffusion index per technology and diffusion index per patent are considered respectively. In the second module, technologies value prediction model is implemented using artificial intelligence method. This studies use the values of five indexes (i.e., impact index, fusion index per technology, fusion index per patent, diffusion index per technology and diffusion index per patent) at different time (e.g., t-n, t-n-1, t-n-2, ${\cdots}$) as input variables. The out variables are values of five indexes at time t, which is used for learning. The learning method adopted in this study is backpropagation algorithm. In the third module, this study recommends final promising technologies based on analytic hierarchy process. AHP provides relative importance of each index, leading to final promising index for technology. Applicability of the proposed methodology is tested by using U.S. patents in international patent class G06F (i.e., electronic digital data processing) from 2000 to 2008. The results show that mean absolute error value for prediction produced by the proposed methodology is lower than the value produced by multiple regression analysis in cases of fusion indexes. However, mean absolute error value of the proposed methodology is slightly higher than the value of multiple regression analysis. These unexpected results may be explained, in part, by small number of patents. Since this study only uses patent data in class G06F, number of sample patent data is relatively small, leading to incomplete learning to satisfy complex artificial intelligence structure. In addition, fusion index per technology and impact index are found to be important criteria to predict promising technology. This study attempts to extend the existing knowledge by proposing a new methodology for prediction technology value by integrating patent information analysis and artificial intelligence network. It helps managers who want to technology develop planning and policy maker who want to implement technology policy by providing quantitative prediction methodology. In addition, this study could help other researchers by proving a deeper understanding of the complex technological forecasting field.

• Strategy21
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• s.46
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• pp.239-276
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• 2020

The failure of early economic sanctions aimed at hurting the overall economies of targeted states called for a more sophisticated design of economic sanctions. This paved way for the advent of 'smart sanctions,' which target the supporters of the regime instead of the public mass. Despite controversies over the effectiveness of economic sanctions as a coercive tool to change the behavior of a targeted state, the transformation from 'comprehensive sanctions' to 'smart sanctions' is gaining the status of a legitimate method to impose punishment on states that do not conform to international norms, the nonproliferation of weapons of mass destruction in this particular context of the paper. The five permanent members of the United Nations Security Council proved that it can come to an accord on imposing economic sanctions over adopting resolutions on waging military war with targeted states. The North Korean nuclear issue has been the biggest security threat to countries in the region, even for China out of fear that further developments of nuclear weapons in North Korea might lead to a 'domino-effect,' leading to nuclear proliferation in the Northeast Asia region. Economic sanctions had been adopted by the UNSC as early as 2006 after the first North Korean nuclear test and has continually strengthened sanctions measures at each stage of North Korean weapons development. While dubious of the effectiveness of early sanctions on North Korea, recent sanctions that limit North Korea's exports of coal and imports of oil seem to have an impact on the regime, inducing Kim Jong-un to commit to peaceful talks since 2018. The purpose of this paper is to add a variable to the factors determining the success of economic sanctions on North Korea: preventing North Korea's evasion efforts by conducting illegal transshipments at sea. I first analyze the cause of recent success in the economic sanctions that led Kim Jong-un to engage in talks and add the maritime element to the argument. There are three conditions for the success of the sanctions regime, and they are: (1) smart sanctions, targeting commodities and support groups (elites) vital to regime survival., (2) China's faithful participation in the sanctions regime, and finally, (3) preventing North Korea's maritime evasion efforts.

• Journal of agricultural medicine and community health
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• v.25 no.1
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• pp.29-49
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• 2000

Objectives: To estimate the prevalence rate of hypertension, the changes of health behavior, and compliance for the drug treatment after diagnosed as hypertension. Methods: 7,030 persons who live in Cheonan City of Chungnam Province were selected by the cluster sampling method, and 5,372 persons were surveyed by questionnaire and health examination. This data is analyzed by Chi-square test on each variable. Results: 49.8%- of men and 38.8%- of women had been diagnosed as hypertension, and the prevalence rate of hypertension was significantly increased with aging in both gender. The prevalence rate tended to decrease in highly educated women group. Unemployed persons or obese persons showed relatively higher prevalence rate. The prevalence rate of hypertension increased in groups with higher total cholesterol levels over 240 mg/dl, and groups with glucose level over 200 mg/dl. 53.1%- of male patients and 66.6%- of female patients showed compliance for antihypertensive treatment. Compliance for treatment was higher in aged group or lower educated group in both gender. Among men, proportion of compliant subjects was higher in unemployed group(49.3%-), and lower in labor or primary industry than the others but among women, there was not any significant difference. And men with compliance for treatment had higher monthly income than the others, but women did not show any. Conclusion : This population had a high prevalence rate of hypertension which may lead to cardiovascular disease. Therefore health education programs and distribution of information must be emphasized in order to increase compliance to treatment and encourage the change of health behavior to promote health.

• Tuberculosis and Respiratory Diseases
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• v.44 no.6
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• pp.1318-1325
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• 1997

Background : Since the late 1960s, mechanical ventilation has been accomplished primarily using volume controlled ventilation(VCV). While VCV allows a set tidal volume to be guaranteed, VCV could bring about excessive airway pressures that may be lead to barotrauma in the patients with acute lung injury. With the increment of knowledge related to ventilator-induced lung injury, pressure controlled ventilation(PCV) has been frequently applied to these patients. But, PCV has a disadvantage of variable tidal volume delivery as pulmonary impedance changes. Since the concept of combining the positive attributes of VCV and PCV(dual control ventilation, DCV) was described firstly in 1992, a few DCV modes were introduced. Pressure-regulated volume control(PRVC) mode, a kind of DCV, is pressure-limited, time-cycled ventilation that uses tidal volume as a feedback control for continuously adjusting the pressure limit However, no clinical studies were published on the efficacy of PRVC until now. 'This investigation studied the efficacy of PRVC in the patients with unstable respiratory mechanics. Methods : The subjects were 8 mechanically ventilated patients(M : F=6 : 2, $56{\pm}26$ years) who showed unstable respiratory mechanics, which was defined by the coefficients of variation of peak inspiratory pressure for 15 minutes greater than 10% under VCV, or the coefficients of variation of tidal volume greater than 10% under PCV. The study was consisited of 3 modes application with VCV, PCV and PRVC for 15 minutes by random order. To obtain same tidal volume, inspiratory pressure setting was adjusted in PCV. Respiratory parameters were measured by pulmonary monitor(CP-100 pulmonary monitor, Bicore, Irvine, CA, USA). Results : 1) Mean tidal volumes($V_T$) in each mode were not different(VCV, $431{\pm}102ml$ ; PCV, $417{\pm}99ml$ ; PRVC, $414{\pm}97ml$) 2) The coefficient of variation(CV) of $V_T$ were $5.2{\pm}3.9%$ in VCV, $15.2{\pm}7.5%$ in PCV and $19.3{\pm}10.0%$ in PRVC. The CV of $V_T$ in PCV and PRVC were significantly greater than that in VCV(p<0.01). 3) Mean peak inspiratory pressure(PIP) in VCV($31.0{\pm}6.9cm$ $H_2O$) was higher than PIP in PCV($26.0{\pm}6.5cm$ $H_2O$) or PRVC($27.0{\pm}6.4cm$ $H_2O$)(p<0.05). 4) The CV of PIP were $13.9{\pm}3.7%$ in VCV, $4.9{\pm}2.6%$ in PVC and $12.2{\pm}7.0%$ in PRVC. The CV of PIP in VCV and PRVC were greater than that in PCV(p<0.01). Conclusions : Because of wide fluctuations of VT and PIP, PRVC mode did not seem to have advantages compared to VCV or PCV in the patients with unstable respiratory mechanics.

• Journal of Genetic Medicine
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• v.8 no.2
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• pp.89-99
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• 2011

Over the years Korean health care system has improved in delivery of quality care to the general population for many areas of the health problems. The system is now being recognized in the world as the most cost effective one. It is covered by the uniform national health insurance policy for which most people in Korea are mandatory policy holders. Genetic counseling service, however, which is well recognized as an integral part of clinical genetics service deals with diagnosis and management of genetic condition as well as genetic information presentation and family support, is yet to be delivered in comprehensive way for the patients and families in need. Two major obstacles in providing genetic counseling service in korean health care system are identified; One is the lack of recognition for the need for genetic counseling service as necessary service by the national health insurance. Genetic counseling consumes a significant time in delivery and the current very low-fee schedule for physician service makes it very difficult to provide meaningful service. Second is the critical shortage of qualified professionals in the field of medical genetics and genetic counseling who can provide the service of genetic counseling in clinical setting. However, recognition and understanding of the fact that the scope and role of genetic counseling is expanding in post genomic era of personalized medicine for delivery of quality health care, will lead to the efforts to overcome obstacles in providing genetic counseling service in korean health care system. Only concerted efforts from health care policy makers of government on clinical genetics service and genetic counseling for establishing adequate reimbursement coverage and professional communities for developing educational program and certification process for professional genetic counselors, are necessary for the delivery of much needed clinical genetic counseling service in Korea.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.19-43
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• 2014

The Pareto principle, also known as the 80-20 rule, states that roughly 80% of the effects come from 20% of the causes for many events including natural phenomena. It has been recognized as a golden rule in business with a wide application of such discovery like 20 percent of customers resulting in 80 percent of total sales. On the other hand, the Long Tail theory, pointing out that "the trivial many" produces more value than "the vital few," has gained popularity in recent times with a tremendous reduction of distribution and inventory costs through the development of ICT(Information and Communication Technology). This study started with a view to illuminating how these two primary business paradigms-Pareto principle and Long Tail theory-relates to the success of virtual knowledge collaboration. The importance of virtual knowledge collaboration is soaring in this era of globalization and virtualization transcending geographical and temporal constraints. Many previous studies on knowledge sharing have focused on the factors to affect knowledge sharing, seeking to boost individual knowledge sharing and resolve the social dilemma caused from the fact that rational individuals are likely to rather consume than contribute knowledge. Knowledge collaboration can be defined as the creation of knowledge by not only sharing knowledge, but also by transforming and integrating such knowledge. In this perspective of knowledge collaboration, the relative distribution of knowledge sharing among participants can count as much as the absolute amounts of individual knowledge sharing. In particular, whether the more contribution of the upper 20 percent of participants in knowledge sharing will enhance the efficiency of overall knowledge collaboration is an issue of interest. This study deals with the effect of this sort of knowledge sharing distribution on the efficiency of knowledge collaboration and is extended to reflect the work characteristics. All analyses were conducted based on actual data instead of self-reported questionnaire surveys. More specifically, we analyzed the collaborative behaviors of editors of 2,978 English Wikipedia featured articles, which are the best quality grade of articles in English Wikipedia. We adopted Pareto ratio, the ratio of the number of knowledge contribution of the upper 20 percent of participants to the total number of knowledge contribution made by the total participants of an article group, to examine the effect of Pareto principle. In addition, Gini coefficient, which represents the inequality of income among a group of people, was applied to reveal the effect of inequality of knowledge contribution. Hypotheses were set up based on the assumption that the higher ratio of knowledge contribution by more highly motivated participants will lead to the higher collaboration efficiency, but if the ratio gets too high, the collaboration efficiency will be exacerbated because overall informational diversity is threatened and knowledge contribution of less motivated participants is intimidated. Cox regression models were formulated for each of the focal variables-Pareto ratio and Gini coefficient-with seven control variables such as the number of editors involved in an article, the average time length between successive edits of an article, the number of sections a featured article has, etc. The dependent variable of the Cox models is the time spent from article initiation to promotion to the featured article level, indicating the efficiency of knowledge collaboration. To examine whether the effects of the focal variables vary depending on the characteristics of a group task, we classified 2,978 featured articles into two categories: Academic and Non-academic. Academic articles refer to at least one paper published at an SCI, SSCI, A&HCI, or SCIE journal. We assumed that academic articles are more complex, entail more information processing and problem solving, and thus require more skill variety and expertise. The analysis results indicate the followings; First, Pareto ratio and inequality of knowledge sharing relates in a curvilinear fashion to the collaboration efficiency in an online community, promoting it to an optimal point and undermining it thereafter. Second, the curvilinear effect of Pareto ratio and inequality of knowledge sharing on the collaboration efficiency is more sensitive with a more academic task in an online community.

• Journal of Intelligence and Information Systems
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• v.20 no.1
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• pp.195-211
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• 2014

Cloud computing services provide IT resources as services on demand. This is considered a key concept, which will lead a shift from an ownership-based paradigm to a new pay-for-use paradigm, which can reduce the fixed cost for IT resources, and improve flexibility and scalability. As IT services, cloud services have evolved from early similar computing concepts such as network computing, utility computing, server-based computing, and grid computing. So research into cloud computing is highly related to and combined with various relevant computing research areas. To seek promising research issues and topics in cloud computing, it is necessary to understand the research trends in cloud computing more comprehensively. In this study, we collect bibliographic information and citation information for cloud computing related research papers published in major international journals from 1994 to 2012, and analyzes macroscopic trends and network changes to citation relationships among papers and the co-occurrence relationships of key words by utilizing social network analysis measures. Through the analysis, we can identify the relationships and connections among research topics in cloud computing related areas, and highlight new potential research topics. In addition, we visualize dynamic changes of research topics relating to cloud computing using a proposed cloud computing "research trend map." A research trend map visualizes positions of research topics in two-dimensional space. Frequencies of key words (X-axis) and the rates of increase in the degree centrality of key words (Y-axis) are used as the two dimensions of the research trend map. Based on the values of the two dimensions, the two dimensional space of a research map is divided into four areas: maturation, growth, promising, and decline. An area with high keyword frequency, but low rates of increase of degree centrality is defined as a mature technology area; the area where both keyword frequency and the increase rate of degree centrality are high is defined as a growth technology area; the area where the keyword frequency is low, but the rate of increase in the degree centrality is high is defined as a promising technology area; and the area where both keyword frequency and the rate of degree centrality are low is defined as a declining technology area. Based on this method, cloud computing research trend maps make it possible to easily grasp the main research trends in cloud computing, and to explain the evolution of research topics. According to the results of an analysis of citation relationships, research papers on security, distributed processing, and optical networking for cloud computing are on the top based on the page-rank measure. From the analysis of key words in research papers, cloud computing and grid computing showed high centrality in 2009, and key words dealing with main elemental technologies such as data outsourcing, error detection methods, and infrastructure construction showed high centrality in 2010~2011. In 2012, security, virtualization, and resource management showed high centrality. Moreover, it was found that the interest in the technical issues of cloud computing increases gradually. From annual cloud computing research trend maps, it was verified that security is located in the promising area, virtualization has moved from the promising area to the growth area, and grid computing and distributed system has moved to the declining area. The study results indicate that distributed systems and grid computing received a lot of attention as similar computing paradigms in the early stage of cloud computing research. The early stage of cloud computing was a period focused on understanding and investigating cloud computing as an emergent technology, linking to relevant established computing concepts. After the early stage, security and virtualization technologies became main issues in cloud computing, which is reflected in the movement of security and virtualization technologies from the promising area to the growth area in the cloud computing research trend maps. Moreover, this study revealed that current research in cloud computing has rapidly transferred from a focus on technical issues to for a focus on application issues, such as SLAs (Service Level Agreements).

• 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.

• Economic and Environmental Geology
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• v.25 no.4
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• pp.417-433
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• 1992

Lead-zinc-copper deposits of the Jeonheung and the Oksan mines around Euiseong area occur as hydrothermal quartz and calcite veins that crosscut Cretaceous sedimentary rocks of the Gyeongsang Basin. The mineralization occurred in three distinct stages (I, II, and III): (I) quartz-sulfides-sulfosalts-hematite mineralization stage; (II) barren quartz-fluorite stage; and (III) barren calcite stage. Stage I ore minerals comprise pyrite, chalcopyrite, sphalerite, galena and Pb-Ag-Bi-Sb sulfosalts. Mineralogies of the two mines are different, and arsenopyrite, pyrrhotite, tetrahedrite and iron-rich (up to 21 mole % FeS) sphalerite are restricted to the Oksan mine. A K-Ar radiometric dating for sericite indicates that the Pb-Zn-Cu deposits of the Euiseong area were formed during late Cretaceous age ($62.3{\pm}2.8Ma$), likely associated with a subvolcanic activity related to the volcanic complex in the nearby Geumseongsan Caldera and the ubiquitous felsite dykes. Stage I mineralization occurred at temperatures between > $380^{\circ}C$ and $240^{\circ}C$ from fluids with salinities between 6.3 and 0.7 equiv. wt. % NaCl. The chalcopyrite deposition occurred mostly at higher temperatures of > $300^{\circ}C$. Fluid inclusion data indicate that the Pb-Zn-Cu ore mineralization resulted from a complex history of boiling, cooling and dilution of ore fluids. The mineralization at Jeonheung resulted mainly from cooling and dilution by an influx of cooler meteoric waters, whereas the mineralization at Oksan was largely due to fluid boiling. Evidence of fluid boiling suggests that pressures decreased from about 210 bars to 80 bars. This corresponds to a depth of about 900 m in a hydrothermal system that changed from lithostatic (closed) toward hydrostatic (open) conditions. Sulfur isotope compositions of sulfide minerals (${\delta}^{34}S=2.9{\sim}9.6$ per mil) indicate that the ${\delta}^{34}S_{{\Sigma}S}$ value of ore fluids was ${\approx}8.6$ per mil. This ${\delta}^{34}S_{{\Sigma}S}$ value is likely consistent with an igneous sulfur mixed with sulfates (?) in surrounding sedimentary rocks. Measured and calculated hydrogen and oxygen isotope values of ore-forming fluids suggest meteoric water dominance, approaching unexchanged meteoric water values. Equilibrium thermodynamic interpretation indicates that the temperature versus $fs_2$ variation of stage I ore fluids differed between the two mines as follows: the $fs_2$ of ore fluids at Jeonheung changed with decreasing temperature constantly near the pyrite-hematite-magnetite sulfidation curve, whereas those at Oksan changed from the pyrite-pyrrhotite sulfidation state towards the pyrite-hematite-magnetite state. The shift in minerals precipitated during stage I also reflects a concomitant $fo_2$ increase, probably due to mixing of ore fluids with cooler, more oxidizing meteoric waters. Thermodynamic consideration of copper solubility suggests that the ore-forming fluids cooled through boiling at Oksan and mixing with less-evolved meteoric waters at Jeonheung, and that this cooling was the main cause of copper deposition through destabilization of copper chloride complexes.

• The Korean Society of Law and Medicine
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• v.16 no.2
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• pp.87-130
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• 2015

In a case in which National Health Insurance Corporation (NHIC) pays medical care expenses to a victim of a traffic accident resulting in injury or death and asks the assailant for compensation of its share in the medical care expenses, as the precedent treats the subrogation of a claim set by National Health Insurance Act the same as that set by Industrial Accident Compensation Insurance Act, it draws the range of its compensation from the range of deduction, according to the principle of deduction after offsetting and acknowledges the compensation of all medical care expenses borne by the NHIC, within the amount of compensation claimed by the victim. However, both the National Health Insurance Act and the Industrial Accident Compensation Insurance Act are laws that regulate social insurance, but medical care expenses in the National Health Insurance Act have a character of 'an underinsurance that fixes the ratio of indemnification,' while insurance benefit on the Industrial Accident Compensation Insurance Act has a character of full insurance, or focuses on helping the insured that suffered an industrial accident lead a life, approximate to that in the past, regardless of the amount of damages according to its character of social insurance. Therefore, there is no reason to treat the subrogation of a claim on the National Health Insurance Act the same as that on the Industrial Accident Compensation Insurance Act. Since the insured loses the right of claim acquired by the insurer by subrogation in return for receiving a receipt, there is no benefit from receiving insurance in the range. Thus, in a suit in which the insured seeks compensation for damages from the assailant, there is no room for the application of the legal principle of offset of profits and losses, and the range of subrogation of a claim or the amount of deduction from compensation should be decided by the contract between the persons directly involved or a related law. Therefore, it is not reasonable that the precedent draws the range of the NHIC's compensation from the principle of deduction after offsetting. To interpret Clause 1, Article 58 of the National Health Insurance Act that sets the range of the NHIC's compensation uniformly and systematically in combination with Clause 2 of the same article that sets the range of exemption, if the compensation is made first, it is reasonable to fix the range of the NHIC's compensation by multiplying the medical care expenses paid by the ratio of the assailant's liability. This is contrasted with the range of the Korea Labor Welfare Corporation's compensation which covers the total amount of the claim of the insured within the insurance benefit paid in the interpretation of Clauses 1 and 2, Article 87 of the Industrial Accident Compensation Insurance Act. In the meantime, there are doubts about why the profit should be deducted from the amount of compensation claimed, though it is enough for the principle of deduction after offsetting that the precedent took as the premise in judging the range of the NHIC's compensation to deduct the profit made by the victim from the amount of damages, so as to achieve the goal of not attributing profit more than the amount of damage to a victim; whether it is reasonable to attribute all the profit made by the victim to the assailant, while the damages suffered by the victim are distributed fairly; and whether there is concrete validity in actual cases. Therefore, the legal principle of the precedent concerning the range of the NHIC's compensation and the legal principle of the precedent following the principle of deduction after offsetting should be reconsidered.