• Journal of Korean Medical classics
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• v.11 no.2
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• pp.114-134
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• 1998

The conception of pyo(標) bon(本) joong(中) in the part of woongihak(運氣學) of negeong(內徑) one of the important thing that decides the relation between six gi(六氣) and samyum and samyang(三陰三陽) or between each other's of samyum and samyang itself, it says that the relation of Pyo-rce(表裏). So this conception from the ancient times have been used to explain the theory of meridian(經絡) and organs(五臟六腑) and in other important field of oriental medicine - Sanghannon(傷寒論), it became basis of explanation of pcthoiogical principles in the system of six kyung(六徑). At first, the subject or this study is limited to the rament of $\ll$Somun(素問)$\gg$ in order to find the accurate and original meanings of pyo(標) bon(本) joong(中). And the meanings are studied by the way of expanding it's meaning with basic conceptions of woongihak(運氣學) and astronomy included in negeong(內徑). In this study, the results are summarized as the followings. 1. The contents of - the 68th chapter of negeong(內徑), concerning pyo(標) and joong(中) come under chogi(初氣) and joonggi(中氣) of the same chapter, after consideration of astronomical knowledge. And they become active during the period that last about 30days, a haft of one step(一步) of kaekgi(客氣). 2. Bon(本) as a kind of six gi(六氣) that is revealed from internal principle of something, that is to say Ohhaeng(五行), comes mainly under the kaekgi(客氣) of woongihak(運氣學) with the meaning of 'sign' is thai the specific properties of six gi(六氣) are revealed to our sight, so we can feel that through the change of nature, Joong(中) is the other property hidden in the inside of six gi(六氣), that is a portion of original nature(本性) like the bon(本). 3. The relation of pyo(標) and bon(本) is like that bctween the principle hidden inside in all things(理) and it's expression into the real world(氣) also similar to thai of yumyang(陰陽) and ohhaeng(五行). Therefore bon(本), though it means one of the six gi(六氣), hale the property of ohhaeng(五行) and pyo(標) is revealed, with an appearance of samyum-samyang(三陰三陰). 4. pyo(標) and joong(中) are also the both sides of yum(陰) and yang(陰) that revealed under the change of yumyang-ohhaengl(陰陽五行) in the nature. For example, if the one is yang(陰), the other is yum(陰). In the process that the change of all things is revealed out, first the property of pyo(標) appears strongly and then that of joong(中) appears comparatively weakly. But, in spite of the inhibitive relation of yumyang(陰陽), pyo(標) and joong(中) promote each other. 5. Under the course of change. It happens according to the bon(本), the property of ohhaeng(五行) in the case of soyang(少陽) and taeyum(太陰), because the effect of moisture(濕) and fire(火) that makes hyung(形) and gi(氣) is very strong in the universe. In the case of taeyang(太陽) and soyum(少陰), it happens according to the bon(本) and pyo(標) because they hare the polarity of water and fire(火水), at the same time, are not separated each other. In the case of yangmeong(陽明) and gualyum(厥陰), the change appears only according to the joong(中), but not strongly because the phase of yangmeong(陽明) and gualyum(厥陰) is a lull phase processing to the next one.

• Proceedings of the KOSOMBE Conference
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• v.1992 no.05
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• pp.27-47
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• 1992

Engineers have developed new instruments that aid in diagnosis and therapy Ultrasonic imaging has provided a nondamaging method of imaging internal organs. A complex transducer emits ultrasonic waves at many angles and reconstructs a map of internal anatomy and also velocities of blood in vessels. Fast computed tomography permits reconstruction of the 3-dimensional anatomy and perfusion of the heart at 20-Hz rates. Positron emission tomography uses certain isotopes that produce positrons that react with electrons to simultaneously emit two gamma rays in opposite directions. It locates the region of origin by using a ring of discrete scintillation detectors, each in electronic coincidence with an opposing detector. In magnetic resonance imaging, the patient is placed in a very strong magnetic field. The precessing of the hydrogen atoms is perturbed by an interrogating field to yield two-dimensional images of soft tissue having exceptional clarity. As an alternative to radiology image processing, film archiving, and retrieval, picture archiving and communication systems (PACS) are being implemented. Images from computed radiography, magnetic resonance imaging (MRI), nuclear medicine, and ultrasound are digitized, transmitted, and stored in computers for retrieval at distributed work stations. In electrical impedance tomography, electrodes are placed around the thorax. 50-kHz current is injected between two electrodes and voltages are measured on all other electrodes. A computer processes the data to yield an image of the resistivity of a 2-dimensional slice of the thorax. During fetal monitoring, a corkscrew electrode is screwed into the fetal scalp to measure the fetal electrocardiogram. Correlations with uterine contractions yield information on the status of the fetus during delivery To measure cardiac output by thermodilution, cold saline is injected into the right atrium. A thermistor in the right pulmonary artery yields temperature measurements, from which we can calculate cardiac output. In impedance cardiography, we measure the changes in electrical impedance as the heart ejects blood into the arteries. Motion artifacts are large, so signal averaging is useful during monitoring. An intraarterial blood gas monitoring system permits monitoring in real time. Light is sent down optical fibers inserted into the radial artery, where it is absorbed by dyes, which reemit the light at a different wavelength. The emitted light travels up optical fibers where an external instrument determines O2, CO2, and pH. Therapeutic devices include the electrosurgical unit. A high-frequency electric arc is drawn between the knife and the tissue. The arc cuts and the heat coagulates, thus preventing blood loss. Hyperthermia has demonstrated antitumor effects in patients in whom all conventional modes of therapy have failed. Methods of raising tumor temperature include focused ultrasound, radio-frequency power through needles, or microwaves. When the heart stops pumping, we use the defibrillator to restore normal pumping. A brief, high-current pulse through the heart synchronizes all cardiac fibers to restore normal rhythm. When the cardiac rhythm is too slow, we implant the cardiac pacemaker. An electrode within the heart stimulates the cardiac muscle to contract at the normal rate. When the cardiac valves are narrowed or leak, we implant an artificial valve. Silicone rubber and Teflon are used for biocompatibility. Artificial hearts powered by pneumatic hoses have been implanted in humans. However, the quality of life gradually degrades, and death ensues. When kidney stones develop, lithotripsy is used. A spark creates a pressure wave, which is focused on the stone and fragments it. The pieces pass out normally. When kidneys fail, the blood is cleansed during hemodialysis. Urea passes through a porous membrane to a dialysate bath to lower its concentration in the blood. The blind are able to read by scanning the Optacon with their fingertips. A camera scans letters and converts them to an array of vibrating pins. The deaf are able to hear using a cochlear implant. A microphone detects sound and divides it into frequency bands. 22 electrodes within the cochlea stimulate the acoustic the acoustic nerve to provide sound patterns. For those who have lost muscle function in the limbs, researchers are implanting electrodes to stimulate the muscle. Sensors in the legs and arms feed back signals to a computer that coordinates the stimulators to provide limb motion. For those with high spinal cord injury, a puff and sip switch can control a computer and permit the disabled person operate the computer and communicate with the outside world.

• Asia pacific journal of information systems
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• v.18 no.2
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• pp.95-114
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• 2008

Recent interests in data mining result from the expansion of the amount of business data and the growing business needs for extracting valuable knowledge from the data and then utilizing it for decision making process. In particular, recent advances in association rule mining techniques enable us to acquire knowledge concerning sales patterns among individual items from the voluminous transactional data. Certainly, one of the major purposes of association rule mining is to utilize acquired knowledge in providing marketing strategies such as cross-selling, sales promotion, and shelf-space allocation. In spite of the potential applicability of association rule mining, unfortunately, it is not often the case that the marketing mix acquired from data mining leads to the realized profit. The main difficulty of mining-based profit realization can be found in the fact that tremendous numbers of patterns are discovered by the association rule mining. Due to the many patterns, data mining experts should perform additional mining of the results of initial mining in order to extract only actionable and profitable knowledge, which exhausts much time and costs. In the literature, a number of interestingness measures have been devised for estimating discovered patterns. Most of the measures can be directly calculated from what is known as a contingency table, which summarizes the sales frequencies of exclusive items or itemsets. A contingency table can provide brief insights into the relationship between two or more itemsets of concern. However, it is important to note that some useful information concerning sales transactions may be lost when a contingency table is constructed. For instance, information regarding the size of each market basket(i.e., the number of items in each transaction) cannot be described in a contingency table. It is natural that a larger basket has a tendency to consist of more sales patterns. Therefore, if two itemsets are sold together in a very large basket, it can be expected that the basket contains two or more patterns and that the two itemsets belong to mutually different patterns. Therefore, we should classify frequent itemset into two categories, inter-pattern co-occurrence and intra-pattern co-occurrence, and investigate the effect of the market basket size on the two categories. This notion implies that any interestingness measures for association rules should consider not only the total frequency of target itemsets but also the size of each basket. There have been many attempts on analyzing various interestingness measures in the literature. Most of them have conducted qualitative comparison among various measures. The studies proposed desirable properties of interestingness measures and then surveyed how many properties are obeyed by each measure. However, relatively few attentions have been made on evaluating how well the patterns discovered by each measure are regarded to be valuable in the real world. In this paper, attempts are made to propose two notions regarding association rule measures. First, a quantitative criterion for estimating accuracy of association rule measures is presented. According to this criterion, a measure can be considered to be accurate if it assigns high scores to meaningful patterns that actually exist and low scores to arbitrary patterns that co-occur by coincidence. Next, complementary measures are presented to improve the accuracy of traditional association rule measures. By adopting the factor of market basket size, the devised measures attempt to discriminate the co-occurrence of itemsets in a small basket from another co-occurrence in a large basket. Intensive computer simulations under various workloads were performed in order to analyze the accuracy of various interestingness measures including traditional measures and the proposed measures.

• Progress in Medical Physics
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• v.20 no.3
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• pp.132-138
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• 2009

Studies on target motion in 4-dimensional radiotherapy are being world-widely conducted to enhance treatment record and protection of normal organs. Prediction of tumor motion might be very useful and/or essential for especially free-breathing system during radiation delivery such as respiratory gating system and tumor tracking system. Neural network is powerful to express a time series with nonlinearity because its prediction algorithm is not governed by statistic formula but finds a rule of data expression. This study intended to assess applicability of neural network method to predict tumor motion in 4-dimensional radiotherapy. Scaled Conjugate Gradient algorithm was employed as a learning algorithm. Considering reparation data for 10 patients, prediction by the neural network algorithms was compared with the measurement by the real-time position management (RPM) system. The results showed that the neural network algorithm has the excellent accuracy of maximum absolute error smaller than 3 mm, except for the cases in which the maximum amplitude of respiration is over the range of respiration used in the learning process of neural network. It indicates the insufficient learning of the neural network for extrapolation. The problem could be solved by acquiring a full range of respiration before learning procedure. Further works are programmed to verify a feasibility of practical application for 4-dimensional treatment system, including prediction performance according to various system latency and irregular patterns of respiration.

• Communications of Mathematical Education
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• v.20 no.2 s.26
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• pp.295-326
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• 2006

Despite the importance of mathematics education, many students in high school have lost their interests and felt difficulties and they don't have 'mathematical' experience with meanings attached because of the entrance examination. This paper attempted to resolve these problems and find the teaching-method with which students can study by themselves with more confidence. Nowadays students' use of Internet is very popular. After develop 'the development of mathematical power' program based on mathematics history, history, science, the application of problems in real world, and self-evaluation, I made students repeat them after making teaching lessons in classroom as moving pictures. Through this processes, I attempted to develop the Self-Directed Learning' ability by making public education substantial. First of all I analyzed the actual conditions on 'Self-Directed Learning' ability in mathematics subject, the conditions of seeing and hearing in Internet learning program, and students' and their parents' interests in Internet education. By analyzing the records, I observed the significance of the introducing mathematics history in mathematics subject in early stager, cooperative-learning, leveled-learning, self-directed learning, and Internet learning. Actually in aspect of applying 'the development of mathematical power' program, at first I made up the educational conditions to fix the program, collected the teaching materials, established the system of teaching-learning model, developed materials for the learning applying Internet mail and instruments of classroom, and carried out instruction to establish and practice mathematics learning plan. Then I applied the teaching-learning model of leveled cooperation and presentation loaming and at the same time constructed and used the leveled learning materials of complementary, average, and advanced process and instructed to watch teaching moving pictures through Internet mail and in the classroom. After that I observed how effective this program was through the interest arid attitude toward mathematics subject, learning accomplishment, and the change of self-directed learning. Finally, I wrote the conclusion and suggestion on the preparation of conditions fur the students' voluntary participation in mathematics learning and the project and application on 'the development of mathematical power' program and repeated learning with the materials of moving pictures in classroom.

• Korean Journal of Clinical Laboratory Science
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• v.52 no.3
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• pp.284-295
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• 2020

In December 2019, the first coronavirus disease- 2019 (COVID-19) patient was reported in Wuhan, Hubei Province, China. Since then, the number of patients who suffered severe acute respiratory syndrome caused by the novel Coronavirus (SARS-CoV-2 or 2019-nCoV) has increased dramatically in Korea. This new variant virus induces pulmonary diseases, including cough, sore throat, rhinorrhea, dyspnea, and pneumonia. Because SARS-CoV-2 is an RNA virus, real-time reverse-transcriptase PCR has been used widely to diagnose COVID-19. As the Korea Centers for Disease Prevention and Control (KCDC) and Ministry of Food & Drug Safety (MFDS) approved emergency use authorization, clinical specimens collected from COVID-19 patients and even healthy people have been clinically diagnosed by laboratory medicine. Based on a literature search, this paper reviews the epidemiology, symptoms, molecular diagnostics approved by KCDC, a current diagnosis of COVID-19 in the laboratories, the difference between molecular and serological diagnosis, and guidelines for clinical specimens. In addition, the Korean guidelines of biosafety for clinical laboratory scientists are evaluated to prevent healthcare-associated infection. The author's experience and lessons as clinical laboratory scientists will provide valuable insights to protect the domestic and international health community in this COVID-19 pandemic around the world.

• Journal of Science and Technology Studies
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• v.18 no.2
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• pp.135-179
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• 2018

How do robots interact with the elderly? In this paper, we analyze the contexts of interaction between robots and the elderly and the role of mediators in initiating, facilitating, and maintaining the interaction. We do not attempt to evaluate the robot's performance or measure the impact of robots on the elderly. Instead, we focus on the circumstances and contexts within which a robot is situated as it interacts with the elderly. Our premise is that the success of human-robot interaction does not depend solely on the robot's technical capability, but also on the pre-arranged settings and local contingencies at the site of interaction. We select three television shows that feature robots for the elderly and one "dementia-prevention" robot in a regional healthcare center as our sites for observing robot-elderly interaction: "Grandma's Robot"(tvN), "Co-existence Experiment''(JTBC), "Future Diary"(MBC), and the Silbot class in Suwon. By analyzing verbal and non-verbal interactions between the elderly and the robots in these programs, we point out that in most cases the robots and the elderly do not meet one-to-one; the interaction is usually mediated by an actor who is not an old person. These mediators are not temporary or secondary components in the robot-elderly interaction; they play a key role in the relationship by arranging the first meeting, triggering initial interactions, and carefully observing unfolding interactions. At critical moments, the mediators prevent the interaction from falling apart by intervening verbally or physically. Based on our observation of the robot-elderly interaction, we argue that we can better understand and evaluate the human-robot interaction in general by paying attention to the existence and role of the mediators. We suggest that researchers in human-robot interaction should expand their analytical focus from one-to-one interactions between humans and robots to human-robot-human interactions in diverse real-world situations.

• Asia pacific journal of information systems
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• v.19 no.2
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• pp.157-178
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• 2009

Corporate credit rating is a very important factor in the market for corporate debt. Information concerning corporate operations is often disseminated to market participants through the changes in credit ratings that are published by professional rating agencies, such as Standard and Poor's (S&P) and Moody's Investor Service. Since these agencies generally require a large fee for the service, and the periodically provided ratings sometimes do not reflect the default risk of the company at the time, it may be advantageous for bond-market participants to be able to classify credit ratings before the agencies actually publish them. As a result, it is very important for companies (especially, financial companies) to develop a proper model of credit rating. From a technical perspective, the credit rating constitutes a typical, multiclass, classification problem because rating agencies generally have ten or more categories of ratings. For example, S&P's ratings range from AAA for the highest-quality bonds to D for the lowest-quality bonds. The professional rating agencies emphasize the importance of analysts' subjective judgments in the determination of credit ratings. However, in practice, a mathematical model that uses the financial variables of companies plays an important role in determining credit ratings, since it is convenient to apply and cost efficient. These financial variables include the ratios that represent a company's leverage status, liquidity status, and profitability status. Several statistical and artificial intelligence (AI) techniques have been applied as tools for predicting credit ratings. Among them, artificial neural networks are most prevalent in the area of finance because of their broad applicability to many business problems and their preeminent ability to adapt. However, artificial neural networks also have many defects, including the difficulty in determining the values of the control parameters and the number of processing elements in the layer as well as the risk of over-fitting. Of late, because of their robustness and high accuracy, support vector machines (SVMs) have become popular as a solution for problems with generating accurate prediction. An SVM's solution may be globally optimal because SVMs seek to minimize structural risk. On the other hand, artificial neural network models may tend to find locally optimal solutions because they seek to minimize empirical risk. In addition, no parameters need to be tuned in SVMs, barring the upper bound for non-separable cases in linear SVMs. Since SVMs were originally devised for binary classification, however they are not intrinsically geared for multiclass classifications as in credit ratings. Thus, researchers have tried to extend the original SVM to multiclass classification. Hitherto, a variety of techniques to extend standard SVMs to multiclass SVMs (MSVMs) has been proposed in the literature Only a few types of MSVM are, however, tested using prior studies that apply MSVMs to credit ratings studies. In this study, we examined six different techniques of MSVMs: (1) One-Against-One, (2) One-Against-AIL (3) DAGSVM, (4) ECOC, (5) Method of Weston and Watkins, and (6) Method of Crammer and Singer. In addition, we examined the prediction accuracy of some modified version of conventional MSVM techniques. To find the most appropriate technique of MSVMs for corporate bond rating, we applied all the techniques of MSVMs to a real-world case of credit rating in Korea. The best application is in corporate bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. For our study the research data were collected from National Information and Credit Evaluation, Inc., a major bond-rating company in Korea. The data set is comprised of the bond-ratings for the year 2002 and various financial variables for 1,295 companies from the manufacturing industry in Korea. We compared the results of these techniques with one another, and with those of traditional methods for credit ratings, such as multiple discriminant analysis (MDA), multinomial logistic regression (MLOGIT), and artificial neural networks (ANNs). As a result, we found that DAGSVM with an ordered list was the best approach for the prediction of bond rating. In addition, we found that the modified version of ECOC approach can yield higher prediction accuracy for the cases showing clear patterns.

• Journal of the Korean Institute of Landscape Architecture
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• v.42 no.5
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• pp.1-12
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• 2014

Recently, the reenaction of place's memories that were considered sense of place based on its historical and structural characteristic were assumed important topics for recovering and making the park from industrial sites, such as factory, industrial complex, industrial city, labor residential development, landfill, etc., to the public all over the world. This research aimed to conduct some preliminary data for making the park's sense of place highly. So, after conducting the structural forms of sense of place for Seoul Forest and Seonyudo Park that were designed and built by considering its place memories actively, park planning and design implications that were considered its sense of place were suggested. The research results those were derived from the structural forms of sense of place for Seoul Forest and Seonyudo Park's are the following. First, the Structural Equation Modeling(SEM) on Seoul Forest and Seonyudo Park were determined that the natural-physical, artificial-physical, and experiential environmental factors' satisfaction of Seoul Forest and Seonyudo Park have an effect on forming the Sense of Place. In addition, the sense of place was affected by the willingness to visit. Second, according to its physical environment, the experiential factors, such as plays, exercises and etc., were more important relatively. Therefore, experiential factors should be considered significantly with physical factors to make the sense of place highly. Third, even the places were under similar category, the factors' and valuables' relative importance were changed. As the results of structural equation modeling said, specific valuables' related with each factors would be differentiated due to the places' characteristics. For example, the results were showed that natural-physical factor was more important than artificial-physical factor in Seoul Forest. On the other hand, artificial-physical factor was more important than the natural- physical factor. This research carries some significance for applying a quantitative research method(structural equation modeling) to various place to conduct the sense of place's structural model, for suggesting relative specific methods to make the sense of place, and for being a step forward to substance of sense of place. If further studies conduct focusing on various places to draw the forming models of sense of place that were based this research's analysis methods and results, those researches would contribute to make the urban place meaningful, characteristically and affectionately. Furthermore, those researches would contribute in making a humane and competitiveness city.

• Korean Journal of Cognitive Science
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• v.27 no.3
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• pp.441-467
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• 2016

This fMRI study is aim to investigate effects of competitive environment in cognitive empathic process in human brain. Empathy is known as a crucial factor for human's adaptive behavior in aspects of social cognition and it is almost automatic process, on the other hand competitive situation is psychologically devastated environment to win someone for getting rewards. We hypnotized that reading and understanding of other person's mind are a specific characteristic related to survival evolutionarily, however competition would have an effect on the empathic cognitive process because of mechanisms of competition. To manipulate the competitive atmosphere, one researcher took a role of competitor against participants and they were instructed to get monetary rewards when their performance was better than a competitor. 21 participants(9 males and 12 females) performed to judge the emotional valence of the empathic task consisted of illustrated images with various situation could be experienced in real world as on $1^{st}$ person perspective in both competitive and non-competitive condition, and did same performance with objects stimulus in control condition. In order to examine the competition effects on empathic process,, hemodynamic response were obtained during fMRI session and the imaging data were analyzed to identify brain regions where responses to each condition across the two consecutive runs. Participants' reaction time in competitive condition was faster statistically significant than non-competitive one. Activation for competitive condition increased in the following areas: ACC, mPFC, SMG, thalamus extended caudate and Nacc, parahippocampal gyrus, and for non-competitive condition increased paracingulate gyrus, temporal pole, vmPFC, superior occipital gyrus. As a result of regression analysis using empathic scores as covariance, the rSMG, IFG, fusiform gyrus, thalamus, putamen were correlated with higher empathic levels, and TPJ were correlated with lower empathic scores. We suggest that these observations could mean competitive environment have an effect on neural base of cognitive empathic process.