• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.2
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• pp.96-113
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• 1996

It has been found that the misfit dislocations in heavily boron-doped layers originate from wafer edges. Moreover, the propagation of the misfit dislocation into a heavily boron-doped region can be suppressed by placing a surrounding undoped region. Using a surrounding undoped region the disloction-free heavily boron-deoped silicon membranes have been fabricated. The measured surface roughness, fracture strength, and residual tensile stress of the membrane are 20.angs. peak-to-peak, 1.39${\times}$10$^{10}$ and 2.7${\times}$10$^{9}$dyn/cm$^{2}$, while those of the conventional heavily boron-doped silicon membrane with high density of misfit dislocations are 500 peak-to-peak, 8.27${\times}$10$^{9}$ and 9.3${\times}$10$^{8}$dyn/cm$^{2}$ respectively. The differences between these two membranes are due to the misfit dislocations. Young's modulus has been extracted as 1.45${\times}$10$^{12}$dyn/cm$^{2}$ for both membranes. Also, the effective lattice constant of heavily boron-doped silicon, the in-plane lattice constant of the conventional membrane, and the density of misfit dislocation contained in the conventional membrane have been extracted as density of misfit dislocation contained in the conventional membrane have been extracted as density of misfit dislocation contained in the conventional membrane have been extracted as 5.424.angs. 5.426.angs. and 2.3${\times}$10$^{4}$/cm for the average boron concentration of 1.3${\times}$10$^{20}$/cm$^{-23}$ cm$^{3}$/atom. Without any buffer layers, a disloction-free lightly boron-doped epitaxial layer with good crsytalline quality has been directly grown on the dislocation-free heavily boron-doped silicon layer. X-ray diffraction analysis revealed that the epitaxial silicon has good crystallinity, similar to that grown on lightly doped silicon substrate. The leakage current of the n+/p gated diode fabricated in the epitaxial silicon has been measured to be 0.6nA/cm$^{2}$ at the reverse bias of 5V.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.11 s.353
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• pp.48-57
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• 2006

This work describes a 12b 200KHz 0.52mA $0.47mm^2$ algorithmic ADC for sensor applications such as motor controls, 3-phase power controls, and CMOS image sensors simultaneously requiring ultra-low power and small size. The proposed ADC is based on the conventional algorithmic architecture with recycling techniques to optimize sampling rate, resolution, chip area, and power consumption. The input SHA with eight input channels for high integration employs a folded-cascode architecture to achieve a required DC gain and a sufficient phase margin. A signal insensitive 3-D fully symmetrical layout with critical signal lines shielded reduces the capacitor and device mismatch of the MDAC. The improved switched bias power-reduction techniques reduce the power consumption of analog amplifiers. Current and voltage references are integrated on the chip with optional off-chip voltage references for low glitch noise. The employed down-sampling clock signal selects the sampling rate of 200KS/s or 10KS/s with a reduced power depending on applications. The prototype ADC in a 0.18um n-well 1P6M CMOS technology demonstrates the measured DNL and INL within 0.76LSB and 2.47LSB. The ADC shows a maximum SNDR and SFDR of 55dB and 70dB at all sampling frequencies up to 200KS/s, respectively. The active die area is $0.47mm^2$ and the chip consumes 0.94mW at 200KS/s and 0.63mW at 10KS/s at a 1.8V supply.

• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.3
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• pp.46-55
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• 2016

This work proposes a 13b 100MS/s 45nm CMOS ADC with a high dynamic performance for IF-domain high-speed signal processing systems based on a four-step pipeline architecture to optimize operating specifications. The SHA employs a wideband high-speed sampling network properly to process high-frequency input signals exceeding a sampling frequency. The SHA and MDACs adopt a two-stage amplifier with a gain-boosting technique to obtain the required high DC gain and the wide signal-swing range, while the amplifier and bias circuits use the same unit-size devices repeatedly to minimize device mismatch. Furthermore, a separate analog power supply voltage for on-chip current and voltage references minimizes performance degradation caused by the undesired noise and interference from adjacent functional blocks during high-speed operation. The proposed ADC occupies an active die area of $0.70mm^2$, based on various process-insensitive layout techniques to minimize the physical process imperfection effects. The prototype ADC in a 45nm CMOS demonstrates a measured DNL and INL within 0.77LSB and 1.57LSB, with a maximum SNDR and SFDR of 64.2dB and 78.4dB at 100MS/s, respectively. The ADC is implemented with long-channel devices rather than minimum channel-length devices available in this CMOS technology to process a wide input range of $2.0V_{PP}$ for the required system and to obtain a high dynamic performance at IF-domain input signal bands. The ADC consumes 425.0mW with a single analog voltage of 2.5V and two digital voltages of 2.5V and 1.1V.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.622-629
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• 2022

The study aim was to derive a stem taper equation for Phyllostachys pubescens, a type of bamboo in South Korea, and to develop a stem volume table. To derive the stem taper equation, three stem taper models (Max & Burkhart, Kozak, and Lee) were used. Since bamboo stalks are hollow because of its woody characteristics, the outer and inner diameters of the tree were calculated, and connecting them enabled estimating the tree curves. The results of the three equations for estimating the outer and inner diameters led to selection of the Kozak model for determining the optimal stem taper because it had the highest fitness index and lowest error and bias. We used the Kozak model to estimate the diameter of Phyllostachys pubescens by stem height, which proved optimal, and drew the stem curve. After checking the residual degree in the stem taper equation, all residuals were distributed around "0", which proved the suitability of the equation. To calculate the stem volume of Phyllostachys pubescens, a rotating cube was created by rotating the stem curve with the outer diameter at 360°, and the volume was calculated by applying Smalian's method. The volume of Phyllostachys pubescens was calculated by deducting the inner diameter calculated volume from the outer diameter calculated volume. The volume of Phyllostachys pubescens was only 20~30% of the volume of Larix kaempferi, which is a general species. However, considering the current trees/ha of Phyllostachys pubescens and the amount of bamboo shoots generated every year, the individual tree volume was predicted to be small, but the volume/ha was not very different or perhaps more. The significance of this study is the stem taper equation and stem volume table for Phyllostachys pubescens developed for the first time in South Korea. The results are expected to be used as basic data for bamboo trading that is in increasing public and industrial demand and carbon absorption estimation.

• Journal of Service Research and Studies
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• v.13 no.3
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• pp.172-189
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• 2023

This study investigated the potential contribution of ChatGPT, a massive language and information model, in the decision-making process of public design policies, focusing on the characteristics inherent to public design. Public design utilizes the principles and approaches of design to address societal issues and aims to improve public services. In order to formulate public design policies and plans, it is essential to base them on extensive data, including the general status of the area, population demographics, infrastructure, resources, safety, existing policies, legal regulations, landscape, spatial conditions, current state of public design, and regional issues. Therefore, public design is a field of design research that encompasses a vast amount of data and language. Considering the rapid advancements in artificial intelligence technology and the significance of public design, this study aims to explore how massive language and information models like ChatGPT can contribute to public design policies. Alongside, we reviewed the concepts and principles of public design, its role in policy development and implementation, and examined the overview and features of ChatGPT, including its application cases and preceding research to determine its utility in the decision-making process of public design policies. The study found that ChatGPT could offer substantial language information during the formulation of public design policies and assist in decision-making. In particular, ChatGPT proved useful in providing various perspectives and swiftly supplying information necessary for policy decisions. Additionally, the trend of utilizing artificial intelligence in government policy development was confirmed through various studies. However, the usage of ChatGPT also unveiled ethical, legal, and personal privacy issues. Notably, ethical dilemmas were raised, along with issues related to bias and fairness. To practically apply ChatGPT in the decision-making process of public design policies, first, it is necessary to enhance the capacities of policy developers and public design experts to a certain extent. Second, it is advisable to create a provisional regulation named 'Ordinance on the Use of AI in Policy' to continuously refine the utilization until legal adjustments are made. Currently, implementing these two strategies is deemed necessary. Consequently, employing massive language and information models like ChatGPT in the public design field, which harbors a vast amount of language, holds substantial value.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.1-32
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• 2018

In addition to stakeholders including managers, employees, creditors, and investors of bankrupt companies, corporate defaults have a ripple effect on the local and national economy. Before the Asian financial crisis, the Korean government only analyzed SMEs and tried to improve the forecasting power of a default prediction model, rather than developing various corporate default models. As a result, even large corporations called 'chaebol enterprises' become bankrupt. Even after that, the analysis of past corporate defaults has been focused on specific variables, and when the government restructured immediately after the global financial crisis, they only focused on certain main variables such as 'debt ratio'. A multifaceted study of corporate default prediction models is essential to ensure diverse interests, to avoid situations like the 'Lehman Brothers Case' of the global financial crisis, to avoid total collapse in a single moment. The key variables used in corporate defaults vary over time. This is confirmed by Beaver (1967, 1968) and Altman's (1968) analysis that Deakins'(1972) study shows that the major factors affecting corporate failure have changed. In Grice's (2001) study, the importance of predictive variables was also found through Zmijewski's (1984) and Ohlson's (1980) models. However, the studies that have been carried out in the past use static models. Most of them do not consider the changes that occur in the course of time. Therefore, in order to construct consistent prediction models, it is necessary to compensate the time-dependent bias by means of a time series analysis algorithm reflecting dynamic change. Based on the global financial crisis, which has had a significant impact on Korea, this study is conducted using 10 years of annual corporate data from 2000 to 2009. Data are divided into training data, validation data, and test data respectively, and are divided into 7, 2, and 1 years respectively. In order to construct a consistent bankruptcy model in the flow of time change, we first train a time series deep learning algorithm model using the data before the financial crisis (2000~2006). The parameter tuning of the existing model and the deep learning time series algorithm is conducted with validation data including the financial crisis period (2007~2008). As a result, we construct a model that shows similar pattern to the results of the learning data and shows excellent prediction power. After that, each bankruptcy prediction model is restructured by integrating the learning data and validation data again (2000 ~ 2008), applying the optimal parameters as in the previous validation. Finally, each corporate default prediction model is evaluated and compared using test data (2009) based on the trained models over nine years. Then, the usefulness of the corporate default prediction model based on the deep learning time series algorithm is proved. In addition, by adding the Lasso regression analysis to the existing methods (multiple discriminant analysis, logit model) which select the variables, it is proved that the deep learning time series algorithm model based on the three bundles of variables is useful for robust corporate default prediction. The definition of bankruptcy used is the same as that of Lee (2015). Independent variables include financial information such as financial ratios used in previous studies. Multivariate discriminant analysis, logit model, and Lasso regression model are used to select the optimal variable group. The influence of the Multivariate discriminant analysis model proposed by Altman (1968), the Logit model proposed by Ohlson (1980), the non-time series machine learning algorithms, and the deep learning time series algorithms are compared. In the case of corporate data, there are limitations of 'nonlinear variables', 'multi-collinearity' of variables, and 'lack of data'. While the logit model is nonlinear, the Lasso regression model solves the multi-collinearity problem, and the deep learning time series algorithm using the variable data generation method complements the lack of data. Big Data Technology, a leading technology in the future, is moving from simple human analysis, to automated AI analysis, and finally towards future intertwined AI applications. Although the study of the corporate default prediction model using the time series algorithm is still in its early stages, deep learning algorithm is much faster than regression analysis at corporate default prediction modeling. Also, it is more effective on prediction power. Through the Fourth Industrial Revolution, the current government and other overseas governments are working hard to integrate the system in everyday life of their nation and society. Yet the field of deep learning time series research for the financial industry is still insufficient. This is an initial study on deep learning time series algorithm analysis of corporate defaults. Therefore it is hoped that it will be used as a comparative analysis data for non-specialists who start a study combining financial data and deep learning time series algorithm.

• Journal of Intelligence and Information Systems
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• v.19 no.3
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• pp.1-23
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• 2013

To discover significant social issues such as unemployment, economy crisis, social welfare etc. that are urgent issues to be solved in a modern society, in the existing approach, researchers usually collect opinions from professional experts and scholars through either online or offline surveys. However, such a method does not seem to be effective from time to time. As usual, due to the problem of expense, a large number of survey replies are seldom gathered. In some cases, it is also hard to find out professional persons dealing with specific social issues. Thus, the sample set is often small and may have some bias. Furthermore, regarding a social issue, several experts may make totally different conclusions because each expert has his subjective point of view and different background. In this case, it is considerably hard to figure out what current social issues are and which social issues are really important. To surmount the shortcomings of the current approach, in this paper, we develop a prototype system that semi-automatically detects social issue keywords representing social issues and problems from about 1.3 million news articles issued by about 10 major domestic presses in Korea from June 2009 until July 2012. Our proposed system consists of (1) collecting and extracting texts from the collected news articles, (2) identifying only news articles related to social issues, (3) analyzing the lexical items of Korean sentences, (4) finding a set of topics regarding social keywords over time based on probabilistic topic modeling, (5) matching relevant paragraphs to a given topic, and (6) visualizing social keywords for easy understanding. In particular, we propose a novel matching algorithm relying on generative models. The goal of our proposed matching algorithm is to best match paragraphs to each topic. Technically, using a topic model such as Latent Dirichlet Allocation (LDA), we can obtain a set of topics, each of which has relevant terms and their probability values. In our problem, given a set of text documents (e.g., news articles), LDA shows a set of topic clusters, and then each topic cluster is labeled by human annotators, where each topic label stands for a social keyword. For example, suppose there is a topic (e.g., Topic1 = {(unemployment, 0.4), (layoff, 0.3), (business, 0.3)}) and then a human annotator labels "Unemployment Problem" on Topic1. In this example, it is non-trivial to understand what happened to the unemployment problem in our society. In other words, taking a look at only social keywords, we have no idea of the detailed events occurring in our society. To tackle this matter, we develop the matching algorithm that computes the probability value of a paragraph given a topic, relying on (i) topic terms and (ii) their probability values. For instance, given a set of text documents, we segment each text document to paragraphs. In the meantime, using LDA, we can extract a set of topics from the text documents. Based on our matching process, each paragraph is assigned to a topic, indicating that the paragraph best matches the topic. Finally, each topic has several best matched paragraphs. Furthermore, assuming there are a topic (e.g., Unemployment Problem) and the best matched paragraph (e.g., Up to 300 workers lost their jobs in XXX company at Seoul). In this case, we can grasp the detailed information of the social keyword such as "300 workers", "unemployment", "XXX company", and "Seoul". In addition, our system visualizes social keywords over time. Therefore, through our matching process and keyword visualization, most researchers will be able to detect social issues easily and quickly. Through this prototype system, we have detected various social issues appearing in our society and also showed effectiveness of our proposed methods according to our experimental results. Note that you can also use our proof-of-concept system in http://dslab.snu.ac.kr/demo.html.

• Journal of Global Scholars of Marketing Science
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• v.17 no.4
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• pp.247-269
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• 2007

In recent years, one of the major reasons for the fierce competition amongst firms is that they strive to increase their own market shares and customer acquisition rate in the same market with similar and apparently undifferentiated products in terms of quality and perceived benefit. Because of this change in recent marketing environment, the differentiated after-sales service and diversified promotion strategies have become more important to gain competitive advantage. Price promotion is the favorite strategy that most retailers use to achieve short-term sales increase, induce consumer's brand switch, in troduce new product into market, and so forth. However, if marketers apply or copy an identical price promotion strategy without considering the characteristic differences in product and consumer preference, it will cause serious problems because discounted price itself could make people skeptical about product quality, and the changes of perceived value might appear differently depending on other factors such as consumer involvement or brand attitude. Previous studies showed that price promotion would certainly increase sales, and the discounted price compared to regular price would enhance the consumer's perceived values. On the other hand, discounted price itself could make people depreciate or skeptical about product quality, and reduce the consumers' positivity bias because consumers might be unsure whether the current price promotion is the retailer's best price offer. Moreover, we cannot say that discounted price absolutely enhances the consumer's perceived values regardless of product category and purchase situations. That is, the factors that affect consumers' value perceptions and buying behavior are so diverse in reality that the results of studies on the same dependent variable come out differently depending on what variable was used or how experiment conditions were designed. Majority of previous researches on the effect of price-comparison advertising have used consumers' buying behavior as dependent variable. In order to figure out consumers' buying behavior theoretically, analysis of value perceptions which influence buying intentions is needed. In addition, they did not combined the independent variables such as brand loyalty and price discount rate together. For this reason, this paper tried to examine the moderating effect of brand loyalty on relationship between the different levels of discounting rate and buyers' value perception. And we provided with theoretical and managerial implications that marketers need to consider such variables as product attributes, brand loyalty, and consumer involvement at the same time, and then establish a differentiated pricing strategy case by case in order to enhance consumer's perceived values properl. Three research concepts were used in our study and each concept based on past researches was defined. The perceived acquisition value in this study was defined as the perceived net gains associated with the products or services acquired. That is, the perceived acquisition value of the product will be positively influenced by the benefits buyers believe they are getting by acquiring and using the product, and negatively influenced by the money given up to acquire the product. And the perceived transaction value was defined as the perception of psychological satisfaction or pleasure obtained from taking advantage of the financial terms of the price deal. Lastly, the brand loyalty was defined as favorable attitude towards a purchased product. Thus, a consumer loyal to a brand has an emotional attachment to the brand or firm. Repeat purchasers continue to buy the same brand even though they do not have an emotional attachment to it. We assumed that if the degree of brand loyalty is high, the perceived acquisition value and the perceived transaction value will increase when higher discount rate is provided. But we found that there are no significant differences in values between two different discount rates as a result of empirical analysis. It means that price reduction did not affect consumer's brand choice significantly because the perceived sacrifice decreased only a little, and customers are satisfied with product's benefits when brand loyalty is high. From the result, we confirmed that consumers with high degree of brand loyalty to a specific product are less sensitive to price change. Thus, using price promotion strategy to merely expect sale increase is not recommendable. Instead of discounting price, marketers need to strengthen consumers' brand loyalty and maintain the skimming strategy. On the contrary, when the degree of brand loyalty is low, the perceived acquisition value and the perceived transaction value decreased significantly when higher discount rate is provided. Generally brands that are considered inferior might be able to draw attention away from the quality of the product by making consumers focus more on the sacrifice component of price. But considering the fact that consumers with low degree of brand loyalty are known to be unsatisfied with product's benefits and have relatively negative brand attitude, bigger price reduction offered in experiment condition of this paper made consumers depreciate product's quality and benefit more and more, and consumer's psychological perceived sacrifice increased while perceived values decreased accordingly. We infer that, in the case of inferior brand, a drastic price-cut or frequent price promotion may increase consumers' uncertainty about overall components of product. Therefore, it appears that reinforcing the augmented product such as after-sale service, delivery and giving credit which is one of the levels consisting of product would be more effective in reality. This will be better rather than competing with product that holds high brand loyalty by reducing sale price. Although this study tried to examine the moderating effect of brand loyalty on relationship between the different levels of discounting rate and buyers' value perception, there are several limitations. This study was conducted in controlled conditions where the high involvement product and two different levels of discount rate were applied. Given the presence of low involvement product, when both pieces of information are available, it is likely that the results we have reported here may have been different. Thus, this research results explain only the specific situation. Second, the sample selected in this study was university students in their twenties, so we cannot say that the results are firmly effective to all generations. Future research that manipulates the level of discount along with the consumer involvement might lead to a more robust understanding of the effects various discount rate. And, we used a cellular phone as a product stimulus, so it would be very interesting to analyze the result when the product stimulus is an intangible product such as service. It could be also valuable to analyze whether the change of perceived value affects consumers' final buying behavior positively or negatively.

• Journal of Preventive Medicine and Public Health
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• v.7 no.1
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• pp.29-94
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• 1974

Today most developed countries provide modern medical care for most of the population. The rural area is the more neglected area in the medical and health field. In public health, the philosophy is that medical care for in maintenance of health is a basic right of man; it should not be discriminated against racial, environmental or financial situations. The deficiency of the medical care system, cultural bias, economic development, and ignorance of the residents about health care brought about the shortage of medical personnel and facilities on the rural areas. Moreover, medical students and physicians have been taught less about rural health care than about urban health care. Medical care, therefore, is insufficient in terms of health care personnel/and facilities in rural areas. Under such a situation, there is growing concern about the health problems among the rural population. The findings presented in this report are useful measures of the major health problems and even more important, as a guide to planning for improved medical care systems. It is hoped that findings from this study will be useful to those responsible for improving the delivery of health service for the rural population. Objectives: -to determine the health status of the residents in the rural areas. -to assess the rural population's needs in terms of health and medical care. -to make recommendations concerning improvement in the delivery of health and medical care for the rural population. Procedures: For the sampling design, the ideal would be to sample according to the proportion of the composition age-groups. As the health problems would be different by group, the sample was divided into 10 different age-groups. If the sample were allocated by proportion of composition of each age group, some age groups would be too small to estimate the health problem. The sample size of each age-group population was 100 people/age-groups. Personal interviews were conducted by specially trained medical students. The interviews dealt at length with current health status, medical care problems, utilization of medical services, medical cost paid for medical care and attitudes toward health. In addition, more information was gained from the public health field, including environmental sanitation, maternal and child health, family planning, tuberculosis control, and dental health. The sample Sample size was one fourth of total population: 1,438 The aged 10-14 years showed the largest number of 254 and the aged under one year was the smallest number of 81. Participation in examination Examination sessions usually were held in the morning every Tuesday, Wenesday, and Thursday for 3 hours at each session at the Namchun Health station. In general, the rate of participation in medical examination was low especially in ages between 10-19 years old. The highest rate of participation among are groups was the under one year age-group by 100 percent. The lowest use rate as low as 3% of those in the age-groups 10-19 years who are attending junior and senior high school in Taegu city so the time was not convenient for them to recieve examinations. Among the over 20 years old group, the rate of participation of female was higher than that of males. The results are as follows: A. Publie health problems Population: The number of pre-school age group who required child health was 724, among them infants numbered 96. Number of eligible women aged 15-44 years was 1,279, and women with husband who need maternal health numbered 700. The age-group of 65 years or older was 201 needed more health care and 65 of them had disabilities. (Table 2). Environmental sanitation: Seventy-nine percent of the residents relied upon well water as a primary source of dringking water. Ninety-three percent of the drinking water supply was rated as unfited quality for drinking. More than 90% of latrines were unhygienic, in structure design and sanitation (Table 15). Maternal and child health: Maternal health Average number of pregnancies of eligible women was 4 times. There was almost no pre- and post-natal care. Pregnancy wastage Still births was 33 per 1,000 live births. Spontaneous abortion was 156 per 1,000 live births. Induced abortion was 137 per 1,000 live births. Delivery condition More than 90 percent of deliveries were conducted at home. Attendants at last delivery were laymen by 76% and delivery without attendants was 14%. The rate of non-sterilized scissors as an instrument used to cut the umbilical cord was as high as 54% and of sickles was 14%. The rate of difficult delivery counted for 3%. Maternal death rate estimates about 35 per 10,000 live births. Child health Consultation rate for child health was almost non existant. In general, vaccination rate of children was low; vaccination rates for children aged 0-5 years with BCG and small pox were 34 and 28 percent respectively. The rate of vaccination with DPT and Polio were 23 and 25% respectively but the rate of the complete three injections were as low as 5 and 3% respectively. The number of dead children was 280 per 1,000 living children. Infants death rate was 45 per 1,000 live births (Table 16), Family planning: Approval rate of married women for family planning was as high as 86%. The rate of experiences of contraception in the past was 51%. The current rate of contraception was 37%. Willingness to use contraception in the future was as high as 86% (Table 17). Tuberculosis control: Number of registration patients at the health center currently was 25. The number indicates one eighth of estimate number of tuberculosis in the area. Number of discharged cases in the past accounted for 79 which showed 50% of active cases when discharged time. Rate of complete treatment among reasons of discharge in the past as low as 28%. There needs to be a follow up observation of the discharged cases (Table 18). Dental problems: More than 50% of the total population have at least one or more dental problems. (Table 19) B. Medical care problems Incidence rate: 1. In one month Incidence rate of medical care problems during one month was 19.6 percent. Among these health problems which required rest at home were 11.8 percent. The estimated number of patients in the total population is 1,206. The health problems reported most frequently in interviews during one month are: GI trouble, respiratory disease, neuralgia, skin disease, and communicable disease-in that order, The rate of health problems by age groups was highest in the 1-4 age group and in the 60 years or over age group, the lowest rate was the 10-14 year age group. In general, 0-29 year age group except the 1-4 year age group was low incidence rate. After 30 years old the rate of health problems increases gradually with aging. Eighty-three percent of health problems that occured during one month were solved by primary medical care procedures. Seventeen percent of health problems needed secondary care. Days rested at home because of illness during one month were 0.7 days per interviewee and 8days per patient and it accounts for 2,161 days for the total productive population in the area. (Table 20) 2. In a year The incidence rate of medical care problems during a year was 74.8%, among them health problems which required rest at home was 37 percent. Estimated number of patients in the total population during a year was 4,600. The health problems that occured most frequently among the interviewees during a year were: Cold (30%), GI trouble (18), respiratory disease (11), anemia (10), diarrhea (10), neuralgia (10), parasite disease (9), ENT (7), skin (7), headache (7), trauma (4), communicable disease (3), and circulatory disease (3) -in that order. The rate of health problems by age groups was highest in the infants group, thereafter the rate decreased gradually until the age 15-19 year age group which showed the lowest, and then the rate increased gradually with aging. Eighty-seven percent of health problems during a year were solved by primary medical care. Thirteen percent of them needed secondary medical care procedures. Days rested at home because of illness during a year were 16 days per interviewee and 44 days per patient and it accounted for 57,335 days lost among productive age group in the area (Table 21). Among those given medical examination, the conditions observed most frequently were respiratory disease, GI trouble, parasite disease, neuralgia, skin disease, trauma, tuberculosis, anemia, chronic obstructive lung disease, eye disorders-in that order (Table 22). The main health problems required secondary medical care are as fellows: (previous page). Utilization of medical care (treatment) The rate of treatment by various medical facilities for all health problems during one month was 73 percent. The rate of receiving of medical care of those who have health problems which required rest at home was 52% while the rate of those who have health problems which did not required rest was 61 percent (Table 23). The rate of receiving of medical care for all health problems during a year was 67 percent. The rate of receiving of medical care of those who have health problems which required rest at home was 82 percent while the rate of those who have health problems which did not required rest was as low as 53 percent (Table 24). Types of medical facilitied used were as follows: Hospital and clinics: 32-35% Herb clinics: 9-10% Drugstore: 53-58% Hospitalization Rate of hospitalization was 1.7% and the estimate number of hospitalizations among the total population during a year will be 107 persons (Table 25). Medical cost: Average medical cost per person during one month and a year were 171 and 2,800 won respectively. Average medical cost per patient during one month and a year were 1,109 and 3,740 won respectively. Average cost per household during a year was 15,800 won (Table 26, 27). Solution measures for health and medical care problems in rural area: A. Health problems which could be solved by paramedical workers such as nurses, midwives and aid nurses etc. are as follows: 1. Improvement of environmental sanitation 2. MCH except medical care problems 3. Family planning except surgical intervention 4. Tuberculosis control except diagnosis and prescription 5. Dental care except operational intervention 6. Health education for residents for improvement of utilization of medical facilities and early diagnosis etc. B. Medical care problems 1. Eighty-five percent of health problems could be solved by primary care procedures by general practitioners. 2. Fifteen percent of health problems need secondary medical procedures by a specialist. C. Medical cost Concidering the economic situation in rural area the amount of 2,062 won per residents during a year will be burdensome, so financial assistance is needed gorvernment to solve health and medical care problems for rural people.