• Title/Summary/Keyword: Model Based

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Modeling of Sensorineural Hearing Loss for the Evaluation of Digital Hearing Aid Algorithms (디지털 보청기 알고리즘 평가를 위한 감음신경성 난청의 모델링)

  • 김동욱;박영철
    • Journal of Biomedical Engineering Research
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    • v.19 no.1
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    • pp.59-68
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    • 1998
  • Digital hearing aids offer many advantages over conventional analog hearing aids. With the advent of high speed digital signal processing chips, new digital techniques have been introduced to digital hearing aids. In addition, the evaluation of new ideas in hearing aids is necessarily accompanied by intensive subject-based clinical tests which requires much time and cost. In this paper, we present an objective method to evaluate and predict the performance of hearing aid systems without the help of such subject-based tests. In the hearing impairment simulation(HIS) algorithm, a sensorineural hearing impairment medel is established from auditory test data of the impaired subject being simulated. Also, the nonlinear behavior of the loudness recruitment is defined using hearing loss functions generated from the measurements. To transform the natural input sound into the impaired one, a frequency sampling filter is designed. The filter is continuously refreshed with the level-dependent frequency response function provided by the impairment model. To assess the performance, the HIS algorithm was implemented in real-time using a floating-point DSP. Signals processed with the real-time system were presented to normal subjects and their auditory data modified by the system was measured. The sensorineural hearing impairment was simulated and tested. The threshold of hearing and the speech discrimination tests exhibited the efficiency of the system in its use for the hearing impairment simulation. Using the HIS system we evaluated three typical hearing aid algorithms.

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A Study on the Factors Affecting the Global Performance in Chinese Small and Medium Sized Enterprises (중국 중소기업의 글로벌 성과에 미치는 영향요인에 관한 연구)

  • Li, Jun-Jian;Kim, Tae-In
    • International Commerce and Information Review
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    • v.14 no.3
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    • pp.3-30
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    • 2012
  • In the development process, small and medium-sized enterprises in China have shown their unique features and regularities which are closely related to China's national condition and economic characteristics. But in 2008, because of the global financial crisis which started in the USA, the rate of Chinese export and the rate of economic growth has evidently slowed. Due to shortage of funds, foreign orders fell, increase the value of RMB, lack of talented factors, Chinese SMEs are facing bankruptcy. In this context, the purpose of this study is to examine the effects of domestic and international market environment, the government assistance for entering overseas market, entrepreneur characteristics, etc. on the global performance. Based on these, a research model and some hypotheses were set up and tested by the multiple regression analysis with total 317 effective survey data. The results of this paper are as follows. First, a positive effect relation on the financial performance was shown for the companies with high domestic and international market environment in the aspect of market environment. According to such analysis result, it was found that the market environment in which SMEs belong to is a very important factor. Second, in the aspect of government export assistance related to overseas, market development showed a positive effect relation on the both financial and non-financial performance. However, the direct financial assistance showed a positive effect relation only on the non-financial performance. Overall, it was found that the government assistance program on entering overseas market is having significant effects on SMEs, but direct financial assistance have not achieved the desired results. Third, the innovative-ness and progressiveness of entrepreneur showed a positive effect relation on the global market performance. However, the risk-taking of entrepreneur only showed a negative effect relation on the non-financial performance. Overall, it was found that the entrepreneurship of SMEs is an important and influential factor. This is a result implying that the propensity of taking too much risk is not desirable based on the uncertainty of the global environment market. To sum up, this study confirmed that the market environment, the government assistance and entrepreneur characteristics, which are the major prerequisites of global performance, have effects on global performance.

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A Study on the Current Status of the Curriculum Operation of the Basic Medical Sciences in Nursing Education (간호학교육에서 기초의.과학 교과운영에 대한 연구)

  • 최명애;신기수
    • Journal of Korean Academy of Nursing
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    • v.27 no.4
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    • pp.975-987
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    • 1997
  • The purpose of this study was to investigate the current status of curriculum operation of the basic medical sciences in nursing education at college of nursing, department of nursing and junior college of nursing, ultimately to provide the basic data to improve a curriculum of basic medical science in nursing education. 78 professors who were in charge of basic medical science at 22 colleges of nursing and department of nursing, and 20 junior colleges of nursing responded the questionnaire consisted of 22 question items about the status of objectives, lectures, laboratory practice and characteristics of professors, and mailed to the author. The findings of this study were as follows : 1. The subjects of basic medical science were identified as physiology, anatomy, biochemistry, pathology, microbiology, pharmacology in the most colleges of nursing and junior colleges of nursing. 2 colleges of nursing and department of nursing(9.1%) and 19 junior colleges of nursing(95%) did not open biochemistry, 1 college of nursing and department of nursing(5%) did not open pathology and pharmacology. 2 Junior colleges of nursing(10%) did not open pharmacology, 1 junior college of nursing(5%) did not open pathology, the other 1 junior college of nursing did not open microbiology. 2. Credits of the subjects were ranged from 1 to 4. Lecture hours of one semester of physiology at school of nursing and junior college of nursing was average 103.6 and average 102.67, that of anatomy was average 127.1 and average 98, that of microbiology was average 109.7 and average 86.33, that of biochemistry was average 105, that of pathology was average 91 and average 94, that of pharmacology was average 86 and average 85.75. 3. Most of schools used 1 textbook for lectures, 3 school of nursing and department of nursing recommended references without using textbook, while all 36 junior colleges of nursing used textbooks. 4. 5 among 10 schools of nursing and department of nursing had a laboratory practice in physiology, 4 among 7 schools in anatomy, 4 among 6 schools in biochemistry, 2 among 6 schools in pathology 5 among 6 schools in microbiology. Not all the schools had a laboratory practice in pharmacology. 4 among 9 junior colleges of nursing had a laboratory practice in physiology. 1 among 4 schools in anatomy, 2 among 7 schools in microbiology. Not all the junior colleges of nursing had a laboratory practice in pathology and pharmacology. 11 among 20 colleges of nursing and department of nursing, 4 among 7 junior schools of nursing used a textbook of laboratory practice. 5. All the subjects at school of nursing and department of nursing responded that content of lectures and laboratory practices of basic medical science should be different from that of medical education, 34 junior schools of nursing responded that content of lecture of basic medical science in nursing education should be different from that of medical education. 33 junior schools of nursing responded that content of practice of basic medical science in nursing education should be different from that of medical education. 6. The final degree of 25 professors who were in charge of basic medical science were doctors of. medicine, that of 5 professors were masters of medicine, that of 5 were doctor of pharmacology, that of 2 were a master of pharmacology, that of 1 was physical science. The final degree of 8 professors who were in charge of basic medical science were masters of medicine, 7 doctors of medicine, 4 masters of nursing science, 4 masters of pharmacology, 2 doctors of nursing, 2 doctors of physical science, 2 doctors of pharmacology and 1 master of public health. 9 full professors, 13 associate professors, 11 assist ant professors, 3 full time instructors, and 6 part time instructors were in charge of basic medical science at college of nursing and department of nursing, 20 part time instructors, 8 associate professors, 6 assistant professors, and 2 full professors were in charge of has basic medical science at junior college of nursing. Based on these results, curriculum of basic medical science in nursing education should be reviewed deeply based on nursing model.

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Sensitivity Experiment of Surface Reflectance to Error-inducing Variables Based on the GEMS Satellite Observations (GEMS 위성관측에 기반한 지면반사도 산출 시에 오차 유발 변수에 대한 민감도 실험)

  • Shin, Hee-Woo;Yoo, Jung-Moon
    • Journal of the Korean earth science society
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    • v.39 no.1
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    • pp.53-66
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    • 2018
  • The information of surface reflectance ($R_{sfc}$) is important for the heat balance and the environmental/climate monitoring. The $R_{sfc}$ sensitivity to error-induced variables for the Geostationary Environment Monitoring Spectrometer (GEMS) retrieval from geostationary-orbit satellite observations at 300-500 nm was investigated, utilizing polar-orbit satellite data of the MODerate resolution Imaging Spectroradiometer (MODIS) and Ozone Mapping Instrument (OMI), and the radiative transfer model (RTM) experiment. The variables in this study can be cloud, Rayleigh-scattering, aerosol, ozone and surface type. The cloud detection in high-resolution MODIS pixels ($1km{\times}1km$) was compared with that in GEMS-scale pixels ($8km{\times}7km$). The GEMS detection was consistent (~79%) with the MODIS result. However, the detection probability in partially-cloudy (${\leq}40%$) GEMS pixels decreased due to other effects (i.e., aerosol and surface type). The Rayleigh-scattering effect in RGB images was noticeable over ocean, based on the RTM calculation. The reflectance at top of atmosphere ($R_{toa}$) increased with aerosol amounts in case of $R_{sfc}$<0.2, but decreased in $R_{sfc}{\geq}0.2$. The $R_{sfc}$ errors due to the aerosol increased with wavelength in the UV, but were constant or slightly decreased in the visible. The ozone absorption was most sensitive at 328 nm in the UV region (328-354 nm). The $R_{sfc}$ error was +0.1 because of negative total ozone anomaly (-100 DU) under the condition of $R_{sfc}=0.15$. This study can be useful to estimate $R_{sfc}$ uncertainties in the GEMS retrieval.

A Comparison of the Characteristics of Maritally Violent Men in a Community Sample and Batterers in the Criminal Justice System (지역사회의 폭력남편과 가정폭력범죄 행위자들의 특성 비교)

  • Chang, Hee-Suk
    • Korean Journal of Social Welfare
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    • v.58 no.4
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    • pp.141-168
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    • 2006
  • The present study explored and compared the risk factors of two subtypes of maritally violent men with those of a nonviolent comparison group. One type of batterers consisted of a community sample, and the other was sought from the criminal justice system. The identities of the male community batterers were not exposed to the society since their victims did not contact any of the social service agents related to domestic violence. To identify the different characteristics associated with two subtypes of woman abusers, a total of 152 nonviolent men, 82 male community batterers, and 336 offenders in a criminal justice system were considered. The results of the descriptive analysis showed that the level of physical violence of the community batterers was two times lower than that of the batterers who received legal punishments. The results of the multinominal logistic regression were as follows: (1) The variables that distinguished the male community batterers from the nonviolent men were the use of physical violence towards children, marital decision power, and income. (2) Four factors had been found to distinguish batterers in the criminal justice system from nonbatterers, namely: attitudes towards woman battering, education, violence towards children, and level of jealousy. (3) The community batterers showed a higher level of education and of stress as well as a longer period of marital relationship compared to the batterers in the criminal justice system. On the other hand, the batterers who received legal punishments had more severe alcohol problems and had an accepting attitude towards the use of violence. This study also investigated psychopathology among batterers using MCMI-III, based on 333 subjects. In terms of the mean scores, there were no subscales associated with personality pathology in all the male groups. Based on the logit model, the community batterers showed a stronger tendency towards having a passive-aggressive personality than did their counterparts, and they recorded a higher level of narcissism compared to the court-referred battering men. Post-traumatic stress was the only symptom that distinguished the batterers who received legal punishments from the other groups. The theoretical and practical implications of these results were pointed out and discussed in the paper.

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Mental health and nutritional intake according to sleep duration in adolescents - Based on the 2007-2016 Korea National Health and Nutrition Examination Survey - (청소년들의 수면시간에 따른 정신건강 및 영양섭취 상태 - 국민건강영양조사(2007-2016년)자료를 이용하여 -)

  • Ki, Ye Jin;Kim, Yookyung;Shin, Woo-Kyoung
    • Journal of Korean Home Economics Education Association
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    • v.30 no.4
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    • pp.1-14
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    • 2018
  • The purpose of this study was to examine the relevance of mental health and nutritional intake according to the sleep duration of Korean adolescents. This study was based on data from the 2007-2016 Korea National Health and Nutrition Examination Survey(KNHNES), including 5,489 total subjects (2,795 middle school students, 2,694 high school students). The association between sleep duration and mental health was analyzed using a logistic regression analysis, and the link between sleep duration and nutritional intake was analyzed via a generalized linear model. An analysis of sleep duration showed that middle school students had a higher average sleep duration than high school students (P<0.0001). An analysis of the relationship between sleep duration and mental health showed that middle school students had lower rates of stress perception (P<0.0001) and suicidal ideation (P=0.0005) as their sleep duration increased. High school students had 53% less suicidal ideation in the group getting 6-7 hours compared to the group getting less than 6 hours, and 37% less suicidal ideation than the group getting 7-8 hours. The link between sleep duration and stress perception was statistically significant among both middle and high school students (P for interaction=0.02). An analysis of the daily intake of major nutrients according to sleep hours found high intake of vitamin C in groups where high school students slept more than nine hours (P=0.003). The state of nutritional intake according to higher sleep duration showed statistically significant differences between higher intake of phosphorus, riboflavin, niacin, and vitamin C in Nutrient Adequacy Ratio for high school students. In conclusion, adolescents' sleep duration is associated with stress perception, suicidal ideation and nutritional intake. Therefore, this study emphasizes the mental importance of adolescent sleep and can be used as a basis for nutrition education.

Estimation of Growing Stock and Carbon Stock based on Components of Forest Type Map: The case of Kangwon Province (임상도 특성에 따른 임목축적 및 탄소저장량 추정: 강원도를 중심으로)

  • Kim, So Won;Son, Yeong Mo;Kim, Eun Sook;Park, Hyun
    • Journal of Korean Society of Forest Science
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    • v.103 no.3
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    • pp.446-452
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    • 2014
  • This research aimed to provide a method to estimate growing stock and carbon stock using the characteristics of forest type map such as the age-class, DBH class and crown density class. We transformed the growing stock data of national forest inventory (mainly Kangwon-do province) onto those of time when the forest type map was established. We developed a simulation model for the growing stock using the transformed data and the characteristics of forest type map by the quantification method I. By comparing partial correlation coefficient, we found that quantification of growing stock was largely affected by age-class followed by crown density class, forest type and DBH class. The growing stock, was estimated as minimum in the broadleaved forest with age-class II, DBH class 'Small', and crown density class 'Low' as $20.0m^3/ha$, whereas showed maximum value in the coniferous forest with age-class VI, DBH class 'Large', and crown density class 'High' as $305.0m^3/ha$. The growing stock for coniferous, broadleaved, and mixed forest were estimated as $30.5{\sim}305.0m^3/ha$, $20.0{\sim}200.4m^3/ha$, and $23.8{\sim}238.1m^3/ha$, respectively. When we compared the carbon stock by forest type, the carbon stock by age class based on growing stock was maximum when DBH class was 'Large' and crown density class was 'High' regardless of forest type. This estimation of growing stock by using characteristic of forest type can be used to estimate the changes in growing stock and carbon stock resulting from deforestation or natural disaster. In addition, we hope it provide a useful advice when forest officials and policy makers have to make decisions in regard to forest management.

The Analysis on the Relationship between Firms' Exposures to SNS and Stock Prices in Korea (기업의 SNS 노출과 주식 수익률간의 관계 분석)

  • Kim, Taehwan;Jung, Woo-Jin;Lee, Sang-Yong Tom
    • Asia pacific journal of information systems
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    • v.24 no.2
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    • pp.233-253
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    • 2014
  • Can the stock market really be predicted? Stock market prediction has attracted much attention from many fields including business, economics, statistics, and mathematics. Early research on stock market prediction was based on random walk theory (RWT) and the efficient market hypothesis (EMH). According to the EMH, stock market are largely driven by new information rather than present and past prices. Since it is unpredictable, stock market will follow a random walk. Even though these theories, Schumaker [2010] asserted that people keep trying to predict the stock market by using artificial intelligence, statistical estimates, and mathematical models. Mathematical approaches include Percolation Methods, Log-Periodic Oscillations and Wavelet Transforms to model future prices. Examples of artificial intelligence approaches that deals with optimization and machine learning are Genetic Algorithms, Support Vector Machines (SVM) and Neural Networks. Statistical approaches typically predicts the future by using past stock market data. Recently, financial engineers have started to predict the stock prices movement pattern by using the SNS data. SNS is the place where peoples opinions and ideas are freely flow and affect others' beliefs on certain things. Through word-of-mouth in SNS, people share product usage experiences, subjective feelings, and commonly accompanying sentiment or mood with others. An increasing number of empirical analyses of sentiment and mood are based on textual collections of public user generated data on the web. The Opinion mining is one domain of the data mining fields extracting public opinions exposed in SNS by utilizing data mining. There have been many studies on the issues of opinion mining from Web sources such as product reviews, forum posts and blogs. In relation to this literatures, we are trying to understand the effects of SNS exposures of firms on stock prices in Korea. Similarly to Bollen et al. [2011], we empirically analyze the impact of SNS exposures on stock return rates. We use Social Metrics by Daum Soft, an SNS big data analysis company in Korea. Social Metrics provides trends and public opinions in Twitter and blogs by using natural language process and analysis tools. It collects the sentences circulated in the Twitter in real time, and breaks down these sentences into the word units and then extracts keywords. In this study, we classify firms' exposures in SNS into two groups: positive and negative. To test the correlation and causation relationship between SNS exposures and stock price returns, we first collect 252 firms' stock prices and KRX100 index in the Korea Stock Exchange (KRX) from May 25, 2012 to September 1, 2012. We also gather the public attitudes (positive, negative) about these firms from Social Metrics over the same period of time. We conduct regression analysis between stock prices and the number of SNS exposures. Having checked the correlation between the two variables, we perform Granger causality test to see the causation direction between the two variables. The research result is that the number of total SNS exposures is positively related with stock market returns. The number of positive mentions of has also positive relationship with stock market returns. Contrarily, the number of negative mentions has negative relationship with stock market returns, but this relationship is statistically not significant. This means that the impact of positive mentions is statistically bigger than the impact of negative mentions. We also investigate whether the impacts are moderated by industry type and firm's size. We find that the SNS exposures impacts are bigger for IT firms than for non-IT firms, and bigger for small sized firms than for large sized firms. The results of Granger causality test shows change of stock price return is caused by SNS exposures, while the causation of the other way round is not significant. Therefore the correlation relationship between SNS exposures and stock prices has uni-direction causality. The more a firm is exposed in SNS, the more is the stock price likely to increase, while stock price changes may not cause more SNS mentions.

Study on the Optimum Range of Weight-Age Data for Estimation of Growth Curve Parameters of Hanwoo (한우의 체중 성장곡선 모수 추정을 위한 체중 측정 자료의 최적 범위에 관한 연구)

  • Cho, Y.M.;Yoon, H.B.;Park, B.H.;Ahn, B.S.;Jeon, B.S.;Park, Y.I.
    • Journal of Animal Science and Technology
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    • v.44 no.2
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    • pp.165-170
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    • 2002
  • Mature weight (A) and rate of maturing (k) estimated by nonlinear regression were studied to determine the optimum age range over which the estimate of growth curve parameters can be estimated. The weight-age data from 1,133 Hanwoo bulls at Hanwoo Improvement Center of N.A.C.F. were used to fit the growth curve using Gompertz model. All available weight data from birth to the specific age of months were used for the estimation of parameters: the six specific ages used were 12, 14, 16, 18, 20 22 and 24 months of age. The mean estimates of mature weight (A) were 966.5, 1,255.9, 1,126.2, 916.5, 842.2, 780.9 and 767.0kg for ages 12 through 24 months, respectively. The mean estimates of mature weight (A) to 22 and 24 months of age were not different from each other. However, they were different from the estimates based on the data to other ages. Mean estimates of rate of maturing (k) were 3.362, 3.595, 3.536, 3.421, 3.403, 3.409 and 3.411 for ages 12 through 24 months, respectively. The mean estimates of maturing rate (k) for ages 18 through 24 months of age were not significantly different from each other. However, they were different from the estimates based on the data to other ages. Correlations among estimates of A at various ages showed the highest value of 0.93 between 22 and 24 months. Correlations among estimates of k at various ages were highest ranging from 0.91 to 0.99 among 18 to 24 months. The correlations between A and k were positive and tended to decrease with the increase of the age from 0.84 for the age of 12 months to 0.10 for the age of 24 months. Thus, the estimates of growth curve parameters, A and k, suitable for genetic studies can be derived from accumulated Hanwoo bulls after 22 months of age.

Development of Traffic Volume Estimation System in Main and Branch Roads to Estimate Greenhouse Gas Emissions in Road Transportation Category (도로수송부문 온실가스 배출량 산정을 위한 간선 및 지선도로상의 교통량 추정시스템 개발)

  • Kim, Ki-Dong;Lee, Tae-Jung;Jung, Won-Seok;Kim, Dong-Sool
    • Journal of Korean Society for Atmospheric Environment
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    • v.28 no.3
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    • pp.233-248
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    • 2012
  • The national emission from energy sector accounted for 84.7% of all domestic emissions in 2007. Of the energy-use emissions, the emission from mobile source as one of key categories accounted for 19.4% and further the road transport emission occupied the most dominant portion in the category. The road transport emissions can be estimated on the basis of either the fuel consumed (Tier 1) or the distance travelled by the vehicle types and road types (higher Tiers). The latter approach must be suitable for simultaneously estimating $CO_2$, $CH_4$, and $N_2O$ emissions in local administrative districts. The objective of this study was to estimate 31 municipal GHG emissions from road transportation in Gyeonggi Province, Korea. In 2008, the municipalities were consisted of 2,014 towns expressed as Dong and Ri, the smallest administrative district unit. Since mobile sources are moving across other city and province borders, the emission estimated by fuel sold is in fact impossible to ensure consistency between neighbouring cities and provinces. On the other hand, the emission estimated by distance travelled is also impossible to acquire key activity data such as traffic volume, vehicle type and model, and road type in small towns. To solve the problem, we applied a hierarchical cluster analysis to separate town-by-town road patterns (clusters) based on a priori activity information including traffic volume, population, area, and branch road length obtained from small 151 towns. After identifying 10 road patterns, a rule building expert system was developed by visual basic application (VBA) to assort various unknown road patterns into one of 10 known patterns. The expert system was self-verified with original reference information and then objects in each homogeneous pattern were used to regress traffic volume based on the variables of population, area, and branch road length. The program was then applied to assign all the unknown towns into a known pattern and to automatically estimate traffic volumes by regression equations for each town. Further VKT (vehicle kilometer travelled) for each vehicle type in each town was calculated to be mapped by GIS (geological information system) and road transport emission on the corresponding road section was estimated by multiplying emission factors for each vehicle type. Finally all emissions from local branch roads in Gyeonggi Province could be estimated by summing up emissions from 1,902 towns where road information was registered. As a result of the study, the GHG average emission rate by the branch road transport was 6,101 kilotons of $CO_2$ equivalent per year (kt-$CO_2$ Eq/yr) and the total emissions from both main and branch roads was 24,152 kt-$CO_2$ Eq/yr in Gyeonggi Province. The ratio of branch roads emission to the total was 0.28 in 2008.