• Korean Journal of Agricultural Science
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• v.4 no.2
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• pp.344-390
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• 1977

The purpose of this paper was to schedule optimum cutting strategy which could maximize the total yield under certain restrictions on periodic timber removals and harvest areas from an industrial forest, based on a linear programming technique. Sensitivity of the regulation model to variations in restrictions has also been analyzed to get information on the changes of total yield in the planning period. The regulation procedure has been made on the experimental forest of the Agricultural College of Seoul National University. The forest is composed of 219 cutting units, and characterized by younger age group which is very common in Korea. The planning period is devided into 10 cutting periods of five years each, and cutting is permissible only on the stands of age groups 5-9. It is also assumed in the study that the subsequent forests are established immediately after cutting existing forests, non-stocked forest lands are planted in first cutting period, and established forests are fully stocked until next harvest. All feasible cutting regimes have been defined to each unit depending on their age groups. Total yield (Vi, k) of each regime expected in the planning period has been projected using stand yield tables and forest inventory data, and the regime which gives highest Vi, k has been selected as a optimum cutting regime. After calculating periodic yields and cutting areas, and total yield from the optimum regimes selected without any restrictions, the upper and lower limits of periodic yields(Vj-max, Vj-min) and those of periodic cutting areas (Aj-max, Aj-min) have been decided. The optimum regimes under such restrictions have been selected by linear programming. The results of the study may be summarized as follows:- 1. The fluctuations of periodic harvest yields and areas under cutting regimes selected without restrictions were very great, because of irregular composition of age classes and growing stocks of existing stands. About 68.8 percent of total yield is expected in period 10, while none of yield in periods 6 and 7. 2. After inspection of the above solution, restricted optimum cutting regimes were obtained under the restrictions of Amin=150 ha, Amax=400ha, $Vmin=5,000m^3$ and $Vmax=50,000m^3$, using LP regulation model. As a result, about $50,000m^3$ of stable harvest yield per period and a relatively balanced age group distribution is expected from period 5. In this case, the loss in total yield was about 29 percent of that of unrestricted regimes. 3. Thinning schedule could be easily treated by the model presented in the study, and the thinnings made it possible to select optimum regimes which might be effective for smoothing the wood flows, not to speak of increasing total yield in the planning period. 4. It was known that the stronger the restrictions becomes in the optimum solution the earlier the period comes in which balanced harvest yields and age group distribution can be formed. There was also a tendency in this particular case that the periodic yields were strongly affected by constraints, and the fluctuations of harvest areas depended upon the amount of periodic yields. 5. Because the total yield was decreased at the increasing rate with imposing stronger restrictions, the Joss would be very great where strict sustained yield and normal age group distribution are required in the earlier periods. 6. Total yield under the same restrictions in a period was increased by lowering the felling age and extending the range of cutting age groups. Therefore, it seemed to be advantageous for producing maximum timber yield to adopt wider range of cutting age groups with the lower limit at which the smallest utilization size of timber could be produced. 7. The LP regulation model presented in the study seemed to be useful in the Korean situation from the following point of view: (1) The model can provide forest managers with the solution of where, when, and how much to cut in order to best fulfill the owners objective. (2) Planning is visualized as a continuous process where new strateges are automatically evolved as changes in the forest environment are recognized. (3) The cost (measured as decrease in total yield) of imposing restrictions can be easily evaluated. (4) Thinning schedule can be treated without difficulty. (5) The model can be applied to irregular forests. (6) Traditional regulation methods can be rainforced by the model.

• Tuberculosis and Respiratory Diseases
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• v.42 no.3
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• pp.277-294
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• 1995

Background: The prevalence of tuberculosis in Korea decreased remarkably for the past 30 years, while the incidence of disease caused by mycobacteria other than tuberculosis is unknown. Korean Academy of Tuberculosis and Respiratory Diseases performed national survey to estimate the incidence of mycobacterial diseases other than tuberculosis in Korea. We analyzed the clinical data of confirmed cases for the practice of primary care physicians and pulmonary specialists. Methods: The period of study was from January 1981 to October 1994. We collected the data retrospectively by correspondence with physicians in the hospitals that referred the specimens to Korean Institute of Tuberculosis, The Korean National Tuberculosis Association for the detection of mycobacteria other than tuberculosis. In confirmed cases, we obtained the records for clinical, laboratory and radiological findings in detail using protocols. Results: 1) Mycobacterial diseases other than tuberculosis were confirmed that 1 case was in 1981, 2 cases in 1982, 4 cases in 1983, 2 cases in 1984, 5 cases in 1985, 1 case in 1986, 3 cases in 1987, 1 case in 1988, 6 cases in 1989, 9 cases in 1990, 14 cases in 1990, 10 cases in 1992, 4 cases in 1993, and 96 cases in 1994. Cases since 1990 were 133 cases(84.2%) of a total. 2) Fifty seven percent of patients were in the age group of over 60 years. The ratio of male to female patients was 2.6:1. 3) The distribution of hospitals in Korea showed that 61 cases(38.6%) were referred from Double Cross Clinic, 42 cases(26.6%) from health centers, 21 cases(13.3%) from tertiary referral hospitals, 15 cases(9.5%) from secondary referral hospitals, and 10 cases(6.3%) from primary care hospitals. The area distribution in Korea revealed that 98 cases(62%) were in Seoul, 17 cases(10.8%) in Gyeongsangbuk-do, 12 cases(7.6%) in Kyongki-do, 8 cases(5.1%) in Chungchongnam-do, each 5 cases(3.2%) in Gyeongsangnam-do and Chungchongbuk-do, 6 cases(3.8%) in other areas. 4) In the species of isolated mycobacteria other than tuberculosis, M. avium-intracellulare was found in 104 cases(65.2%), M. fortuitum in 20 cases(12.7%), M. chelonae in 15 cases(9.5%), M. gordonae in 7 cases(4.4%), M. terrae in 5 cases(3.2%), M. scrofulaceum in 3 cases(1.9%), M. kansasii and M. szulgai in each 2 cases(1.3%), and M. avium-intracellulare coexisting with M. terrae in 1 case(0.6%). 5) In pre-existing pulmonary diseases, pulmonary tuberculosis was 113 cases(71.5%), bronchiectasis 6 cases(3.8%), chronic bronchitis 10 cases(6.3%), and pulmonary fibrosis 6 cases(3.8%). The timing of diagnosis as having pulmonary tuberculosis was within 1 year in 7 cases(6.2%), 2~5 years ago in 32 cases(28.3%), 6~10 years ago in 29 cases(25.7%), 11~15 years ago in 16 cases(14.2%), 16~20 years ago in 15 cases (13.3%), and 20 years ago in 14 cases(12.4%). Duration of anti-tuberculous treatment was within 3 months in 6 cases(5.3%), 4~6 months in 17 cases(15%), 7~9 months in 16 cases(14.2%), 10~12 months in 11 cases(9.7%), 1~2 years in 21 cases(18.6%), and over 2 years in 8 cases(7.1%). The results of treatment were cure in 44 cases(27.9%) and failure in 25 cases(15.8%). 6) Associated extra-pulmonary diseases were chronic liver disease coexisting with chronic renal failure in 1 case(0.6%), diabetes mellitus in 9 cases(5.7%), cardiovascular diseases in 2 cases(1.3%), long-term therapy with steroid in 2 cases(1.3%) and chronic liver disease, chronic renal failure, colitis and pneumoconiosis in each 1 case(0.6%). 7) The clinical presentations of mycobacterial diseases other than tuberculosis were 86 cases (54.4%) of chronic pulmonary infections, 1 case(0.6%) of cervical or other site lymphadenitis, 3 cases(1.9%) of endobronchial tuberculosis, and 1 case(0.6%) of intestinal tuberculosis. 8) The symptoms of patients were cough(62%), sputum(61.4%), dyspnea(30.4%), hemoptysis or blood-tinged sputum(20.9%), weight loss(13.3%), fever(6.3%), and others(4.4%). 9) Smear negative with culture negative cases were 24 cases(15.2%) in first examination, 27 cases(17.1%) in second one, 22 cases(13.9%) in third one, and 17 cases(10.8%) in fourth one. Smear negative with culture positive cases were 59 cases(37.3%) in first examination, 36 cases (22.8%) in second one, 24 cases(15.2%) in third one, and 23 cases(14.6%) in fourth one. Smear positive with culture negative cases were 1 case(0.6%) in first examination, 4 cases(2.5%) in second one, 1 case (0.6%) in third one, and 2 cases(1.3%) in fourth one. Smear positive with culture positive cases were 48 cases(30.4%) in first examination, 34 cases(21.5%) in second one, 34 cases(21.5%) in third one, and 22 cases(13.9%) in fourth one. 10) The specimens isolated mycobacteria other than tuberculosis were sputum in 143 cases (90.5%), sputum and bronchial washing in 4 cases(2.5%), bronchial washing in 1 case(0.6%). 11) Drug resistance against all species of mycobacteria other than tuberculosis were that INH was 62%, EMB 55.7%, RMP 52.5%, PZA 34.8%, OFX 29.1%, SM 36.7%, KM 27.2%, TUM 24.1%, CS 23.4%, TH 34.2%, and PAS 44.9%. Drug resistance against M. avium-intracellulare were that INH was 62.5%, EMB 59.6%, RMP 51.9%, PZA 29.8%, OFX 33.7%, SM 30.8%, KM 20.2%, TUM 17.3%, CS 14.4%, TH 31.7%, and PAS 38.5%. Drug resistance against M. chelonae were that INH was 66.7%, EMB 66.7%, RMP 66.7%, PZA 40%, OFX 26.7%, SM 66.7%, KM 53.3%, TUM 53.3%, CS 60%, TH 53.3%, and PAS 66.7%. Drug resistance against M. fortuitum were that INH was 65%, EMB 55%, RMP 65%, PZA 50%, OFX 25%, SM 55%, KM 45%, TUM 55%, CS 65%, TH 45%, and PAS 60%. 12) The activities of disease on chest roentgenogram showed that no active disease was 7 cases(4.4%), mild 20 cases(12.7%), moderate 67 cases(42.4%), and severe 47 cases(29.8%). Cavities were found in 43 cases(27.2%) and pleurisy in 18 cases(11.4%). 13) Treatment of mycobacterial diseases other than tuberculosis was done in 129 cases(81.7%). In cases treated with the first line anti-tuberculous drugs, combination chemotherapy including INH and RMP was done in 86 cases(66.7%), INH or RMP in 30 cases(23.3%), and not including INH and RMP in 9 cases(7%). In 65 cases treated with the second line anti-tuberculous drugs, combination chemotherapy including below 2 drugs were in 2 cases(3.1%), 3 drugs in 15 cases(23.1%), 4 drugs in 20 cases(30.8%), 5 drugs in 9 cases(13.8%), and over 6 drugs in 19 cases (29.2%). The results of treatment were improvement in 36 cases(27.9%), no interval changes in 65 cases(50.4%), aggravation in 4 cases(3.1%), and death in 4 cases(3.1%). In improved 36 cases, 34 cases(94.4%) attained negative conversion of mycobacteria other than tuberculosis on cultures. The timing in attaining negative conversion on cultures was within 1 month in 2 cases(1.3%), within 3 months in 11 cases(7%), within 6 months in 14 eases(8.9%), within 1 year in 2 cases(1.3%) and over 1 year in 1 case(0.6%). Conclusion: Clinical, laboratory and radiological findings of mycobacterial diseases other than tuberculosis were summarized. This collected datas will assist in the more detection of mycobacterial diseases other than tuberculosis in Korea in near future.

• Journal of Intelligence and Information Systems
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• v.23 no.2
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• pp.107-122
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• 2017

Volatility in the stock market returns is a measure of investment risk. It plays a central role in portfolio optimization, asset pricing and risk management as well as most theoretical financial models. Engle(1982) presented a pioneering paper on the stock market volatility that explains the time-variant characteristics embedded in the stock market return volatility. His model, Autoregressive Conditional Heteroscedasticity (ARCH), was generalized by Bollerslev(1986) as GARCH models. Empirical studies have shown that GARCH models describes well the fat-tailed return distributions and volatility clustering phenomenon appearing in stock prices. The parameters of the GARCH models are generally estimated by the maximum likelihood estimation (MLE) based on the standard normal density. But, since 1987 Black Monday, the stock market prices have become very complex and shown a lot of noisy terms. Recent studies start to apply artificial intelligent approach in estimating the GARCH parameters as a substitute for the MLE. The paper presents SVR-based GARCH process and compares with MLE-based GARCH process to estimate the parameters of GARCH models which are known to well forecast stock market volatility. Kernel functions used in SVR estimation process are linear, polynomial and radial. We analyzed the suggested models with KOSPI 200 Index. This index is constituted by 200 blue chip stocks listed in the Korea Exchange. We sampled KOSPI 200 daily closing values from 2010 to 2015. Sample observations are 1487 days. We used 1187 days to train the suggested GARCH models and the remaining 300 days were used as testing data. First, symmetric and asymmetric GARCH models are estimated by MLE. We forecasted KOSPI 200 Index return volatility and the statistical metric MSE shows better results for the asymmetric GARCH models such as E-GARCH or GJR-GARCH. This is consistent with the documented non-normal return distribution characteristics with fat-tail and leptokurtosis. Compared with MLE estimation process, SVR-based GARCH models outperform the MLE methodology in KOSPI 200 Index return volatility forecasting. Polynomial kernel function shows exceptionally lower forecasting accuracy. We suggested Intelligent Volatility Trading System (IVTS) that utilizes the forecasted volatility results. IVTS entry rules are as follows. If forecasted tomorrow volatility will increase then buy volatility today. If forecasted tomorrow volatility will decrease then sell volatility today. If forecasted volatility direction does not change we hold the existing buy or sell positions. IVTS is assumed to buy and sell historical volatility values. This is somewhat unreal because we cannot trade historical volatility values themselves. But our simulation results are meaningful since the Korea Exchange introduced volatility futures contract that traders can trade since November 2014. The trading systems with SVR-based GARCH models show higher returns than MLE-based GARCH in the testing period. And trading profitable percentages of MLE-based GARCH IVTS models range from 47.5% to 50.0%, trading profitable percentages of SVR-based GARCH IVTS models range from 51.8% to 59.7%. MLE-based symmetric S-GARCH shows +150.2% return and SVR-based symmetric S-GARCH shows +526.4% return. MLE-based asymmetric E-GARCH shows -72% return and SVR-based asymmetric E-GARCH shows +245.6% return. MLE-based asymmetric GJR-GARCH shows -98.7% return and SVR-based asymmetric GJR-GARCH shows +126.3% return. Linear kernel function shows higher trading returns than radial kernel function. Best performance of SVR-based IVTS is +526.4% and that of MLE-based IVTS is +150.2%. SVR-based GARCH IVTS shows higher trading frequency. This study has some limitations. Our models are solely based on SVR. Other artificial intelligence models are needed to search for better performance. We do not consider costs incurred in the trading process including brokerage commissions and slippage costs. IVTS trading performance is unreal since we use historical volatility values as trading objects. The exact forecasting of stock market volatility is essential in the real trading as well as asset pricing models. Further studies on other machine learning-based GARCH models can give better information for the stock market investors.