• Radiation Oncology Journal
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• v.14 no.1
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• pp.77-85
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• 1996

Purpose : Multileaf collimator(MLC) is very suitable tool for conformal radio-therapy and commissioning measurements for a multileaf collimator installed on a dual energy accelerator with 6 and 10MV photons are required, For modeling the collimator with treament planning software, detailed dosimetric characterization of the multileaf collimator including the penumbra width, leaf transmission between leaf leakage and localization of the leaf ends and sides is an essential requirement. materials and Methods : Measurement of characteristic data of the MLC with 26 pair block leaves installed on CLINAC 2100C linear accelerator was performed. Low sensitive radiographic film(X-omatV) was used for the penumbra measurement and separate experiments using radiographic film and thermoluminescent dosimeters were performed to verify the dose distribution, Measured films were analized with a photodensitometer of WP700i scanner. Results : For 6 & 10 MV x-ray energies, approximately $2.0\%$ of photons incident on the multileaf collimator were transmitted and an additional $0.5\%$ leakage occurs between the leaves. Localizing the physical end of the leaves showed less than 1mm deviation from the $50\%$ decrement line and this difference is attributed to the curved shaped end on the leaves One side of a sin히e leaf corresponded to the $50\%$ decrement line, but the opposite face was aligned with a lower value. This difference is due to the tongue and groove used to decrease between leaf leakage. Alignment of the leaves to form a straight edge resulted larger penumbra at far position from isocenter as compare with divergent alloy blocks. When the MLC edge is stepped by sloping field, the isodose lines follow the leaf pattern and Produce scalloping isodose curves in tissue. The effective penumbra by 45 degree stepped MLC is about 10mm at 10cm depth for 6MV x-ray. The difference of effective penumbra in deep tissue between MLC and divergent alloy blocks is small (5mm). Conclusion : Using the characteristic data of MLC, the MLC has the clinlical acceptability and suitability for 3-D conformal radiotherapy except small field size.

• Korea journal of population studies
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• v.14 no.1
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• pp.55-69
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• 1991

The objective of the study is to figure out the status of reproductive health and general characteristics related to maternal health for Korean-Americans living in Los Angeles. We collected data from the married women who wanted no more additional child birth and were attending the Family Planning Clinic of Koryo Health Foundation in Los Angeles during 1988. There were 494 women met the eligibility requirement for this study. The results are summarized below. 1. In the age distribution of the women who desired no more additional child birth, women 30-34 age group constituted the largest proportion at 36.6 percent ; the mean age of women was 35.1915.55. The mean number of child birth was 1.77, and the proportion of the women by number of child birth were 35.2 percent for one children, 50.1 percent for two children 10.5 percent for three children, and 2.6 percent for four children. All of the women experienced pregnancy at least once, and mean number of pregnancy was 3.42. The mean number of total experience of induced abortion was 1.56. and 76.7 percent of these women had experience with induced abortions. To prevent further pregnancies, 90.1 percent of the women were utilizing the contraceptive methods, and the highest proportion by the contraceptive methods was condoms(53.7%), 9.3 percent in spermicides, 8.7 percent in IUDs, 8.7 percent in rhythm method, and 6.9 percent in oral pills. 2. The mean age of women at each stage of reproductive life cycle were 14.74 years at time of menarche, 24.55 years at time of marriage, 26.60 years at time of the first child birth, and 28.75 years at time of the last child birth. In age distribution of the women by birth cohort (Group I : birth cohort 1940-1954, Group H : birth cohort 1955-1970), the mean menar-cheal age of the women was 14.96 years in group I , and 14.53 years in group H . Mean age at time of marriage was 25.01 years in group I and 24.08 years in group H . Mean child birth age of the women by birth cohort was 27.19 years In group I and 26.01 years in Group II for the first child birth and 30.07 years in group I and 27.45 years in group II for the last child birth. The total length of reproductive life cycle from menarche to menopause (presumed to be at 49 of age years) was 34.26 years. The len-gth of phase I (from menarche to marriage) was 9.81 years, while phase H (marriage to first birth) was 2.05 years, and phase Ill (first birth to last birth) was 2. 15 years, and the last phase of reproductive life cycle, phase IV (last birth to menopause) was 20.25 years. The proportion of each phase 10 total length of reproductive life cycle was 28.6 percent, 6.0 percent 6.3 percent, and 59.t percent respectively. In the tendency of each phase in reproductive life cycle by birth cohort (group I , U ), the length of phase I, II , III of birth cohort group II was diminished in comparison with those of birth cohort group I , but the length of phase IV was extended by 2.38 years. 3. Among the women, the mean number of total pregnancy by birth cohort group was 2.01 in group I and 1.10 in Group II, and mean number of child birth was 1.97 in group I and 1.58 in group II. In terms of pregnancy was-tage rate by birth cohort group, among the total pregnancy of birth cohort group I , 51.8 percent of the cases resulted in induced abortions or spontaneous abortions whils 48.2 percent resulted in live births, and 42.2 percent or total pregnancy in group II resulted in pregnancy wastage and 57.8 percent of the cases resulted in live births.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1107-1118
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• 2021

Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.