• Proceedings of the Korean Society of Medical Physics Conference
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• 2002.09a
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• pp.119-120
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• 2002

The aim is to urge the need of elaborate commissioning of 3D RTP system from the firsthand experience. A 3D RTP system requires so much data such as beam data and patient data. Most data of radiation beam are directly transferred from a 3D dose scanning system, and some other data are input by editing. In the process inputting parameters and/or data, no error should occur. For RTP system using algorithm-bas ed-on beam-modeling, careless beam-data processing could also cause the treatment error. Beam data of 3 different qualities of photon from two linear accelerators, patient data and calculated results were commissioned. For PDD, the doses by Clarkson, convolution, superposition and fast superposition methods at 10 cm for 10${\times}$10 cm field, 100 cm SSD were compared with the measured. An error in the SCD for one quality was input by the service engineer. Whole SCD defined by a physicist is SAD plus d$\sub$max/, the value was just SAD. That resulted in increase of MU by 100${\times}$((1_d$\sub$max//SAD)$^2$-1)%. For 10${\times}$10 cm open field, 1 m SSD and at 10 cm depth in uniform medium of relative electron density (RED) 1, PDDs for 4 algorithms of dose calculation, Clarkson, convolution, superposition and fast-superposition, were compared with the measured. The calculated PDD were similar to the measured. For 10${\times}$10 cm open field, 1 m SSD and at 10 cm depth with 5 cm thick inhomogeneity of RED 0.2 under 2 cm thick RED 1 medium, PDDs for 4 algorithms were compared. PDDs ranged from 72.2% to 77.0% for 4 MV X-ray and from 90.9% to 95.6% for 6 MV X-ray. PDDs were of maximum for convolution and of minimum for superposition. For 15${\times}$15 cm symmetric wedged field, wedge factor was not constant for calculation mode, even though same geometry. The reason is that their wedge factor is considering beam hardness and ray path. Their definition requires their users to change the concept of wedge factor. RTP user should elaborately review beam data and calculation algorithm in commissioning.

• Journal of The Korea Institute of Healthcare Architecture
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• v.22 no.4
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• pp.47-55
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• 2016

Purpose: Growth and change are the most important things in planning of hospital architecture. It is especially necessary for countless changes taken place since the hospital opens to be adapted to the planning of hospital architecture phase. The space depth in the hospital serves a very crucial role in accepting these changes. The purpose of this study is to provide basic data necessary to space depth planning to prepare for change through analyzing space depth's change in hospital architecture chronologically. Methods:: The method of this study is analyzing space depth's change in cases of 19 hospitals in total, from the 1980's, which is the quantitative growth period, until recently. Especially this study is analyzing Max & Min space depth focusing change of medical environment. Based on this, this study suggests an form of space depth and optimum range of space depth response to growth and change of hospital architecture. Results: The conclusions of this study are as follows. Considering these conclusion, double linear system is most appropriate for space depth for hospital architecture planning focused on system. Optimal range of space depth is at least 21.6m or more in case of clinic room and from 27 meter to 37meter in case of examination & treatment room. Implications: Space of Depth is a key element determining system for hospital architecture planning focused on system. The results of this paper can be data for planning system of hospital architecture which copes with the change.

• Journal of Advanced Marine Engineering and Technology
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• v.39 no.5
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• pp.563-569
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• 2015

A chemical reaction occurring in CSTR (Continuous Stirred Tank Reactor) is significantly affected by the concentration, temperature, pressure, and reacting time of materials, and thus it has strong nonlinear and time-varying characteristics. Also, when an existing linear PID controller with fixed gain is used, the performance could deteriorate or could be unstable if the system parameters change due to the change in the operating point of CSTR. In this study, a technique for the design of a fuzzy PD plus I controller was proposed for the temperature control of a CSTR process. In the fuzzy PD plus I controller, a linear integral controller was added to a fuzzy PD controller in parallel, and the steady-state performance could be improved based on this. For the fuzzy membership function, a Gaussian type was used; for the fuzzy inference, the Max-Min method of Mamdani was used; and for the defuzzification, the center of gravity method was used. In addition, the saturation state of the actuator was also considered during controller design. The validity of the proposed method was examined by comparing the set-point tracking performance and the robustness to the parameter change with those of an adaptive controller and a nonlinear proportional-integral-differential controller.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.64-71
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• 2015

In this paper, we present a multi-period 0-1 knapsack problem which has the cardinality constraints. Theoretically, the presented problem can be regarded as an extension of the multi-period 0-1 knapsack problem. In the multi-period 0-1 knapsack problem, there are n jobs to be performed during m periods. Each job has the execution time and its completion gives profit. All the n jobs are partitioned into m periods, and the jobs belong to i-th period may be performed not later than in the i-th period, i = 1, ${\cdots}$, m. The total production time for periods from 1 to i is given by $b_i$ for each i = 1, ${\cdots}$, m, and the objective is to maximize the total profit. In the extended problem, we can select a specified number of jobs from each of periods associated with the corresponding cardinality constraints. As the extended problem is NP-hard, the branch and bound method is preferable to solve it, and therefore it is important to have efficient procedures for solving its linear programming relaxed problem. So we intensively explore the LP relaxed problem and suggest a polynomial time algorithm. We first decompose the LP relaxed problem into m subproblems associated with each cardinality constraints. Then we identify some new properties based on the parametric analysis. Finally by exploiting the special structure of the LP relaxed problem, we develop an efficient algorithm for the LP relaxed problem. The developed algorithm has a worst case computational complexity of order max[$O(n^2logn)$, $O(mn^2)$] where m is the number of periods and n is the total number of jobs. We illustrate a numerical example.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.13
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• pp.5259-5264
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• 2014

Background: CT based brachytherapy allows 3-dimensional (3D) assessment of organs at risk (OAR) doses with dose volume histograms (DVHs). The purpose of this study was to compare computed tomography (CT) based volumetric calculations and International Commission on Radiation Units and Measurements (ICRU) reference-point estimates of radiation doses to the bladder and rectum in patients with carcinoma of the cervix treated with high-dose-rate (HDR) intracavitary brachytherapy (ICBT). Materials and Methods: Between March 2011 and May 2012, 20 patients were treated with 55 fractions of brachytherapy using tandem and ovoids and underwent post-implant CT scans. The external beam radiotherapy (EBRT) dose was 48.6Gy in 27 fractions. HDR brachytherapy was delivered to a dose of 21 Gy in three fractions. The ICRU bladder and rectum point doses along with 4 additional rectal points were recorded. The maximum dose ($D_{Max}$) to rectum was the highest recorded dose at one of these five points. Using the HDRplus 2.6 brachyhtherapy treatment planning system, the bladder and rectum were retrospectively contoured on the 55 CT datasets. The DVHs for rectum and bladder were calculated and the minimum doses to the highest irradiated 2cc area of rectum and bladder were recorded ($D_{2cc}$) for all individual fractions. The mean $D_{2cc}$ of rectum was compared to the means of ICRU rectal point and rectal $D_{Max}$ using the Student's t-test. The mean $D_{2cc}$ of bladder was compared with the mean ICRU bladder point using the same statistical test. The total dose, combining EBRT and HDR brachytherapy, were biologically normalized to the conventional 2 Gy/fraction using the linear-quadratic model. (${\alpha}/{\beta}$ value of 10 Gy for target, 3 Gy for organs at risk). Results: The total prescribed dose was $77.5Gy{\alpha}/{\beta}10$. The mean dose to the rectum was $4.58{\pm}1.22Gy$ for $D_{2cc}$, $3.76{\pm}0.65Gy$ at $D_{ICRU}$ and $4.75{\pm}1.01Gy$ at $D_{Max}$. The mean rectal $D_{2cc}$ dose differed significantly from the mean dose calculated at the ICRU reference point (p<0.005); the mean difference was 0.82 Gy (0.48-1.19Gy). The mean EQD2 was $68.52{\pm}7.24Gy_{{\alpha}/{\beta}3}$ for $D_{2cc}$, $61.71{\pm}2.77Gy_{{\alpha}/{\beta}3}$ at $D_{ICRU}$ and $69.24{\pm}6.02Gy_{{\alpha}/{\beta}3}$ at $D_{Max}$. The mean ratio of $D_{2cc}$ rectum to $D_{ICRU}$ rectum was 1.25 and the mean ratio of $D_{2cc}$ rectum to $D_{Max}$ rectum was 0.98 for all individual fractions. The mean dose to the bladder was $6.00{\pm}1.90Gy$ for $D_{2cc}$ and $5.10{\pm}2.03Gy$ at $D_{ICRU}$. However, the mean $D_{2cc}$ dose did not differ significantly from the mean dose calculated at the ICRU reference point (p=0.307); the mean difference was 0.90 Gy (0.49-1.25Gy). The mean EQD2 was $81.85{\pm}13.03Gy_{{\alpha}/{\beta}3}$ for $D_{2cc}$ and $74.11{\pm}19.39Gy_{{\alpha}/{\beta}3}$ at $D_{ICRU}$. The mean ratio of $D_{2cc}$ bladder to $D_{ICRU}$ bladder was 1.24. In the majority of applications, the maximum dose point was not the ICRU point. On average, the rectum received 77% and bladder received 92% of the prescribed dose. Conclusions: OARs doses assessed by DVH criteria were higher than ICRU point doses. Our data suggest that the estimated dose to the ICRU bladder point may be a reasonable surrogate for the $D_{2cc}$ and rectal $D_{Max}$ for $D_{2cc}$. However, the dose to the ICRU rectal point does not appear to be a reasonable surrogate for the $D_{2cc}$.

• Journal of the Korean Society for Railway
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• v.19 no.2
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• pp.204-212
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• 2016

The soils used as trackbed in Korea are selected using USCS utilizing basic soil properties such as Grain Size Distribution(GSD), % passing of #200 sieve ($P_{200}$), % passing of #4 sieve ($P_4$), Coefficient of uniformity ($C_u$), and Coefficient of curvature ($C_c$). Degree of compaction of the soils adapted in the code by KR should be evaluated by maximum dry density (${\gamma}_{d-max}$) and deformation modulus $E_{v2}$. The most important influencing factor that is critical to stability and deformation of the compacted soils used as trackbed is stiffness. Thus, it is necessary to construct a correlation between the modulus and the basic soil properties of trackbed soil in order to redefine a new soil classification system adaptable only to railway construction. To construct the relationship, basic soil test data is collected as a database, including GSD, maximum dry unit weight (${\gamma}_{d-max}$), OMC, $P_{200}$, $P_4$, $C_u$, $C_c$, etc.; deformation modulus $E_{v2}$ and $E_{vd}$ are obtained independently by performing a Repeated Plated Bearing Test (RPBT) and Light Weight Deflectometer Test (LWDT) for ten different railway construction sites. A linear regression analysis is performed using SPSS to obtain the relationship between the basic soil properties and the deformation modulus $E_{v2}$ and $E_v$. Based on the constructed relationship and the various obtained mechanical test data, a new soil classification system will be proposed later as a guideline for the design and construction of trackbed foundation in Korea.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.199-208
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• 2023

Taguchi method is one of the most popular approaches for design optimization such that performance characteristics become robust to uncontrollable noise variables. However, most previous Taguchi method applications have addressed a single-characteristic problem. Problems with multiple characteristics are more common in practice. The multi-criteria decision making(MCDM) problem is to select the optimal one among multiple alternatives by integrating a number of criteria that may conflict with each other. Representative MCDM methods include TOPSIS(Technique for Order of Preference by Similarity to Ideal Solution), GRA(Grey Relational Analysis), PCA(Principal Component Analysis), fuzzy logic system, and so on. Therefore, numerous approaches have been conducted to deal with the multi-characteristic design problem by combining original Taguchi method and MCDM methods. In the MCDM problem, multiple criteria generally have different measurement units, which means that there may be a large difference in the physical value of the criteria and ultimately makes it difficult to integrate the measurements for the criteria. Therefore, the normalization technique is usually utilized to convert different units of criteria into one identical unit. There are four normalization techniques commonly used in MCDM problems, including vector normalization, linear scale transformation(max-min, max, or sum). However, the normalization techniques have several shortcomings and do not adequately incorporate the practical matters. For example, if certain alternative has maximum value of data for certain criterion, this alternative is considered as the solution in original process. However, if the maximum value of data does not satisfy the required degree of fulfillment of designer or customer, the alternative may not be considered as the solution. To solve this problem, this paper employs the desirability function that has been proposed in our previous research. The desirability function uses upper limit and lower limit in normalization process. The threshold points for establishing upper or lower limits let us know what degree of fulfillment of designer or customer is. This paper proposes a new design optimization technique for multi-characteristic design problem by integrating the Taguchi method and our desirability functions. Finally, the proposed technique is able to obtain the optimal solution that is robust to multi-characteristic performances.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.329-339
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• 2021

Soybeans (Glycine max), one of major upland crops, require precise management of environmental conditions, such as temperature, water, and soil, during cultivation since they are sensitive to environmental changes. Application of spectral technologies that measure the physiological state of crops remotely has great potential for improving quality and productivity of the soybean by estimating yields, physiological stresses, and diseases. In this study, we developed and validated a soybean growth prediction model using multispectral imagery. We conducted a linear regression analysis between vegetation indices and soybean growth data (fresh weight and LAI) obtained at Miryang fields. The linear regression model was validated at Goesan fields. It was found that the model based on green ratio vegetation index (GRVI) had the greatest performance in prediction of fresh weight at the calibration stage (R²=0.74, RMSE=246 g/m², RE=34.2%). In the validation stage, RMSE and RE of the model were 392 g/m² and 32%, respectively. The errors of the model differed by cropping system, For example, RMSE and RE of model in single crop fields were 315 g/m² and 26%, respectively. On the other hand, the model had greater values of RMSE (381 g/m²) and RE (31%) in double crop fields. As a result of developing models for predicting a fresh weight into two years (2018+2020) with similar accumulated temperature (AT) in three years and a single year (2019) that was different from that AT, the prediction performance of a single year model was better than a two years model. Consequently, compared with those models divided by AT and a three years model, RMSE of a single crop fields were improved by about 29.1%. However, those of double crop fields decreased by about 19.6%. When environmental factors are used along with, spectral data, the reliability of soybean growth prediction can be achieved various environmental conditions.

• The Journal of the Korea Contents Association
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• v.11 no.4
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• pp.74-82
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• 2011

To do fuzzy modelling of a nonlinear process needs to analyze the characteristics of input-output of fuzzy inference systems according to the division of entire input spaces and the fuzzy reasoning methods. For this, fuzzy model is expressed by identifying the structure and parameters of the system by means of input variables, fuzzy partition of input spaces, and consequence polynomial functions. In the premise part of the fuzzy rules Min-Max method using the minimum and maximum values of input data set and C-Means clustering algorithm forming input data into the clusters are used for identification of fuzzy model and membership functions are used as a series of triangular, gaussian-like, trapezoid-type membership functions. In the consequence part of the fuzzy rules fuzzy reasoning is conducted by two types of inferences such as simplified and linear inference. The identification of the consequence parameters, namely polynomial coefficients, of each rule are carried out by the standard least square method. And lastly, using gas furnace process which is widely used in nonlinear process we evaluate the performance and the system characteristics.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.61 no.2
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• pp.104-112
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• 2016

A double-cropping system with soybean (Glycine max) following the cultivation of potato, garlic, and onion is widely adopted in the southern region of Korea. For this system, marginal dates for planting must be determined for profitable soybean yields, because the decision to plant soybean as a second crop is occasionally delayed by harvest of the first crop and weather conditions. In order to investigate the effect of planting date on soybean yield, three cultivars (early and late maturity) were planted on seven different dates from May 1 to July 30 in both paddy and upland fields across 2012 and 2013. Soybean yields were significantly different among the planting dates and the cultivars; however, the interaction between cultivar and planting date was not significant. Based on linear regression, the maximum yield of soybean was reached with a June 10 planting date, with a sharp decline in yield for crops planted after this date. The results of this study were consistent with those of a previous one that recommends early and mid-June as the optimum planting period. Regardless of soybean ecotype, a reduction in yield of greater than 20% occurred when soybean was planted after mid-July. Frost during soybean growth can reduce yields, and the late maturity cultivars planted on July 30 were damaged by frost before completing maturation and harvest; however, early maturity cultivars were safely harvested. For sufficient time to develop and reach profitable yields, the planting of soybean before mid-July is recommended.