• Asia pacific journal of information systems
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• v.17 no.4
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• pp.187-206
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• 2007

The development of computer and information technology has been combined with the information superhighway internet infrastructure, so information widely spreads not only in special fields but also in the daily lives of people. Information ubiquity influences the traditional way of transaction, and leads a new E-commerce which distinguishes from the existing E-commerce. Not only goods as physical but also service as non-physical come into E-commerce. As the scale of E-Commerce is being enlarged as well. It keeps people from finding information they want. Recommender systems are now becoming the main tools for E-Commerce to mitigate the information overload. Recommender systems can be defined as systems for suggesting some Items(goods or service) considering customers' interests or tastes. They are being used by E-commerce web sites to suggest products to their customers who want to find something for them and to provide them with information to help them decide which to purchase. There are several approaches of recommending goods to customer in recommender system but in this study, the main subject is focused on collaborative filtering technique. This study presents a possibility of pre-evaluation for the prediction performance of customer's preference in collaborative filtering before the process of customer's preference prediction. Pre-evaluation for the prediction performance of each customer having low performance is classified by using the statistical features of ratings rated by each customer is conducted before the prediction process. In this study, MovieLens 100K dataset is used to analyze the accuracy of classification. The classification criteria are set by using the training sets divided 80% from the 100K dataset. In the process of classification, the customers are divided into two groups, classified group and non classified group. To compare the prediction performance of classified group and non classified group, the prediction process runs the 20% test set through the Neighborhood Based Collaborative Filtering Algorithm and Correspondence Mean Algorithm. The prediction errors from those prediction algorithm are allocated to each customer and compared with each user's error. Research hypothesis : Two research hypotheses are formulated in this study to test the accuracy of the classification criterion as follows. Hypothesis 1: The estimation accuracy of groups classified according to the standard deviation of each user's ratings has significant difference. To test the Hypothesis 1, the standard deviation is calculated for each user in training set which is divided 80% from MovieLens 100K dataset. Four groups are classified according to the quartile of the each user's standard deviations. It is compared to test the estimation errors of each group which results from test set are significantly different. Hypothesis 2: The estimation accuracy of groups that are classified according to the distribution of each user's ratings have significant differences. To test the Hypothesis 2, the distributions of each user's ratings are compared with the distribution of ratings of all customers in training set which is divided 80% from MovieLens 100K dataset. It assumes that the customers whose ratings' distribution are different from that of all customers would have low performance, so six types of different distributions are set to be compared. The test groups are classified into fit group or non-fit group according to the each type of different distribution assumed. The degrees in accordance with each type of distribution and each customer's distributions are tested by the test of ${\chi}^2$ goodness-of-fit and classified two groups for testing the difference of the mean of errors. Also, the degree of goodness-of-fit with the distribution of each user's ratings and the average distribution of the ratings in the training set are closely related to the prediction errors from those prediction algorithms. Through this study, the customers who have lower performance of prediction than the rest in the system are classified by those two criteria, which are set by statistical features of customers ratings in the training set, before the prediction process.

• Journal of the Korean Society of Radiology
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• v.7 no.2
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• pp.157-163
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• 2013

This study was to analyze quantitatively movement of planning target volume (PTV) and change of PTV volume through movement of diaphragm according to breathing phase. The purpose of present study was to investigate optimized respiration phase for radiation therapy of lung cancer. Simulated breathing training was performed in order to minimize systematic errors which is caused non-specific or irregular breathing. We performed 4-dimensional computed tomography (4DCTi) in accordance with each respiratory phase in the normalized respiratory gated radiation therapy procedures, then not only defined PTVi in 0 ~ 90%, 30 ~ 70% and 40 ~ 60% in the reconstructed 4DCTi images but analyzed quantitatively movement and changes of volume in PTVi. As a results, average respiratory cycle was $3.4{\pm}0.5$ seconds by simulated breathing training. R2-value which is expressed as concordance between clinically induced expected value and actual measured value, was almost 1. There was a statistically significant. And also movement of PTVi according to each respiration phase 0 ~ 90%, 30 ~ 70% and 40 ~ 60% were $13.4{\pm}6.4mm$, $6.1{\pm}2.9mm$ and $4.0{\pm}2.1mm$ respectively. Change of volume in PTVi of respiration phase 30 ~ 70% was decreased by $32.6{\pm}8.7%$ and 40 ~ 60% was decreased by $41.6{\pm}6.2%$. In conclusion, PTVi movement and volume change was reduced, when we apply a short breathing phase (40 ~ 60%: 30% duty cycle) range. Furthermore, PTVi margin considered respiration was not only within 4mm but able to get uniformity of dose.

• The Journal of Korean Society for Radiation Therapy
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• v.22 no.1
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• pp.11-18
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• 2010

Purpose: In every time radiation therapy set up errors occur because internal anatomical organs move due to breathing and change of patient's position. These errors may affect the change of dose distribution between target area and normal structure. This study investigates the usefulness of body-fix in clinical treatment. Materials and Methods: Among 55~60 aged male patients who has hepatocellular carcinoma in area of liver's couinaud classification, we chose 10 patients and divided two groups by using body-fix or not. When applying body-fix, we maintained a vacuum of 80 mbar pressure by using vacuum pump (Medical intelligence, Germany). Patients had free breathing with supine position. After working to fuse and consist MV-CT (megavoltage computed tomography) with KV-CT (kilovoltage computed tomography) obtained by 5 times treatments, we compared and analyzed set up errors occurred to (Right to Left, RL) of X axis, (Anterioposterio, AP) of Z axis, (Cranicoudal, CC) of Y axis. Results: Average Set up errors through image fusion showed that group A moved $0.3{\pm}1.1\;mm$ (Cranicoudal, CC), $-1.1{\pm}0.7\;mm$ (Right to Left, RL), $-0.2{\pm}0.7\;mm$ (Anterioposterio, AP) and group B moved $0.62{\pm}1.94\;mm$ (Cranicoudal, CC), $-3.62{\pm}1.5\;mm$ (Right to Left, RL), $-0.22{\pm}1.2\;mm$ (Anterioposterio, AP). Deviations of X, Y and Z axis directions by applying body-fix indicated that maximum X axis was 5.5 mm, Y axis was 19.8 mm and Z axis was 3.2 mm. In relation to analysis of error directions, consistency doesn't exist for every patient but by using body-fix showed that the result of stable aspect in spite of changes of everyday's patient position and breathing. Conclusion: Using body-fix for liver cancer patient is considered effectively for tomotherapy. Because deviations between group A and B exist but they were stable and regular.

• The Journal of Korean Society for Radiation Therapy
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• v.22 no.1
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• pp.33-39
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• 2010

Purpose: It is very important to confirm conformance of dose distribution that is formed with treatment planning from IMRS or IMRT. It has been a problem dropped accuracy and conformance when the field size is getting smaller because of character of the 2D ion chamber. Verification of MatriXX Phantom dose distribution with a change in the SAD. Dose distribution measurement and analysis to improve the accuracy and should be useful to evaluate the award. Materials and Methods: A use of Novalis linear accelerator 6 MV photon beams. In general, IMRS were 25 patients with small field size. The selected patients were divided into three groups on the basis of the field size. SAD was changed from 80 to 130 cm and field size to determine the dose distribution to the change, each dose was measured using MatriXX Phantom. Analysis of measured values obtained from the program for each patient through the treatment planning system comparison and analysis of the dose distribution and gamma values were expressed. Result: SAD 80, 100, and 120 cm in size in the gamma value to the investigation of patients less than $3\;cm^2$ average 0.939, 0.969, and 0.979, respectively. Patients with more than $5\;cm^2$ 0.962, 0.983, and 0.988, respectively. $5\;cm^2$ or more patients 0.982, 0.990, and 0.992, respectively. Conclusion: The error rate of less than $3\;cm^2$ field size is increased rapidly. If the field size is increased, resolution is increased by 2D ion chambers. It has been approved that it can be credible if it is around $3\;cm^2$ when measuring dose distribution using MatriXX. Adjusting geometric field size by changing SAD is likely to be very useful when you measure dose distribution using MatriXX.

• The Journal of Korean Society for Radiation Therapy
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• v.20 no.1
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• pp.17-23
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• 2008

Purpose: Cone-beam CT using linear accelerator attached to on-board imager is a image guided therapy equipment. Because it is to check the patient's set-up error, correction, organ and target movement. but imaging dose should be cause of the secondary cancer when taking a image. The aim of this study is investigation of appropriate cone beam CT scan mode to compare and estimate the image quality and skin dose. Materials and Methods: Measurement by Thermoluminescence dosimeter (TLD-100, Harshaw) with using the Rando phantom are placed on each eight sites in seperately H&N, thoracic, abdominal section. each 4 methods of scan modes of are measured the for skin dose in three time. Subsequently, obtained average value. Following image quality QA protocol of equipment manufacturers using the catphan 504 phantom, image quality of each scan mode is compared and analyzed. Results: The results of the measured skin dose are described in here. The skin dose of Head & Neck are measured mode A: 8.96 cGy, mode B: 4.59 cGy, mode C: 3.46 cGy mode D: 1.76 cGy and thoracic mode A: 9.42 cGy, mode B: 4.58 cGy, mode C: 3.65 cGy, mode D: 1.85 cGy, and abdominal mode A: 9.97 cGy, mode B: 5.12 cGy, mode C: 4.03 cGy, mode D: 2.21 cGy. Approximately, dose of mode B are reduced 50%, mode C are reduced 60%, mode D are reduced 80% a point of reference dose of mode A. the results of analyzed HU reproducibility, low contrast resolution, spatial resolution (high contrast resolution), HU uniformity in evaluation item of image quality are within the tolerance value by recommended equipment manufacturer in all scan mode. Conclusion: Maintaining the image quality as well as reducing the image dose are very important in cone beam CT. In the result of this study, we are considered when to take mode A when interested in soft tissue. And we are considered to take mode D when interested in bone scan and we are considered to take mode B, C when standard scan. Increasing secondary cancer risk due to cone beam CT scan should be reduced by low mAs technique.

• Analytical Science and Technology
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• v.31 no.2
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• pp.96-105
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• 2018

This study aimed to improve the method for detecting eight secondary aliphatic amines (SAAs), so as to measure their concentrations in fresh water and tap water samples. NaOH (8 mL, 10 M) and benzenesulfonyl chloride (2 mL) were added to a water sample (200 mL), and the mixture was stirred at $80^{\circ}C$ for 30 min. An additional NaOH solution (10 mL) was added and the stirring was continued for another 30 min. The pH of the cooled mixture was adjusted to 5.5-6.0 by adding HCl (35 %), and the SAAs were extracted using dichloromethane (50 mL). This extraction was repeated once. The extract was then washed with $NaHCO_3$ (15 mL, 0.05 M) and dried over $Na_2SO_4$ (4 g). The extract was finally concentrated to 0.1 mL, of which $1{\mu}L$ was analyzed for SAAs by GC-MS. The linearity of the spike calibration curves was high ($r^2=0.9969-0.9996$). The detection limits of the method ranged from 0.01 to $0.20{\mu}g/L$, and its repeatability and reproducibility (expressed as relative standard deviation) were both less than 10 % (6.6-9.4 %). Its accuracy (measured in percentage error) ranged between 2.4 % and 6.1 %. The established method was applied to the analysis of five surface water and 82 tap water samples. Dimethylamine was the only SAA detected in all the water samples, and its average concentration was $0.79{\mu}g/L$ (range: $0.20-2.54{\mu}g/L$). Therefore, this study improved the analytical method for SAAs in surface water and tap water, and the regional and seasonal concentration distributions were obtained.

• Journal of Korean Ophthalmic Optics Society
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• v.12 no.2
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• pp.1-12
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• 2007

Object of this research is to estimate the effect of myopia correction and safety on reverse geometry contact lens fitting in school children. This research include 53(106eyes) schoolchildren among 7 to 18 years who has low to moderate myopia(-1.00D~-5.00D) and prescribed reverse geometry contact lens for purpose on orthokeratology between January to July 2004 and had 3months full follow up examination. They were tested for slit lamp examinations, BUT(Break up time), direct ophthalmoscopy, retinoscopy, uncorrected visual acuity, best corrected visual acuity, autorefraction, autokeratometry and corneal topography in each examination(1day, 1week, 2weeks, 1, 2, and 3months) of before-and-after lens wearing to find out the effect of myopic correction and side effect. The results came out as follow. The average of uncorrected visual acuity was $0.0938{\pm}0.378$ before lens wear and $0.3136{\pm}0.283$ after 1day lens wear, and there was fast improvement after 1week($0.7925{\pm}0.301$) and little improvement after 2weeks period but still they shows better uncorrected visual acuity(p<0.01). The result of this study, the reverse geometry lens is very useful to correct refractive error and control the progression of myopia temporally among low to moderate myopic patient. The side effects were relatively rare but further study should be necessary with long term lens wear effect on eye health. For the lens prescription, the clinical fitting process had higher rate of success with consideration of eccentricity and corneal topography.

• Journal of Intelligence and Information Systems
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• v.18 no.4
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• pp.43-57
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• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.

• Journal of the Korean Wood Science and Technology
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• v.16 no.2
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• pp.69-78
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• 1988

For the modification of kiln drying schedule, rela ons between drying resistance R and moisture content or drying times were found 2.5cm-and 5.0cm-thick pitch pine (Pinus rigida Mill.) board and dimension lumber by the conventional kiln drying schedule until the average moisture content was 10%. The results of this study were as follows. 1. Drying resistance increased curvilinearly as moisture content decreased, and was higher for dimension lumber than for board at a given moisture content. The relationships between drying resistance and moisture content for the conventional kiln drying schedule and thickness of lumber were 1) $R_{2.5}=6.795\times10^3M^{-1.27^{**}}$ for 2.5cm-thick board by the conventional kiln drying schedule. 3) $R_{5.0}=5.206\times10^4M^{-1.55^{**}}$ for 5.0cm-thick dimension lumber by the conventional kiln drying schedule. 2. As drying time increased, moisture content decreased and drying resistance increased at the same time. Gradient of slope for dimension lumber was gentler than board. 3. The predicted drying times to 10% moisture content with the conventional kiln drying schedule were a little shorter than actual drying times with relatively small error. 4. It is necessary for the conventional kiln drying schedule to be modified to provide the desired final moisture content at minimum drying time with no significant degrade under severe drying conditions. 5. The kiln factors for 2.5cm-thick board and 5.0cm-thick dimension lumber with the conventional kiln drying schedule were 1.112, 1.136, respectively.

• Journal of the Korean Wood Science and Technology
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• v.44 no.3
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• pp.370-380
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• 2016

The black pine logs damaged by pine wilt disease in Jeju-do were heat-treated to extend the utilization of domestic trees damaged by pine wilt disease. The heat-treatment of wood requires wood to be heated to $56^{\circ}C$ for 30 min at the core. The average moisture content and top-diameter of the black pine logs were ranged from 46% to 141% and from 180 mm to 500 mm, respectively. And the basic specific gravity and oven-dry specific gravity of the black pine logs were 0.47 and 0.52, respectively. The time required for heat-treatment at $105^{\circ}C$ temperature was ranged from 7.7 h to 44.2 h, depending on moisture content and top-diameter. The temperature distribution was used to predict the time required for heat-treatment of black pine log with various moisture contents and top-diameters using finite difference method. The thermal properties of wood including the thermal conductivity and specific heat in accordance with moisture content were calculated. Heat transfer coefficient for mixed convection in form of adding natural convection and forced convection was used for heat transfer analysis. The error between the measured and predicted values ranged from 3% to 45%. The predicted times required for heat-treatment of black pine log with 50% moisture content and 200 mm, 300 mm, and 400 mm top-diameter were 10.9 h, 18.3 h, and 27.0 h, respectively. If the initial moisture content of black pine log is 75%, heat treatment times of 13.6 h, 22.5 h, and 32.8 h were predicted in accordance with top-diameter. And if the initial moisture content of black pine log is 100%, heat treatment times of 16.2 h, 26.5 h, and 38.2 h were predicted in accordance with top-diameter. When the physical properties of logs damaged by pine wilt disease are presented, these results can be applicable to the heat-treatment of red pine and Korean pine logs as well.