• The Journal of Korean Society for Radiation Therapy
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• v.16 no.2
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• pp.81-89
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• 2004

Introduction : The setup error due to the patient and the staff from radiation treatment as the reason which is important the treatment record could be decided is a possibility of effect. The SET-UP ERROR of the patient analyzes the effect of dose distribution and DVH from radiation treatment of the patient. Material & Methode : This test uses human phantom and when C-T scan doing, It rotated the Left direction of the human phantom and it made SET-UP ERROR , Standard plan and 3mm, 5mm, 7mm, 10mm, 15mm, 20mm with to distinguish, it made the C-T scan error. With the result, The SET-UP ERROR got each C-T image Using RTP equipment It used the plan which is used generally from clinical - Box plan, 3Dimension plan( identical angle 5beam plan) Also, ( CTV+1cm margin, CTV+0.5cm margin, CTV+0.3,cm margin = PTV) it distinguished the standard plan and each set-up error plan and The plan used a dose distribution and the DVH and it analyzed Result : The Box4 the plan and 3Dimension plan which it bites it got similar an dose distribution and DVH in 3mm, 5mm From rotation error and Rectilinear movement( $0\%{\sim}2\%$ ). Rotation error and rectilinear error 7mm, 10mm, 15mm, 20mm appeared effect it will go mad to a enough change in treatment ( $2\%{\sim}^11\%$ ) Conclusion : The diminishes the effect of the SET-UP ERROR must reduce move with tension of the patient Also, we are important accessory development and the supply that it reducing of reproducibility and the move

• The Journal of Korean Society for Radiation Therapy
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• v.29 no.1
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• pp.57-68
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• 2017

Purpose: The purpose of this study was to compare volumetric modulated arc therapy(VMAT) with fixed-field intensity modulated radiation therapy(IMRT) using non-coplanar beam when the shape of target is irregular and the location is adjacent to organ at risk(OAR). Materials and Methods: The subjects of this study were a total of 6 patients who had radiation therapy for whole scalp(2 patients), partial scalp(2 patients), and whole ventricle(2 patients) by True Beam STX(Varian Medical Systems, USA). VMAT plans consisted of coplanar or non-coplanar arcs which can minimize the volume of OAR included in beamlets. All fixed-field IMRT plans consisted of non-coplanar beams using more than 2 angles of Couch. Results: The VMAT and IMRT plans were compared with regard to the maximum dose of both lens, both optic nerves, optic chiasm, and brain stem and the mean dose of both eyeballs and hippocampus. VMAT plans showed higher dose than ncIMRT plans at more than 6 of all OARs in every patient, and the ratio was from 1.1 times to 8.2 times. In case of total scalp and partial scalp, the volume of brain which received more than 20 Gy in the VMAT plans was 2 times larger than the volume in the ncIMRT plans. In case of whole ventricle, there was no significant difference. Target coverage was satisfied in both plans($PTV_{100%}=95%$). The maximum dose in target volume and required monitor unit(MU) of ncIMRT were higher than them of VMAT plans. Conclusion: Even though ncIMRT is less efficient than VMAT with regard to required MU and treatment time, the dose to OARs is much lower than VMAT and PTV Coverage is similar with VMAT. If the shape of target is irregular and location is adjacent to OAR, comparison VMAT plan with ncIMRT plan deserves to be considered.

• Journal of Nutrition and Health
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• v.50 no.5
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• pp.426-436
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• 2017

Purpose: To compare the extent to which three different levels of D-ribose in sugar reduce the glycemic index (GI) and blood glucose response in healthy adults. Methods: Healthy adults (eight male and six female participants, n = 14) fasted for 14~16 h after eating the same dinner. Participants were then randomized to receive glucose, sucrose, sucrose containing 5% D-ribose (RB5), sucrose containing 10% D-ribose (RB10), or sucrose containing 14% D- ribose (RB14) every week on the same day for 10 weeks (repeating the sample twice). Blood samples were collected by finger prick before and 15, 30, 45, 60, 90, and 120 min after starting to eat. Results: We observed a decreased glycemic response to sucrose containing D-ribose. GIs for sucrose, RB5, RB10, and RB14 were 67.39, 67.07, 47.57, and 45.62, respectively. GI values for sucrose and RB5 were similar to those for foods with a medium GI, and GI values for RB10 and RB14 were similar to those for foods with a low GI. The postprandial maximum blood glucose rise (Cmax) with RB14 was the lowest among the test foods. Cmax values for RB10 and RB14 were significantly lower than that for sucrose. Conclusion: The results of this study suggest that sucrose containing D-ribose has an acute suppressive effect on GI and Cmax. In addition, D-ribose active elements in sugar may be effective in preventing blood glucose spikes induced by sucrose intake.

• Restorative Dentistry and Endodontics
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• v.35 no.5
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• pp.335-343
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• 2010

Objectives: To compared the effect of different levels of moisture of root canal on the sealing ability after filling with four different types of sealer. Materials and Methods: Single-rooted teeth (n = 90) instrumented to and apical size of 0.06 / 45 were randomly assigned to 12 experimental groups (n = 7 per group), positive/negative control groups (n = 3 per group). The teeth of the experimental groups (a. DRY; b. PAPER POINT DRY; c. WET) were obturated with sealer (Group 1-3: Sealapex; Group 4-6: AH plus; Group 7-9: Tubuli-seal; Group 10-12: EndoRez) and warm vertical compaction method. After 7 days in $37^{\circ}C$, 100% humidity, the coronal-to-apical microleakage was evaluated quantitatively using a glucose leakage model. The leaked glucose concentration was measured with spectrophotometer at 1, 3, 7, 14, 21, and 30 days. Data were recorded ad mmol/L and statistically analysed with the two-way ANOVA and Duncan test (p = 0.05). Results: Throughout the experimental period Tubuli-seal/WET (Group 9) showed the highest mean cumulative glucose penetration (178.75 mmol/L), whereas AH plus/DRY (Group 4) had the least (20.78 mmol/L). Conclusions: The results of this study demonstrated that the moisture condition of root canals at the time of obturation and the type of sealer that was used had a significant effect on leakage and sealing ability. Thus drying procedure according to sealer types is a critical step and should not be missed in endodontic treatment.

• 대한공업교육학회지
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• v.33 no.1
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• pp.149-168
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• 2008

The purpose of this study is to verify the effect of PSpice instruction on academic achievement in 'Combination logic circuit' unit of 'Digital Logic Circuit' in industrial high school. Three kinds of null hypotheses were formulated. Two classes of the third grade of C technical high school in Gyeong-buk were divided into experimental group and control group in order to verify null hypotheses. In the experimental design, 'Non-equivalent control group pretest-posttest' model was utilized. This experiment was conducted for six classes, the experimental group was applied to PSpice instruction method before the circuit traning while the control group was applied to traditional lecture oriented method before the circuit traning. Window SPSS 10.0 korean language version program was used for the data analysis and independent sample t-test was used to identify the average of each group. Significance level was set to .05 level. The results obtained in this study were as follows; First, PSpice instruction had not an effect on academic achievement according to a group type. However, these instruction had an effect on the following sub-domains; the psychomotor domain. Second, PSpice instruction had not an effect on academic achievement according to a studies level. However, these instruction for middle and low level students had an effect on the cognitive and psychomotor domain, and for middle level students had an effect on the affective domain. Third, PSpice instruction had not an effect on shortening of a training requirement. However, this instruction for low level students had an effect on shortening of a training requirement. The study results of simulation instruction was chiefly efficient in the psychomotor domain. We could know that simulation instruction is efficient as went to a low level students than an upper level students. Thus, We may make the study effectiveness in various instruction method.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.79-99
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• 2015

The prediction of bankruptcy has been extensively studied in the accounting and finance field. It can have an important impact on lending decisions and the profitability of financial institutions in terms of risk management. Many researchers have focused on constructing a more robust bankruptcy prediction model. Early studies primarily used statistical techniques such as multiple discriminant analysis (MDA) and logit analysis for bankruptcy prediction. However, many studies have demonstrated that artificial intelligence (AI) approaches, such as artificial neural networks (ANN), decision trees, case-based reasoning (CBR), and support vector machine (SVM), have been outperforming statistical techniques since 1990s for business classification problems because statistical methods have some rigid assumptions in their application. In previous studies on corporate bankruptcy, many researchers have focused on developing a bankruptcy prediction model using financial ratios. However, there are few studies that suggest the specific types of bankruptcy. Previous bankruptcy prediction models have generally been interested in predicting whether or not firms will become bankrupt. Most of the studies on bankruptcy types have focused on reviewing the previous literature or performing a case study. Thus, this study develops a model using data mining techniques for predicting the specific types of bankruptcy as well as the occurrence of bankruptcy in Korean small- and medium-sized construction firms in terms of profitability, stability, and activity index. Thus, firms will be able to prevent it from occurring in advance. We propose a hybrid approach using two artificial neural networks (ANNs) for the prediction of bankruptcy types. The first is a back-propagation neural network (BPN) model using supervised learning for bankruptcy prediction and the second is a self-organizing map (SOM) model using unsupervised learning to classify bankruptcy data into several types. Based on the constructed model, we predict the bankruptcy of companies by applying the BPN model to a validation set that was not utilized in the development of the model. This allows for identifying the specific types of bankruptcy by using bankruptcy data predicted by the BPN model. We calculated the average of selected input variables through statistical test for each cluster to interpret characteristics of the derived clusters in the SOM model. Each cluster represents bankruptcy type classified through data of bankruptcy firms, and input variables indicate financial ratios in interpreting the meaning of each cluster. The experimental result shows that each of five bankruptcy types has different characteristics according to financial ratios. Type 1 (severe bankruptcy) has inferior financial statements except for EBITDA (earnings before interest, taxes, depreciation, and amortization) to sales based on the clustering results. Type 2 (lack of stability) has a low quick ratio, low stockholder's equity to total assets, and high total borrowings to total assets. Type 3 (lack of activity) has a slightly low total asset turnover and fixed asset turnover. Type 4 (lack of profitability) has low retained earnings to total assets and EBITDA to sales which represent the indices of profitability. Type 5 (recoverable bankruptcy) includes firms that have a relatively good financial condition as compared to other bankruptcy types even though they are bankrupt. Based on the findings, researchers and practitioners engaged in the credit evaluation field can obtain more useful information about the types of corporate bankruptcy. In this paper, we utilized the financial ratios of firms to classify bankruptcy types. It is important to select the input variables that correctly predict bankruptcy and meaningfully classify the type of bankruptcy. In a further study, we will include non-financial factors such as size, industry, and age of the firms. Thus, we can obtain realistic clustering results for bankruptcy types by combining qualitative factors and reflecting the domain knowledge of experts.

• Journal of Intelligence and Information Systems
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• v.18 no.1
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• pp.39-57
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• 2012

Recently, due to the introduction of high-tech equipment in interactive exhibits, many people's attention has been concentrated on Interactive exhibits that can double the exhibition effect through the interaction with the audience. In addition, it is also possible to measure a variety of audience reaction in the interactive exhibition. Among various audience reactions, this research uses the change of the facial features that can be collected in an interactive exhibition space. This research develops an artificial neural network-based prediction model to predict the response of the audience by measuring the change of the facial features when the audience is given stimulation from the non-excited state. To present the emotion state of the audience, this research uses a Valence-Arousal model. So, this research suggests an overall framework composed of the following six steps. The first step is a step of collecting data for modeling. The data was collected from people participated in the 2012 Seoul DMC Culture Open, and the collected data was used for the experiments. The second step extracts 64 facial features from the collected data and compensates the facial feature values. The third step generates independent and dependent variables of an artificial neural network model. The fourth step extracts the independent variable that affects the dependent variable using the statistical technique. The fifth step builds an artificial neural network model and performs a learning process using train set and test set. Finally the last sixth step is to validate the prediction performance of artificial neural network model using the validation data set. The proposed model is compared with statistical predictive model to see whether it had better performance or not. As a result, although the data set in this experiment had much noise, the proposed model showed better results when the model was compared with multiple regression analysis model. If the prediction model of audience reaction was used in the real exhibition, it will be able to provide countermeasures and services appropriate to the audience's reaction viewing the exhibits. Specifically, if the arousal of audience about Exhibits is low, Action to increase arousal of the audience will be taken. For instance, we recommend the audience another preferred contents or using a light or sound to focus on these exhibits. In other words, when planning future exhibitions, planning the exhibition to satisfy various audience preferences would be possible. And it is expected to foster a personalized environment to concentrate on the exhibits. But, the proposed model in this research still shows the low prediction accuracy. The cause is in some parts as follows : First, the data covers diverse visitors of real exhibitions, so it was difficult to control the optimized experimental environment. So, the collected data has much noise, and it would results a lower accuracy. In further research, the data collection will be conducted in a more optimized experimental environment. The further research to increase the accuracy of the predictions of the model will be conducted. Second, using changes of facial expression only is thought to be not enough to extract audience emotions. If facial expression is combined with other responses, such as the sound, audience behavior, it would result a better result.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.7
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• pp.2358-2370
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• 2010

This research aims to empirically analyze the factors that affect the success of technology marketing by Korean universities. The total of 207 universities which successfully made technology transfers from 2006 to 2008 was examined to test the nine hypotheses. For the purpose of testing the hypotheses, technology infrastructure (research costs and the number of SCIE papers), the compensation system for the patents (application and registration), the number of patents (application and registration), TLO staff (the number of people in charge of technology transfer and the job experience in industries), the compensation system for technology transfers (researchers and contributors), and attitudes of university management and industries were analyzed with structural equation methods to figure out their effects on the revenues of technology transfer. The results of this research are summarized as follows. First, technology infrastructures of universities were found to have positive effects on securing patents. As the university research costs in the field of science and technology are increases, the research capabilities are enhanced and this a larger number of researchers are conducted. Second, this research shows that compensation systems for patent application and registration in universities have motivated researchers to take out patents for the outputs of their research. Third, the number of patents universities possess was found to have a positive effect on technology transfer. An increase in the number of patents universities possess implies an increase in the diversity and excellence of the target technologies for transfer. Fourth, the number of patents universities possess turned out to have a positive effect on TLO staff. The number of experts in charge of technology transfer including technology dealers, valuation analysis and patent attorneys should be increased as target technologies for transfer increase according to the increase of patents possessed. Because the technologies are transferee from universities to businesses, businesses (job) experience of TLO staff in industries are also important. This research is meaningful because it has identified the factors affecting the results of technology transfer by employing structural equation methods. In particular, an official governmental survey data for the academic-industrial cooperation were analyzed systematically in terms of technology infrastructure, compensation systems related to patents, the number of patents, TLO staff, compensation systems for technology transfer, and attitudes of university management and industries. All these facts might could differentiate this study from the previous studies.

• Journal of the Korea institute for structural maintenance and inspection
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• v.19 no.5
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• pp.104-111
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• 2015

This study shows the mechanical properties of alkali-activated slag cement (AASC) synthesized using sulfate with NaOH solution. The used sulfates were calcium sulfate ($CaSO_4$, denoted CS) and sodium sulfate ($Na_2SO_4$, denoted SS). The replacement ratio of sulfates was 2.5, 5.0, 7.5 and 10.0% by weight of slag. NaOH solution of 2M and 4M concentration was used. A sample was activated with sulfate and activated with blended activator (blending NaOH solution with sulfate) respectively. 24 mix ratios were used and the water-binder weight ratio for the test was set 0.5. This research carried out the compressive strength, flexural strength, ultrasonic pulse velocity (UPV), absorption and X-ray diffraction (XRD). In the case of samples with CS, sample with 7.5% CS, sample with 2M NaOH+5.0% CS and sample with 4M NaOH+5.0% CS showed the good performance in the strength development. In the case of samples with SS, sample with 10.0% SS, sample with 2M NaOH+7.5% SS and sample with 4M NaOH+2.5% SS obtained good performance in strength. The results of UPV and water absorption showed a similar tendency to the strength properties. The XRD analysis of samples indicated that the hydration products formed in samples were ettringite, CSH and silicate phases. In this study, it is indicated that when compared to the use of sulfate only, the use of both sulfate and NaOH solution makes mechanical properties of AASC better.

• Restorative Dentistry and Endodontics
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• v.35 no.2
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• pp.88-95
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• 2010

The purpose of this study was to compare the root canal shaping ability of 4 rotary NiTi instruments in simulated root canals. For the preparation of thirty two curved root canals, Mtwo instruments using "single length"technique, and Profile, ProTaper Universal, and K3 using crown-down technique (N = 8) were used. All canal samples were prepared by reaching an apical canal size of #30. Pre- and post-instrumentation digital images were recorded and an assessment of canal shape was determined using a computer image analysis program SigmaScan Pro (Systat Software Inc., San Jose, CA, USA). The changes of the dimension of inner walls of canals, (2) the changes of the dimension of outer walls of canals, and (3) the centering ratio were measured at 7 measuring points, and then data were statistically analyzed using one-way ANOVA and Duncan's test. The results were as below; 1. The root canal shaping ability of Profile was significantly faster than that of other rotary NiTi instruments (p < 0.05). 2. The deformation and fracture of all instruments used for this study were not experienced. 3. In the degree of changes of the dimension of inner walls of canals, Profile demonstrated the lowest changes of the dimension of inner walls of canals except at the measuring points of the 1 and 2 mm (p < 0.05). However, the ProTaper Universal showed the highest changes of the dimension of inner walls of canals at all measuring points (p < 0.05). 4. In the degree of changes of the dimension of outer walls of canals, Mtwo demonstrated the lowest changse of the dimension of outer walls of canals except at the measuring point of the 1 mm (p < 0.05). However, Profile exhibited the highest changes of the dimension of outer walls of canals at the measuring points of 3 and 4 mm and ProTaper Universal and K3 showed the largest changes of the dimension of outer walls of canals at the measuring points of 1, 2, 6, and 7 mm (p < 0.05). 5. In degree of centering ratio, Profile demonstrated the least centering ratio comparing with the centering ratio shown by other NiTi instruments at the measuring points of 1, 4, 5, and 6 mm. Results suggest that in the coronal part of canal preparation, active cutting files such as ProTaper Universal may efficiently flare the canal orifice and form a better taper, and in the apical part of the canal, files which have a better centering ability such as Profile may maintain the original canal curvature and reduce the shaping time.