• The Korean Journal of Nuclear Medicine Technology
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• v.13 no.3
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• pp.81-85
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• 2009

Purpose: The examination of nuclear medicine observes the change in accordance with the time elapsed in the same region purposed and there are many examinations to acquire the image during the same term. At this time, the same parameter should be applied. The hepatobiliary scan, lung scan etc, are the acquired examination in the divided time with a regular term. Pre-set time that is applied in continued next image is set in order to acquire the fixed counts. The same scan time should be applied for each image. This study will look for the rational plan and analyze the change of scan time in accordance with the time of the decision of scan time at examination that pre-set time is applied. Methods: The hapatobiliary scan that use the radio pharmaceutical $^{99m}Tc$-mebrofenin is choosed as compensation from Jan. 2009 to Mar. 2009 in the department of nuclear medicine in ASAN MEDICAL CENTER. Scan is started after 5 minutes from when 222 MBq (6 mCi) is injected to patient. We let patient stand up between both detectors, and possibly close to the front of detector. When scan time reach 10%, 25%, 50%, 75% of total scan time, we measured the expected total scan time. After finishing all of scan, we compared the total scan time and the expected total scan time, while image is acquiring. and we observed the change of scan time in accordance with radio activity by using phantom. Results: After starting scan, a difference of when scan time reach 10%, 25%, 50%, 75% of total scan time is that the biggest difference is 5 seconds on 10%. There statistically is difference between 25% (t:2.88, p<0.01) and 50% (t:2.05, p<0.01). Conclusions: When the same the scan time is applied in the examination that acquire the many frame, concluding the same scan time has a important effect on a quantitative analysis. Although method that decide the scan time after finish all of the examinations, there is a few problem to apply practical affairs. This may cause an inaccurate result on the examination that need a quantitative analysis. We think that operator should try to improve it. At least, after reach 50% of total scan time, deciding the total scan time mean that you can minimize error of a quantitative analysis caused by unmatched scan time from a gap of image.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.2111-2111
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• 2001

A chemoinfometrical method for evaluating the quantitative determination of crystallinity one polymorphs based on fourie-transformed near-infrared (FT-NIR) spectroscopy was established. A direct comparison of the data with the ones collected from using the and compared with the conventional powder X-ray diffraction method was performed. [Method] The pPure a and g forms of indomethacin (IMC) were prepared by reportedusing published methods. Six kinds of standard samples obtained by physically mixing of a and g forms. After the powder X-ray diffraction profiles of samples have been measured, the intensity values were normalized to against the intensity of silicon powder as the as an external standard. The calibration curves for quantification of crystal content were based upon the total relative intensity of four diffraction peaks from of the form g crystal. FT-NIR spectra of six calibration sample sets were recorded 5 times with the NIR spectrometer (BRAN+LUEBBE). Chemoinfometric analysis was performed on the NIR spectral data sets by applying the principal component regression (PCR). [Results] The relation between the actual and predicted polymorphic contents of form g IMC measured using by the X-ray diffraction method shows a good straight linen linear relation., and it has slope of 0.023, an intercept of 0.131 and a correlation coefficient of 0.986. PCR analyses wereis was performed based on normalized NIR spectra sets offer standard samples of known content of IMC g form. IMC. A calibration equation was determined to minimize the root mean square error of the predictionthe prediction. Figure 1 shows a plot of the calibration data obtained by NIR method between the actual and predicted contents of form g IMC. The predicted values were reproducible and had a smaller standard deviation. Figure 2 shows that the plot for the predicted transformation rate (%) of form a IMC to form g as measured by X-ray diffractomeoy against to those as measured by NIR method. The plot has a slope of 1.296, an intercept of 1,109, and a correlation coefficient of 0.992. The line represents a satisfactory correlation between the two predicted values of form g IMC content. Thus NIR spectroscopy is an effective method for the evaluation to the pharmaceutical products of quantitative of polymorph.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.10 no.2
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• pp.22-34
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• 2011

This paper presents the investigation results of a research on how engineers can analyze the economic effect of the ETCS(Electronic Toll Collection System) installed to minimize the vehicle delays on freeway tollgates during toll payments. This research considered this economic effect to occur in the form of vehicle passing time reductions at the ETCS, and the multi-service queuing theory was applied to estimate these values. This research found: 1) When vehicles approaching tollgates show Poisson distribution and the service time of the ETCS shows Exponential distribution, the multi-service queuing theory would be applicable for estimating vehicle passing times at toll-gates, 2) Despite the ETCS placement, exit sections of tollgates give a greater reduction of vehicle passing times than entering sections due to more delays at conventional toll payments, and 3)The ETCS would not guarantee vehicle passing time reductions all the time, because in such a case as many vehicles were queuing at the ETCS, the total delay level for a toll gate would increase greatly. In addition, in order to examine the accuracy of the estimated vehicle passing values, this research compared the values from the multi-service queuing theory with the observed values from a set of field survey values at freeway toll-gates, and found that the two values were in a good agreement with a very low error range of 1-3 seconds per vehicle. Based on this result, the multi-service queuing theory was recommended for practice.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.12
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• pp.106-115
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• 2003

Diverse multimedia services will be deployed at hand on 3G-and-beyond multi-service CDMA systems in order to satisfy different quality of service (QoS) according to traffic types. In order to use appropriate resources efficiently the call admission control (CAC) as a major resource control mechanism needs to be used to take care of efficient utilization of limited resources. In this paper, we propose a QoS-aware CAC (QCAC) that is enabled to provide service fairness and service differentiation in accordance with priority order and that applies the different thresholds in received power considering different QoS requirements such as different bit error rates (BER) when adopting total received power as the ceil load estimation. The proposed QCAC calculates the different thresholds of the different traffic types based on different required BER applies it for admission policy, and can get service fairness and differentiation in terms of call dropping probability as a main performance metric. The QCAC is aware of the QoS requirement per traffic type and allows admission discrimination according to traffic types in order to minimize the probability of QoS violation. Also the CAC needs to consider the resource allocation schemes such as complete sharing (CS), complete partitioning (CP), and priority sharing(PS) in order to provide fairness and service differentiation among traffic types. Among them, PS is closely related with the proposed QCAC having differently calculated threshold per each traffic type according to traffic priority orders.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.4 no.1
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• pp.89-111
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• 2009

Since the financial crisis in 1997, the Korean economy has a steady increase of people who tend to establish their own business by 2008. Business foundations can be divided into independent businesses and franchise businesses. This study focuses on what type of business owners among franchise enterprisers can achieve success. This is intended to reduce trial and error by drawing upon success factors in the stages of establishment, operation, and achievement based on a total sample of 350 individual business sites. The result shows that the success factors in the stage of establishment include (1) Preparation such as foundation education (2) Marketing capability (3) Appropriateness of Business Item (4) Other founder's entry barrier, conglomerate's entry regulation and (5) Head Office Support including service education, market survey education, marketing support. On the other hand, the success factors in the stage of operation include the supervisor capability, Marketing capability, Head Office Support, Customer Management Capability and Employee Satisfaction. Additionally after choosing the major factors according to each stage, multiple regression analysis was processed and interpreted. Finally, we believe that the franchise or independent business foundations can make a profit as well as increase continuous sales and customer satisfaction only with thorough and careful preparation in all stages of foundation and operation. This study is expected to contribute to those who prepare new business in franchise domain to minimize failures with deep consideration of the success factors in the franchise.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.5
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• pp.103-111
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• 2007

In this paper, we propose a VLSI architecture of hardware optimized high quality image signal processor for a Single-chip CMOS Image Sensor(CIS). The Single-chip CIS is usually used for mobile applications, so it has to be implemented as small as possible while maintaining the image quality. Several image processing algorithms are used in ISP to improve captured image quality. Among the several image processing blocks, demosaicing and image filter are the core blocks in ISP. These blocks need line memories, but the number of line memories is limited in a low cost Single-chip CIS. In our design, high quality edge-adaptive and cross channel correlation considered demosaicing algorithm is adopted. To minimize the number of required line memories for image filter, we share the line memories using the characteristics of demosaicing algorithm which consider the cross correlation. Based on the proposed method, we can achieve both high quality and low hardware complexity with a small number of line memories. The proposed method was implemented and verified successfully using verilog HDL and FPGA. It was synthesized to gate-level circuits using 0.25um CMOS standard cell library. The total logic gate count is 37K, and seven and half line memories are used.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.6
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• pp.27-35
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• 2021

Generally, a proper evaluation method of the aging phenomenon of PV modules is required as the electrical performance and lifespan of PV modules can degrade significantly due to several environmental factors, while they are generally known as devices that are used semi-permanently for more than 20 years. On the other hand, there is a lack of objectivity in the existing evaluation method of the aging phenomenon, which compares the adjusted PV output based on STC with the initial PV module specifications due to the data distortion while adjusting the measured data. Therefore, this study implemented a test device for an aging diagnosis to measure and collect actual data from a PV module section and modeled the data for aging using MATLAB S/W to minimize the variability of the PV output, communication error, and delay. Furthermore, this study confirmed the usefulness of the presented test device for aging diagnosis of the PV modules by diagnosing the total period and yearly-basis degradation rate of aging PV modules as 25.73% and 1.55%, respectively, according to the on-site output characteristics of the PV modules by season.

• Journal of Practical Engineering Education
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• v.15 no.2
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• pp.381-388
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• 2023

Through artificial neural network education using spreadsheets, non-major undergraduate students can understand the operation principle of artificial neural networks and develop their own artificial neural network software. Here, training of the operation principle of artificial neural networks starts with the generation of training data and the assignment of correct answer labels. Then, the output value calculated from the firing and activation function of the artificial neuron, the parameters of the input layer, hidden layer, and output layer is learned. Finally, learning the process of calculating the error between the correct label of each initially defined training data and the output value calculated by the artificial neural network, and learning the process of calculating the parameters of the input layer, hidden layer, and output layer that minimize the total sum of squared errors. Training on the operation principles of artificial neural networks using a spreadsheet was conducted for undergraduate non-major students. And image training data and basic artificial neural network development results were collected. In this paper, we analyzed the results of collecting two types of training data and the corresponding artificial neural network SW with small 12-pixel images, and presented methods and execution results of using the collected training data for Orange machine learning model learning and analysis tools.

• Journal of Intelligence and Information Systems
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• v.16 no.4
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• pp.67-84
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• 2010

In terms of business, forecasting is a work of what is expected to happen in the future to make managerial decisions and plans. Therefore, the accurate forecasting is very important for major managerial decision making and is the basis for making various strategies of business. But it is very difficult to make an unbiased and consistent estimate because of uncertainty and complexity in the future business environment. That is why we should use scientific forecasting model to support business decision making, and make an effort to minimize the model's forecasting error which is difference between observation and estimator. Nevertheless, minimizing the error is not an easy task. Case-based reasoning is a problem solving method that utilizes the past similar case to solve the current problem. To build the successful case-based reasoning models, retrieving the case not only the most similar case but also the most relevant case is very important. To retrieve the similar and relevant case from past cases, the measurement of similarities between cases is an important key factor. Especially, if the cases contain symbolic data, it is more difficult to measure the distances. The purpose of this study is to improve the forecasting accuracy of case-based reasoning approach using fuzzy relation and composition. Especially, two methods are adopted to measure the similarity between cases containing symbolic data. One is to deduct the similarity matrix following binary logic(the judgment of sameness between two symbolic data), the other is to deduct the similarity matrix following fuzzy relation and composition. This study is conducted in the following order; data gathering and preprocessing, model building and analysis, validation analysis, conclusion. First, in the progress of data gathering and preprocessing we collect data set including categorical dependent variables. Also, the data set gathered is cross-section data and independent variables of the data set include several qualitative variables expressed symbolic data. The research data consists of many financial ratios and the corresponding bond ratings of Korean companies. The ratings we employ in this study cover all bonds rated by one of the bond rating agencies in Korea. Our total sample includes 1,816 companies whose commercial papers have been rated in the period 1997~2000. Credit grades are defined as outputs and classified into 5 rating categories(A1, A2, A3, B, C) according to credit levels. Second, in the progress of model building and analysis we deduct the similarity matrix following binary logic and fuzzy composition to measure the similarity between cases containing symbolic data. In this process, the used types of fuzzy composition are max-min, max-product, max-average. And then, the analysis is carried out by case-based reasoning approach with the deducted similarity matrix. Third, in the progress of validation analysis we verify the validation of model through McNemar test based on hit ratio. Finally, we draw a conclusion from the study. As a result, the similarity measuring method using fuzzy relation and composition shows good forecasting performance compared to the similarity measuring method using binary logic for similarity measurement between two symbolic data. But the results of the analysis are not statistically significant in forecasting performance among the types of fuzzy composition. The contributions of this study are as follows. We propose another methodology that fuzzy relation and fuzzy composition could be applied for the similarity measurement between two symbolic data. That is the most important factor to build case-based reasoning model.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.129-141
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• 2023

Crop models have been used to predict yield under diverse environmental and cultivation conditions, which can be used to support decisions on the management of forage crop. Cultivar parameters are one of required inputs to crop models in order to represent genetic properties for a given forage cultivar. The objectives of this study were to compare calibration and ensemble approaches in order to minimize the uncertainty of crop yield estimates using the SIMPLE crop model. Cultivar parameters were calibrated using Log-likelihood (LL) and Generic Composite Similarity Measure (GCSM) as an objective function for Metropolis-Hastings (MH) algorithm. In total, 20 sets of cultivar parameters were generated for each method. Two types of ensemble approach. First type of ensemble approach was the average of model outputs (E_em), using individual parameters. The second ensemble approach was model output (E_pm) of cultivar parameter obtained by averaging given 20 sets of parameters. Comparison was done for each cultivar and for each error calculation methods. 'Jowoo' and 'Yeongwoo', which are forage rice cultivars used in Korea, were subject to the parameter calibration. Yield data were obtained from experiment fields at Suwon, Jeonju, Naju and I ksan. Data for 2013, 2014 and 2016 were used for parameter calibration. For validation, yield data reported from 2016 to 2018 at Suwon was used. Initial calibration indicated that genetic coefficients obtained by LL were distributed in a narrower range than coefficients obtained by GCSM. A two-sample t-test was performed to compare between different methods of ensemble approaches and no significant difference was found between them. Uncertainty of GCSM can be neutralized by adjusting the acceptance probability. The other ensemble method (E_pm) indicates that the uncertainty can be reduced with less computation using ensemble approach.