• The Journal of Korean Society for Radiation Therapy
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• v.24 no.2
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• pp.67-75
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• 2012

Purpose: The study is to check the specialty of radiotherapists working in the department of radiation oncology and find job satisfaction, organizational commitment and job commitment having an effect on professional parts. After making analysis of the mutual relation, it is to provide radiotechnologists with making progress in the future. Materials and Methods: From March 2 to March 30, we had carried out a survey with email. It is possible to have 272 questionnaires answered in the survey. We make use of SPSS 13.0 for Windows to analyze the data collected for study. Frequency and a percentage are meant to show general characteristics, and t-test and ANOVA to do the difference between general properties and professionalism. Pearson's correlation coefficient also is meant to do the correlation of professionalism, organizational job commitment and job satisfaction, and multiple regression analysis to do the factor for a relevant variable to affect professionalism. Results: There are subdivisions in the professionalism informing us of the self-regulation $17.74{\pm}2.32/3.55{\pm}.46$, a sense of calling $17.58{\pm}2.63/3.52{\pm}.53$, reference of the professional $17.14{\pm}2.39/3.43{\pm}.48$, service to the public $15.97{\pm}2.48/3.19{\pm}50$, and autonomy $15.68{\pm}2.28/3.14{\pm}46$. Grand mean turns out to be $83.89{\pm}7.63$(Summation of items)/$3.37{\pm}0.49$ (Numbers of items). When it comes to a statistical relation between general characteristics and professionalism, the statistics have it that these come within age (P<.001), period of employment (P<.001), education status (P<.05), a monthly income (P<.001), radiotherapists who get a special license (P<.001), the position (P<.001), and an opportunity for developing (P<.001). As a result of organizational commitment, job commitment, and job satisfaction, grand mean in organizational commitment proves to be $80.10{\pm}8.15/3.34{\pm}.34$. There are subvisions showing affective commitment $28.64{\pm}4.61$/3.58, continuance commitment $27.54{\pm}4.22/3.44{\pm}.53$, and normative commitment $23.95{\pm}2.94/2.99{\pm}.37$ in order of precedence. The average grade in job commitment is $32.47{\pm}5.77/3.30{\pm}.60$ and that in job satisfaction is $63.39{\pm}10.16/3.17{\pm}.51$, respectively. We find the positive relationship between professionalism and organizational commitment (r=.522, P<.05), between professionalism and job commitment (r=.444, P<.05), and between professionalism and job satisfaction (r=.507, P<.05). And we also get the positive relationship between organizational commitment and job commitment (r=.549, P<.05), between organizational commitment and job satisfaction (r=.433, P<.05), and between job commitment and job satisfaction (r=.462, P<.05). To catch the factors influencing the professionalism of radiotherapists, we used multiple regression analysis. According to the final model, it appears affective commitment (B=.755, P<.05), normative commitment (B=.305, P<.05), job satisfaction (B=.092, P<.05), an opportunity for developing (B=-1.505, P<.05), and the position (B=-1.155, P<.05) in order of precedence. It seems that explaining influece on $R^2$ is 0.504. Conclusion: The results of the factors that influence professionalism working as radiotherapists in the department of radiation oncology have it that the more affective commitment, normative commitment, and job satisfaction we feel, the more professionalism we recognize. We think that the focus of professionalism is increased if getting the chances for radiotherapists to have little to do with developing opportunities given.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.18 no.4
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• pp.570-593
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• 1996

This study was intended to perform the influence of condyle positional change after surgical correction of skeletal Class III malocclusion after BSSRO in 20 patients(males 9, females 11) using computed tomogram that were taken in centric occlusion before, immediate, and long term after surgery and lateral cephalogram that were taken in centric occlusion before, 7 days within the period intermaxillary fixation, 24hour after removing intermaxillary fixation and long term after surgery. 1. Mean intercondylar distance was $84.45{\pm}4.01mm$ and horizontal long axis of condylar angle was $11.89{\pm}5.19^{\circ}$on right, $11.65{\pm}2.09^{\circ}$on left side and condylar lateral poles were located about 12mm and medial poles about 7mm from reference line(AA') on the axial tomograph. Mean intercondylar distance was $84.43{\pm}3.96mm$ and vertical axis angle of condylar angle was $78.72{\pm}3.43^{\circ}$on right, $78.09{\pm}6.12^{\circ}$on left. 2. No statistical significance was found on the condylar change(T2C-T1C) but it had definitive increasing tendency. There was significant decreasing of the distance between both condylar pole and the AA'(p<0.05) during the long term(TLC-T2C). 3. On the lateral cephalogram, no statistical significance was found between immediate after surgery and 24 hours after the removing of intermaxillary fixation but only the lower incisor tip moved forward about 0.33mm(p<0.05). Considering individual relapse rate, mean relapse rate was 1.2% on L1, 5.0% on B, 2.0% on Pog, 9.1% on Gn, 10.3% on Me(p<0.05). 4. There was statistical significance on the influence of the mandibular set-back to the total mandibular relapse(p<0.05). 5. There was no statistical significance on the influence of the mandibular set-back(T2-T1) to the condylar change(T2C-T1C), the condylar change(T2C-T1C, TLC-T2C) to the mandibular total relapse, the pre-operative condylar position to the condylar change(T2C-T1C, TLC-T2C), the pre-operative mandibular posture to the condylar change(T2C-T1C, TLC-T2C)(p>0.05). 6. The result of multiple regression analysis on the influence of the pre-operative condylar position to the total mandibular relapse revealed that the more increasing of intercondylar distance and condylar vertical axis angle and decreasing of condyalr head long axis angle, the more increasing of mandibular horizontal relapse(L1,B,Pog,Gn,Me) on the right side condyle. The same result was founded in the case of horizontal relapse(L1,Me) on the left side condyle.(p<0.05). 7. The result of multiple regression analysis on the influence of the pre-operative condylar position to the pre-operative mandibular posture revealed that the more increasing of intercondylar distance and condylar vertical axis angle and decreasing of condylar head long axis angle, the more increasing of mandibular vertical length on the right side condyle. and increasing of vertical lengh & prognathism on the left side condyle(p<0.05). 8. The result of simple regression analysis on the influence of the pre-operative mandibular posture to the mandibular total relapse revealed that the more increasing of prognathism, the more increasing of mandibular total relapse in B and the more increasing of over-jet the more increasing of mandibular total relapse(p<0.05). Consequently, surgical mandibular repositioning was not significantly influenced to the change of condylar position with condylar reposition method.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.77-110
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• 2017

Recently, the diversification and individualization of consumption patterns through the web and mobile devices based on the Internet have been rapid. As this happens, the efficient operation of the offline store, which is a traditional distribution channel, has become more important. In order to raise both the sales and profits of stores, stores need to supply and sell the most attractive products to consumers in a timely manner. However, there is a lack of research on which SKUs, out of many products, can increase sales probability and reduce inventory costs. In particular, if a company sells products through multiple in-store stores across multiple locations, it would be helpful to increase sales and profitability of stores if SKUs appealing to customers are recommended. In this study, the recommender system (recommender system such as collaborative filtering and hybrid filtering), which has been used for personalization recommendation, is suggested by SKU recommendation method of a store unit of a distribution company that handles a homogeneous brand through a plurality of sales stores by country and region. We calculated the similarity of each store by using the purchase data of each store's handling items, filtering the collaboration according to the sales history of each store by each SKU, and finally recommending the individual SKU to the store. In addition, the store is classified into four clusters through PCA (Principal Component Analysis) and cluster analysis (Clustering) using the store profile data. The recommendation system is implemented by the hybrid filtering method that applies the collaborative filtering in each cluster and measured the performance of both methods based on actual sales data. Most of the existing recommendation systems have been studied by recommending items such as movies and music to the users. In practice, industrial applications have also become popular. In the meantime, there has been little research on recommending SKUs for each store by applying these recommendation systems, which have been mainly dealt with in the field of personalization services, to the store units of distributors handling similar brands. If the recommendation method of the existing recommendation methodology was 'the individual field', this study expanded the scope of the store beyond the individual domain through a plurality of sales stores by country and region and dealt with the store unit of the distribution company handling the same brand SKU while suggesting a recommendation method. In addition, if the existing recommendation system is limited to online, it is recommended to apply the data mining technique to develop an algorithm suitable for expanding to the store area rather than expanding the utilization range offline and analyzing based on the existing individual. The significance of the results of this study is that the personalization recommendation algorithm is applied to a plurality of sales outlets handling the same brand. A meaningful result is derived and a concrete methodology that can be constructed and used as a system for actual companies is proposed. It is also meaningful that this is the first attempt to expand the research area of the academic field related to the existing recommendation system, which was focused on the personalization domain, to a sales store of a company handling the same brand. From 05 to 03 in 2014, the number of stores' sales volume of the top 100 SKUs are limited to 52 SKUs by collaborative filtering and the hybrid filtering method SKU recommended. We compared the performance of the two recommendation methods by totaling the sales results. The reason for comparing the two recommendation methods is that the recommendation method of this study is defined as the reference model in which offline collaborative filtering is applied to demonstrate higher performance than the existing recommendation method. The results of this model are compared with the Hybrid filtering method, which is a model that reflects the characteristics of the offline store view. The proposed method showed a higher performance than the existing recommendation method. The proposed method was proved by using actual sales data of large Korean apparel companies. In this study, we propose a method to extend the recommendation system of the individual level to the group level and to efficiently approach it. In addition to the theoretical framework, which is of great value.

• The Korean Journal of Mycology
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• v.4 no.1
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• pp.31-44
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• 1976

The studies were carried out to examine the effects of supplementation of nutritional substances and physical conditions in substrate on the mycelial growth and yield of fresh sporophores of winter mushroom, Flammulina velutipes(Curt. ex Fr.) Sing. and to obtain further informations on the nutritional requirements of the fungus with reference to improvement of substrate through [analysis of chemical composition of the substrates during the cultivation period. The results obtained are summarized as follows: 1. The best yield of fresh sporophores, 84.4 g per 280 g substrate in a bottle, was obtained from the mixture of poplar sawdust 10 and rice bran 3 by volume when Flammulina velutipes was cultivated on the poplar sawdust supplemented by rice bran, wheat bran, cattle manure and various combinations of these materials as nutrient sources. The substrates of poplar sawdust 10 plus rice bran 3 and 2 or wheat bran 3 with a higher yield of fresh sporophores showed a comparatively higher content of total nitrogen. total sugar, and potassium. 2. The mycelial growth of the fungus was compared on the substrates of poplar sawdust supplemented by the several nutrient sources and poplar sawdust alone. The fastest linear growth occurred on substrates of poplar sawdust alone and poplar sawdust plus cattle manure deficient in sugar and nitrogen sources, but mycelial density was more sparse on the substrates. Also, growth in a solution extracted from these substrates was very meager. 3. In the substrates which varied with bulk density and moisture content optimum bulk density and moisture content for mycelial growth was 0.2g/cc and 72% on a dry weight basis, respectively, but the highest yield of fresh sporophores was obtained at the bulk density of 0.3g/cc and moisture content of 67%. 4. By increasing the ratio of rice bran in poplar sawdust the loss of total weight and ash, content at each stage was increased, and during the cultivation period of 75 days, loss of total weight of the substrates at inoculation was 17.8 to 28.8% and ash content increased about 12%. 5. 11 to 14% of the cellulose and 3 to 4% of the lignin content per original substrate were decreased without a great difference depending of the mixing ratio of rice bran. The soluble glucose concentration in the substrates was increased during the same period. 6. In the process of vegetative and reproductive growth of the fungus upon the substrates, the total nitrogen was increased in quantity per dry weight of sample but was reduced in absolute quantity to a minute extent. There is no great changes in content of organic nitrogen including amino acid nitrogen, and hydrolysable ammonium nitrogen during the vegetative growth period, but occurrence of sporophores resulted in a decrease in the nitrogen content of these forms. On the one hand, by an increase of additive amounts of rice bran, nitrogen contents of these forms were higher and the reduction range during the reproductive growth period became wider. 7. Mycelial growth of the fungus was accelerated in various liquid media supplemented with organic nitrogen sources such as peptone and yeast extract in comparison with addition of inorganic nitrogen sources. Furthermore, mycelial growth was mere vigorous in the media with higher content of organic nitrogen sources.

• The Journal of Korean Society for Radiation Therapy
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• v.29 no.2
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• pp.101-108
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• 2017

Purpose: The proton used in proton therapy has a characteristic of giving a small dose to the normal tissue in front of the tumor site while forming a Bragg peak at the cancer tissue site and giving up the maximum dose and disappearing immediately. It is very important to verify the proton arrival position. In this study, we used the off-line PET CT method to measure the distribution of positron emitted from nucleons such as 11C (half-life = 20 min), 150 (half-life = 2 min) and 13N The range and distal falloff point of the proton were verified by measurement. Materials and Methods: In the IEC 2001 Body Phantom, 37 mm, 28 mm, and 22 mm spheres were inserted. The phantom was filled with water to obtain a CT image for each sphere size. To verify the proton range and distal falloff points, As a treatment planning system, SOBP were set at 46 mm on 37 mm sphere, 37 mm on 28 mm, and 33 mm on 22 mm sphere for each sphere size. The proton was scanned in the same center with a single beam of Gantry 0 degree by the scanning method. The phantom was scanned using PET-CT equipment. In the PET-CT image acquisition method, 50 images were acquired per minute, four ROIs including the spheres in the phantom were set, and 10 images were reconstructed. The activity profile according to the depth was compared to the dose profile according to the sphere size established in the treatment plan Results: The PET-CT activity profile decreased rapidly at the distal falloff position in the 37 mm, 28 mm, and 22 mm spheres as well as the dose profile. However, in the SOBP section, which is a range for evaluating the range, the results in the proximal part of the activity profile are different from those of the dose profile, and the distal falloff position is compared with the proton therapy plan and PET-CT As a result, the maximum difference of 1.4 mm at the 50 % point of the Max dose, 1.1 mm at the 45 % point at the 28 mm sphere, and the difference at the 22 mm sphere at the maximum point of 1.2 mm were all less than 1.5 mm in the 37 mm sphere. Conclusion: To maximize the advantages of proton therapy, it is very important to verify the range of the proton beam. In this study, the proton range was confirmed by the SOBP and the distal falloff position of the proton beam using PET-CT. As a result, the difference of the distally falloff position between the activity distribution measured by PET-CT and the proton therapy plan was 1.4 mm, respectively. This may be used as a reference for the dose margin applied in the proton therapy plan.

• Korean Journal of Soil Science and Fertilizer
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• v.10 no.3
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• pp.189-201
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• 1977

Some of basic aspects of soil potassium with special reference to soil physical properties were discussed. Data in the Official Soil Series Description(Korea) was analyzed according to soil type, land form, and soil texture to find soil potassium status which may explain different response to potassium application. Exchangeable potassium contents decreased with soil depth irrespective of soil type, land form and soil texture. Change in degree of potassium saturation within soil profile was not so clear as exchangeable potassium but the degree of potassium saturation of A horizon was highest among soil horizon. Soils of terrace and mountain foot slope showed high values both in exchangeable potassium and degree of potassium sauration and only these two soils were classified as soils having exchangeable potassium higher than 0.3 meq per 100g of soil and degree of potassium saturation higher than 5.0%. Exchangeable potassium of fine loamy and fine clayey soils is higher than 0.3 meq per 100g of soil but degree of potassium saturation is lower than 4.0%. Degree of potassium saturation of sandy soils exceeds 5.0% but exchangeable potassium is very low. Soils of rolling, hilly, unmatured and alpine land soils have lower exchangeable potassium and show lower degree of potassium saturation. The highest distribution of exchangeable potassium content irrespective of soil horizons was shown in the range of 0.1-0.2 meq per 100g of soil. The highest distribution of degree of potassium saturation was in the range of 2.0-3.0% in A horizon and 1.0-2.0% in B and C horizons. Of the soil series concerned in this analysis, 27.3% in A horizon, 11.1% in B horizon and 4.0% in C horizon had exchangeable potassium higher than 0.3 meq per 100g of soil and 18.0% in A horizon, 6.3% in B horizon, and 4.1% in C horizon showed degree of potassium saturation higher than 5.0%. The low response of potassium application only to soils in terrace and mountain foot slope may be resulted from the high exchangeable potassium content and high degree of potassium saturation. It is concluded that a great response of potassium application to soils is expected especially in dry season.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.111-124
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• 2018

This study aims to develop a classification model for predicting the occurrence of hyperlipidemia, one of the chronic diseases. Prior studies applying data mining techniques for predicting disease can be classified into a model design study for predicting cardiovascular disease and a study comparing disease prediction research results. In the case of foreign literatures, studies predicting cardiovascular disease were predominant in predicting disease using data mining techniques. Although domestic studies were not much different from those of foreign countries, studies focusing on hypertension and diabetes were mainly conducted. Since hypertension and diabetes as well as chronic diseases, hyperlipidemia, are also of high importance, this study selected hyperlipidemia as the disease to be analyzed. We also developed a model for predicting hyperlipidemia using SVM and meta learning algorithms, which are already known to have excellent predictive power. In order to achieve the purpose of this study, we used data set from Korea Health Panel 2012. The Korean Health Panel produces basic data on the level of health expenditure, health level and health behavior, and has conducted an annual survey since 2008. In this study, 1,088 patients with hyperlipidemia were randomly selected from the hospitalized, outpatient, emergency, and chronic disease data of the Korean Health Panel in 2012, and 1,088 nonpatients were also randomly extracted. A total of 2,176 people were selected for the study. Three methods were used to select input variables for predicting hyperlipidemia. First, stepwise method was performed using logistic regression. Among the 17 variables, the categorical variables(except for length of smoking) are expressed as dummy variables, which are assumed to be separate variables on the basis of the reference group, and these variables were analyzed. Six variables (age, BMI, education level, marital status, smoking status, gender) excluding income level and smoking period were selected based on significance level 0.1. Second, C4.5 as a decision tree algorithm is used. The significant input variables were age, smoking status, and education level. Finally, C4.5 as a decision tree algorithm is used. In SVM, the input variables selected by genetic algorithms consisted of 6 variables such as age, marital status, education level, economic activity, smoking period, and physical activity status, and the input variables selected by genetic algorithms in artificial neural network consist of 3 variables such as age, marital status, and education level. Based on the selected parameters, we compared SVM, meta learning algorithm and other prediction models for hyperlipidemia patients, and compared the classification performances using TP rate and precision. The main results of the analysis are as follows. First, the accuracy of the SVM was 88.4% and the accuracy of the artificial neural network was 86.7%. Second, the accuracy of classification models using the selected input variables through stepwise method was slightly higher than that of classification models using the whole variables. Third, the precision of artificial neural network was higher than that of SVM when only three variables as input variables were selected by decision trees. As a result of classification models based on the input variables selected through the genetic algorithm, classification accuracy of SVM was 88.5% and that of artificial neural network was 87.9%. Finally, this study indicated that stacking as the meta learning algorithm proposed in this study, has the best performance when it uses the predicted outputs of SVM and MLP as input variables of SVM, which is a meta classifier. The purpose of this study was to predict hyperlipidemia, one of the representative chronic diseases. To do this, we used SVM and meta-learning algorithms, which is known to have high accuracy. As a result, the accuracy of classification of hyperlipidemia in the stacking as a meta learner was higher than other meta-learning algorithms. However, the predictive performance of the meta-learning algorithm proposed in this study is the same as that of SVM with the best performance (88.6%) among the single models. The limitations of this study are as follows. First, various variable selection methods were tried, but most variables used in the study were categorical dummy variables. In the case with a large number of categorical variables, the results may be different if continuous variables are used because the model can be better suited to categorical variables such as decision trees than general models such as neural networks. Despite these limitations, this study has significance in predicting hyperlipidemia with hybrid models such as met learning algorithms which have not been studied previously. It can be said that the result of improving the model accuracy by applying various variable selection techniques is meaningful. In addition, it is expected that our proposed model will be effective for the prevention and management of hyperlipidemia.

• Progress in Medical Physics
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• v.22 no.3
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• pp.140-147
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• 2011

The purpose of this study was to estimate internal motion using molecular sieve for quantitative improvement of lung tumor and to localize lung tumor in the small animal PET image by evaluated data. Internal motion has been demonstrated in small animal lung region by molecular sieve contained radioactive substance. Molecular sieve for internal lung motion target was contained approximately 37 kBq Cu-64. The small animal PET images were obtained from Siemens Inveon scanner using external trigger system (BioVet). SD-Rat PET images were obtained at 60 min post injection of FDG 37 MBq/0.2 mL via tail vein for 20 min. Each line of response in the list-mode data was converted to sinogram gated frames (2~16 bin) by trigger signal obtained from BioVet. The sinogram data was reconstructed using OSEM 2D with 4 iterations. PET images were evaluated with count, SNR, FWHM from ROI drawn in the target region for quantitative tumor analysis. The size of molecular sieve motion target was $1.59{\times}2.50mm$. The reference motion target FWHM of vertical and horizontal was 2.91 mm and 1.43 mm, respectively. The vertical FWHM of static, 4 bin and 8 bin was 3.90 mm, 3.74 mm, and 3.16 mm, respectively. The horizontal FWHM of static, 4 bin and 8 bin was 2.21 mm, 2.06 mm, and 1.60 mm, respectively. Count of static, 4 bin, 8 bin, 12 bin and 16 bin was 4.10, 4.83, 5.59, 5.38, and 5.31, respectively. The SNR of static, 4 bin, 8 bin, 12 bin and 16 bin was 4.18, 4.05, 4.22, 3.89, and 3.58, respectively. The FWHM were improved in accordance with gate number increase. The count and SNR were not proportionately improve with gate number, but shown the highest value in specific bin number. We measured the optimal gate number what minimize the SNR loss and gain improved count when imaging lung tumor in small animal. The internal motion estimation provide localized tumor image and will be a useful method for organ motion prediction modeling without external motion monitoring system.

• Journal of Preventive Medicine and Public Health
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• v.24 no.3 s.35
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• pp.441-458
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• 1991

The objective of this study was to provide basic reference data for stabilization scheme of medical insurance benefits through forecasting of the medical care utilization rate, the medical expence per case, and the treatment days per case in medical insurance program for government employees & private school teachers and for industrial workers. For the achievement of above objective, this study was carried out by Box-Jenkins time series analysis (ARIMA Model), using monthly statistical data from Jan. 1979 to Dec. 1989, of medical insurance program for government employees & private school teachers and for industrial workers. The results are as follows ; ARIMA model of the medical care utilization rate in medical insurance program for government employees & private school teachers was ARIMA (1, 1, 1) and it for outpatient in medical insurance program for industrial workers was ARIMA (1, 1, 1), while it for inpatient in medical insurance program for industrial workers was ARIMA (1, 0, 1). ARIMA model of the medical expense per case in medical insurance program for government employees & private school teachers and for outpatient in medical insurance program for industrial workers were ARIMA (1, 1, 0), while it for inpatient in medical insurance program for industrial workers was ARIMA (1, 0, 1). ARIMA model of the treatment days per case of both medical insurance program for government employees & private school teachers and industrial workers were ARIMA (1, 1, 1). Forecasting value of the medical care utilzation rate for inpatient in medical insurance program for government employees & private school teachers was 0.0061 at dec. 1989, 0.0066 at dec. 1994 and it for outpatient was 0.280 at dec. 1989, 0.294 at dec. 1994, while it for inpatient in medical insurance program for industrial workers was 0.0052 at dec. 1989, 0.0056 at dec. 1994 and it for outpatient was 0.203 at dec. 1989, 0.215 at 1994. Forecasting value of the medical expense per case for inpatient in medical insurance program for government employees & private school teachers was 332,751 at dec. 1989, 354,511 at dec. 1994 and it for outpatient was 11,925 at dec. 1989, 12,904 at dec. 1994, while it for inpatient in medical insurance program for industrial workers was 281,835 at dec. 1989, 293,973 at dec. 1994 and it for outpatient was 11,599 at dec. 1989, 11,585 at 1994. Forecasting value of the treatment days per case for inpatient in medical insurance program for government employees & private school teachers was 13.79 at dec. 1989,13.85 at an. 1994 and in for outpatient was 5.03 at dec. 1989, 5.00 at dec. 1994, while it for inpatient in medical insurance program for industrial workers was 12.23 at dec. 1989, 12.85 at dec. 1994 and it for outpatient was 4.61 at dec. 1989, 4.60 at 1994.

• Nuclear Medicine and Molecular Imaging
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• v.43 no.1
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• pp.10-18
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• 2009

Purpose: We investigated quantification of dopaminergic transporter (DAT) and serotonergic transporter (SERT) on $^{123}I$-FP-CIT SPECT for differentiating between multiple systemic atrophy (MSA) and idiopathic Parkinson's disease (IPD). Materials and Methods: N-fluoropropyl-$2{\beta}$-carbomethoxy-$3{\beta}$-4-[$^{123}I$]-iodophenylnortropane SPECT ($^{123}I$-FP-CIT SPECT) was performed in 8 patients with MSA (mean age: $64.0{\pm}4.5yrs$, m:f=6:2), 13 with early IPD (mean age: $65.5{\pm}5.3yrs$, m:f=9:4), and 12 healthy controls (mean age: $63.3{\pm}5.7yrs$, m:f=8:4). Standard regions of interests (ROls) of striatum to evaluate DAT, and hypothalamus and midbrain for SERT were drawn on standard template images and applied to each image taken 4 hours after radiotracer injection. Striatal specific binding for DAT and hypothalamic and midbrain specific binding for SERT were calculated using region/reference ratio based on the transient equilibrium method. Group differences were tested using ANOVA with the postHoc analysis. Results: DAT in the whole striatum and striatal subregions were significantly decreased in both patient groups with MSA and early IPD, compared with healthy control (p<0.05 in all). In early IPD, a significant increase in the uptake ratio in anterior and posterior putamen and a trend of increase in caudate to putamen ratio was observed. In MSA, the decrease of DAT was accompanied with no difference in the striatal uptake pattern compared with healthy controls. Regarding the brain regions where $^{123}I$-FP-CIT binding was predominant by SERT, MSA patients showed a decrease in the binding of $^{123}I$-FP-CIT in the pons compared with controls as well as early IPD patients (MSA: $0.22{\pm}0.1$ healthy controls: $0.33{\pm}0.19$, IPD: $0.29{\pm}0.19$), however, it did not reach the statistical significance. Conclusion: In this study, the differential patterns in the reduction of DAT in the striatum and the reduction of pontine $^{123}I$-FP-CIT binding predominant by SERT could be observed in MSA patients on $^{123}I$-FP-CIT SPECT. We suggest that the quantification of SERT as well as DAT using $^{123}I$-FP-CIT SPECT is helpful to differentiate parkinsonian disorders in early stage.