• Journal of Astronomy and Space Sciences
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• v.36 no.1
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• pp.21-33
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• 2019

This paper focuses on the interpretation of radiation fluxes from active galactic nuclei. The advantage of positron annihilation spectroscopy over other methods of spectral diagnostics of active galactic nuclei (therefore AGN) is demonstrated. A relationship between regular and random components in both bolometric and spectral composition of fluxes of quanta and particles generated in AGN is found. We consider their diffuse component separately and also detect radiative feedback after the passage of high-velocity cosmic rays and hard quanta through gas-and-dust aggregates surrounding massive black holes in AGN. The motion of relativistic positrons and electrons in such complex systems produces secondary radiation throughout the whole investigated region of active galactic nuclei in form of cylinder with radius R= 400-1000 pc and height H=200-400 pc, thus causing their visible luminescence across all spectral bands. We obtain radiation and electron energy distribution functions depending on the spatial distribution of the investigated bulk of matter in AGN. Radiation luminescence of the non-central part of AGN is a response to the effects of particles and quanta falling from its center created by atoms, molecules and dust of its diffuse component. The cross-sections for the single-photon annihilation of positrons of different energies with atoms in these active galactic nuclei are determined. For the first time we use the data on the change in chemical composition due to spallation reactions induced by high-energy particles. We establish or define more accurately how the energies of the incident positron, emitted ${\gamma}-quantum$ and recoiling nucleus correlate with the atomic number and weight of the target nucleus. For light elements, we provide detailed tables of all indicated parameters. A new criterion is proposed, based on the use of the ratio of the fluxes of ${\gamma}-quanta$ formed in one- and two-photon annihilation of positrons in a diffuse medium. It is concluded that, as is the case in young supernova remnants, the two-photon annihilation tends to occur in solid-state grains as a result of active loss of kinetic energy of positrons due to ionisation down to thermal energy of free electrons. The single-photon annihilation of positrons manifests itself in the gas component of active galactic nuclei. Such annihilation occurs as interaction between positrons and K-shell electrons; hence, it is suitable for identification of the chemical state of substances comprising the gas component of the investigated media. Specific physical media producing high fluxes of positrons are discussed; it allowed a significant reduction in the number of reaction channels generating positrons. We estimate the brightness distribution in the ${\gamma}-ray$ spectra of the gas-and-dust media through which positron fluxes travel with the energy range similar to that recorded by the Payload for Antimatter Matter Exploration and Light-nuclei Astrophysics (PAMELA) research module. Based on the results of our calculations, we analyse the reasons for such a high power of positrons to penetrate through gas-and-dust aggregates. The energy loss of positrons by ionisation is compared to the production of secondary positrons by high-energy cosmic rays in order to determine the depth of their penetration into gas-and-dust aggregations clustered in active galactic nuclei. The relationship between the energy of ${\gamma}-quanta$ emitted upon the single-photon annihilation and the energy of incident electrons is established. The obtained cross sections for positron interactions with bound electrons of the diffuse component of the non-central, peripheral AGN regions allowed us to obtain new spectroscopic characteristics of the atoms involved in single-photon annihilation.

• Journal of Bio-Environment Control
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• v.31 no.3
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• pp.221-229
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• 2022

This study was aimed to investigate spatial and vertical characteristics of greenhouse environments according to the location of the environmental sensors, and to investigate the correlations between temperature, light intensity, and carbon dioxide (CO₂) concentration according to the type of greenhouse. Temperature, relative humidity (RH), CO₂, and light sensors were installed in the four-different vertical positions of the whole canopy as well as ground and roof space at the five spatial locations of the Venlo greenhouse. Also, correlations between temperature, light intensity, and CO₂ concentration in Venlo and semi-closed greenhouses were analyzed using the Curve Expert Professional program. The deviations among the spatial locations were larger in the CO₂ concentration than other environmental factors in the Venlo greenhouse. The average CO₂ concentration ranged from 465 to 761 µmol·mol^-1 with the highest value (646 µmol·mol^-1) at the Middle End (4ME) close to the main pipe (50Ø) of the liquefied CO₂ gas supply and lowest (436 µmol·mol^-1) at the Left Middle (5LM). The deviation among the vertical positions was greater in temperature and relative humidity than other environments. The time zone with the largest deviation in average temperature was 2 p.m. with the highest temperature (26.51℃) at the Upper Air (UA) and the lowest temperature (25.62℃) at the Lower Canopy (LC). The time zone with the largest deviation in average RH was 1 p.m. with the highest RH (76.90%) at the LC and the lowest RH (71.74%) at the UA. The highest average CO₂ concentration at each hour was Roof Air (RF) and Ground (GD). The coefficient of correlations between temperature, light intensity, and CO₂ concentration were 0.07 for semi-closed greenhouse and 0.66 for Venlo greenhouse. All the results indicate that while the CO₂ concentration in the greenhouse needs to be analyzed in the spatial locations, temperature and humidity needs to be analyzed in the vertical positions of canopy. The target CO₂ fertilization concentration for the semi-closed greenhouse with low ventilation rate should be different from that of general greenhouses.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.221-241
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• 2018

Deep learning is getting attention recently. The deep learning technique which had been applied in competitions of the International Conference on Image Recognition Technology(ILSVR) and AlphaGo is Convolution Neural Network(CNN). CNN is characterized in that the input image is divided into small sections to recognize the partial features and combine them to recognize as a whole. Deep learning technologies are expected to bring a lot of changes in our lives, but until now, its applications have been limited to image recognition and natural language processing. The use of deep learning techniques for business problems is still an early research stage. If their performance is proved, they can be applied to traditional business problems such as future marketing response prediction, fraud transaction detection, bankruptcy prediction, and so on. So, it is a very meaningful experiment to diagnose the possibility of solving business problems using deep learning technologies based on the case of online shopping companies which have big data, are relatively easy to identify customer behavior and has high utilization values. Especially, in online shopping companies, the competition environment is rapidly changing and becoming more intense. Therefore, analysis of customer behavior for maximizing profit is becoming more and more important for online shopping companies. In this study, we propose 'CNN model of Heterogeneous Information Integration' using CNN as a way to improve the predictive power of customer behavior in online shopping enterprises. In order to propose a model that optimizes the performance, which is a model that learns from the convolution neural network of the multi-layer perceptron structure by combining structured and unstructured information, this model uses 'heterogeneous information integration', 'unstructured information vector conversion', 'multi-layer perceptron design', and evaluate the performance of each architecture, and confirm the proposed model based on the results. In addition, the target variables for predicting customer behavior are defined as six binary classification problems: re-purchaser, churn, frequent shopper, frequent refund shopper, high amount shopper, high discount shopper. In order to verify the usefulness of the proposed model, we conducted experiments using actual data of domestic specific online shopping company. This experiment uses actual transactions, customers, and VOC data of specific online shopping company in Korea. Data extraction criteria are defined for 47,947 customers who registered at least one VOC in January 2011 (1 month). The customer profiles of these customers, as well as a total of 19 months of trading data from September 2010 to March 2012, and VOCs posted for a month are used. The experiment of this study is divided into two stages. In the first step, we evaluate three architectures that affect the performance of the proposed model and select optimal parameters. We evaluate the performance with the proposed model. Experimental results show that the proposed model, which combines both structured and unstructured information, is superior compared to NBC(Naïve Bayes classification), SVM(Support vector machine), and ANN(Artificial neural network). Therefore, it is significant that the use of unstructured information contributes to predict customer behavior, and that CNN can be applied to solve business problems as well as image recognition and natural language processing problems. It can be confirmed through experiments that CNN is more effective in understanding and interpreting the meaning of context in text VOC data. And it is significant that the empirical research based on the actual data of the e-commerce company can extract very meaningful information from the VOC data written in the text format directly by the customer in the prediction of the customer behavior. Finally, through various experiments, it is possible to say that the proposed model provides useful information for the future research related to the parameter selection and its performance.

• Journal of Dairy Science and Biotechnology
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• v.34 no.2
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• pp.99-116
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• 2016

We herein performed animal safety assessment in accordance with Good Laboratory Practice (GLP) regulations with the aim of developing sialic acid from glycomacropeptide (hereafter referred to as "GMP") as an index ingredient and functional component in functional foods. GMP is a type of whey protein derived from milk and a safe food, with multiple functions, such as antiviral activity. A test substance was produced containing 7% (w/w) sialic acid and mostly-hydrolyzed whey protein (hereafter referred to as "7%-GNANA") by enzymatic treatment of substrate GMP. The maximum intake test dose level was selected based on 5,000 mg/kg/day dose set for male NOEL (no-observed-effect-level) and female NOAEL (no-observed-adverse-effect-level) determined by a dose-range finding (DRF) test (GLP Center of Catholic University of Daegu, Report No. 15-NREO-001) that was previously conducted with the same test substance. To evaluate the toxicity of a repeated oral dose of the test substance in connection with the previous DRF study, 1,250, 2,500, and 5,000 mg/kg of the substance were administered by a probe into the stomachs of 6-week-old SPF Sprague-Dawley male and female rats for 90 d. Each test group consisted of 10 male and 10 female rats. To determine the toxicity index, all parameters, such as observation of common signs; measurements of body weight and food consumption; ophthalmic examination; urinalysis, electrolyte, hematological, and serum biochemical examination; measurement of organ weights during autopsy; and visual and histopathological examinations were conducted according to GLP standards. After evaluating the results based on the test toxicity assessment criteria, it was determined that NOAEL of the test substance, 7%-GNANA, was 5,000 mg/kg/day, for both male and female rats. No animal death was noted in any of the test groups, including the control group, during the study period, and there was no significant difference associated with test substance, as compared with the control group, with respect to general symptoms, body weight changes, food consumption, ophthalmic examination, urinalysis, hematological and serum biochemical examination, and electrolyte and blood coagulation tests during the administration period (P<0.05). As assessed by the effects of the test substance on organ weights, food consumption, autopsy, and histopathological safety, change in kidney weight as an indicator of male NOAEL revealed up to 20% kidney weight increase in the high-dose group (5,000 mg/kg/day) compared with the change in the control group. However, it was concluded that this effect of the test substance was minor. In the case of female rats, reduction of food consumption, increase of kidney weight, and decrease of thymus weight were observed in the high-dose group. The kidney weight increased by 10.2% (left) and 8.9% (right) in the high-dose group, with a slight dose-dependency compared with that of the control group. It was observed that the thymus weight decreased by 25.3% in the high-dose group, but it was a minor test substance-associated effect. During the autopsy, botryoid tumor was detected on the ribs of one subject in the high-dose group, but we concluded that the tumor has been caused by a naturally occurring (non-test) substance. Histopathological examination revealed lesions on the kidney, liver, spleen, and other organs in the low-dose test group. Since these lesions were considered a separate phenomenon, or naturally occurring and associated with aging, it was checked whether any target organ showed clear symptoms caused by the test substance. In conclusion, different concentrations of the test substance were fed to rats and, consequently, it was verified that only a minor effect was associated with the test substance in the high-dose (5,000 mg/kg/day) group of both male and female rats, without any other significant effects associated with the test substance. Therefore, it was concluded that NOAEL of 7%-GNANA (product name: Helicobactrol) with male and female rats as test animals was 5,000 mg/kg/day, and it thus was determined that the substance is safe for the ultimate use as an ingredient of health functional foods.

• Radiation Oncology Journal
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• v.15 no.4
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• pp.393-402
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• 1997

Purpose : When an x-ray beam of small field size is irradiated to target area containing an air cavity, such as larynx, the underdosing effect is observed in the region near the interfaces of air and soft tissue. With a larynx model, air cavity embedded in tissue-equivalent material, this study is intonded for examining Parameters, such as beam quality, field size, and cavity size, to affect the dose distribution near the air cavity. Materials and Methods : Three x-rar beams, 4-, 6- and 10-MV, were employed to Perform a measurement using a 2cm $(width){\times}L$ (length in cm, one side of x-ray field used 2cm (height) air cavity in the simulated larynx. A thin window parallel-plate chamber connected to an electrometer was used for a dosimetry system. A ratio of the dose at various distances from the cavity-tissue interface to the dose at the same points in a homogeneous Phantom (ebservedlexpected ratio, O/E) normalized buildup curves, and ratio of distal surface dose to dose at the maximum buildup depth were examined for various field sizes. Measurement for cavity size effect was performed by varying the height (Z) of the air cavity with the width kept constant for several field sizes. Results : No underdosing effect for 4-MV beam for fields larger than $5cm\times5cm$ was found For both 6- and 10-MV beams, the underdosing portion of the larynx at the distal surface was seen to occur for small fields, $4cm\times4cm\;and\;5cm\times5cm$. The underdosed tissue was increased in its volume with beam energy even for similar surface doses. The relative distal surface dose to maximum dose was changed to 0.99 from 0.95, 0.92, and 0.91 for 4-, 6-, and 10-MV, respectively, with increasing field size, $4cm\times4cm\;to\;8cm\times8cm$, For 6- and 10-MV beams, the dose at the surface of the cavity is measured less than the predicted by about two and three percent. respectively. but decrease was found for 4-MV beam for $5cm\times5cm$ field. For the $4cm\timesL\timesZ$ (height in cm). varying depth from 0.0 to 4.8cm, cavity, O/E> 1.0 was observed regardless of the cavity size for any field larger than about $8cm\times8cm$. Conclusion : The magnitude of underdosing depends on beam energy, field size. and cavity size for the larynx model. Based on the result of the study. caution must be used when a small field of a high quality x-ray beam is irradiated to regions including air cavities. and especially the region where the tumor extends to the surface. Low quality beam. such as. 4-MV x-ray, and larger fields can be used preferably to reduce the risk of underdosing, local failure. In the case of high quality beams such as 6- and 10-MV x-rays, however. an additional boost field is recommended to add for the compensation of the underdosing region when a typically used treatment field. $8cm\times8cm$, is employed.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.171-183
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• 2012

In the development of technologies, the exhibition industry has received much attention from governments and companies as an important way of marketing activities. Also, the exhibitors have considered the exhibition as new channels of marketing activities. However, the growing size of exhibitions for net square feet and the number of visitors naturally creates the competitive environment for them. Therefore, to make use of the effective marketing tools in these environments, they have planned and implemented many promotion technics. Especially, through smart environment which makes them provide real-time information for visitors, they can implement various kinds of promotion. However, promotions ignoring visitors' various needs and preferences can lose the original purposes and functions of them. That is, as indiscriminate promotions make visitors feel like spam, they can't achieve their purposes. Therefore, they need an approach using STP strategy which segments visitors through right evidences (Segmentation), selects the target visitors (Targeting), and give proper services to them (Positioning). For using STP Strategy in the smart exhibition environment, we consider these characteristics of it. First, an exhibition is defined as market events of a specific duration, which are held at intervals. According to this, exhibitors who plan some promotions should different events and promotions in each exhibition. Therefore, when they adopt traditional STP strategies, a system can provide services using insufficient information and of existing visitors, and should guarantee the performance of it. Second, to segment automatically, cluster analysis which is generally used as data mining technology can be adopted. In the smart exhibition environment, information of visitors can be acquired in real-time. At the same time, services using this information should be also provided in real-time. However, many clustering algorithms have scalability problem which they hardly work on a large database and require for domain knowledge to determine input parameters. Therefore, through selecting a suitable methodology and fitting, it should provide real-time services. Finally, it is needed to make use of data in the smart exhibition environment. As there are useful data such as booth visit records and participation records for events, the STP strategy for the smart exhibition is based on not only demographical segmentation but also behavioral segmentation. Therefore, in this study, we analyze a case of the promotion methodology which exhibitors can provide a differentiated service to segmented visitors in the smart exhibition environment. First, considering characteristics of the smart exhibition environment, we draw evidences of segmentation and fit the clustering methodology for providing real-time services. There are many studies for classify visitors, but we adopt a segmentation methodology based on visitors' behavioral traits. Through the direct observation, Veron and Levasseur classify visitors into four groups to liken visitors' traits to animals (Butterfly, fish, grasshopper, and ant). Especially, because variables of their classification like the number of visits and the average time of a visit can estimate in the smart exhibition environment, it can provide theoretical and practical background for our system. Next, we construct a pilot system which automatically selects suitable visitors along the objectives of promotions and instantly provide promotion messages to them. That is, based on the segmentation of our methodology, our system automatically selects suitable visitors along the characteristics of promotions. We adopt this system to real exhibition environment, and analyze data from results of adaptation. As a result, as we classify visitors into four types through their behavioral pattern in the exhibition, we provide some insights for researchers who build the smart exhibition environment and can gain promotion strategies fitting each cluster. First, visitors of ANT type show high response rate for promotion messages except experience promotion. So they are fascinated by actual profits in exhibition area, and dislike promotions requiring a long time. Contrastively, visitors of GRASSHOPPER type show high response rate only for experience promotion. Second, visitors of FISH type appear favors to coupon and contents promotions. That is, although they don't look in detail, they prefer to obtain further information such as brochure. Especially, exhibitors that want to give much information for limited time should give attention to visitors of this type. Consequently, these promotion strategies are expected to give exhibitors some insights when they plan and organize their activities, and grow the performance of them.

• Journal of Intelligence and Information Systems
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• v.24 no.4
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• pp.137-154
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• 2018

Animal infectious diseases, such as avian influenza and foot and mouth disease, occur almost every year and cause huge economic and social damage to the country. In order to prevent this, the anti-quarantine authorities have tried various human and material endeavors, but the infectious diseases have continued to occur. Avian influenza is known to be developed in 1878 and it rose as a national issue due to its high lethality. Food and mouth disease is considered as most critical animal infectious disease internationally. In a nation where this disease has not been spread, food and mouth disease is recognized as economic disease or political disease because it restricts international trade by making it complex to import processed and non-processed live stock, and also quarantine is costly. In a society where whole nation is connected by zone of life, there is no way to prevent the spread of infectious disease fully. Hence, there is a need to be aware of occurrence of the disease and to take action before it is distributed. Epidemiological investigation on definite diagnosis target is implemented and measures are taken to prevent the spread of disease according to the investigation results, simultaneously with the confirmation of both human infectious disease and animal infectious disease. The foundation of epidemiological investigation is figuring out to where one has been, and whom he or she has met. In a data perspective, this can be defined as an action taken to predict the cause of disease outbreak, outbreak location, and future infection, by collecting and analyzing geographic data and relation data. Recently, an attempt has been made to develop a prediction model of infectious disease by using Big Data and deep learning technology, but there is no active research on model building studies and case reports. KT and the Ministry of Science and ICT have been carrying out big data projects since 2014 as part of national R &D projects to analyze and predict the route of livestock related vehicles. To prevent animal infectious diseases, the researchers first developed a prediction model based on a regression analysis using vehicle movement data. After that, more accurate prediction model was constructed using machine learning algorithms such as Logistic Regression, Lasso, Support Vector Machine and Random Forest. In particular, the prediction model for 2017 added the risk of diffusion to the facilities, and the performance of the model was improved by considering the hyper-parameters of the modeling in various ways. Confusion Matrix and ROC Curve show that the model constructed in 2017 is superior to the machine learning model. The difference between the2016 model and the 2017 model is that visiting information on facilities such as feed factory and slaughter house, and information on bird livestock, which was limited to chicken and duck but now expanded to goose and quail, has been used for analysis in the later model. In addition, an explanation of the results was added to help the authorities in making decisions and to establish a basis for persuading stakeholders in 2017. This study reports an animal infectious disease prevention system which is constructed on the basis of hazardous vehicle movement, farm and environment Big Data. The significance of this study is that it describes the evolution process of the prediction model using Big Data which is used in the field and the model is expected to be more complete if the form of viruses is put into consideration. This will contribute to data utilization and analysis model development in related field. In addition, we expect that the system constructed in this study will provide more preventive and effective prevention.

• The Journal of Korean Society for Radiation Therapy
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• v.28 no.2
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• pp.171-178
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• 2016

Purpose : In order to minimize the dose of femoral head as an appropriate treatment plan for rectal cancer radiation therapy, we compare and evaluate the usefulness of 3-field 3D conformal radiation therapy(below 3fCRT), which is a universal treatment method, and 5-field 3D conformal radiation therapy(below 5fCRT), and Volumetric Modulated Arc Therapy (VMAT). Materials and Methods : The 10 cases of rectal cancer that treated with 21EX were enrolled. Those cases were planned by Eclipse(Ver. 10.0.42, Varian, USA), PRO3(Progressive Resolution Optimizer 10.0.28) and AAA(Anisotropic Analytic Algorithm Ver. 10.0.28). 3fCRT and 5fCRT plan has $0^{\circ}$, $270^{\circ}$, $90^{\circ}$ and $0^{\circ}$, $95^{\circ}$, $45^{\circ}$, $315^{\circ}$, $265^{\circ}$ gantry angle, respectively. VMAT plan parameters consisted of 15MV coplanar $360^{\circ}$ 1 arac. Treatment prescription was employed delivering 54Gy to recum in 30 fractions. To minimize the dose difference that shows up randomly on optimizing, VMAT plans were optimized and calculated twice, and normalized to the target V100%=95%. The indexes of evaluation are D of Both femoral head and aceta fossa, total MU, H.I.(Homogeneity index) and C.I.(Conformity index) of the PTV. All VMAT plans were verified by gamma test with portal dosimetry using EPID. Results : D of Rt. femoral head was 53.08 Gy, 50.27 Gy, and 30.92 Gy, respectively, in the order of 3fCRT, 5fCRT, and VMAT treatment plan. Likewise, Lt. Femoral head showed average 53.68 Gy, 51.01 Gy and 29.23 Gy in the same order. D of Rt. aceta fossa was 54.86 Gy, 52.40 Gy, 30.37 Gy, respectively, in the order of 3fCRT, 5fCRT, and VMAT treatment plan. Likewise, Lt. Femoral head showed average 53.68 Gy, 51.01 Gy and 29.23 Gy in the same order. The maximum dose of both femoral head and aceta fossa was higher in the order of 3fCRT, 5fCRT, and VMAT treatment plan. C.I. showed the lowest VMAT treatment plan with an average of 1.64, 1.48, and 0.99 in the order of 3fCRT, 5fCRT, and VMAT treatment plan. There was no significant difference on H.I. of the PTV among three plans. Total MU showed that the VMAT treatment plan used 124.4MU and 299MU more than the 3fCRT and 5fCRT treatment plan, respectively. IMRT verification gamma test results for the VMAT plan passed over 90.0% at 2mm/2%. Conclusion : In rectal cancer treatment, the VMAT plan was shown to be advantageous in most of the evaluation indexes compared to the 3D plan, and the dose of the femoral head was greatly reduced. However, because of practical limitations there may be a case where it is difficult to select a VMAT treatment plan. 5fCRT has the advantage of reducing the dose of the femoral head as compared to the existing 3fCRT, without regard to additional problems. Therefore, not only would it extend survival time but the quality of life in general, if hospitals improved radiation therapy efficiency by selecting the treatment plan in accordance with the hospital's situation.

• Journal of Radiation Protection and Research
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• v.32 no.3
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• pp.105-110
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• 2007

Purpose : In spite of recent remarkable improvement of diagnostic imaging modalities such as CT, MRI, and PET and radiation therapy planing systems, ICR plan of uterine cervix cancer, based on recommendation of ICRU38(2D film-based) such as Point A, is still used widely. A 3-dimensional ICR plan based on CT image provides dose-volume histogram(DVH) information of the tumor and normal tissue. In this study, we compared tumor-dose, rectal-dose and bladder-dose through an analysis of DVH between CTV plan and ICRU38 plan based on CT image. Method and Material : We analyzed 11 patients with a cervix cancer who received the ICR of Ir-192 HDR. After 40Gy of external beam radiation therapy, ICR plan was established using PLATO(Nucletron) v.14.2 planing system. CT scan was done to all the patients using CT-simulator(Ultra Z, Philips). We contoured CTV, rectum and bladder on the CT image and established CTV plan which delivers the 100% dose to CTV and ICRU plan which delivers the 100% dose to the point A. Result : The volume$(average{\pm}SD)$ of CTV, rectum and bladder in all of 11 patients is $21.8{\pm}6.6cm^3,\;60.9{\pm}25.0cm^3,\;111.6{\pm}40.1cm^3$ respectively. The volume covered by 100% isodose curve is $126.7{\pm}18.9cm^3$ in ICRU plan and $98.2{\pm}74.5cm^3$ in CTV plan(p=0.0001), respectively. In (On) ICRU planning, $22.0cm^3$ of CTV volume was not covered by 100% isodose curve in one patient whose residual tumor size is greater than 4cm, while more than 100% dose was irradiated unnecessarily to the normal organ of $62.2{\pm}4.8cm^3$ other than the tumor in the remaining 10 patients with a residual tumor less than 4cm in size. Bladder dose recommended by ICRU 38 was $90.1{\pm}21.3%$ and $68.7{\pm}26.6%$ in ICRU plan and in CTV plan respectively(p=0.001) while rectal dose recommended by ICRU 38 was $86.4{\pm}18.3%$ and $76.9{\pm}15.6%$ in ICRU plan and in CTV plan, respectively(p=0.08). Bladder and rectum maximum dose was $137.2{\pm}50.1%,\;101.1{\pm}41.8%$ in ICRU plan and $107.6{\pm}47.9%,\;86.9{\pm}30.8%$ in CTV plan, respectively. Therefore, the radiation dose to normal organ was lower in CTV plan than in ICRU plan. But the normal tissue dose was remarkably higher than a recommended dose in CTV plan in one patient whose residual tumor size was greater than 4cm. The volume of rectum receiving more than 80% isodose (V80rec) was $1.8{\pm}2.4cm^3$ in ICRU plan and $0.7{\pm}1.0cm^3$ in CTV plan(p=0.02). The volume of bladder receiving more than 80% isodose(V80bla) was $12.2{\pm}8.9cm^3$ in ICRU plan and $3.5{\pm}4.1cm^3$ in CTV plan(p=0.005). According to these parameters, CTV plan could also save more normal tissue compared to ICRU38 plan. Conclusion : An unnecessary excessive radiation dose is irradiated to normal tissues within 100% isodose area in the traditional ICRU plan in case of a small size of cervix cancer, but if we use CTV plan based on CT image, the normal tissue dose could be reduced remarkably without a compromise of tumor dose. However, in a large tumor case, we need more research on an effective 3D-planing to reduce the normal tissue dose.