• Title, Summary, Keyword: 모형실험

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Characteristics of Greenhouse Gas Emissions from Charcoal Kiln (숯가마에서 발생하는 온실가스 배출 특성)

  • Lee, Seul-Ki;Jeon, Eui-Chan;Park, Seong-Kyu;Choi, Sang-Jin
    • Journal of Climate Change Research
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    • v.4 no.2
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    • pp.115-126
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    • 2013
  • Recently Korea considers the source of biomass burning emissions reflecting national characteristic, so that includes the inventory of emission source but preceding research is rarely implemented in Korea. Therefore, a study on characteristics of greenhouse gas emissions from biomass burning is necessary and it also makes the source management effectively when the climate-atmospheric management system takes effect. In this study, using the manufactured charcoal kiln and the number of experiment was three times to get a reliable experiment result. The sampling time was decided by changing degree in charcoal kiln and charcoal manufacturing process. The results of calculation greenhouse gas emission factor from charcoal kiln were $668g\;CO_2/kg$, $20g\;CH_4/kg$, $0.01g\;N_2O/kg$. Using the emission factor developed in this study, estimate the emissions from charcoal kiln in Korea. The results of calculation were $46,040ton\;CO_2/yr$, $1,378ton\;CH_4/yr$, $0.69ton\;N_2O/yr$ and greenhouse gas emissions applying GWP are as follows. $CH_4$ emissions was $28,947ton\;CO_2eq./yr$, $N_2O$ emissions was $214ton\;CO_2eq./yr$. As a results, Gross emissions of charcoal kiln in Korea was $75,201ton\;CO_2eq./yr$, but the oak used in this study is included to the biomass so emissions of $CO_2$ are excluded. Therefore the net emissions of charcoal kiln in Korea was $29,161ton\;CO_2eq./yr$.

Debris flow characteristics and sabo dam function in urban steep slopes (도심지 급경사지에서 토석류 범람 특성 및 사방댐 기능)

  • Kim, Yeonjoong;Kim, Taewoo;Kim, Dongkyum;Yoon, Jongsung
    • Journal of Korea Water Resources Association
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    • v.53 no.8
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    • pp.627-636
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    • 2020
  • Debris flow disasters primarily occur in mountainous terrains far from cities. As such, they have been underestimated to cause relatively less damage compared with other natural disasters. However, owing to urbanization, several residential areas and major facilities have been built in mountainous regions, and the frequency of debris flow disasters is steadily increasing owing to the increase in rainfall with environmental and climate changes. Thus, the risk of debris flow is on the rise. However, only a few studies have explored the characteristics of flooding and reduction measures for debris flow in areas designated as steep slopes. In this regard, it is necessary to conduct research on securing independent disaster prevention technology, suitable for the environment in South Korea and reflective of the topographical characteristics thereof, and update and improve disaster prevention information. Accordingly, this study aimed to calculate the amount of debris flow, depending on disaster prevention performance targets for regions designated as steep slopes in South Korea, and develop an independent model to not only evaluate the impact of debris flow but also identify debris barriers that are optimal for mitigating damage. To validate the reliability of the two-dimensional debris flow model developed for the evaluation of debris barriers, the model's performance was compared with that of the hydraulic model. Furthermore, a 2-D debris model was constructed in consideration of the regional characteristics around the steep slopes to analyze the flow characteristics of the debris that directly reaches the damaged area. The flow characteristics of the debris delivered downstream were further analyzed, depending on the specifications (height) and installation locations of the debris barriers employed to reduce the damage. The experimental results showed that the reliability of the developed model is satisfactory; further, this study confirmed significant performance degradation of debris barriers in areas where the barriers were installed at a slope of 20° or more, which is the slope at which debris flows occur.

Development and Evaluation of the PBL Teaching/Learning Process Plan of 'Housing Culture and Practical Space Use' for Home Economics in Middle School (중학교 가정과 문제 중심 '주생활 문화와 주거 공간 활용' 교수·학습 과정안 개발과 평가)

  • Cho, Jiwon;Cho, Jaesoon
    • Journal of Korean Home Economics Education Association
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    • v.32 no.2
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    • pp.59-76
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    • 2020
  • The purpose of this study was to develop and evaluate the teaching/learning process plan of 'housing culture and practical space use' for home economics in middle school according to the problem based learning(PBL) model. The plan consisting of 4-lessons has been developed and implemented following the steps of ADDIE model. Various activity materials (4 scenarios, 6 individual activity sheets, 10 reading texts, and 5 working resources) and visual materials (4 sets of ppt and 4 moving pictures) as well as questionnaire were developed for the 4-session lessons. The plans were implemented to a single class of 21 junior students at H middle school in rural area, Kyeongnam, from 1st to 12th of April, 2019. Students highly enjoyed and were satisfied with the whole 4-lessons in aspects such as understanding of the contents, adequacy of materials and activities, and usefulness in one's own daily life. Additionally, they have more actively participated in the lessons than usual and even interested in learning more of such lessons. Students also reported that they highly accomplished the goal of each lesson as well as overall objectives. They showed interest in the major part of PBL lesson such as scenario and group activities. And they engaged themselves in drawing the share housing space plan with '5D planner' web program which they described as the best part of the lessons. The teaching/learning process plan developed in this study may be used as a theme of maker education, which is emerging these days. It can be concluded that the PBL teaching/learning process plans for 'housing values and practical space use' would contribute to improving students' attitude on living with others and ability to manage one's individual life.

Evaluation of Proper Image Acquisition Time by Change of Infusion dose in PET/CT (PET/CT 검사에서 주입선량의 변화에 따른 적정한 영상획득시간의 평가)

  • Kim, Chang Hyeon;Lee, Hyun Kuk;Song, Chi Ok;Lee, Gi Heun
    • The Korean Journal of Nuclear Medicine Technology
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    • v.18 no.2
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    • pp.22-27
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    • 2014
  • Purpose There is the recent PET/CT scan in tendency that use low dose to reduce patient's exposure along with development of equipments. We diminished $^{18}F$-FDG dose of patient to reduce patient's exposure after setting up GE Discovery 690 PET/CT scanner (GE Healthcare, Milwaukee, USA) establishment at this hospital in 2011. Accordingly, We evaluate acquisition time per proper bed by change of infusion dose to maintain quality of image of PET/CT scanner. Materials and Methods We inserted Air, Teflon, hot cylinder in NEMA NU2-1994 phantom and maintained radioactivity concentration based on the ratio 4:1 of hot cylinder and back ground activity and increased hot cylinder's concentration to 3, 4.3, 5.5, 6.7 MBq/kg, after acquisition image as increase acquisition time per bed to 30 seconds, 1 minute, 1 minute 30 seconds, 2 minute, 2 minutes 30 seconds, 3 minutes, 3 minutes 30 seconds, 4 minutes, 4 minutes 30 seconds, 5 minutes, 5 minutes 30 seconds, 10 minutes, 20 minutes, and 30 minutes, ROI was set up on hot cylinder and back radioactivity region. We computated standard deviation of Signal to Noise Ratio (SNR) and BKG (Background), compared with hot cylinder's concentration and change by acquisition time per bed, after measured Standard Uptake Value maximum ($SUV_{max}$). Also, we compared each standard deviation of $SUV_{max}$, SNR, BKG following in change of inspection waiting time (15minutes and 1 hour) by using 4.3 MBq phantom. Results The radioactive concentration per unit mass was increased to 3, 4.3, 5.5, 6.7 MBqs. And when we increased time/bed of each concentration from 1 minute 30 seconds to 30 minutes, we found that the $SUV_{max}$ of hot cylinder acquisition time per bed changed seriously according to each radioactive concentration in up to 18.3 to at least 7.3 from 30 seconds to 2 minutes. On the other side, that displayed changelessly at least 5.6 in up to 8 from 2 minutes 30 seconds to 30 minutes. SNR by radioactive change per unit mass was fixed to up to 0.49 in at least 0.41 in 3 MBqs and accroding as acquisition time per bed increased, rose to up to 0.59, 0.54 in each at least 0.23, 0.39 in 4.3 MBqs and in 5.5 MBqs. It was high to up to 0.59 from 30 seconds in radioactivity concentration 6.7 MBqs, but kept fixed from 0.43 to 0.53. Standard deviation of BKG (Background) was low from 0.38 to 0.06 in 3 MBqs and from 2 minutes 30 seconds after, low from 0.38 to 0 in 4.3 MBqs and 5.5 MBqs from 1 minute 30 seconds after, low from 0.33 to 0.05 in 6.7 MBqs at all section from 30 seconds to 30 minutes. In result that was changed the inspection waiting time to 15 minutes and 1 hour by 4.3 MBq phantoms, $SUV_{max}$ represented each other fixed values from 2 minutes 30 seconds of acquisition time per bed and SNR shown similar values from 1 minute 30 seconds. Conclusion As shown in the above, when we increased radioactive concentration per unit mass by 3, 4.3, 5.5, 6.7 MBqs, the values of $SUV_{max}$ and SNR was kept changelessly each other more than 2 minutes 30 seconds of acquisition time per bed. In the same way, in the change of inspection waiting time (15 minutes and 1 hour), we could find that the values of $SUV_{max}$ and SNR was kept changelessly each other more than 2 minutes 30 seconds of acquisition time per bed. In the result of this NEMA NU2-1994 phantom experiment, we found that the minimum acquisition time per bed was 2 minutes 30 seconds for evaluating values of fixed $SUV_{max}$ and SNR even in change of inserting radioactive concentration. However, this acquisition time can be different according to features and qualities of equipment.

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A Hybrid Recommender System based on Collaborative Filtering with Selective Use of Overall and Multicriteria Ratings (종합 평점과 다기준 평점을 선택적으로 활용하는 협업필터링 기반 하이브리드 추천 시스템)

  • Ku, Min Jung;Ahn, Hyunchul
    • Journal of Intelligence and Information Systems
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    • v.24 no.2
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    • pp.85-109
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    • 2018
  • Recommender system recommends the items expected to be purchased by a customer in the future according to his or her previous purchase behaviors. It has been served as a tool for realizing one-to-one personalization for an e-commerce service company. Traditional recommender systems, especially the recommender systems based on collaborative filtering (CF), which is the most popular recommendation algorithm in both academy and industry, are designed to generate the items list for recommendation by using 'overall rating' - a single criterion. However, it has critical limitations in understanding the customers' preferences in detail. Recently, to mitigate these limitations, some leading e-commerce companies have begun to get feedback from their customers in a form of 'multicritera ratings'. Multicriteria ratings enable the companies to understand their customers' preferences from the multidimensional viewpoints. Moreover, it is easy to handle and analyze the multidimensional ratings because they are quantitative. But, the recommendation using multicritera ratings also has limitation that it may omit detail information on a user's preference because it only considers three-to-five predetermined criteria in most cases. Under this background, this study proposes a novel hybrid recommendation system, which selectively uses the results from 'traditional CF' and 'CF using multicriteria ratings'. Our proposed system is based on the premise that some people have holistic preference scheme, whereas others have composite preference scheme. Thus, our system is designed to use traditional CF using overall rating for the users with holistic preference, and to use CF using multicriteria ratings for the users with composite preference. To validate the usefulness of the proposed system, we applied it to a real-world dataset regarding the recommendation for POI (point-of-interests). Providing personalized POI recommendation is getting more attentions as the popularity of the location-based services such as Yelp and Foursquare increases. The dataset was collected from university students via a Web-based online survey system. Using the survey system, we collected the overall ratings as well as the ratings for each criterion for 48 POIs that are located near K university in Seoul, South Korea. The criteria include 'food or taste', 'price' and 'service or mood'. As a result, we obtain 2,878 valid ratings from 112 users. Among 48 items, 38 items (80%) are used as training dataset, and the remaining 10 items (20%) are used as validation dataset. To examine the effectiveness of the proposed system (i.e. hybrid selective model), we compared its performance to the performances of two comparison models - the traditional CF and the CF with multicriteria ratings. The performances of recommender systems were evaluated by using two metrics - average MAE(mean absolute error) and precision-in-top-N. Precision-in-top-N represents the percentage of truly high overall ratings among those that the model predicted would be the N most relevant items for each user. The experimental system was developed using Microsoft Visual Basic for Applications (VBA). The experimental results showed that our proposed system (avg. MAE = 0.584) outperformed traditional CF (avg. MAE = 0.591) as well as multicriteria CF (avg. AVE = 0.608). We also found that multicriteria CF showed worse performance compared to traditional CF in our data set, which is contradictory to the results in the most previous studies. This result supports the premise of our study that people have two different types of preference schemes - holistic and composite. Besides MAE, the proposed system outperformed all the comparison models in precision-in-top-3, precision-in-top-5, and precision-in-top-7. The results from the paired samples t-test presented that our proposed system outperformed traditional CF with 10% statistical significance level, and multicriteria CF with 1% statistical significance level from the perspective of average MAE. The proposed system sheds light on how to understand and utilize user's preference schemes in recommender systems domain.

Study on the Tractive Characteristics of the Seed Furrow Opener for No-till Planter (무경운(無耕耘) 파종기용(播種機用) 구체기(溝切器)의 견인특성(牽引特性)에 관(關)한 연구(硏究))

  • La, Woo-Jung
    • Korean Journal of Agricultural Science
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    • v.5 no.2
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    • pp.149-157
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    • 1978
  • This study was carried out to obtain basic data for the type selection of furrow openers for the no-tillage soybean planter trailed by the two-wheel tractor from the standpoint of minimum draft and good performance of furrowing. For this study, two models of furrow opener, hoe and disc type, were tested on the artificial soil stuffed in the moving soil bin. The results obtained were as follows. In the case of disc furrow opener, the drafts were measured according to various diameters of discs under the condition of disc angle $8^{\circ}$ and $16^{\circ}$, working depth 3cm and 6cm, working speed 2.75cm/sec. Minimum draft appeared when the diameter of disc was about 28cm and the drafts increased as the diameter of discs became larger or smaller than this diameter. Specific draft showed almost same tendencies as above but showed the minimum when the diameter was about 30cm. For the purpose of controlling the seeding depth, the relationships between draft and working depths, 3cm and 6cm, were tested. The variations of draft concerning the various working depths showed linear changes and were affected in higher degree by depths than other factors. There were general tendencies at both working depths, 3cm and 6cm, that total draft showed the minimum with the disc diameter of about 28cm and specific draft showed it with the disc diameter of about 30cm regardless of disc angle and working speed. For the purpose of controlling the working width and speed, the relationships among drafts, disc angle and working speed were investigated and there were general tendencies that the draft increased as the angle and speed were increased and the draft was affected more by speed than by angle. To compare the hoe-type with disc-type opener, the specific drafts of hoe openers were compared with those of disc opener of $16^{\circ}$ angle and 30cm diameter. The specific draft of disc-type opener with the diameter of 30cm was $0.35{\sim}0.5kg/cm^2$, while $0.71{\sim}1.02kg/cm^2$ in the case of hoe type with the lift angle of $20^{\circ}$ which is 2 times as much as that of disc type in average value. And the furrows opened by disc openers were cleaner than those opened by hoe openers.

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THE EFFECTS OF THERMAL STIMULI TO THE FILLED TOOTH STRUCTURE (온도자극이 충전된 치질에 미치는 영향)

  • Baik, Byeong-Ju;Roh, Yong-Kwan;Lee, Young-Su;Yang, Jeong-Suk;Kim, Jae-Gon
    • JOURNAL OF THE KOREAN ACADEMY OF PEDTATRIC DENTISTRY
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    • v.26 no.2
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    • pp.339-349
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    • 1999
  • The dental structure substituted by restorative materials may produce discomfort resulting from hot or cold stimuli. To investigate the effects of this stimuli on the human teeth, thermal analysis was carried out by calculation of general heat conduction equation in a modeled tooth using numerical method. The method has been applied to axisymmetric and two-dimensional model, analyzing the effects of constant temperature $4^{\circ}C\;and\;60^{\circ}C$. That thermal shock was provided for 2 seconds and 4 seconds, respectively and recovered to normal condition of $20^{\circ}C$ until 10 seconds. The thermal behavior of tooth covered with a crown of gold or stainless steel was compared with that of tooth without crown. At the same time, the effects of restorative materials(amalgam, gold and zinc oxide-eugenol(ZOE)) on the temperature of PDJ(pulpo-dentinal junction) has been studied. The geometry used for thermal analysis so far has been limited to two-dimensional as well as axisymmetric tooth models. But the general restorative tooth forms a cross shaped cavity which is no longer two-dimensional and axisymmetric. Therefore, in this study, the three-dimensional model was developed to investigate the effect of shape and size of cavity. This three-dimensional model might be used for further research to investigate the effects of restorative materials and cavity design on the thermal behavior of the real shaped tooth. The results were as follows; 1. When cold temperature of $4^{\circ}C$ was applied to the surface of the restored teeth with amalgam for 2 seconds and recovered to ambient temperature of $20^{\circ}C$, the PDJ temperature decreased rapidly to $29^{\circ}C$ until 3 seconds and reached to $25^{\circ}C$ after 9 seconds. This temperature decreased rather slowly with stainless steel crown, but kept similar temperature within $1^{\circ}C$ differences. Using the gold as a restorative material, the PDJ temperature decreased very fast due to the high thermal conductivity and reached near to $25^{\circ}C$ but the temperature after 9 seconds was similar to that in the teeth without crown. The effects of coldness could be attenuated with the ZOE situated under the cavity. The low thermal conductivity caused a delay in temperature decrease and keeps $4^{\circ}C$ higher than the temperature of other conditions after 9 seconds. 2. The elapse time of cold stimuli was increased also until 4 seconds and recovered to $20^{\circ}C$ after 4 seconds to 9 seconds. The temperature after 9 seconds was about $2-3^{\circ}C$ lower than the temperature of 2 seconds stimuli, but in case of gold restoration, the high thermal conductivity of gold caused the minimum temperature of $21^{\circ}C$ after 5 seconds and got warm to $23^{\circ}C$ after 9 seconds. 3. The effects of hot stimuli was also investigated with the temperature of $60^{\circ}C$. For 2 seconds stimuli, the temperature increased to $40^{\circ}C$ from the initial temperature of $35^{\circ}C$ after 3 seconds of stimuli and decreased to $30^{\circ}C$ after 9 seconds in the teeth without crown. This temperature was sensitive to surface temperature in the teeth with gold restoration. It increased rapidly to $41^{\circ}C$ from the initial temperature of $35^{\circ}C$ after 2 seconds and decreased to $28^{\circ}C$ after 9 seconds, which showed $13^{\circ}C$ temperature variations for 9 seconds upon the surface temperature. This temperature variations were only in the range of $5^{\circ}C$ by using ZOE in the bottom of cavity and showed maximum temperature of $37^{\circ}C$ after 3 seconds of stimuli.

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Optimization and Development of Prediction Model on the Removal Condition of Livestock Wastewater using a Response Surface Method in the Photo-Fenton Oxidation Process (Photo-Fenton 산화공정에서 반응표면분석법을 이용한 축산폐수의 COD 처리조건 최적화 및 예측식 수립)

  • Cho, Il-Hyoung;Chang, Soon-Woong;Lee, Si-Jin
    • Journal of Korean Society of Environmental Engineers
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    • v.30 no.6
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    • pp.642-652
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    • 2008
  • The aim of our research was to apply experimental design methodology in the optimization condition of Photo-Fenton oxidation of the residual livestock wastewater after the coagulation process. The reactions of Photo-Fenton oxidation were mathematically described as a function of parameters amount of Fe(II)($x_1$), $H_2O_2(x_2)$ and pH($x_3$) being modeled by the use of the Box-Behnken method, which was used for fitting 2nd order response surface models and was alternative to central composite designs. The application of RSM using the Box-Behnken method yielded the following regression equation, which is an empirical relationship between the removal(%) of livestock wastewater and test variables in coded unit: Y = 79.3 + 15.61x$_1$ - 7.31x$_2$ - 4.26x$_3$ - 18x$_1{^2}$ - 10x$_2{^2}$ - 11.9x$_3{^2}$ + 2.49x$_1$x$_2$ - 4.4x$_2$x$_3$ - 1.65x$_1$x$_3$. The model predicted also agreed with the experimentally observed result(R$^2$ = 0.96) The results show that the response of treatment removal(%) in Photo-Fenton oxidation of livestock wastewater were significantly affected by the synergistic effect of linear terms(Fe(II)($x_1$), $H_2O_2(x_2)$, pH(x$_3$)), whereas Fe(II) $\times$ Fe(II)(x$_1{^2}$), $H_2O_2$ $\times$ $H_2O_2$(x$_2{^2}$) and pH $\times$ pH(x$_3{^2}$) on the quadratic terms were significantly affected by the antagonistic effect. $H_2O_2$ $\times$ pH(x$_2$x$_3$) had also a antagonistic effect in the cross-product term. The estimated ridge of the expected maximum response and optimal conditions for Y using canonical analysis were 84 $\pm$ 0.95% and (Fe(II)(X$_1$) = 0.0146 mM, $H_2O_2$(X$_2$) = 0.0867 mM and pH(X$_3$) = 4.704, respectively. The optimal ratio of Fe/H$_2O_2$ was also 0.17 at the pH 4.7.

Bankruptcy Forecasting Model using AdaBoost: A Focus on Construction Companies (적응형 부스팅을 이용한 파산 예측 모형: 건설업을 중심으로)

  • Heo, Junyoung;Yang, Jin Yong
    • Journal of Intelligence and Information Systems
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    • v.20 no.1
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    • pp.35-48
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    • 2014
  • According to the 2013 construction market outlook report, the liquidation of construction companies is expected to continue due to the ongoing residential construction recession. Bankruptcies of construction companies have a greater social impact compared to other industries. However, due to the different nature of the capital structure and debt-to-equity ratio, it is more difficult to forecast construction companies' bankruptcies than that of companies in other industries. The construction industry operates on greater leverage, with high debt-to-equity ratios, and project cash flow focused on the second half. The economic cycle greatly influences construction companies. Therefore, downturns tend to rapidly increase the bankruptcy rates of construction companies. High leverage, coupled with increased bankruptcy rates, could lead to greater burdens on banks providing loans to construction companies. Nevertheless, the bankruptcy prediction model concentrated mainly on financial institutions, with rare construction-specific studies. The bankruptcy prediction model based on corporate finance data has been studied for some time in various ways. However, the model is intended for all companies in general, and it may not be appropriate for forecasting bankruptcies of construction companies, who typically have high liquidity risks. The construction industry is capital-intensive, operates on long timelines with large-scale investment projects, and has comparatively longer payback periods than in other industries. With its unique capital structure, it can be difficult to apply a model used to judge the financial risk of companies in general to those in the construction industry. Diverse studies of bankruptcy forecasting models based on a company's financial statements have been conducted for many years. The subjects of the model, however, were general firms, and the models may not be proper for accurately forecasting companies with disproportionately large liquidity risks, such as construction companies. The construction industry is capital-intensive, requiring significant investments in long-term projects, therefore to realize returns from the investment. The unique capital structure means that the same criteria used for other industries cannot be applied to effectively evaluate financial risk for construction firms. Altman Z-score was first published in 1968, and is commonly used as a bankruptcy forecasting model. It forecasts the likelihood of a company going bankrupt by using a simple formula, classifying the results into three categories, and evaluating the corporate status as dangerous, moderate, or safe. When a company falls into the "dangerous" category, it has a high likelihood of bankruptcy within two years, while those in the "safe" category have a low likelihood of bankruptcy. For companies in the "moderate" category, it is difficult to forecast the risk. Many of the construction firm cases in this study fell in the "moderate" category, which made it difficult to forecast their risk. Along with the development of machine learning using computers, recent studies of corporate bankruptcy forecasting have used this technology. Pattern recognition, a representative application area in machine learning, is applied to forecasting corporate bankruptcy, with patterns analyzed based on a company's financial information, and then judged as to whether the pattern belongs to the bankruptcy risk group or the safe group. The representative machine learning models previously used in bankruptcy forecasting are Artificial Neural Networks, Adaptive Boosting (AdaBoost) and, the Support Vector Machine (SVM). There are also many hybrid studies combining these models. Existing studies using the traditional Z-Score technique or bankruptcy prediction using machine learning focus on companies in non-specific industries. Therefore, the industry-specific characteristics of companies are not considered. In this paper, we confirm that adaptive boosting (AdaBoost) is the most appropriate forecasting model for construction companies by based on company size. We classified construction companies into three groups - large, medium, and small based on the company's capital. We analyzed the predictive ability of AdaBoost for each group of companies. The experimental results showed that AdaBoost has more predictive ability than the other models, especially for the group of large companies with capital of more than 50 billion won.

The Evaluation of SUV Variations According to the Errors of Entering Parameters in the PET-CT Examinations (PET/CT 검사에서 매개변수 입력오류에 따른 표준섭취계수 평가)

  • Kim, Jia;Hong, Gun Chul;Lee, Hyeok;Choi, Seong Wook
    • The Korean Journal of Nuclear Medicine Technology
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    • v.18 no.1
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    • pp.43-48
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    • 2014
  • Purpose: In the PET/CT images, The SUV (standardized uptake value) enables the quantitative assessment according to the biological changes of organs as the index of distinction whether lesion is malignant or not. Therefore, It is too important to enter parameters correctly that affect to the SUV. The purpose of this study is to evaluate an allowable error range of SUV as measuring the difference of results according to input errors of Activity, Weight, uptake Time among the parameters. Materials and Methods: Three inserts, Hot, Teflon and Air, were situated in the 1994 NEMA Phantom. Phantom was filled with 27.3 MBq/mL of 18F-FDG. The ratio of hotspot area activity to background area activity was regulated as 4:1. After scanning, Image was re-reconstructed after incurring input errors in Activity, Weight, uptake Time parameters as ${\pm}5%$, 10%, 15%, 30%, 50% from original data. ROIs (region of interests) were set one in the each insert areas and four in the background areas. $SUV_{mean}$ and percentage differences were calculated and compared in each areas. Results: $SUV_{mean}$ of Hot. Teflon, Air and BKG (Background) areas of original images were 4.5, 0.02. 0.1 and 1.0. The min and max value of $SUV_{mean}$ according to change of Activity error were 3.0 and 9.0 in Hot, 0.01 and 0.04 in Teflon, 0.1 and 0.3 in Air, 0.6 and 2.0 in BKG areas. And percentage differences were equally from -33% to 100%. In case of Weight error showed $SUV_{mean}$ as 2.2 and 6.7 in Hot, 0.01 and 0.03 in Tefron, 0.09 and 0.28 in Air, 0.5 and 1.5 in BKG areas. And percentage differences were equally from -50% to 50% except Teflon area's percentage deference that was from -50% to 52%. In case of uptake Time error showed $SUV_{mean}$ as 3.8 and 5.3 in Hot, 0.01 and 0.02 in Teflon, 0.1 and 0.2 in Air, 0.8 and 1.2 in BKG areas. And percentage differences were equally from 17% to -14% in Hot and BKG areas. Teflon area's percentage difference was from -50% to 52% and Air area's one was from -12% to 20%. Conclusion: As shown in the results, It was applied within ${\pm}5%$ of Activity and Weight errors if the allowable error range was configured within 5%. So, The calibration of dose calibrator and weighing machine has to conduct within ${\pm}5%$ error range because they can affect to Activity and Weight rates. In case of Time error, it showed separate error ranges according to the type of inserts. It showed within 5% error when Hot and BKG areas error were within ${\pm}15%$. So we have to consider each time errors if we use more than two clocks included scanner's one during the examinations.

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