• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.109-131
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• 2014

As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.

• Journal of Intelligence and Information Systems
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• v.26 no.4
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• pp.111-126
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• 2020

Most industries have recently become aware of the importance of customer lifetime value as they are exposed to a competitive environment. As a result, preventing customers from churn is becoming a more important business issue than securing new customers. This is because maintaining churn customers is far more economical than securing new customers, and in fact, the acquisition cost of new customers is known to be five to six times higher than the maintenance cost of churn customers. Also, Companies that effectively prevent customer churn and improve customer retention rates are known to have a positive effect on not only increasing the company's profitability but also improving its brand image by improving customer satisfaction. Predicting customer churn, which had been conducted as a sub-research area for CRM, has recently become more important as a big data-based performance marketing theme due to the development of business machine learning technology. Until now, research on customer churn prediction has been carried out actively in such sectors as the mobile telecommunication industry, the financial industry, the distribution industry, and the game industry, which are highly competitive and urgent to manage churn. In addition, These churn prediction studies were focused on improving the performance of the churn prediction model itself, such as simply comparing the performance of various models, exploring features that are effective in forecasting departures, or developing new ensemble techniques, and were limited in terms of practical utilization because most studies considered the entire customer group as a group and developed a predictive model. As such, the main purpose of the existing related research was to improve the performance of the predictive model itself, and there was a relatively lack of research to improve the overall customer churn prediction process. In fact, customers in the business have different behavior characteristics due to heterogeneous transaction patterns, and the resulting churn rate is different, so it is unreasonable to assume the entire customer as a single customer group. Therefore, it is desirable to segment customers according to customer classification criteria, such as loyalty, and to operate an appropriate churn prediction model individually, in order to carry out effective customer churn predictions in heterogeneous industries. Of course, in some studies, there are studies in which customers are subdivided using clustering techniques and applied a churn prediction model for individual customer groups. Although this process of predicting churn can produce better predictions than a single predict model for the entire customer population, there is still room for improvement in that clustering is a mechanical, exploratory grouping technique that calculates distances based on inputs and does not reflect the strategic intent of an entity such as loyalties. This study proposes a segment-based customer departure prediction process (CCP/2DL: Customer Churn Prediction based on Two-Dimensional Loyalty segmentation) based on two-dimensional customer loyalty, assuming that successful customer churn management can be better done through improvements in the overall process than through the performance of the model itself. CCP/2DL is a series of churn prediction processes that segment two-way, quantitative and qualitative loyalty-based customer, conduct secondary grouping of customer segments according to churn patterns, and then independently apply heterogeneous churn prediction models for each churn pattern group. Performance comparisons were performed with the most commonly applied the General churn prediction process and the Clustering-based churn prediction process to assess the relative excellence of the proposed churn prediction process. The General churn prediction process used in this study refers to the process of predicting a single group of customers simply intended to be predicted as a machine learning model, using the most commonly used churn predicting method. And the Clustering-based churn prediction process is a method of first using clustering techniques to segment customers and implement a churn prediction model for each individual group. In cooperation with a global NGO, the proposed CCP/2DL performance showed better performance than other methodologies for predicting churn. This churn prediction process is not only effective in predicting churn, but can also be a strategic basis for obtaining a variety of customer observations and carrying out other related performance marketing activities.

• Journal of Korean Society of Forest Science
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• v.90 no.4
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• pp.524-534
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• 2001

The pressure-volume curve parameters were investigated to elucidate the effects of shading treatment on the water relations of the one year old seedlings of Betula platyphylla var. japonica, Betula schmidtii, Zelkova serrata, Acer mono and Prunes sargentii subjected to five levels of artificial shading treatments. The osmotic potentials at full turgor(${\phi}_{{\pi}o}$) measured under full sunlight changed with species and growing season in the ranges of -1.04~-1.27MPa, -1.03~-1.48MPa, -0.94~-1.44MPa in first year treatment, and -0.90~-1.37MPa, -1.05~-1.79MPa, -0.99~-1.30MPa in second year treatment in June, July, and September, respectively. The osmotic potentials at full turgor increased with increment of shading level in the ranges of -0.90~-1.79MPa in full sunlight and -0.58~-1.23MPa in nearly full shading level(E) through the growing seasons in all the species studied. The osmotic potentials at turgor loss point(${\phi}_{{\pi}p}$) measured in full sunlight changed in the ranges of -1.64~-2.11MPa, -1.67~-2.15MPa, -1.47~-2.11MPa, and -1.45~-2.04MPa, -1.30~-2.00MPa, -1.28~-2.33MPa in June, July, and September of first and second years, respectively. Most of ${\phi}_{{\pi}p}$ measurements were lower within about 0.5MPa in comparison with those of ${\phi}_{{\pi}o}$. The measurements of ${\phi}_{{\pi}p}$ also increased with increment of shading level, and the differences in ${\phi}_{{\pi}p}$ among shading levels were generally greater than those in ${\phi}_{{\pi}o}$ by species and by growing season. Most of the osmotic potentials at turgor loss point as like as at full turgor were lowered in July than in June and September. The measurements of relative water content at turgor lass point(RWCp) in full sunlight were in the similar ranges of 81~88%, 71~86%, 75~84%, and 82~87, 72~84%, 76~86% in June, July, and September of first and second years, respectively. The RWCp were a little higher in A. mono and P. sargentii than in B. platyphylla var. japonica, B. schmidtii, and Z. serrata. The RWCp also decreased from 71~88% in full sunlight to 48~77% in nearly full shading treatment with increment of shading level. Even if there were some exceptions by species or by growing season, the shading effects on the changes in some P-V parameters were distinctly observed in the present study. The change in P-V parameters following shading treatment may be presumably inferred on the changes in solute accumulation, membrane elasticity, symplasmic water volume, and so on. But much more experiments should be necessarily continued for getting detailed informations on the physiological mechanism of shading effects relating to the changes in P-V parameters.

• The Korean Journal of Nuclear Medicine Technology
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• v.16 no.1
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• pp.17-26
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• 2012

Purpose: This study mainly focuses on the patients treated with chemically stable radiopharmaceutical product $^{99m}Tc$-HMPAO (d,l-hexamethylpropylene amine oxime) which yielded reduced image quality due to a decreased brain extraction rate. $^{99m}Tc$-HMPAO will be examined further to determine whether this product may be accounted as a factor for this cause. Material and Methods: From January 2010 until December 2010, out of 272 patients who were all subjected to $^{99m}Tc$-HMPAO brain blood flow SPECT scans resulting from Cerebral Infarction; 23 patients(ages $55.3{\pm}9$, 21 males, 3 females) with decreased tissue extraction rate were examined in detail. The radiopharmaceutical product $^{99m}Tc$-HMPAO was used on patients with normal brain tissue exchange rate as well as those with reduced rate in order to prove its' chemical stability. The patients' age, sex, blood pressure, existence of diabetes, drug use, current health status, known side effects from CT/MRI, examination of the patients' past SPECT before/after images were accounted to determine the factors and correlations affecting the rate of blood tissue extractions. Result: After multiple linear regression analysis, there were no unusual correlations between the 6 factors excluding sex, and before/after examination images. Male subjects showed reduced brain tissue extraction rate than the females ($p$ > 0.05) 91.3% male, 8.7% female. Wilcoxon Matched-Pairs Signed-Ranks Test was used on the before/after images which yielded a value of 0.06, which did not indicate a significant amount of difference on the 2 tests ($p$ > 0.05). As a result, the before/after images indicated similar brain tissue extraction rates, and there were variations depending on the individual patient. Conclusion: The effects of the chemically stable radiopharmaceutical product $^{99m}Tc$-HMPAO depended on the patient's personal characteristics and status, therefore was considered to be a factor in reducing brain tissue extraction rate. The related articles of $^{99m}Tc$-HMPAO cerebral blood flow SPECT speculates a cerebrovascular disease and factors resulting from portal veins, and it was not possible to pin point the exact cause of decreasing brain tissue extraction rate. However, the $^{99m}Tc$-HMPAO cerebral blood flow SPECT scan proved to be extremely useful in tracking and inspecting brain diseases, as well as offering accurate results from patients suffering from reduced brain tissue extraction rates.

• Pediatric Infection and Vaccine
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• v.14 no.2
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• pp.145-154
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• 2007

Purpose : Rotavirus is one of the most important etiologic agents of nosocomial infections among the neonates. This study was designed to investigate nosocomial rotavirus infection in neonates who were admitted to a postpartum-care center after birth. Methods : From March 2005 to September 2006, 957 healthy neonates were examined for rotavirus antigen in stool by immunochromatographic method and 216 neonates were rotavirus antigen positive within 24 hours after admitted to a postpartum-care center. We reviewed the nursing charts retrospectively such as characteristics, monthly distribution, birth hospitals, delivery methods, feeding types and clinical manifestations. Results : Among 957 neonates, 216 neonates (22.6%) were rotavirus antigen positive and there were no differences in sex, birth weight, gestational age. Monthly positive rate of rotavirus antigen showed diversity from 10% to 36%. According to birth hospitals, positive rate showed diversity from 3.5% to 53.6%. Out of 957 neonates, 655 cases (68.4%) were born of vaginal delivery and mean hospitalized duration was 2.4 days, 302 cases (31.6%) were born of cesarean section and mean hospitalized duration was 5.7 days. 17.6% of vaginal delivery and 33.4% of cesarean section were rotavirus antigen positive. The positive rate was higher in neonates by cesarean section than vaginal delivery (P<0.001). According to feeding types, positive rate of rotavirus antigen was lower in breast-fed group than formula-fed group (P<0.001). Proportion of symptomatic case among rotavirus antigen positive was 34.7%. Most common clinical manifestation was diarrhea (61.3%), following poor feeding (45.3%), fever (40.0%), vomiting (25.3%), delayed weight gain (12.0%), and decreased urine amount (5.3%). Conclusion : Some neonates were already infected before admission to a postpartum-care center. Without meticulous management, nosocomial rotavirus infection would transmit rapidly in a postpartum-care center spreading to the community. Recommendation of breast-feeding, routine rotavirus screeing test with or without symptom, and isolation of all rotavirus antigen positive neonates in a postpartum-care center seem to be necessary. Also attentive hygiene education and further investigations of rotavirus infection in a postpartum-care center would be needed.

• The Journal of the Petrological Society of Korea
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• v.25 no.4
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• pp.311-324
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• 2016

The characteristics of the rock cleavage in Jurassic granite from Geochang were analysed. The evaluation for three quarrying planes and three rock cleavages was performed using the parameters such as (1) reduction ratio between the value of spacing and the value of length, (2) microcrack spacing frequency(N), (3) total spacing($1mm{\geq}$), (4) exponential constant(a), (5) magnitude of exponent(${\lambda}$), (6) mean spacing($S_{mean}$), (7) difference value($S_{mean}-S_{median}$) between mean spacing and median spacing($S_{median}$) and (8) density of spacing. Especially the close dependence between the above spacing parameters and the parameters from the spacing-cumulative frequency diagrams was derived. The discrimination factors representing three quarrying planes and three rock cleavages were acquired through these mutual contrast. The analysis results of the research are summarized as follows. First, the reduction ratios of frequency(N), mean value, median value, the above difference value($S_{mean}-S_{median}$) and density for three rock cleavages are in orders of G(grain, (G1 + G2)/2) < H(hardway, (H1 + H2)/2) < R(rift, (R1 + R2)/2), H < G $\ll$ R, H < G $\ll$ R, H < G < R and H < G $\ll$ R. The values of the above five parameters for three planes show the various orders of R'(rift plane) $\ll$ H'(hardway plane) < G'(grain plane), R' $\ll$ G' < H', R' < H' < G', R' < G' < H' and R' $\ll$ H' < G', respectively. Second, the values of (I) parameters(2, 3, 4 and 5) and (II) parameters(6, 7 and 8) are in orders of (I) H < G < R and (II) R < G < H. On the contrary, the values of the above two groups(I~II) of parameters for three planes show reverse orders. Third, to review the overall characteristics of the arrangement among the six diagrams, these diagrams show an order of R2 < R1 < G2 < G1 < H2 < H1 from the related chart. In other words, above six diagrams can be summarized in order of rift(R1 + R2) < grain(G1 + G2) < hardway(H1 + H2). These results indicate a relative magnitude of rock cleavage related to microcrack spacing. Especially, two parameters for each diagram, the above difference value($S_{mean}-S_{median}$) and mean spacing, could provide advanced information for prediction the order of arrangement among the diagrams. Finally, the general chart for three planes and three rock cleavages were made. From the related chart, three exponential straight lines for three rock cleavages show an order of R(R1 + R2) < G(G1 + G2) < H(H1 + H2). On the contrary, three lines for three planes show an order of H'(R2 + G2) < G'(R1 + H2) < R'(G1 + H1). Consequently, correlation of the mutually reverse order between three planes and three rock cleavages can be drawn from the related chart.

• Pediatric Infection and Vaccine
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• v.10 no.2
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• pp.167-177
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• 2003

Purpose : To know the trends of antimicrobial susceptibility is critical for antimicrobial treatment. We studied the organisms isolated from blood, urine, stool, and cerebrospinal fluid from 1997 to 2001 to reveal the trends of their antimicrobial susceptibility. Methods : We conducted a retrospective study with isolates obtained from 0~18 year old outpatients and inpatients from 1997 to 2001 at Department of Pediatrics, Hanil general hospital. We gathered the data through the laboratory test files and the origin of microorganisms cultured from blood, urine, stool and cerebrospinal fluid and their antimicrobial susceptibility. Results : Microorganisms were isolated from 226(3.3%) out of 6,974 blood cultures, 365 (8.0%) out of 4,549 urine cultures, 50(1.9%) out of 2,593 stool cultures and 9(1.4%) in 655 cerebrospinal fluid cultures. The most frequently isolated organisms from blood cultures was Staphylococcus epidermidis(33.5%) which was followed by Staphylococcus aureus(19.7%), Escherichia coli(13.8%), and Burkholderia cepacia(9.0%). Among the urine cultures, E. coli was the most common(74.7%) which was followed by Group D Enterococcus(11.3%), Klebsiella pneumoniae(7.1%) and Proteus mirabilis(2.5%). The positive stool cultures all yield Salmonella species. Group D Salmonella was obtained most frequently. Among the positive cerebrospinal fluid cultures, Group B Streptococcus was isolated most frequently. Among the 40 cases of S. aureus in blood cultures, 27 cases were methicillin-resistant. The rates of susceptibility for amikacin, ceftizoxime and ceftriaxone of E. coli isolated from blood cultures were 80%, 100% and 60% in 1997 and 60%, 80% and 60% in 2001. The rates of susceptibility for amikacin, ceftizoxime and ceftriaxone of K. pnumoniae isolated from urine cultures. were 80%, 100% and 80% in 1997 and 50%, 83% and 50% in 2001 Enterococcus was isolated from 6.7% to 15.8% and vancomycin-resistant Enterococcus was observed in 17% of Group D Enterococcus isolated from urine cultures. The rates of susceptibility for amikacin, ceftizoxime and ceftriaxone of Group D Salmonella were 96%, 96% and 92% during the study period. Conclusion : Among the blood cultures S. epidermidis, S. aureus, E. coli and B. cepacia were isolated in order of frequency and among the urine cultures E. coli, Group D Enterococcus, K. pneumoniae and P. mirabilis were isolated in order of frequency. During the study period there was no big difference in major organisms isolated from blood and urine. The methicillin-resistant S. aureus was observed in 67% of S. aureus isolated from blood cultures but vancomycin-reistant S. aureus or vancomycin intermediate resistant S. aureus was not observed. The rates of susceptibility to amikacin and the third generation cephalosporin of E. coli isolated from blood cultures and K. pneumoniae from urine cultures have decreased. The isolation rates of Group D Enterococcus and vancomycin resistant Enterococcus have increased.

• Information Systems Review
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• v.16 no.3
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• pp.161-177
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• 2014

Corporate credit rating assessment consists of complicated processes in which various factors describing a company are taken into consideration. Such assessment is known to be very expensive since domain experts should be employed to assess the ratings. As a result, the data-driven corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has received considerable attention from researchers and practitioners. In particular, statistical methods such as multiple discriminant analysis (MDA) and multinomial logistic regression analysis (MLOGIT), and AI methods including case-based reasoning (CBR), artificial neural network (ANN), and multiclass support vector machine (MSVM) have been applied to corporate credit rating.2) Among them, MSVM has recently become popular because of its robustness and high prediction accuracy. In this study, we propose a novel optimized MSVM model, and appy it to corporate credit rating prediction in order to enhance the accuracy. Our model, named 'GAMSVM (Genetic Algorithm-optimized Multiclass Support Vector Machine),' is designed to simultaneously optimize the kernel parameters and the feature subset selection. Prior studies like Lorena and de Carvalho (2008), and Chatterjee (2013) show that proper kernel parameters may improve the performance of MSVMs. Also, the results from the studies such as Shieh and Yang (2008) and Chatterjee (2013) imply that appropriate feature selection may lead to higher prediction accuracy. Based on these prior studies, we propose to apply GAMSVM to corporate credit rating prediction. As a tool for optimizing the kernel parameters and the feature subset selection, we suggest genetic algorithm (GA). GA is known as an efficient and effective search method that attempts to simulate the biological evolution phenomenon. By applying genetic operations such as selection, crossover, and mutation, it is designed to gradually improve the search results. Especially, mutation operator prevents GA from falling into the local optima, thus we can find the globally optimal or near-optimal solution using it. GA has popularly been applied to search optimal parameters or feature subset selections of AI techniques including MSVM. With these reasons, we also adopt GA as an optimization tool. To empirically validate the usefulness of GAMSVM, we applied it to a real-world case of credit rating in Korea. Our application is in bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. The experimental dataset was collected from a large credit rating company in South Korea. It contained 39 financial ratios of 1,295 companies in the manufacturing industry, and their credit ratings. Using various statistical methods including the one-way ANOVA and the stepwise MDA, we selected 14 financial ratios as the candidate independent variables. The dependent variable, i.e. credit rating, was labeled as four classes: 1(A1); 2(A2); 3(A3); 4(B and C). 80 percent of total data for each class was used for training, and remaining 20 percent was used for validation. And, to overcome small sample size, we applied five-fold cross validation to our dataset. In order to examine the competitiveness of the proposed model, we also experimented several comparative models including MDA, MLOGIT, CBR, ANN and MSVM. In case of MSVM, we adopted One-Against-One (OAO) and DAGSVM (Directed Acyclic Graph SVM) approaches because they are known to be the most accurate approaches among various MSVM approaches. GAMSVM was implemented using LIBSVM-an open-source software, and Evolver 5.5-a commercial software enables GA. Other comparative models were experimented using various statistical and AI packages such as SPSS for Windows, Neuroshell, and Microsoft Excel VBA (Visual Basic for Applications). Experimental results showed that the proposed model-GAMSVM-outperformed all the competitive models. In addition, the model was found to use less independent variables, but to show higher accuracy. In our experiments, five variables such as X7 (total debt), X9 (sales per employee), X13 (years after founded), X15 (accumulated earning to total asset), and X39 (the index related to the cash flows from operating activity) were found to be the most important factors in predicting the corporate credit ratings. However, the values of the finally selected kernel parameters were found to be almost same among the data subsets. To examine whether the predictive performance of GAMSVM was significantly greater than those of other models, we used the McNemar test. As a result, we found that GAMSVM was better than MDA, MLOGIT, CBR, and ANN at the 1% significance level, and better than OAO and DAGSVM at the 5% significance level.

• Journal of Nutrition and Health
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• v.47 no.1
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• pp.77-88
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• 2014

Purpose: This study analyzed the foodservice satisfaction and menu preference of 506 high school boarding students in Jeju surveyed from July 2-30, 2012 with the aim of providing basic data for improving the quality of boarding food-service management. Methods: The data were analyzed using descriptive analysis, t-test, and Pearson's correlation coefficients, using the SPSS Win program (version 12.0). Results: Regarding satisfaction with dormitory foodservice, the satisfaction scores for service and hygiene were 3.46 (out of 5 scales), whereas the score for menu quality was 3.26 points. In terms of satisfaction by meal, dinner showed the highest score, at 3.70 (out of 5 scales). The satisfaction scores for breakfast were significantly higher in girls (3.36) than boys (2.93). Regarding intake of meals provided, dinner showed the highest score, at 3.96 (out of 5 scales), whereas breakfast showed the lowest score, at 3.63 points. Intake of lunch and dinner was significantly higher in boys (4.12, 4.17, respectively) than girls (3.72, 3.76, respectively). Regarding the requirements of subjects for dormitory foodservice, 43.4% of subjects selected improvement of food taste and 36.6% of girls chose menu diversity. In terms of menu preferences for main dishes, the students preferred noodles (4.06) and one-dish cooked rice (3.92) to cooked rice (3.66). The subjects preferred beef rib soup (4.10) and Kimchi stew (3.99) in soups and stews. With regard to the menu preferences for side dishes, steamed foods showed the highest score, at 3.95 (out of 5 scales), whereas seasoned foods showed the lowest score, at 2.89 points. The students preferred beef, pork, and chicken to fish and vegetables. The students preferred dessert the most with fruit juices (4.52). Bread and rice cake were more favored by girls, showing significant differences between boys and girls (p < 0.05, p < 0.01, respectively). Conclusion: Development of a systematic nutrition education program that can encourage practice of proper eating habits is needed. In addition improvement of the quality of boarding school meals through the service of various menus is needed.

• The Korean Journal of Nuclear Medicine Technology
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• v.12 no.3
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• pp.235-240
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• 2008

Purpose: At the beginning of PET/CT, Computed Tomography was mainly used only for Attenuation Correction (AC), but as the performance of the CT have been increase, it could give improved diagnostic information with Contrast Media. But it was controversial that Contrast Media could affect AC on PET/CT scan. Some submitted thesis' show that Contrast Media could overestimate when it is for AC data processing. On the contrary, the opinion that Contrast Media could be possible to affect the alteration of SUV because of the overestimated AC. But it does not have a definite effect on the diagnosis. Thus, the affection of Contrast Media on AC was investigated in this study. Materials and Methods: Patient inclusion criteria required a history of a malignancy and performance of an integrated PET/CT scan and contrast- enhanced CT scan within a 1-day period. Thirty oncologic patients who had PET/CT scan from December 2007 to June 2008 underwent staging evaluation and met these criteria. All patients fasted for at least 6 hr before the IV injection of approximately 5.6 MBq/kg (0.15 mCi/kg) of $^{18}F$-FDG and were scanned about 60 min after injection. All patients had a whole body PET/CT performed without IV contrast media followed by a contrast-enhanced CT on the Discovery STe PET/CT scanner. CT data were used for AC and PET images came out after AC. The ROIs drew and measured SUV. A paired t-test of these results was performed to assess the significance of the difference between the SUV obtained from the two attenuation corrected PET images. Results: The mean and maximum Standardized Uptake Values (SUV) for different regions averaged over all Patients. Comparing before using Contrast Media and after using, Most of ROIs have the increased SUV when it did Contrast Enhanced CT compare to Non-Contrast enhanced CT. All regions have increased SUV and also their p value was under 0.05 except the mean SUV of the Heart region. Conclusion: In this regard, the effect on SUV measurements that occurs when a contrast-enhanced CT is used for attenuation correction could have significant clinical ramifications. But some submitted thesis insisted that the percentage change in SUV that can determine or modify clinical management of oncology patients is small. Because there was not much difference that could be discovered by interpreter. But obviously the numerical change was occurred and on the stage finding primary region, small change would be base line, such as the region of liver which has greater change than the other regions needs more attention.