• Asian Pacific Journal of Cancer Prevention
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• v.14 no.4
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• pp.2627-2630
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• 2013

Background: Ovarian cancer continues to pose a major challenge to physicians and radiologists. It is the third most common gynecologic malignancy and estimated to be fifth leading cancer cause of death in women, constituting 23% of all gynecological malignancies. Multi-detector computed tomography (MDCT) appears to offer an excellent modality in diagnosing ovarian cancer based on combination of its availability, meticulous technique, efficacy and familiarity of radiologists and physicians. The aim of this study was to compute sensitivity, specificity, positive and negative predictive values and diagnostic accuracy of 64-slice MDCT in classifying ovarian masses; 95% confidence intervals were reported. Materials and Methods: We prospectively designed a cross-sectional analytical study to collect data from July 2010 to August 2011 from a tertiary care hospital in Karachi, Pakistan. A sample of 105 women aged between 15-80 years referred for 64-MDCT of abdomen and pelvis with clinical suspicion of malignant ovarian cancer, irrespective of stage of disease, were enrolled by non-probability purposive sampling. All patients who were already known cases of histologically proven ovarian carcinoma and having some contraindication to radiation or iodinated contrast media were excluded. Results: Our prospective study reports sensitivity, specificity; positive and negative predictive values with 95%CI and accuracy were computed. Kappa was calculated to report agreement among the two radiologists. For reader A, MDCT was found to have 92% (0.83, 0.97) sensitivity and 86.7% (0.68, 0.96) specificity, while PPV and NPV were 94.5% (0.86, 0.98) and 86.7% (0.63, 0.92), respectively. Accuracy reported by reader A was 90.5%. For reader B, sensitivity, specificity, PPV and NPV were 94.6% (0.86, 0.98) 90% (0.72, 0.97) 96% (0.88, 0.99) and 87.1% (0.69, 0.95) respectively. Accuracy computed by reader B was 93.3%. Excellent agreement was found between the two radiologists with a significant kappa value of 0.887. Conclusion: Based on our study results, we conclude MDCT is a reliable imaging modality in diagnosis of ovarian masses accurately with insignificant interobserver variability.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.6
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• pp.8-17
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• 2011

Recently, fusion camera systems that consist of depth sensors and color cameras have been widely developed with the advent of a new type of sensor, time-of-flight (TOF) depth sensor. The physical limitation of depth sensors usually generates low resolution images compared to corresponding color images. Therefore, the pre-processing module, such as camera calibration, three dimensional warping, and hole filling, is necessary to generate the high resolution depth map that is placed in the image plane of the color image. However, the result of the pre-processing step is usually inaccurate due to errors from the camera calibration and the depth measurement. Therefore, in this paper, we present a depth map upsampling method robust these errors. First, the confidence of the measured depth value is estimated by the interrelation between the color image and the pre-upsampled depth map. Then, the detailed depth map can be generated by the modified kernel regression method which exclude depth values having low confidence. Our proposed algorithm guarantees the high quality result in the presence of the camera calibration errors. Experimental comparison with other data fusion techniques shows the superiority of our proposed method.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.4 no.2
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• pp.208-223
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• 1994

The purpose of this study was to evaluate the efficiency of diffusive(or passive) sampler in measuring airbone organic solvents. Diffusive samplers are generally simple in construction and do not require power for operation. The efficiency of the diffusive samplers has not sufficiently been investigated in Korea. Three types of samplers were studied in this study. The sampling and analytical results by passive samplers were compared with results by charcoal tube method recommended by NIOSH(National Institute for Occupational Safty and Health). The following characteristics are identified and studied as critical to the performance passive monitors; recovery, reverse diffusion, storage stability, accuracy and precision, face velocity and humidity, n-Hexane, TCE(trichloroethylene) and toluene were used as test vapors. A dynamic vapor exposure system consisting of organic vapor generator and sampling chamber for evaluating diffusive samplers are made. The results of the study are summarized as follows. 1. NIOSH recommands that the overall accuracy of a sampling method in the range of 0.5 to 2.0 times the occupational health standard should be ${\pm}25$ percent for 95 percent confidence level. Among three types of diffusive samplers, sampler A has permeation membrane and samplers Band C have diffusive areas, samplers A and B met the criterion that overall accuracy for 95% confidence level of the samplers were within ${\pm}25$ percent of the reference value. Sampler C had overall accuracy ${\pm}9.6%$ and ${\pm}11.8%$ in hexane and TCE, respectively. The concentration of toluene was overestimated in sampler C with overall accuracy of ${\pm}43.9%$. 2. The desorption efficiencies of diffusive samplers were 96-107%. 3. There was no significant sampe loss during four weeks of storage both with and without refrigeration. 4. There was no significant reverse diffusion, when the samplers were exposure to clean air for 2 hours after sampling for 2 hours at the level of 2 TLY. 5. In case of 8 hours sampling, relative differences(RD) of concentrations between charcoal tube method and diffusive method were 15-39%, 13-46%, and 4-35% for sampler A, B and C, respectively. The performance was poor in 8 hours sampling for multiple substance monitors. 6. At high velocity(100 cm/sec), samplers B and C overestimated the concentrations of organic vapors, and sampler A with permeation membrance gave better results. 7. At 80% relative humidity, samplers showed no siginificant effect. Low humidity also did not affect the diffusive samplers.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.8
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• pp.3525-3531
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• 2014

Objective: Fluorine-18-fluorodeoxyglucose positron emission tomography (18F-FDG-PET) is a new technique for identifying different malignant tumors using different uptake values between tumor cells and normal tissues. Here we assessed the diagnostic accuracy of 18F-FDG-PET in patients with testicular cancer by pooling data of existing trials in a meta-analysis. Methods: PubMed/MEDLINE, Embase and Cochrane Central Trials databases were searched and studies published in English relating to the diagnostic value of FDG-PET for testicular cancer were collected. The summary receiver operating characteristic (SROC) curve was used to examine the FDG-PET accuracy. Results: A total of 16 studies which included 957 examinations in 807 patients (median age, 31.1 years) were analyzed. A meta-analysis was performed to combine the sensitivity and specificity and their 95% confidence intervals (CIs), from diagnostic odds ratio (DOR), positive likelihood ratios (PLR), negative likelihood ratio (NLR). SROC were derived to demonstrate the diagnostic accuracy of FDG-PET for testicular cancer. The pooled sensitivity and specificity were 0.75 (95% confidence interval (CI), 0.70-0.80) and 0.87 (95% CI, 0.84-0.89), respectively. The pooled DOR was 35.6 (95% CI, 12.9-98.3). The area under the curve (AUC) was 0.88. The pooled PLR and pooled NLR were 7.80 (95% CI, 3.73-16.3) and 0.31 (95% CI, 0.23-0.43), respectively. Conclusion: In patients with testicular cancer, 18F-FDG-PET demonstrated a high SROC area, and could be a potentially useful tool if combined with other imaging methods such as MRI and CT. Nevertheless, the literature focusing on the use of 18F-FDG-PET in this setting still remains limited.

• Journal of Environmental Impact Assessment
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• v.23 no.5
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• pp.323-336
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• 2014

Using hedonic price method, this paper analyzes the impact of restriction for water quality protection on property value with the officially announced price of reference land in the city of Namyangju in 2012 to evaluate Water Use Fee, based on beneficiary pays principle, levied on the downstream area of the Han River in Korea. The results from the regression analyses of the models used show that the double-log model is the preferred model in the case of Namyangju. Using the double-log model, the total compensation for the city of Namyangju is estimated to be 8.6 trillion won with 95% confidence interval between 4.4 trillion and 12.4 trillion won. Under the perpetuity compensation scheme at the discount rate of 10%, the estimated annual compensation is 0.9 trillion won with 95% confidence interval between 0.4 trillion and 1.2 trillion won. This is more than Water Use Fee collected in 2012 for the Han River, which is approximately 0.5 trillion won. Considering the size of the restricted area of the Paldang area, which is more than 18 times of that of Namyangju, the rate of Water Use Fee, which is based on beneficiary pays principle and imposed on the residents of the downstream area, needs to be increased to sufficiently compensate the economic loss caused to the upstream areas of the Han River in Korea.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.27 no.2
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• pp.103-111
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• 2014

In this study, the probabilistic internal pressure fragility analysis was performed by using the non-linear finite element analysis method. The target structure is one of the containment buildings of typical domestic pressurized water reactors(PWRs). The 3-dimensional finite element model of the containment building was developed with considering the large equipment hatches. To consider uncertainties in the material properties and structural capacities, we performed the sensitivity analysis of the ultimate pressure capacity with respect to the variation of four important uncertain parameters. The results of the sensitivity analysis were used to the selection of the probabilistic variables and the determination of their probabilistic parameters. To reflect the present condition of the tendon pre-stressing force, the data of the pre-stressing force acquired from the in-service inspections of tendon forces were used for the determination of the median value. Two failure modes(leak, rupture) were considered and their limit states were defined to assess the internal pressure fragility of target containment building. The internal pressure fragilities for each failure mode were evaluated in terms of median internal pressure capacity, high confidence low probability of failure(HCLPF) capacity, and fragility curves with respect to the confidence levels. The HCLPF capacity was 115.9 psig for leak failure mode, and 125.0 psig for rupture failure mode.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.1-17
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• 2008

Data mining is defined as the process of discovering meaningful and useful pattern in large volumes of data. In particular, finding associations rules between items in a database of customer transactions has become an important thing. Some data structures and algorithms had been proposed for storing meaningful information compressed from an original database to find frequent itemsets since Apriori algorithm. Though existing method find all association rules, we must have a lot of process to analyze association rules because there are too many rules. In this paper, we propose a new data structure, called a Frequent Pattern Network (FPN), which represents items as vertices and 2-itemsets as edges of the network. In order to utilize FPN, We constitute FPN using item's frequency. And then we use a clustering method to group the vertices on the network into clusters so that the intracluster similarity is maximized and the intercluster similarity is minimized. We generate association rules based on clusters. Our experiments showed accuracy of clustering items on the network using confidence, correlation and edge weight similarity methods. And We generated association rules using clusters and compare traditional and our method. From the results, the confidence similarity had a strong influence than others on the frequent pattern network. And FPN had a flexibility to minimum support value.

• (The)Study of the Eastern Classic
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• no.35
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• pp.75-100
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• 2009

A human being makes a constant effort to find out what he really is. We try to do a great deal in self-culture to know his own self-nature with miscellaneous ways as Buddhism, Taoism and Confucianism. When we are faced with a difficult problem in life, We utilize own knowledge and wisdom to solve them. Thus there are many result of answer what self-confidence is throughout the devoting oneself to the study of man's life which is expressed poetry and prose. We can see the aspect of liberty life in their poetry and prose which is escaping from their restraints as they are willing to find out their own self-nature and want to attain a state of perfect self-nature in every day life. And they are anxious to be born again in spiritual value and to be a man in liberty with removing the narrow-mindedness, the stupidity, the anger and the absolute ego in their mind. That's what we are want to achieve man's purpose understanding of the human being's life. Here, I have a good such example who is Tao yuan ming. It is not easy to give up fame and wealth for maintaining his doctrines. So We have a high regard for this wisdom between entering into politics and withdrawing from his office. It needs a self-conquest and more courage than entering into politics. Retiring from his office, he returns to the place where is native place everything lives and let live without moral pressure in daily life. Because there is real liberty life and immutable truths.

• Journal of Wetlands Research
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• v.23 no.4
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• pp.296-306
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• 2021

Elasticity is a statistical technique that interprets the changing pattern of another variable according to a change in one variable as a quantitative numerical value and provides more information than correlation analysis and is widely used in climate change research. In this study the elasticity was calculated and sensitivity analysis was performed using air temperature and water quality data of the major tributaries of the Nakdong River. In addition the confidence interval for the elasticity was calculated using the T-Test and the validity of the elasticity was examined. The strength of elasticity shows high strength in the order of summer>fall>spring>winter and the direction shows regional characteristics with both negative and positive elasticity. After performing hierarchical cluster analysis on monthly observation data they were classified into 5 clusters and the characteristics of each cluster were visually analyzed using a parallel coordinate graph. The direction and intensity of the air temperature elasticity show regional characteristics due to the relatively high population density and complex influencing factors such as sewage treatment plants, small-scale livestock houses and agricultural activities. In the case of TP it shows great regional variability according to the circulation of nutrients in the ecosystem caused by algae growth and death according to temperature changes. Since the air temperature elasticity of the major tributaries of the Nakdong River is over weak and is valid at the significance level of 5%, it was analyzed that there is a change in water quality according to the air temperature change.

• The Journal of the Korea Contents Association
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• v.21 no.2
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• pp.121-129
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• 2021

In this study, we try to minimize the tariff risk by constructing a hazardous cargo screening model by applying Association Rule Mining, one of the data mining techniques. For this, the risk level between supply chains is calculated using the Apriori Algorithm, which is an association analysis algorithm, using the big data of the import declaration form of the Korea Customs Service(KCS). We perform data preprocessing and association rule mining to generate a model to be used in screening the supply chain. In the preprocessing process, we extract the attributes required for rule generation from the import declaration data after the error removing process. Then, we generate the rules by using the extracted attributes as inputs to the Apriori algorithm. The generated association rule model is loaded in the KCS screening system. When the import declaration which should be checked is received, the screening system refers to the model and returns the confidence value based on the supply chain information on the import declaration data. The result will be used to determine whether to check the import case. The 5-fold cross-validation of 16.6% precision and 33.8% recall showed that import declaration data for 2 years and 6 months were divided into learning data and test data. This is a result that is about 3.4 times higher in precision and 1.5 times higher in recall than frequency-based methods. This confirms that the proposed method is an effective way to reduce tariff risks.