• Asian Pacific Journal of Cancer Prevention
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• v.15 no.18
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• pp.7971-7975
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• 2014

Background: From our previous study, we established that cyclin A1 (CCNA1) promoter methylation is strongly correlated with multistep progression of HPV-associated cervical cancer, suggesting potential use as a diagnostic maker of disease. Objectives: The purpose of the present study was to assess the prevalence of CCNA1 promoter methylation in residual cervical cells isolated from liquid-based cytology that underwent hrHPV DNA screening for cervical cancer, and then to evaluate this marker for diagnostic accuracy using parameters like sensitivity, specificity, predictive values and likelihood ratio. Methods: In this retrospective study, histopathology was used as the gold standard method with specimens separated into the following groups: negative (n=31), low-grade squamous intraepithelial lesions (LSIL, n=34) and high-grade squamous intraepithelial lesions or worse (HSIL+, n=32). The hrHPV was detected by Hybrid Capture 2 (HC2) and CCNA1 promoter methylation was examined by CCNA1 duplex methylation specific PCR. Results: The results showed the frequencies of CCNA1 promoter methylation were 0%, 5.88% and 83.33%, while the percentages of hrHPV were 66.67%, 82.35% and 100% in the negative, LSIL and HSIL+ groups, respectively. Although hrHPV infection showed high frequency in all three groups, it could not differentiate between the different groups and grades of precancerous lesions. In contrast, CCNA1 promoter methylation clearly distinguished between negative/LSIL and HSIL+, with high levels of all statistic parameters. Conclusion: CCNA1 promoter methylation is a potential marker for distinguishing between histologic negative/LSIL and HSIL+using cervical cytology samples.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.24 no.3
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• pp.180-188
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• 2014

Hyundai Motor Group(HMG) carried out experimental investigation of sunroof buffeting phenomena on a simplified car model called Hyundai simplified model(HSM). HMG invited participation from commercial CFD vendors to perform numerical investigation of sunroof buffeting for HSM model with a goal to determine whether CFD can predict sunroof buffeting behavior to sufficient accuracy. ANSYS Korea participated in this investigation and performed numerical simulations of sunroof buffeting for HSM using ANSYS fluent, the general purpose CFD code. First, a flow field validation is performed using closed sunroof HSM model for 60 km/h wind speed. The velocity profiles at three locations on the top surface of HSM model are predicted and compared with experimental measurement. Then, numerical simulations for buffeting are performed over range of wind speeds, using advanced scale resolving turbulence model in the form of detached eddy simulation (DES). Buffeting frequency and buffeting level are predicted in simulation and compared with experimental measurement. With reference to comparison between experimental measurements with CFD predictions of buffeting frequency and level, conclusion are drawn about predictive capabilities of CFD for real vehicle development.

• Mass Spectrometry Letters
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• v.3 no.3
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• pp.68-73
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• 2012

Fat malabsorption is an important cause of poor growth in infancy and childhood. Steatorrhea tests have been developed using various methods. Traditional measurements of stool fat, however, require large samples and it often takes as a week to complete the analysis. In this paper, a liquid chromatography-electrospray ionization/mass spectrometry (LC-ESI/MS) method was developed for simultaneous quantitative analysis of triacylglycerols, triolein, diolein and monoolein, in mouse feces. Moreover, the procedure was rapid, simple as well as compatible with LC-ESI/MS. Chloroform-isopropyl alcohol solution was used for fat-soluble sample extraction. After centrifugation and filtration, an analytical solution was prepared. Triolein, diolein and monoolein were separated using non-aqueous reversed-phase column with the mobile phase consisting of A (methanol) and B (acetone-isopropyl alcohol). The precision (% CV) and accuracy (% bias) of the assay were 3.8-14.7% and 85.2-114.9%, respectively. This method has been successfully applied to simultaneous determination of triolein, diolein and monoolein in feces from 30 mice. This method can therefore be applied to measure triacylglycerols in mouse feces accurately and precisely by LC-ESI/MS, thereby helping to predictive biomarker in fat malabsorption and diagnostic research.

• Journal of the Korea Convergence Society
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• v.9 no.10
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• pp.75-80
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• 2018

In this paper, we propose heterogeneous lifelog mining model in health big-data platform. It is an ontology-based mining model for collecting user's lifelog in real-time and providing healthcare services. The proposed method distributes heterogeneous lifelog data and processes it in real time in a cloud computing environment. The knowledge base is reconstructed by an upper ontology method suitable for the environment constructed based on the heterogeneous ontology. The restructured knowledge base generates inference rules using Jena 4.0 inference engines, and provides real-time healthcare services by rule-based inference methods. Lifelog mining constructs an analysis of hidden relationships and a predictive model for time-series bio-signal. This enables real-time healthcare services that realize preventive health services to detect changes in the users' bio-signal by exploring negative or positive correlations that are not included in the relationships or inference rules. The performance evaluation shows that the proposed heterogeneous lifelog mining model method is superior to other models with an accuracy of 0.734, a precision of 0.752.

• Journal of the Korean Institute of Gas
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• v.4 no.4 s.12
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• pp.50-57
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• 2000

Past accidents have shown that vapor cloud explosions are the predominant cause of the largest losses in the chemical and petrochemical industries due to the generation of significant overpressures. Prediction of such overpressure is of great concern and a knowledge of the likely overpressure is needed for the design of equipment, safety cases and emergency planning. For these reasons, risk assessment for vapor cloud explosion is crucial and this assessment can be carried out using the different models including TNT-Equivalency, TNO Hemispherical, TNO Multi-Energy and CFD models. Accordingly, in this paper, the published VCE prediction models are reviewed to provide a critical comparison of the different models used for the quantification of explosion hazards, in terms of the fundamental assumptions employed, and their predictive accuracy

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.3
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• pp.353-360
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• 2012

Mastitis is a highly morbid disease that requires detection at the subclinical stage. Tropical countries like India mainly depend on milch buffaloes for milk. The present study was conducted to investigate whether the trace minerals viz. copper (Cu), iron (Fe), zinc (Zn), cobalt (Co) and manganese (Mn) and enzyme activity of lactate dehydrogenase (LDH), alkaline phosphatase (ALP) and aspartate aminotransferase (AST) in riverine buffalo milk can be used as an indicator of subclinical mastitis (SCM) with the aim of developing suitable diagnostic kit for SCM. Trace elements and enzyme activity in milk were estimated with Atomic absorption Spectrophotometer, GBC 932 plus and biochemical methods, respectively. Somatic cell count (SCC) was done microscopically. The cultural examination revealed Gram positive bacteria as the most prevalent etiological agent. A statistically significant (p<0.01) increase in SCC, Fe, Zn, Co and LDH occurred in SCM milk containing gram positive bacterial agents only. ALP was found to be elevated in milk infected by both gram positive and negative bacteria. The percent sensitivity, specificity and accuracy, predictive values and likelihood ratios were calculated taking bacterial culture examination and $SCC\geq2{\times}10^5$ cells/ml of milk as the benchmark. Only ALP and Zn, the former being superior, were found to be suitable for diagnosis of SCM irrespective of etiological agents. LDH, Co and Fe can be introduced in the screening programs where Gram positive bacteria are omnipresent. It is recommended that both ALP and Zn be measured together in milk to diagnose buffalo SCM, irrespective of etiology.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.10
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• pp.6121-6125
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• 2013

Background: Endometrial cancers are the most common gynecologic cancers. Endometrial sampling is a preferred procedure for diagnosis of the endometrial pathology. It is performed routinely in many clinics prior to surgery in order to exclude an endometrial malignancy. We aimed to investigate the accuracy of endometrial sampling in the diagnosis of endometrial pathologies and which findings need intra-operative frozen sections. Materials and Methods: Three hundred nine women applying to a university hospital and undergoing endometrial sampling and hysterectomy between 2010 and 2012 were included to this retrospective study. Data were retrieved from patient files and pathology archives. Results: There was 17 patients with malignancy but endometrial sampling could detect this in only 10 of them. The endometrial sampling sensitivity and specificity of detecting cancer were 58.8% and 100%, with negative and positive predictive values of 97.6%, and 100%, respectively. In 7 patients, the endometrial sampling failed to detect malignancy; 4 of these patients had a preoperative diagnosis of complex atypical endometrial hyperplasia and 2 patients had a post-menopausal endometrial polyps and 1 with simple endometrial hyperplasia. Conclusions: There is an increased risk of malignancy in post-menopausal women especially with endometrial polyps and complex atypia hyperplasia. Endometrial sampling is a good choice for the diagnosis of endometrial pathologies. However, the diagnosis should be confirmed by frozen section in patients with post-menopausal endometrial polyps and complex atypia hyperplasia.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.5
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• pp.1953-1956
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• 2012

Objective: The purpose of this study was to correlate the histological diagnosis made during intraoperative frozen section (FS) examination of hysterectomy samples with complex atypical endometrial hyperplasia (CAEH) diagnosed with definitive paraffin block histology. Methods: FS pathology results of 125 patients with a preoperative biopsy showing CAEH were compared retrospectively with paraffin block pathology findings. Results: Paraffin block results were consistent with FS in 78 of 125 patients (62.4%). The FS sensitivity and specificity of detecting cancer were 81.1% and 97.9%, with negative and positive predictive values of 76.7%, and 98.4%, respectively. Paraffin block results were reported as endometrial cancer in 77 of 125 (61.6%) patients. Final pathology was endometrial cancer in 45.3% patients diagnosed at our center and 76.9% for patients who had their diagnosis at other clinics (p=0.018). Paraffin block results were consistent with FS in 62.4% of all cases Consistence was 98.4% in patients who had endometrial cancer in FS. Conclusion: FS does not exclude the possibility of endometrial cancer in patients with the preoperative diagnosis of CAEH. In addition, sufficient endometrial sampling is important for an accurate diagnosis.

• Journal of Korea Multimedia Society
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• v.11 no.9
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• pp.1213-1226
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• 2008

A recommender system supports people in making recommendations finding a set of people who are likely to provide good recommendations for a given person, or deriving recommendations from implicit behavior such as browsing activity, buying patterns, and time on task. We proposed new recommender system which combined SOM(Self-Organizing Map) neural networks with the Collaborative filtering which most recommender systems hat applied First, we segmented user groups according to demographic characteristics and then we trained the SOM with people's preferences as ito inputs. Finally we applied the classic collaborative filtering to the clustering with similarity in which an recommendation seeker belonged to, and therefore we didn't have to apply the collaborative filtering to the whose data set. Experiments were run for EachMovies data set. The results indicated that the predictive accuracy was increased in terms of MAE(Mean-Absolute-Error).

• KIPS Transactions on Software and Data Engineering
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• v.3 no.7
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• pp.263-270
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• 2014

This paper suggests a method for predicting a box-office success of the film. Lately, as the growth of the film industry, a variety of studies for the prediction of market demand is being performed. The product life cycle of film is relatively short cultural goods. Therefore, in order to produce stable profits, marketing costs before opening as well as the number of screen after opening need a plan. To fulfill this plan, the demand for the product and the calculation of economic profit scale should be preceded. The cases of existing researches, as a variable for predicting, primarily use the factors of competition of the market or the properties of the film. However, the proportion of the potential audiences who purchase the goods is relatively insufficient. Therefore, in this paper, in order to consider people's perception of a movie, Twitter was utilized as one of the survey samples. The existing variables and the information extracted from Twitter are defined as off-line and on-line element, and applied those two elements in machine learning by combining. Through the experiment, the proposed predictive techniques are validated, and the results of the experiment predicted the chance of successful film with about 95% of accuracy.