• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2000년도 춘계 학술대회 및 국제 감성공학 심포지움 논문집 Proceeding of the 2000 Spring Conference of KOSES and International Sensibility Ergonomics Symposium
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• pp.120-125
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• 2000

We propose a semi-automatic and dynamic indexing algorithm for multi-media database(e.g. movie files, audio files), which are difficult to create indexes expressing their emotional or abstract contents, according to user's sensitivity by using user's histories of access to database. In this algorithm, we simply categorize data at first, create a vector space of each user's interest(user model) from the history of which categories the data belong to, and create vector space of each data(title model) from the history of which users the data had been accessed from. By continuing the above method, we could create suitable indexes, which show emotional content of each data. In this paper, we define the recurrence formulas based on the proposed algorithm. We also show the effectiveness of the algorithm by simulation result.

• Genomics & Informatics
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• 제3권3호
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• pp.80-85
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• 2005

HExDB is a database for analyzing exon and splicing pattern information in Homo sapiens. HExDB is useful for specific purposes: 1) to design primers for exon amplification from cDNA and 2) to understand the change of ORFs by alternative splicing. HExDB was constructed by integrating data from AltExtron which is the computationally predicted exon database, Ensemble cDNA annotation, and Affymetrix genome tile published recently. Although it may contain false positive data, HExDB is good starting point due to its sensitivity. At present, there areas many as 2,046,519 exons stored in the HExDB. We found that $16.8\%$ of the exons in the database was constitutive exons and $83.1\%$ were novel gene exons.

• Journal of Cancer Prevention
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• 제23권4호
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• pp.183-190
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• 2018

Background: As the number of big-cohort studies increases, validation becomes increasingly more important. We aimed to validate administrative database categorized as colorectal cancer (CRC) by the International Classification of Disease (ICD) 10th code. Methods: Big-cohort was collected from Clinical Data Warehouse using ICD 10th codes from May 1, 2003 to November 30, 2016 at Seoul National University Bundang Hospital. The patients in the study group had been diagnosed with cancer and were recorded in the ICD 10th code of CRC by the National Health Insurance Service. Subjects with codes of inflammatory bowel disease or tuberculosis colitis were selected for the control group. For the accuracy of registered CRC codes (C18-21), the chart, imaging results, and pathologic findings were examined by two reviewers. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) for CRC were calculated. Results: A total of 6,780 subjects with CRC and 1,899 control subjects were enrolled. Of these patients, 22 subjects did not have evidence of CRC by colonoscopy, computed tomography, magnetic resonance imaging, or positron emission tomography. The sensitivity and specificity of hospitalization data for identifying CRC were 100.00% and 98.86%, respectively. PPV and NPV were 99.68% and 100.00%, respectively. Conclusions: The big-cohort database using the ICD 10th code for CRC appears to be accurate.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권2호
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• pp.87-94
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• 2016

In this paper, we discuss a gait representation based on the width of silhouette in terms of discriminative power and robustness against the noise in silhouette image for gait recognition. Its sensitivity to the noise in silhouette image are rigorously analyzed using probabilistic noisy silhouette model. In addition, we develop a gait recognition system using width representation and identify subjects using the decision level fusion based on majority voting. Experiments on CASIA gait dataset A and the SOTON gait database demonstrate the recognition performance with respect to the noise level added to the silhouette image.

• 한국지형학회지
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• 제27권2호
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• pp.81-97
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• 2020

Geopark refers to a single boundary area consisting of a collection of geosites and geotrails, which includes ecological, historical and cultural elements based on geological and geomorphological resources. To ensure the continued development and conservation of existing listed geoparks, it is necessary to carry out an environmental sensitivity analysis of the geopark components by utilizing spatial information from various scales. The objectives of this study are to analyze the environmental sensitivity in Cheongsong UNESCO global geopark in relation with slope disaster using GIS and to understand its spatial distribution in connection with geosites and geotrails. Two types of spatial database were constructed; geosites and geotrails in Cheongsong UNESCO global geopark and spatial data to perform environmental sensitivity. Potential soil loss and slope stability were analyzed to derive environmental sensitivity related to slope hazard. The results showed relatively high environmental sensitivity along the drainage network of Cheongsong UNESCO global geopark. Zonal statistics analysis was conducted for further detailed distribution of environmental sensitivity based on buffer zones of geosites and geotrails. Majority of geological sites, geological trails, Jeolgol gorge~Jusan Pond section in hiking trails, and Dalgi Mineral Spring Site~Artistic Genius Republic of Korea(Jangnankki gonghwaguk) section in road areas show relatively high slope hazard sensitivity within buffer zones.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2000년도 추계학술대회논문집A
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• pp.446-451
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• 2000

In this paper, a S/W system for a structural analysis of machine tools has been suggested. The system is so designed to reduce manual interfacing effort. An object-oriented language is used for making a graphic user interface. In this system parametric modelling technique is applied to construct a FE model without much user intervention. The FE model is automatically updated when the design parameters are changed by user. Not only single FE analysis but also a trade-off analysis for calculating the sensitivity information of design variables is possible using this system. All data generated by this system are saved in the database. So it possible to retrieve the result later without another analysis. It is found that the design time can be reduced and unnecessary operation avoided using this system.

• Safety and Health at Work
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• 제11권3호
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• pp.361-366
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• 2020

Background: This study aimed to identify the validity of breast cancer symptom questionnaire of worker's special health examination and its relationship with breast ultrasonography findings in young female night workers. Methods: The breast cancer symptom questionnaire data of worker's special health examination and breast ultrasonography results in young female shift workers who worked in one electronic manufacture company were collected from 2014 to 2018. Results: Of the 857 workers, 18 had a Breast Imaging Reporting and Database System category 4 or higher. Among other variables, shift work tenure alone was associated with the risk of having a Breast Imaging Reporting and Database System category higher than 4. The sensitivity, specificity, positive predictive value, and negative predictive value of the symptom questionnaire were 16.7%, 87.7%, 2.8%, and 98.0%, respectively. Conclusion: The current breast cancer symptom questionnaire of the worker's special health examination is inappropriate due to its low sensitivity and positive predictive value. In the future, female night workers will need alternative measures for more accurate screening for breast cancer.

• Computers and Concrete
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• 제27권3호
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• pp.225-239
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• 2021

Carbon fiber reinforced polymer (CFRP) has extensive use in strengthening reinforced concrete structures due to its high strength and elastic modulus, low weight, fast and easy application, and excellent durability performance. Many studies have been carried out to determine the performance of the CFRP confined concrete cylinder. Although studies about the prediction of confined compressive strength using ANN are in the literature, the insufficiency of the studies to predict the strain of confined concrete cylinder using ANN, which is the most appropriate analysis method for nonlinear and complex problems, draws attention. Therefore, to predict both strengths and also strain values, two different ANNs were created using an extensive experimental database. The strength and strain networks were evaluated with the statistical parameters of correlation coefficients (R2), root mean square error (RMSE), and mean absolute error (MAE). The estimated values were found to be close to the experimental results. Mathematical equations to predict the strength and strain values were derived using networks prepared for convenience in engineering applications. The sensitivity analysis of mathematical models was performed by considering the inputs with the highest importance factors. Considering the limit values obtained from the sensitivity analysis of the parameters, the performances of the proposed models were evaluated by using the test data determined from the experimental database. Model performances were evaluated comparatively with other analytical models most commonly used in the literature, and it was found that the closest results to experimental data were obtained from the proposed strength and strain models.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2002년도 제1차워크샵
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• pp.5-23
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• 2002

Motivation: Protein-protein interaction plays a critical role in the biological processes. The identification of interacting proteins by bioinformatical methods can provide new lead In the functional studies of uncharacterized proteins without performing extensive experiments. Results: Protein-protein interactions are predicted by a computational algorithm based on the weighted scoring system for domain interactions between interacting protein pairs. Here we propose potential interaction domain (PID) pairs can be extracted from a data set of experimentally identified interacting protein pairs. where one protein contains a domain and its interacting protein contains the other. Every combinations of PID are summarized in a matrix table termed the PID matrix, and this matrix has proposed to be used for prediction of interactions. The database of interacting proteins (DIP) has used as a source of interacting protein pairs and InterPro, an integrated database of protein families, domains and functional sites, has used for defining domains in interacting pairs. A statistical scoring system. named "PID matrix score" has designed and applied as a measure of interaction probability between domains. Cross-validation has been performed with subsets of DIP data to evaluate the prediction accuracy of PID matrix. The prediction system gives about 50% of sensitivity and 98% of specificity, Based on the PID matrix, we develop a system providing several interaction information-finding services in the Internet. The system, named PreDIN (Prediction-oriented Database of Interaction Network) provides interacting domain finding services and interacting protein finding services. It is demonstrated that mapping of the genome-wide interaction network can be achieved by using the PreDIN system. This system can be also used as a new tool for functional prediction of unknown proteins.

• Journal of Preventive Medicine and Public Health
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• 제50권5호
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• pp.294-302
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• 2017

Objectives: The objectives of this study were to investigate the agreement between medical history questionnaire data and claims data and to identify the factors that were associated with discrepancies between these data types. Methods: Data from self-reported questionnaires that assessed an individual's history of hypertension, diabetes mellitus, dyslipidemia, stroke, heart disease, and pulmonary tuberculosis were collected from a general health screening database for 2014. Data for these diseases were collected from a healthcare utilization claims database between 2009 and 2014. Overall agreement, sensitivity, specificity, and kappa values were calculated. Multiple logistic regression analysis was performed to identify factors associated with discrepancies and was adjusted for age, gender, insurance type, insurance contribution, residential area, and comorbidities. Results: Agreement was highest between questionnaire data and claims data based on primary codes up to 1 year before the completion of self-reported questionnaires and was lowest for claims data based on primary and secondary codes up to 5 years before the completion of self-reported questionnaires. When comparing data based on primary codes up to 1 year before the completion of selfreported questionnaires, the overall agreement, sensitivity, specificity, and kappa values ranged from 93.2 to 98.8%, 26.2 to 84.3%, 95.7 to 99.6%, and 0.09 to 0.78, respectively. Agreement was excellent for hypertension and diabetes, fair to good for stroke and heart disease, and poor for pulmonary tuberculosis and dyslipidemia. Women, younger individuals, and employed individuals were most likely to under-report disease. Conclusions: Detailed patient characteristics that had an impact on information bias were identified through the differing levels of agreement.