• Journal of the Korean Home Economics Association
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• v.39 no.11
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• pp.223-232
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• 2001

This study, by explaining the relationship between mechanical properties and clothing formability, aims to propose functional data for tailoring performance of fabrics of good tailorability. The KES-FB system was used to measure factors of mechanical properties and also the technique of stepwise-block-regression method was applied to investigate relationship between functional properties and mechanical properties of men's shirks. As results of vasual inspection of men's shirts, it showed that good fabrics had higher value in the LT, bending properties, shear properties and RC than poor fabrics in Total Appearance Value(TAV). And finally, A formula was obtained for calculating the VIA of men's shirts from functional properties which were calculated from the mechanical properties.

• Transactions on Electrical and Electronic Materials
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• v.17 no.1
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• pp.29-32
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• 2016

Using the various exchange-correlation functionals, such as LDA, GGA-PBE, GGA-PBEsol and GGA-AM05 functionals, first principle studies were conducted to determine the structures of paraelectric and ferroelectric PbTiO₃. Based on the structures determined by the various functionals, the piezoelectric properties of PbTiO₃ are predicted under the density-functional perturbation theory (DFPT). The present prediction with the various GGA functionals are closer to the experimental findings compared to the LDA values. The present DFT calculations using the GGA-PBEsol functional estimate the experimental data more reasonably than the conventional LDA and GGA fucntionals. The GGA-AM05 functional also predicts the experimental data as well as the GGA-PBEsol. The piezoelectric tensor calculated with PBEsol is relatively insensitive to pressure.

• Genomics & Informatics
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• v.18 no.4
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• pp.39.1-39.8
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• 2020

Alzheimer's disease (AD) is a chronic, progressive brain disorder that slowly destroys affected individuals' memory and reasoning faculties, and consequently, their ability to perform the simplest tasks. This study investigated the hub genes of AD. Proteins interact with other proteins and non-protein molecules, and these interactions play an important role in understanding protein function. Computational methods are useful for understanding biological problems, in particular, network analyses of protein-protein interactions. Through a protein network analysis, we identified the following top 10 hub genes associated with AD: PTGER3, C3AR1, NPY, ADCY2, CXCL12, CCR5, MTNR1A, CNR2, GRM2, and CXCL8. Through gene enrichment, it was identified that most gene functions could be classified as integral to the plasma membrane, G-protein coupled receptor activity, and cell communication under gene ontology, as well as involvement in signal transduction pathways. Based on the convergent functional genomics ranking, the prioritized genes were NPY, CXCL12, CCR5, and CNR2.

• Journal of Microbiology and Biotechnology
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• v.28 no.3
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• pp.454-464
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• 2018

Salivary microbiota alterations can correlate with dental caries development in children, and mechanisms mediating this association need to be studied in further detail. Our study explored salivary microbiota shifts in children and their association with the incidence of dental caries with dentine involvement. Salivary samples were collected from children with caries and their subsequently matched caries-free controls before and after caries development. The microbiota was analyzed by 16S rRNA gene-based high-throughput sequencing. The salivary microbiota was more diverse in caries-free subjects than in those with dental caries with dentine involvement (DC). Although both groups exhibited similar shifts in microbiota composition, an association with caries was found by function prediction. Analysis of potential microbiome functions revealed that Granulicatella, Streptococcus, Bulleidia, and Staphylococcus in the DC group could be associated with the bacterial invasion of epithelial cells, phosphotransferase system, and ${\text\tiny{D}}-alanine$ metabolism, whereas Neisseria, Lautropia, and Leptotrichia in caries-free subjects could be associated with bacterial motility protein genes, linoleic acid metabolism, and flavonoid biosynthesis, suggesting that functional differences in the salivary microbiota may be associated with caries formation. These results expand the current understanding of the functional significance of the salivary microbiome in caries development, and may facilitate the identification of novel biomarkers and treatment targets.

• Water for future
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• v.18 no.2
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• pp.153-161
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• 1985

The methods for hydrologic prediction of streamflows for more efficient and functional operations and automation of the flood warning and forecasting system have been studiedand which have been widely used in the control engineering have been studied and investigated for representation of the dynamic behavior of rainfall-runoff precesses, and formulated into mathematical model form. The applicabilities of the model using the adaptive Kalman filter algorithm to the on-line, real-time prediction of river flows have been worked out. The computer programs in FORTRAN which are developed here can be utilized for more efficient operations and better prediction abilities of flood warning and forecasting systems, and also should be modified for better model performance.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.1-6
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• 2006

The prediction of protein function basically make use of a protein-protein interaction map based on the concept of guilt-by-association. The method however cannot determine the functions of proteins in case that the target protein does not interact with proteins with known functions directly. This paper studies protein function prediction considering the given problem as a K-class classification problem and proposes a predictive approach utilizing a modular neural network. The proposed method uses interaction data and protein related attributes as well. The experimental results demonstrate that the proposed approach can predict the functional roles of Yeast proteins whose interaction knowledge is not known and shows better performance than the graph-based models that use protein interaction data.

• Asia Pacific Journal of Business Review
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• v.1 no.1
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• pp.1-22
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• 2016

The prediction of prices of agricultural products in the agriculture IT sector plays a significant role in the economic life of consumers and anyone engaged in agricultural business, and as these prices fluctuate more often than do other prices, the prediction of these prices holds a great deal of research promise. For this reason, academic literature has provided studies on the factors influencing the prices of agricultural products and the price index. However, as these factors vary, they are difficult to predict, resulting in the challenge of acquiring quantitative data. China is one example of a country without a reliable prediction system for prices of agricultural products. Fortunately, disclosed heterogeneous data can be found on the Internet, which allows for the effective collection of factors related to the prediction of these product prices through the use of text mining. The data provided online is valuable in that they reflect the opinions of the general public in real-time. Accordingly, this study aims to use heterogeneous data from the Internet and suggest a model predicting the prices of agricultural products before functional analyses. Toward this end, data analyses were conducted on the Chinese agricultural products market, one of the largest markets in the world.

• Korean Journal of Radiology
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• v.20 no.1
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• pp.83-93
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• 2019

Objective: The purpose of this study was to prospectively investigate the value of the myocardial extracellular volume fraction (ECV) in predicting myocardial functional outcome after revascularization of coronary chronic total occlusion (CTO). Materials and Methods: Thirty patients with CTO underwent cardiovascular magnetic resonance (CMR) before and 6 months after revascularization. Three baseline markers of functional outcome were evaluated in the dysfunctional segments assigned to the CTO vessels: ECV, transmural extent of infarction (TEI), and unenhanced rim thickness (RIM). At the global level, the ECV values of the whole myocardium with and without a hyperenhanced region (global and remote ECV) were respectively measured. Results: In per-segment analysis, ECV was superior to TEI and RIM in predicting functional recovery (area under receiver operating characteristic curve [AUC]: 0.86 vs. 0.75 and 0.73, all p values < 0.010), and it emerged as the only independent predictor of regional functional outcome (odds ratio [OR] = 0.83, 95% confidence interval [CI]: 0.77-0.89; p < 0.001) independent of collateral circulation. In per-patient analysis, global baseline ECV was indicative of ejection fraction (EF) at the follow-up examination (β = -0.61, p < 0.001) and changes in EF (β = -0.57, p = 0.001) in multivariate regression analysis. A patient with global baseline ECV less than 30.0% (AUC, 0.93; sensitivity 94%, specificity 80%) was more likely to demonstrate significant EF improvement (OR: 0.38; 95% CI: 0.17-0.85; p = 0.019). Conclusion: Extracellular volume fraction obtained by CMR may provide incremental value for the prediction of functional recovery both at the segmental and global levels in CTO patients, and may facilitate the identification of patients who can benefit from revascularization.

• Hip & pelvis
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• v.36 no.2
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• pp.135-143
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• 2024

Purpose: Hip fractures are associated with increased mortality. The identification of risk factors of mortality could improve patient care. The aim of the study was to identify risk factors of mortality after surgery for a hip fracture and construct a mortality model. Materials and Methods: A cohort study was conducted on patients with hip fractures at two institutions. Five hundred and ninety-seven patients with hip fractures that were treated in the tertiary hospital, and another 147 patients that were treated in a secondary hospital. The perioperative data were collected from medical charts and interviews. Functional Assessment Measure score, Short Form-12 and mortality were recorded at 12 months. Patients and surgery variables that were associated with increased mortality were used to develop a mortality model. Results: Mortality for the whole cohort was 19.4% at one year. From the variables tested only age >80 years, American Society of Anesthesiologists category, time to surgery (>48 hours), Charlson comorbidity index, sex, use of anti-coagulants, and body mass index <25 kg/m² were associated with increased mortality and used to construct the mortality model. The area under the curve for the prediction model was 0.814. Functional outcome at one year was similar to preoperative status, even though their level of physical function dropped after the hip surgery and slowly recovered. Conclusion: The mortality prediction model that was developed in this study calculates the risk of death at one year for patients with hip fractures, is simple, and could detect high risk patients that need special management.

• Journal of IKEEE
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• v.13 no.3
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• pp.18-23
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• 2009

FEATURE is a computational method to recognize functional and structural sites for automatic protein function prediction. By profiling physicochemical properties around residues, FEATURE can characterize and predict functional and structural sites in 3D protein structures in a high-throughput manner. Despite its effectiveness, it has been challenging to apply FEATURE to novel protein data due to limited customization support. To address this problem, we thoroughly analyze the internal modules of FEATURE and propose a methodology to customize FEATURE so that it can be used for new protein data for automatic functional annotations.