• Nuclear Engineering and Technology
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• v.48 no.6
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• pp.1315-1320
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• 2016

The present study aims to predict the heat transfer characteristics around a square cylinder with different corner radii using multivariate adaptive regression splines (MARS). Further, the MARS-generated objective function is optimized by particle swarm optimization. The data for the prediction are taken from the recently published article by the present authors [P. Dey, A. Sarkar, A.K. Das, Development of GEP and ANN model to predict the unsteady forced convection over a cylinder, Neural Comput. Appl. (2015) 1-13]. Further, the MARS model is compared with artificial neural network and gene expression programming. It has been found that the MARS model is very efficient in predicting the heat transfer characteristics. It has also been found that MARS is more efficient than artificial neural network and gene expression programming in predicting the forced convection data, and also particle swarm optimization can efficiently optimize the heat transfer rate.

• Journal of the Korean Society of Physical Medicine
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• v.13 no.3
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• pp.113-120
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• 2018

PURPOSE: This study was conducted to investigate the characteristics of a specific functional shoe in terms of the range of motion (ROM) of ankle and foot joints during walking when compared to a standardized shoe. METHODS: Kinematic ROM data pertaining to ankle, tarsometatarsal, and metatarsophalangeal joints were collected from twenty-six healthy individuals during walking using a ten-camera motion analysis system. Kinematic ROM of each joint in three planes was obtained over ten walking trials consisting of two different shoe conditions. Visual3D motion analysis was finally used to coordinate the kinematic data. All kinematic ROM data were interpolated using a cubic spline algorithm and low-pass filtered with a cutoff frequency of 6 Hz for smoothing. RESULTS: The overall ROM of the ankle joint in the sagittal and coronal planes when wearing the specific functional shoe was significantly decreased in both ankles during walking when compared to wearing a standard shoe (p<.05). Significantly more flexibility was observed when wearing the specific functional shoe in the tarsometatarsal and metatarsophalangeal joints compared to a standard shoe (p<.05). CONCLUSION: Although clinical application of the specific functional shoe has shown clear positive effects on knee and ankle moments, the results of this study provide important background information regarding the kinematic mechanisms of these effects.

• The Korean Journal of Applied Statistics
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• v.31 no.3
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• pp.343-352
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• 2018

We can use quantile regression and expectile regression analysis to estimate trends in extreme regions as well as the average trends of response variables in given explanatory variables. In this paper, we compare the performance between the parametric and nonparametric methods for expectile regression. We introduce each estimation method and analyze through various simulations and the application to real data. The nonparametric model showed better results if the model is complex and difficult to deduce the relationship between variables. The use of nonparametric methods can be recommended in terms of the difficulty of assuming a parametric model in expectile regression.

• Structural Engineering and Mechanics
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• v.76 no.4
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• pp.435-449
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• 2020

This work presents the formulation of the isogeometric collocation method to solve the strong form equation of a unified and integrated approach of Reissner Mindlin plate theory (UI-RM). In this plate theory model, the total displacement is expressed in terms of bending and shear displacements. Rotations, curvatures, and shear strains are represented as the first, the second, and the third derivatives of the bending displacement, respectively. The proposed formulation is free from shear locking in the Kirchhoff limit and is equally applicable to thin and thick plates. The displacement field is approximated using the B-splines functions, and the strong form equation of the fourth-order is solved using the collocation approach. The convergence properties and accuracy are demonstrated with square plate problems of thin and thick plates with different boundary conditions. Two approaches are used for convergence tests, e.g., increasing the polynomial degree (NELT = 1×1 with p = 4, 5, 6, 7) and increasing the number of element (NELT = 1×1, 2×2, 3×3, 4×4 with p = 4) with the number of control variable (NCV) is used as a comparable equivalent variable. Compared with DKMQ element of a 64×64 mesh as the reference for all L/h, the problem analysis with isogeometric collocation on UI-RM plate theory exhibits satisfying results.

• Nutrition Research and Practice
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• v.15 no.4
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• pp.468-478
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• 2021

BACKGROUND/OBJECTIVES: This study aimed to analyze the association between dietary omega-3 fatty acid intake and depression in postmenopausal women using data from the Korea National Health and Nutrition Examination Survey (KNHANES) VI. SUBJECTS/METHODS: The KNHANES is a cross-sectional nationwide health and nutrition survey. Dietary data, including omega-3 fatty acids, were assessed using the 24-h recall method. Depression was evaluated using a survey questionnaire. The association between dietary omega-3 fatty acids and depression was evaluated using multivariate logistic regression analysis. Depression, according to the dietary omega-3 fatty acid intake, was expressed as the odds ratio (OR) with a 95% confidence interval (CI). A total of 4,150 postmenopausal women were included in the analysis. RESULTS: In the fully-adjusted model, the group with the highest dietary omega-3 fatty acid intake significantly showed lower prevalence of depression than the group with the lowest intake (OR, 0.52; 95% CI, 0.33-0.83); a significant linear trend was detected (P for trend = 0.04). According to the dose-response analysis using cubic restricted spline regression, this association was linear and monotonic (P for non-linearity = 0.32). CONCLUSIONS: In this study, the dietary omega-3 fatty acid intake in postmenopausal women was inversely proportional to depression in a dose-response manner. Large cohort studies are needed to verify the causality between omega-3 fatty acids and depression in Korean postmenopausal women.

• Geotechnical Engineering
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• v.14 no.6
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• pp.81-92
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• 1998

A beam on elasto-plastic foundation modeling of soldier pile and woodlagging tieback walls or anchored walls was developed and tested. An instrumented full scale tieback wall in sand was constructed at the National Geotechnical Experimentation Bite located on Texas A&M University. The experimental earth pressure deflection relationship (p-y curves) was developed from the measurements. The construction sequence was simulated in the proposed method. The conceptual methodology of an anchored wall design was introduced by using the proposed method. The proposed method was evaluated with the measurements of case histories in sand and clay. A parametric research was performed to study the most influencing factors for the proposed method. It is concluded that the proposed method represents a significant improvement on the prediction of bending moments and deflections of the properly designed walls.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.2
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• pp.80-80
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• 2013

대규모 광도곡선 자료에서 다양한 주기변광성들의 정확한 주기를 효율적으로 검출하는 실험을 시도하였다. 실험을 위해 OGLE-III 맥동 변광성(RR Lyrae, Delta Scuti, Cepheid) 목록 중, I 필터로 관측된 총 31,324개의 광도 곡선을 사용하였다. 이 실험에 사용한 주기분석 알고리즘 MS_Period(Multi-Step period searching method)는 주기를 놓치지 않기 위해 두 가지 다른 방법(Multi Polynomial function, Phase Dispersion)으로 후보 주기를 구하고 정밀주기를 도출하기 위해 후보 주기 주변부를 Spline fitting을 통해 재탐색하는 방법이다. 기존의 MS_Period 방식은 주기 탐색 간격(dP/P)이 일정하였으나, 우리는 탐색 주기 구간을 나누고 짧은 주기에서는 작은 간격으로, 긴 주기에서는 보다 넓은 간격으로 주기를 탐색하는 과정을 추가하였다. 그 결과 98% 이상의 별에서 OGLE-III와 거의 일치하는 주기를 얻었으며, 긴 주기에서의 불필요한 정밀 탐색을 회피함으로써 분석시간도 단축되었다. 주기 결정이 어려운 경우들은 주로 1) periodogram에서 실제 주기가 아닌 1일 근처에서 noise보다 큰 peak가 보이는 경우, 2) 하나의 별에 대해 여러 주기가 비슷한 Phase diagram을 보이고, periodogram에서도 비슷한 peak를 갖는 경우, 3) OGLE-III의 주기와 전혀 다른 주기만 찾은 경우, 4) OGLE-III에서 제시하지 않은 혼합된 주기의 존재가 의심되는 경우인 것을 확인하였고, 각 사례들의 특징을 살펴보았다.

• Journal of Sensor Science and Technology
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• v.13 no.5
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• pp.383-391
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• 2004

In this study, we implemented the pulse transit time (PTT) system to examine usefulness of the monitoring method of distensibility and elasticity using photoplethysmography sensor in vivo. PTT is defined as the time interval between the peak of QRS complex in ECG signal and the maximum slope point of photoplethysmography. these two signals were converted to digital data by means of AID converter, then PTT was evaluated by heartbeat using PC. Results of analysis were displayed as a graph using spline interpolation method. The variance of PTT was measured repetitiously to verify efficiency of PTT system in resting state and hyperemic state. Repeated measurement of PTT was not same value but showed that coefficients of correlation were related with each other as 0.8302 (P<0.01) in resting state. And also repeated measurement of PTT showed significant correlation as 0.868 (P<0.01) in the hyperemic state. These result showed that PTT is reflect on transient pressure variance in the artery and is very useful method for the evaluation of prognosis of the hypertension and arteriosclerosis.

• Journal of Sensor Science and Technology
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• v.3 no.3
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• pp.28-35
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• 1994

Caustic Soda Treatment Systems need a concentration measurement device in order to monitor the weight reduction amount of polyester fabrics. Since the reduction process requires several concentration measurements, we have to do the unit titration fast and exactly. Therefore, a proposition of estimation algorithm for finding the equivalent point in the titration process is needed. In this paper, we used the cardinal spline algorithm, to estimate the proper curve with the measured pH-values after each injection of titration sdution, to predict the equivalent point. While the processing time is elapsed, several equivalent points are estimated and drawed the line graph of fabrics weight reduction automatically. Finally, we designed the hardware and the software of an automatic titration system that can generate the reduction ending signal of Caustic Soda Treatment System.

• Geomechanics and Engineering
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• v.33 no.3
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• pp.279-289
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• 2023

Brittleness index (BI) is an important property of rocks because it is a good index to predict rockburst. Due to its importance, several empirical and soft computing (SC) models have been proposed in the literature based on the punch penetration test (PPT) results. These models are very important as there is no clear-cut experimental means for measuring BI asides the PPT which is very costly and time consuming to perform. This study used a novel Multivariate Adaptive regression spline (MARS), M5P, and white-box ANN to predict the BI of rocks using the available data in the literature for an improved BI prediction. The rock density, uniaxial compressive strength (σ_c) and tensile strength (σ_t) were used as the input parameters into the models while the BI was the targeted output. The models were implemented in the MATLAB software. The results of the proposed models were compared with those from existing multilinear regression, linear and nonlinear particle swarm optimization (PSO) and genetic algorithm (GA) based models using similar datasets. The coefficient of determination (R²), adjusted R² (Adj R²), root-mean squared error (RMSE) and mean absolute percentage error (MAPE) were the indices used for the comparison. The outcomes of the comparison revealed that the proposed ANN and MARS models performed better than the other models with R² and Adj R² values above 0.9 and least error values while the M5P gave similar performance to those of the existing models. Weight partitioning method was also used to examine the percentage contribution of model predictors to the predicted BI and tensile strength was found to have the highest influence on the predicted BI.