• Computers and Concrete
• /
• v.33 no.1
• /
• pp.55-75
• /
• 2024

The present study introduces an optimum performance soft computing model for predicting the compressive strength of high-performance concrete (HPC) by comparing models based on conventional (kernel-based, covariance function-based, and tree-based), advanced machine (least square support vector machine-LSSVM and minimax probability machine regressor-MPMR), and deep (artificial neural network-ANN) learning approaches using a common database for the first time. A compressive strength database, having results of 1030 concrete samples, has been compiled from the literature and preprocessed. For the purpose of training, testing, and validation of soft computing models, 803, 101, and 101 data points have been selected arbitrarily from preprocessed data points, i.e., 1005. Thirteen performance metrics, including three new metrics, i.e., a20-index, index of agreement, and index of scatter, have been implemented for each model. The performance comparison reveals that the SVM (kernel-based), ET (tree-based), MPMR (advanced), and ANN (deep) models have achieved higher performance in predicting the compressive strength of HPC. From the overall analysis of performance, accuracy, Taylor plot, accuracy metric, regression error characteristics curve, Anderson-Darling, Wilcoxon, Uncertainty, and reliability, it has been observed that model CS4 based on the ensemble tree has been recognized as an optimum performance model with higher performance, i.e., a correlation coefficient of 0.9352, root mean square error of 5.76 MPa, and mean absolute error of 4.1069 MPa. The present study also reveals that multicollinearity affects the prediction accuracy of Gaussian process regression, decision tree, multilinear regression, and adaptive boosting regressor models, novel research in compressive strength prediction of HPC. The cosine sensitivity analysis reveals that the prediction of compressive strength of HPC is highly affected by cement content, fine aggregate, coarse aggregate, and water content.

• Anatomy and Cell Biology
• /
• v.57 no.2
• /
• pp.271-277
• /
• 2024

Human dentition is unique to individuals and helps in identification of individuals in forensic odontology. This study proposes to study the manually ground sections of single rooted teeth using digital methods for dental age estimation. To assess the dentinal translucency from the scanned digital images of manually ground section of teeth using commercially available image edition software. Corroborating the root dentinal translucency length and region of interest (ROI) of translucency zone in pixels (as a marker of dental age) with the chronological age of the subject, as stratified by different age groups. Twenty single-rooted extracted teeth from 20 patients each from 6 groups divided as per age. Manual sectioning of the teeth followed by scanning the sections was done. Root area in pixels and ROI of translucency zone were measured. From the observed values, translucency length percentage (TLP) and percentage of ROI in pixels (TPP) was calculated and tabulated. Pearson's correlation coefficients were obtained for age with TLP and TPP. Positive correlation existed between age and TLP and also between age and TPP. With the obtained data, multilinear regression equations for specific age groups based on 10-year intervals were derived. By a step-down analysis method, age was estimated with an average error of around ±7.9 years. This study gives a novel method for age-estimation that can be applied in real-time forensic sciences.

• Communications of the Korean Mathematical Society
• /
• v.39 no.3
• /
• pp.693-715
• /
• 2024

Let n ∈ ℕ, n ≥ 2. An element (x₁, . . . , x_n) ∈ Eⁿ is called a norming point of T ∈ 𝓛(ⁿE) if ||x₁|| = ··· = ||x_n|| = 1 and |T(x₁, . . . , x_n)| = ||T||, where 𝓛(ⁿE) denotes the space of all continuous n-linear forms on E. For T ∈ 𝓛(ⁿE), we define Norm(T) = {(x₁, . . . , x_n) ∈ Eⁿ : (x₁, . . . , x_n) is a norming point of T}. Norm(T) is called the norming set of T. Let $0{\leq}{\theta}{\leq}{\frac{{\pi}}{4}}$ and ${\ell}^2_{{\infty},{\theta}}={\mathbb{R}}^2$ with the rotated supremum norm $${\parallel}(x,y){\parallel}_{({\infty},{\theta})}={\max}\{{\mid}x\;cos\;{\theta}+y\;sin\;{\theta}{\mid},\;{\mid}x\;sin\;{\theta}-y\;cos\;{\theta}|\}$$. In this paper, we characterize the norming set of T ∈ 𝓛(ⁿℓ²_(∞,θ)). Using this result, we completely describe the norming set of T ∈ 𝓛_s(ⁿℓ²_(∞,θ)) for n = 3, 4, 5, where 𝓛_s(ⁿℓ²_(∞,θ)) denotes the space of all continuous symmetric n-linear forms on ℓ²_(∞,θ). We generalizes the results from [9] for n = 3 and ${\theta}={\frac{{\pi}}{4}}$.

• Journal of The Korean Society of Integrative Medicine
• /
• v.12 no.3
• /
• pp.131-142
• /
• 2024

Purpose : This study explores the effects of dental hygiene students' ethical propensity and self-esteem on their awareness of protecting patient medical information and how these factors interact to influence their professional ethical consciousness. The aim of this study is to highlight the role of university education in shaping the ethical values of dental hygienists. Methods : Between June 1 and November 30, 2023, 210 dental hygiene students in Busan Metropolitan City participated in this study. After providing consent, the participants completed a self-administered questionnaire comprising 69 questions. The questions covered general characteristics (8 questions), ethical propensity (20 questions), self-esteem (10 questions), and awareness of patient medical information protection (31 questions), all measured on a five-point Likert scale. Results : Correlation analysis indicated that idealism had a significant positive correlation with relativism (r=0.35, p<.001), self-esteem (r=0.28, p<.001), and awareness of patient medical information protection (r=0.46, p<.001). Relativism had a significant positive correlation with self-esteem (r=0.17, p<0.05) and awareness of patient medical information protection (r=0.23, p<.01). Self-esteem had a significant positive correlation with awareness of patient medical information protection (r=0.34, p<.001). Multilinear regression analysis revealed that idealism (ß=0.38) and self-esteem (ß=0.22) significantly increased the level of awareness of patient medical information protection. However, relativism did not have a significant impact on the level of awareness of patient medical information protection. The model explained 26.0 % of the variance (24.9 % when corrected). Conclusion : Higher levels of idealism and self-esteem correlate with greater awareness of patient medical information protection. In addition to appropriate program development and strategies, university curricula for dental hygiene students should include systematic and continuous training to enhance the values of ethical awareness, idealism, and self-esteem.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.23 no.4
• /
• pp.1-15
• /
• 2024

The COVID-19 pandemic significantly impacted societies, particularly the elderly with higher susceptibility and mobility constraints. This study investigates COVID-19's influence on elderly travel at subway stations using card data. Analyzing pre/post-COVID-19 data via multilinear regression, we found factors like subway transfer lines, presence of rivers, the area of traditional markets, number of traditional Korean medicine clinics, number of cultural facilities, and number of large commercial facilities correlated positively with elderly travel. Post-COVID-19, effects of variables related to public transportation and employment, and indoor leisure facilities decreased, while the effects of outdoor and traditional culture-related facilities increased. These findings indicate significant pandemic-induced alterations in the mobility patterns of senior citizens in Seoul, highlighting shifts towards safer, more accessible environments.

• Korean Journal of Childcare and Education
• /
• v.9 no.6
• /
• pp.417-438
• /
• 2013

This study studies the effect of student teacher's sense of humor, psychological well-being and ego-resilience by general characteristics and by examining the correlation with each other and influences. A sample of 323 student teachers was obtained from a college and a university in the Busan area. This study made use of an research instrument which was a questionnaire for sense of humor(Woo, 2008), psychological well-being(Lee, 2006) and ego-resilience(Park, 1997). For the data analysis connection analysis and regression analysis, SPSS version 18.0 was used. The results of study are as follows. First, student teachers have scores which are above average scores of sense of humor, psychological well-being and ego-resilience. Second, there was a positive correlation between the sense of humor and ego-resilience and a low grade variable of ego-resilience of student teachers and their sense of humor and psychological well-being and between their psychological well-being and ego-resilience. Third, When a multilinear regression analysis was made to confirm which variable would affect ego-resilience, sense of humor and a low grade variable of their was found to exert a statistically significant impact by 5%, and psychological well-being and a low grade variable of their was found to exert a statistically significant impact by 26%. Based on the results, the education training or programs for student teacher to use the sense of humor and psychological well-being should be developed according to the ego-resilience.

• Analytical Science and Technology
• /
• v.12 no.5
• /
• pp.375-381
• /
• 1999

Near infrared spectrophotometry(NIR) was developed as a non-invasive determination of blood alcohol. The first pure alcohol/water samples were prepared with ethanol concentration from 0.01 to 0.1%(w/w). Analysis of the second-derivative data was accomplished with multilinear regression(MLR). The standard error of calibration(SEC) of ethanol in ethanol/water solutions was approximately 0.0039%. The calibration models were established from the blood alcohol spectra by MLR and PLSR analysis. The best calibration was built with the second-derivative spectra of 2266 and 2326 nm by MLR. Second-derivative spectra in the spectral ranges of 1100~1340, 1500~1796 and 2064~2300 nm with four PLSR factors provided the standard error of prediction(SEP) of 0.030%(w/w). These results indicate that NIR may be applied for a fast non-invasive determination of alcohol in the blood.

• Food Science of Animal Resources
• /
• v.38 no.5
• /
• pp.1109-1119
• /
• 2018

In this paper, we report the development of a nondestructive prediction model for lean meat percentage (LMP) in Korean pig carcasses and in the major cuts using a machine vision technique. A popular vision system in the meat industry, the VCS2000 was installed in a modern Korean slaughterhouse, and the images of half carcasses were captured using three cameras from 175 selected pork carcasses (86 castrated males and 89 females). The imaged carcasses were divided into calibration (n=135) and validation (n=39) sets and a multilinear regression (MLR) analysis was utilized to develop the prediction equation from the calibration set. The efficiency of the prediction equation was then evaluated by an independent validation set. We found that the prediction equation - developed to estimate LMP in whole carcasses based on six variables - was characterized by a coefficient of determination ($R^2_v$) value of 0.77 (root-mean square error [RMSEV] of 2.12%). In addition, the predicted LMP values for the major cuts: ham, belly, and shoulder exhibited $R^2_v$ values${\geq}0.8$ (0.73 for loin parts) with low RMSEV values. However, lower accuracy ($R^2_v=0.67$) was achieved for tenderloin cuts. These results indicate that the LMP in Korean pig carcasses and major cuts can be predicted successfully using the VCS2000-based prediction equation developed here. The ultimate advantages of this technique are compatibility and speed, as the VCS2000 imaging system can be installed in any slaughterhouse with minor modifications to facilitate the on-line and real-time prediction of LMP in pig carcasses.

• Steel and Composite Structures
• /
• v.48 no.1
• /
• pp.43-57
• /
• 2023

The impacts of waste tire rubber (WTR) on the bending conduct of reinforced concrete beams (RCBs) are investigated in visualization of experimental tests and 3D finite element model (FEM) using both ANSYS and SAP2000. Several WTR rates are used in total 4 various full scale RCBs to observe the impact of WTR rate on the rupture and bending conduct of RCBs. For this purpose, the volumetric ratios (Vf) of WTR were chosen to change to 0%, 2.5%, 5% and 7.5% in the whole concrete. In relation to experimental test consequences, bending and rupture behaviors of the RCBs are observed. The best performance among the beams was observed in the beams with 2.5% WTR. Furthermore, as stated by test consequences, it is noticed that while WTR rate in the RCBs is improved, max. bending in the RCBs rises. For test consequences, it is clearly recognized as WTR rate in the RCB mixture is improved from 0% to 2.5%, deformation value in the RCB remarkably rises from 3.89 cm to 7.69 cm. This consequence is markedly recognized that WTR rates have a favorable result on deformation values in the RCBs. Furthermore, experimental tests are compared to 3D FEM consequences via using ANSYS software. In the ANSYS, special element types are formed and nonlinear multilinear misses plasticity material model and bilinear misses plasticity material model are chosen for concrete and compression and tension elements. As a consequence, it is noticed that each WTR rates in the RCBs mixture have dissimilar bending and rupture impacts on the RCBs. Then, to observe the impacts of WTR rate on the constructions under near-fault ground motions, a reinforced-concrete building was modelled via using SAP2000 software using 3-D model of the construction to complete nonlinear static analysis. Beam, column, steel haunch elements are modeled as nonlinear frame elements. Consequently, the seismic impacts of WTR rate on the lateral motions of each floor are obviously investigated particularly. Considering reduction in weight of structure and capacity of the members with using waste tire rubber, 2.5% of WTR resulted in the best performance while the construction is subjected to near fault earthquakes. Moreover, it is noticeably recognized that WTR rate has opposing influences on the seismic displacement behavior of the RC constructions.

• Journal of Korean Society of Water and Wastewater
• /
• v.38 no.3
• /
• pp.141-153
• /
• 2024

The purpose of this study is to analyze the correlation between ecotoxicity and water quality items using Daphnia magna in public sewage treatment plant process and to obtain operational data to control ecotoxicity through research on removal efficiency. The average value of ecotoxicity was 1.39 TU in the influent, 1.50 TU in the grit chamber, and 0.84 TU in the primary settling tank and it was found that most organic matters, nitrogen, and phosphorus were removed through biological treatment in the bioreactor. Using Pearson's correlation analysis, the positive correlation was confirmed in the order of ecotoxicity and water quality items TOC, BOD, T-N, NH3-N, SS, EC, and Cu. As a result of conducting a multilinear regression analysis with items representing positive correlation as independent variables, the regression model was found to be statistically significant, and the explanatory power of the regression model was about 81.6%. TOC was found to have a significant effect on ecotoxicity with B=0.009 (p<.001) and Cu with B=16.670 (p<.001), and since the B sign is positive (+), an increase of 1 in TOC increases the value of ecotoxicity by 0.009 and an increase in Cu by 1 increases the value of ecotoxicity by 16.670. TOC (β=0.789, p<.001) and Cu (β=0.209, p<.001) were found to have a significant positive effect on ecotoxicity. TOC and Cu have a great effect on ecotoxicity in the sewage treatment plant process, and it is judged that TOC and Cu should be considered preferentially and controlled in order to efficiently control ecotoxicity.