• Composite Materials and Engineering
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• v.3 no.3
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• pp.201-220
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• 2021

In this study, potential of three machine learning techniques i.e., M5P, Support vector machines and Gaussian processes were evaluated to find the best algorithm for the prediction of flexural strength of concrete mix with steel fibre. The study comprises the comparison of results obtained from above-said techniques for given dataset. The dataset consists of 124 observations from past research studies and this dataset is randomly divided into two subsets namely training and testing datasets with (70-30)% proportion by weight. Cement, fine aggregates, coarse aggregates, water, super plasticizer/ high-range water reducer, steel fibre, fibre length and curing days were taken as input parameters whereas flexural strength of the concrete mix was taken as the output parameter. Performance of the techniques was checked by statistic evaluation parameters. Results show that the Gaussian process technique works better than other techniques with its minimum error bandwidth. Statistical analysis shows that the Gaussian process predicts better results with higher coefficient of correlation value (0.9138) and minimum mean absolute error (1.2954) and Root mean square error value (1.9672). Sensitivity analysis proves that steel fibre is the significant parameter among other parameters to predict the flexural strength of concrete mix. According to the shape of the fibre, the mixed type performs better for this data than the hooked shape of the steel fibre, which has a higher CC of 0.9649, which shows that the shape of fibers do effect the flexural strength of the concrete. However, the intricacy of the mixed fibres needs further investigations. For future mixes, the most favorable range for the increase in flexural strength of concrete mix found to be (1-3)%.

• Structural Engineering and Mechanics
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• v.86 no.1
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• pp.119-137
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• 2023

The purpose of this research is to assess the performance of CBN and ceramic tools during the dry turning of gray cast iron EN GJL-350. During the turning operation, the variable machining parameters are cutting speed, feed rate, depth of cut and type of the cutting material. This contribution consists of two sections, the first one deals with the performance evaluation of four materials in terms of evolution of flank wear, surface roughness (2D and 3D) and cutting forces. The focus of the second section is on statistical analysis, followed by modeling and optimization. The experiments are conducted according to the Taguchi design L₃₂ and based on ANOVA approach to quantify the impact of input factors on the output parameters, namely, the surface roughness (Ra), the cutting force (Fz), the cutting power (Pc), specific cutting energy (Ecs). The RSM method was used to create prediction models of several technical factors (Ra, Fz, Pc, Ecs and MRR). Subsequently, the desirability function approach was used to achieve a multi-objective optimization that encompasses the output parameters simultaneously. The aim is to obtain optimal cutting regimes, following several cases of optimization often encountered in industry. The results found show that the CBN tool is the most efficient cutting material compared to the three ceramics. The optimal combination for the first case where the importance is the same for the different outputs is Vc=660 m/min, f=0.116 mm/rev, ap=0.232 mm and the material CBN. The optimization results have been verified by carrying out confirmation tests.

• Journal of the Korean Society of Radiology
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• v.11 no.5
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• pp.303-312
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• 2017

The central goal of Gamma Knife radiosurgery(GKRS) is to maximize the conformity of the prescription isodose surface, and to minimize the radiation effect of the normal tissue surrounding the target volume. There are the various kinds of indices related with the quality of treatment plans such as conformity index, coverage, selectivity, beam-on time, gradient index(GI), and conformity/gradient index(CGI). As the best treatment plan evaluation tool, we must check by all means conformity index, GI, and CGI among them. Specially, GI and CGI related with complication of healthy normal tissue is more indispensible than conformity index. Then author calculated and statistically analysed CGI, the newly defined conformity/gradient index as well as GI being applied widely using the treatment planning system Leksell GammaPlan(LGP) and the verification method Variable Ellipsoid Modeling Technique(VEMT). In the study 10 patients with intracranial lesion treated by GKRS were included. Author computed the indices from LGP and VEMT requiring only four parameters: the prescribed isodose volume, the volume with dose > 30%, the target volume, and the volume of half the prescription isodose. All data were analyzed by paired t-test, which is statistical method used to compare two different measurement techniques. No statistical significance in GI at 10 cases was observed between LGP and VEMT. Differences in GI ranged from -0.14 to 0.01. The newly defined gradient index calculated by two methods LGP and VEMT was not statistically significant either. Author did not find out the statistical difference for the prescribed isodose volume between LGP and VEMT. CGI as the evaluation index for determining the best treatment plan is not significant statistically also. Differences in CGI ranged from -4 to 3. Similarly newly defined Conformity/Gradient index for GKRS was also estimated as the metric for the evaluation of the treatment plans through statistical analysis. Statistical analyses demonstrated that VEMT was in excellent agreement with LGP when considering GI, new gradient index, CGI, and new CGI for evaluating the best plans of GKRS. Due to the application of the fast and easy evaluation tool through LGP and VEMT author hopes CGI and newly defined CGI as well as gradient indices will be widely used.

• Journal of Environmental Impact Assessment
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• v.30 no.2
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• pp.75-88
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• 2021

Six locations in the automated monitoring network at the Geum River Basin were selected forthis study. The water quality characteristics at two of the locations in the water quality monitoring network that were identical, or nearby, were examined, and their correlations were evaluated through statistical analysis. The results of the water quality analysis were converted to the water quality index and expressed in grades for comparison. For the data necessary for the study, public data from four years, from 2016-2019 were used and the evaluation parameters were water temperature, pH, EC, DO, TOC, TN, and TP. Results of the analysis showed that the water quality concentrations measured in the automated monitoring network and the water quality monitoring network differed in some measured values, but they tended to register variation in a specified ratio in most of the locations in the network. The analysis of the correlations of the parameters between the two monitoring networks found that water temperature, EC, and DO showed high correlations between the two monitoring networks. The TOC, TN, and TP showed high correlations, with a 0.7 or higher (correlation coefficient r), with the exception of some of the monitoring networks, although their correlations were lower than those of the basic parameters. The water quality index analysis showed that the water quality index values of the automated monitoring network and the water quality monitoring network were similar. The water quality index decreased and the pollution degree increased in the downstream direction, in both networks.

• Journal of Oral Medicine and Pain
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• v.20 no.2
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• pp.407-420
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• 1995

This study was performed to evaluate and compare conservative treatment results by several parameters such as age, sex, symptom duration, type and timing of joint sound, parafunctional habits, splint type, and diagnostic classification. There have been too many articles reporting long term results of conservative treatment but articles related to comparison of treatment results by patients' self-evaluation have been rarely reported. For this study 258 patients with temporomandibular disorders(TMDs) were selected and examined by routine diagnostic procedure for TMDs. The subjects were classified into 5 TMDs subgroups ad treated with conservative treatments involving splints, physical modalities, jaw exercises, and counseling. Visual analogue scale(VAS) about pain, joint sound, and mouth opening limitation was recorded respectively during treatment period. From the VAS data and treatment duration, VAS treatment index(VAS Ti) was calculated. The obtained results were as follows : 1. Pain was the most frequent main symptom in subjects with temporomandibular disorders, and main symptom for mouth opening limitation was comparatively less than for pain or sound in disk displacement with reduction group or in degenerative joint disease group. 2. Degenerative joint disease group had the most poor treatment results and highest occlusal index of Helkim's index. 3. Good prognosis for conservative treatment was observed in acute group, under 6 months than chronic group, 6months over in symptom duration, and subjects with 40 years over in age showed the most poor prognosis. 4. Subjects treated with anterior repositioning splint had better treatment results than subjects treated with centric relation splint, but statistical significance in VAS Ti and treatment duration was not observed. 5. Treatment results according to affected side, types and point of joint sound did not show consistent statistical results. 6. The result for conservative treatment was observed poor in subjects with bruxism and clenching. 7. In studying coincidence between preferred chewing and affected side, frequency of preferred chewing side, in unilateral affection, was higher in ipsilateral than in contralateral side.

• Nuclear Engineering and Technology
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• v.47 no.4
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• pp.472-478
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• 2015

The patient dose incurred from diagnostic procedures during advanced radiotherapy has become an important issue. Many researchers in medical physics are using computational simulations to calculate complex parameters in experiments. However, extended computation times make it difficult for personal computers to run the conventional Monte Carlo method to simulate radiological images with high-flux photons such as images produced by computed tomography (CT). To minimize the computation time without degrading imaging quality, we applied a deterministic adaptation to the Monte Carlo calculation and verified its effectiveness by simulating CT image reconstruction for an image evaluation phantom (Catphan; Phantom Laboratory, New York NY, USA) and a human-like voxel phantom (KTMAN-2) (Los Alamos National Laboratory, Los Alamos, NM, USA). For the deterministic adaptation, the relationship between iteration numbers and the simulations was estimated and the option to simulate scattered radiation was evaluated. The processing times of simulations using the adaptive method were at least 500 times faster than those using a conventional statistical process. In addition, compared with the conventional statistical method, the adaptive method provided images that were more similar to the experimental images, which proved that the adaptive method was highly effective for a simulation that requires a large number of iterations-assuming no radiation scattering in the vicinity of detectors minimized artifacts in the reconstructed image.

• Journal of the Korea Organic Resources Recycling Association
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• v.21 no.2
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• pp.88-96
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• 2013

The objective of this research was to evaluate the suitability of sigmoidal and firstorder kinetic equations for simulating the methane production from solid wastes. The sigmoidal kinetic equations used were modified Gompertz and Logistic equations. Statistical criteria used to evaluate equation performance were analysis of goodness-of-fit (Residual sum of squares, Root mean squared error and Akaike's Information Criterion). Akaike's Information Criterion (AIC) was employed to compare goodness-of-fit of equations with same and different numbers of parameters. RSS and RMSE were decreased for first-order kinetic equation with lag-phase time, compared to the first-order kinetic equation without lag-phase time. However, first-order kinetic equations had relatively higher AIC than the sigmoidal kinetic equations. It seemed that the sigmoidal kinetic equations had better goodness-of-fit than the first-order kinetic equations in order to simulate the methane production.

• Journal of Korean Society on Water Environment
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• v.24 no.1
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• pp.54-62
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• 2008

It is often believed that a more complex water quality model is better able to simulate reality. The more complex a model, however, the more parameters are involved thus increases the cost and uncertainty of modeling processes. The objective of this study was to compare the performance of two steady-state river water quality models, QUAL2E and QUAL-NIER, that have different complexity. QUAL-NIER is recently developed by National Institute of Environmental Research aiming to enhance the simulation capability of QUAL2E for eutrophic rivers. It is a carbon based model that considers different forms, such as dissolved versus particulate and labile versus refractory, of carbon and nutrients, and the contribution of autochthonous loading due to algal metabolism. The models were simultaneously applied to Nakdong River and their performance was evaluated by statistical verification with field data. Both models showed similar performance and satisfactorily replicated the longitudinal variations of BOD, T-N, T-P, Chl.a concentrations along the river. The algal blooms occurred at the stagnant reaches of downstream were also reasonably captured by the models. Although QUAL-NIER somewhat reduced the magnitude of errors, the hypothesis tests revealed no statistical evidence to justify its better performance. The contribution of autochthonous carbon and nutrient load by algal metabolism was insignificant because the hydraulic retention time is relatively short compare to the time scale of kinetic reactions. The results imply that the kinetic processes included in QUAL-NIER are too complex for the nature and scale of the real processes involved, thus needs to be optimized for improving the modeling efficiency.

• Archives of Pharmacal Research
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• v.18 no.6
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• pp.385-390
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• 1995

The analytical methods for the analysis of cyclosporine (CsA), a fluorescence polarization immunoassay (FPIA) and HPLC method, were compared in a pharmacokinetic study of two CsA soft capsule formultaions ($Sandimmun^{\circledR}$; Sandoz, $Implanta^{\circledR}$; Hanmi). Sixteen healthy volunteers completed the study and each subjected single doses ($4{\tiems}100$ mg) of the test and the reference formulations in a two-way crossover design with a one-week drug-free interval between doses. Following each administration, whole blood concentrations of CsA were monitored over a period of 24 hour by both FPIA and HPLC methods. Blood concentrations nad pharmacokinetic parameters determined by either analytical method showed large intersubject variation, with the FPIA data showing relatively higher magnitude of intersubjecte variation than the HPLC data. The blood concentrations determined by FPIA were 1.1-1.3 times higher than those determined by HPLC. There were strong and significant correlations between the two methods (r>0.83 : p<0.0001). Intersubuject variation for the $AUC_{inf}{\;}and{\;}AUC_{24hr}$ of the test formulation was slightly reduced without statistical significance (paried -t test : p>0.05 $t_{max}$ was earlier nad $C_{max}$ was slightly lower for the test formulation, $AUC_{24h}, {\;}C_{max}, {\;}T_{max}$ and MRT determined separately from the data obtained by the two methods for the two formulations were examined by analyses of variance (ANOVA) for the bioequivalency evaluation. Results of ANOVA and confidence limits of terst/reference ratios of $AUC_{24th}$, $C_{max}$, $t_{max}$ and MRT, and statistical tests indicated the bioequivalence of the two formulations (i.e., test/reference ratio was within $100{\times}20%$) except for $C_{max}$ and $t_{max}$. The mean of tmax also showed 11.1% and 9.3% differences but the detection limit were 29.2% and 29.6% as determined by FPIA and HPLC resepctively. This experiments suggest that the data yielded for the two formulations demonstrated that they were bioequivalent.

• Journal of Korean Society for Quality Management
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• v.49 no.2
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• pp.145-159
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• 2021

Purpose: A statistical similarity evaluation to compare pharmacokinetics(PK) profile data between nonclinical and clinical experiments has become a significant issue on many drug development processes. This study proposes a new similarity index by considering important parameters, such as the area under the curve(AUC) and the time-series profile of various PK data. Methods: In this study, a new profile similarity index(PSI) by using the concept of a process capability index(Cp) is proposed in order to investigate the most similar animal PK profile compared to the target(i.e., Human PK profile). The proposed PSI can be calculated geometric and arithmetic means of all short term similarity indices at all time points on time-series both animal and human PK data. Designed simulation approaches are demonstrated for a verification purpose. Results: Two different simulation studies are conducted by considering three variances(i.e., small, medium, and large variances) as well as three different characteristic types(smaller the better, larger the better, nominal the best). By using the proposed PSI, the most similar animal PK profile compare to the target human PK profile can be obtained in the simulation studies. In addition, a case study represents differentiated results compare to existing simple statistical analysis methods(i.e., root mean squared error and quality loss). Conclusion: The proposed PSI can effectively estimate the level of similarity between animal, human PK profiles. By using these PSI results, we can reduce the number of animal experiments because we only focus on the significant animal representing a high PSI value.