• Asian-Australasian Journal of Animal Sciences
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• v.24 no.9
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• pp.1192-1198
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• 2011

Peri-partum metabolic profile was evaluated in winter and summer calving, with 15 Murrah buffaloes in each seasonal group. In summer calvers, significantly lower values were observed for blood plasma urea nitrogen (BUN) at day 30 pre-partum (p<0.05), on calving day (p<0.05) and at all other stages (p<0.01); plasma non-esterified fatty acids (NEFA) values were significantly lower on day 30 pre-partum (p<0.01) and on day 60 post-partum (p<0.05). This was associated with significant reduction in days to first service (DFS) and service per conception (SPC) and an overall better reproductive performance in terms of service period, risk to first service on days 60, 90 and >90, and pregnancy risk to first service up to days 60 and 90. This may be attributed to better pre-partum nutritional status. Cervical and uterine involution were completed in fewer days, involutional changes took place at a faster pace and there were a lower number of abnormal involutional changes in winter compared to summer season. This may be attributed to better post-partum nutrition and less environmental stress. However, validation requires further targeted cohort investigation with a large sample size.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.847-859
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• 2011

cDNA microarray-based comparative genomic hybridization(CGH) data includes low-intensity spots and thus a statistical strategy is needed to detect subtle differences between different cancer classes. In this study, genes displaying a high frequency of alteration in one of the different classes were selected among the pre-selected genes that show relatively large variations between genes compared to total variations. Utilizing copy-number changes of the selected genes, this study suggests a statistical approach to predict patients' classes with increased performance by pre-classifying patients with similar genetic alteration scores. Two-stage logistic regression model(TLRM) was suggested to pre-classify homogeneous patients and predict patients' classes for cancer prediction; a decision tree(DT) was combined with logistic regression on the set of informative genes. TLRM was constructed in cDNA microarray-based CGH data from the Cancer Metastasis Research Center(CMRC) at Yonsei University; it predicted the patients' clinical diagnoses with perfect matches (except for one patient among the high-risk and low-risk classified patients where the performance of predictions is critical due to the high sensitivity and specificity requirements for clinical treatments. Accuracy validated by leave-one-out cross-validation(LOOCV) was 83.3% while other classification methods of CART and DT performed as comparisons showed worse performances than TLRM.

• Steel and Composite Structures
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• v.20 no.6
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• pp.1205-1219
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• 2016

This paper presents a new type of pre-pressed spring self-centering energy dissipation (PS-SCED) bracing system that combines friction mechanisms between the inner and outer tube members to provide the energy dissipation with the pre-pressed combination disc springs installed on both ends of the brace to provide the self-centering capability. The mechanics and the equations governing the design and hysteretic responses of the bracing system are outlined, and a series of validation tests of components comprising the self-centering mechanism of combination disc springs, the friction energy dissipation mechanism, and a large scale PS-SCED bracing specimen were conducted due to the low cyclic reversed loadings. Experimental results demonstrate that the proposed bracing system performs as predicted by the equations governing its mechanical behaviors, which exhibits a stable and repeatable flag-shaped hysteretic response with excellent self-centering capability and appreciable energy dissipation, and large ultimate bearing and deformation capacities. Results also show that almost no residual deformation occurs when the friction force is less than the initial pre-pressed force of disc springs.

• Structural Engineering and Mechanics
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• v.86 no.4
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• pp.519-533
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• 2023

This work focuses on the dynamic analysis of thermal barrier coated straight and curved turbine blades modelled as functionally graded sandwich panel under thermal environment. The pre- twisted straight/curved blade model is considered to be fixed to the hub and, the complete assembly of the hub and blade are assumed to be rotating. The functionally graded sandwich composite blade is comprised of functionally graded face-sheet material and metal alloy core. The constituents' material properties are assumed to be temperature-dependent, however, the overall properties are evaluated using Voigt's micromechanical scheme in conjunction with the modified power-law functions. The blade model kinematics is based on the equivalent single-layer shear deformation theory. The equations of motion are derived using the extended Hamilton's principle by including the effect of centrifugal forces, and further solved via 2D- isoparametric finite element approximations. The mesh refinement and validation tests are performed to illustrate the stability and accurateness of the present model. In addition, frequency characteristics of the pre-twisted rotating sandwich blades are computed under thermal environment at various sets of parametric conditions such as twist angles, thickness ratios, aspect ratios, layer thickness ratios, volume fractions, rotational velocity and blade curvatures which can be further useful for designing the blade type structures under turbine operating conditions.

• Journal of KIISE:Software and Applications
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• v.34 no.10
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• pp.910-917
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• 2007

Of the possible interactions between human and robot, touch is an important means of providing human beings with emotional relief. However, most previous studies have focused on interactions based on voice and images. In this paper. a method of recognizing human touching behaviors is proposed for developing a robot that can naturally interact with humans through touch. In this method, the recognition process is divided into pre-process and recognition Phases. In the Pre-Process Phase, recognizable characteristics are calculated from the data generated by the touch detector which was fabricated using force sensors. The force sensor used an FSR (force sensing register). The recognition phase classifies human touching behaviors using a multi-layer perceptron which is a neural network model. Experimental data was generated by six men employing three types of human touching behaviors including 'hitting', 'stroking' and 'tickling'. As the experimental result of a recognizer being generated for each user and being evaluated as cross-validation, the average recognition rate was 82.9% while the result of a single recognizer for all users showed a 74.5% average recognition rate.

• Journal of Preventive Medicine and Public Health
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• v.39 no.2
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• pp.165-170
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• 2006

Objectives : The determination of oxalate in urine is required for the diagnosis and treatment of primary hyperoxaluria, idiopathic stone disease and various intestinal diseases. We examined the possibility of using Fourier transform near-infrared (FT-NIR) spectroscopy analysis to quantitate urinary oxalate. The practical advantages of this method include ease of the sample preparation and operation technique, the absence of sample pre-treatments, rapid determination and noninvasiveness. Methods : The range of oxalate concentration in standard urine solutions was $0-221mg/{\ell}$. These 80 different samples were scanned in the region of 780-1,300 nm with a 0.5 nm data interval by a Spectrum One NTS FT-NIR spectrometer. PCR, PLSR and MLR regression models were used to calculate and evaluate the calibration equation. Results : The PCR and PLSR calibration models were obtained from the spectral data and they are exactly same. The standard error of estimation (SEE) and the % variance were $10.34mg/{\ell}$ and 97.86%, respectively. After full cross validation of this model, the standard error of estimation was $5,287mg/{\ell}$, which was much smaller than that of the pre-validation. Furthermore, the MCC (multiple correlation coefficient) was 0.998, which was compatible with the 0.923 or 0.999 obtained from the previous enzymatic methods. Conclusions : These results showed that FT-NIR spectroscopy can be used for rapid determination of the concentration of oxalate in human urine samples.

• KIISE Transactions on Computing Practices
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• v.22 no.3
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• pp.119-126
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• 2016

In this study, we verified the feasibility of a Korean morphological analyzer that uses a pre-analyzed Eojeol dictionary and syllable-based probabilistic model. For the verification, MACH and KLT2000, Korean morphological analyzers, were cloned with a pre-analyzed eojeol dictionary and syllable-based probabilistic model. The analysis results were compared between the cloned morphological analyzer, MACH, and KLT2000. The 10 million Eojeol Sejong corpus was segmented into 10 sets for cross-validation. The 10-fold cross-validated precision and recall for cloned MACH and KLT2000 were 97.16%, 98.31% and 96.80%, 99.03%, respectively. Analysis speed of a cloned MACH was 308,000 Eojeols per second, and the speed of a cloned KLT2000 was 436,000 Eojeols per second. The experimental results indicated that a Korean morphological analyzer that uses a pre-analyzed eojeol dictionary and syllable-based probabilistic model could be used in practical applications.

• Nuclear Engineering and Technology
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• v.44 no.5
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• pp.551-560
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• 2012

The Wolsong-1 (W-1) Phase-B pre-simulations were carried out in preparation for tests to be conducted for the restart of the reactor after a major refurbishment project that included replacement of the pressure tube. These pre-simulations for Wolsong-1 Phase-B differ from those in the past that were performed for the Wolsong-1,2,3,4 tests in that these tests use the WIMS/DRAGON/RFSP-IST code suite for verification of the tests and gadolinium instead of the traditional PPV/MULTICELL/RFSP code system and boron as poison in the moderator system. The use of gadolinium is deemed not to have domestically accumulated experience gained from the previous Phase-B tests. Thus, it is appropriate to conduct a study in order to gain a correct understanding and interpretation of potential differences in test results stemming from using gadolinium rather than boron. Although the calibration of the reactivity device will not be noticeably different using boron and gadolinium at a constant moderator temperature, the temperature dependency of the neutronic behavior due to the presence of gadolinium in the moderator system might be pronounced. The results of the pre-simulations using gadolinium revealed that the moderator temperature reactivity coefficients indeed showed significant differences in comparison with those with boron. In order to secure the validity of the analysis results, the newly acquired WIMS/DRAGON/RFSP-IST code suite was verified against the W-2,3,4 Phase-B test results. The results of the new code suite verifications revealed some overall improvements in accuracy; justification of the use of the code can be claimed for the validation of the W-1 Phase-B test results.

• Journal of Creative Information Culture
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• v.7 no.3
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• pp.129-144
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• 2021

This study was conducted for the purpose of developing a design thinking-based capstone design instructional model for pre-service teachers. Through the analysis of literature related to learner-centered instruction, design thinking and capstone design instructional design principles and instructional models for pre-service teacher education were discovered, and core elements were derived. Based on the core elements derived through literature analysis, the capstone design instructional design model and teaching and learning model based on design thinking for pre-service teachers were developed. The developed model conducted a total of three Delphi surveys including expert validation for 6 experts related to education including design thinking, capstone design, was revised, supplemented, and the final draft was confirmed. The final results of this study contain the overall contents of the instructional design, instructor's activities in detailed steps, and guidelines for learners' activities.

• Structural Engineering and Mechanics
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• v.46 no.5
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• pp.673-693
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• 2013

This paper presents a systematic design and training procedure for the feed-forward back-propagation neural network (NN) modeling of both forward and inverse behavior of a rotary magnetorheological (MR) damper based on experimental data. For the forward damper model, with damper force as output, an optimization procedure demonstrates accurate training of the NN architecture with only current and velocity as input states. For the inverse damper model, with current as output, the absolute value of velocity and force are used as input states to avoid negative current spikes when tracking a desired damper force. The forward and inverse damper models are trained and validated experimentally, combining a limited number of harmonic displacement records, and constant and half-sinusoidal current records. In general the validation shows accurate results for both forward and inverse damper models, where the observed modeling errors for the inverse model can be related to knocking effects in the measured force due to the bearing plays between hydraulic piston and MR damper rod. Finally, the validated models are used to emulate pure viscous damping. Comparison of numerical and experimental results demonstrates good agreement in the post-yield region of the MR damper, while the main error of the inverse NN occurs in the pre-yield region where the inverse NN overestimates the current to track the desired viscous force.