• Journal of Korea Foundry Society
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• v.26 no.4
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• pp.184-190
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• 2006

Presence of inclusions in Ti castings imparts detrimental effects on the mechanical performance of castings. However, actual inclusions do not occur very frequently and they are difficult to locate. As a result, acquirement of specimens for mechanical tests and thus in-depth research of the adverse influence of inclusions are challenging. To address this problem, artificial inclusion seeding methodology is developed to emulate actual inclusions in Ti investment castings. Firstly, to validate that this new methodology does not result in inherent mechanical property degradation, Ti specimens with machined, backfilled and HIPed holes are produced and compared to control (unaltered), cast Ti material. Fatigue test results indicate that this 'machine-and-HIP methodology without seeding' does not result in any fundamental mechanical property alteration, which would bias ensuing comparative results. Secondly, based on this result, validation of the artificially seeded inclusions being equivalent to 'as cast' inclusions is performed by comparing their fatigue behaviors. Test specimens created by the novel artificial inclusion seeding methodology are equivalent to Ti casting specimens containing actual cast-in inclusions, and an adverse effect of inclusions in investment castings is confirmed.

• Aerospace Engineering and Technology
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• v.1 no.1
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• pp.28-41
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• 2002

The purpose of this paper is to show and define the performance, the system mechanization and the algorithm of the Strapdown Inertial Navigation System(SDINS). First, navigation equations are derived in the Earth Fixed mechanization and this mechanization apply to the two kinds of inertial measurement units which consist of same fiber optic gyros and different accelerometers(SDINS-1 and SDINS-2). Those two accelerometers have the different bias. To evaluate its performance, two kinds of tests have been performed - static motionless test, and rectangle-route moving test. The results of the moving test are compared with the results of Differential GPS which has an accuracy with ±2.0mm. and are presented in this paper.

• International Journal of Aeronautical and Space Sciences
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• v.18 no.3
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• pp.565-573
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• 2017

This paper presents a multistage in-flight alignment (MIFA) method for a strapdown inertial navigation system (SDINS) suitable for moving vehicles with no initial attitude references. A SDINS mounted on a moving vehicle frequently loses attitude information for many reasons, and it makes solving navigation equations impossible because the true motion is coupled with an undefined vehicle attitude. To determine the attitude in such a situation, MIFA consists of three stages: a coarse horizontal attitude, coarse heading, and fine attitude with adaptive Kalman navigation filter (AKNF) in order. In the coarse horizontal alignment, the pitch and roll are coarsely estimated from the second order damping loop with an input of acceleration differences between the SDINS and GPS. To enhance estimation accuracy, the acceleration is smoothed by a scalar filter to reflect the true dynamics of a vehicle, and the effects of the scalar filter gains are analyzed. Then the coarse heading is determined from the GPS tracking angle and yaw increment of the SDINS. The attitude from these two stages is fed back to the initial values of the AKNF. To reduce the estimated bias errors of inertial sensors, special emphasis is given to the timing synchronization effects for the measurement of AKNF. With various real flight tests using an UH60 helicopter, it is proved that MIFA provides a dramatic position error improvement compared to the conventional gyro compass alignment.

• Journal of Information Processing Systems
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• v.10 no.2
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• pp.314-333
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• 2014

When analyzing default predictions in real estate companies, the number of non-defaulted cases always greatly exceeds the defaulted ones, which creates the two-class imbalance problem. This lowers the ability of prediction models to distinguish the default sample. In order to avoid this sample selection bias and to improve the prediction model, this paper applies a minority sample generation approach to create new minority samples. The logistic regression, support vector machine (SVM) classification, and neural network (NN) classification use an imbalanced dataset. They were used as benchmarks with a single prediction model that used a balanced dataset corrected by the minority samples generation approach. Instead of using prediction-oriented tests and the overall accuracy, the true positive rate (TPR), the true negative rate (TNR), G-mean, and F-score are used to measure the performance of default prediction models for imbalanced dataset. In this paper, we describe an empirical experiment that used a sampling of 14 default and 315 non-default listed real estate companies in China and report that most results using single prediction models with a balanced dataset generated better results than an imbalanced dataset.

• Journal of the Korean earth science society
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• v.42 no.4
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• pp.390-400
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• 2021

Ocean biogeochemistry plays a crucial role in sustaining the marine ecosystem and global carbon cycle. To investigate the oceanic biogeochemical responses to iron parameters in the tropical Pacific, we conducted sensitivity experiments using the Nucleus for European Modelling of the Ocean-Tracers of Ocean Phytoplankton with Allometric Zooplankton (NEMO-TOPAZ) model. Compared to observations, the NEMO-TOPAZ model overestimated the concentrations of chlorophyll and dissolved iron (DFe). The sensitivity tests showed that with increasing (+50%) iron scavenging rates, chlorophyll concentrations in the tropical Pacific were reduced by approximately 16%. The bias in DFe also decreased by approximately 7%; however, the sea surface temperature was not affected. As such, these results can facilitate the development of the model tuning strategy to improve ocean biogeochemical performance using the NEMO-TOPAZ model.

• Communications for Statistical Applications and Methods
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• v.26 no.2
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• pp.205-216
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• 2019

Diagnostic tests in medical fields detect or diagnose a disease with results measured by continuous or discrete ordinal data. The performance of a diagnostic test is summarized using the receiver operating characteristic (ROC) curve and the area under the curve (AUC). The diagnostic test is considered clinically useful if the outcomes in actually-positive cases are higher than actually-negative cases and the ROC curve is concave. In this study, we apply the stochastic ordering method in a Bayesian hierarchical model to estimate the proper ROC curve and AUC when the diagnostic test results are measured in discrete ordinal data. We compare the conventional binormal model and binormal model under stochastic ordering. The simulation results and real data analysis for breast cancer indicate that the binormal model under stochastic ordering can be used to estimate the proper ROC curve with a small bias even though the sample sizes were small or the sample size of actually-negative cases varied from actually-positive cases. Therefore, it is appropriate to consider the binormal model under stochastic ordering in the presence of large differences for a sample size between actually-negative and actually-positive groups.

• Clinical and Experimental Pediatrics
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• v.65 no.3
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• pp.131-135
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• 2022

Purpose: There is inconsistent evidence about the association between fetal nuchal cord and the risk of autism spectrum disorder (ASD). We performed a meta-analysis to investigate whether fetal nuchal cord is associated with an increased risk of ASD in offspring. Methods: Three main English databases were searched until January 2021. The Newcastle-Ottawa Scale was used to assess study quality. Study heterogeneity was determined using the I 2 statistic, while publication bias was assessed using Begg and Egger tests. Results are presented as odds ratios (ORs) and relative ratios with 95% confidence intervals (CI) and were determined by a random-effects model. Results: Five articles (1 cohort, 4 case-control; 3,088 total children) were included in the present meta-analysis. Fetal nuchal cord was not a risk factor for ASD (OR, 1.11; 95% CI, 0.66-1.57). There was homogeneity among studies that reported a risk of ASD (I²=0.0%). Conclusion: Our results showed that fetal nuchal cord is not a risk factor for ASD. Future large cohort studies should confirm this finding.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.18
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• pp.8653-8658
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• 2016

Background: Heparanase is believed to be involved in gastric carcinogenesis. However, the clinicopathologic features of gastric cancer with high heparanase expression remain unclear. Aim : The purpose of this study was to comprehensively and quantitatively summarize available evidence for the use of heparanase mRNA and protein expression to evaluate the clinicopathological associations in gastric cancer in Asian patients by meta-analysis. Materials and Methods: Relevant articles listed in MEDLINE, CNKI and the Cochrane Library databases up to MARCH 2015 were searched by use of several keywords in electronic databases. A meta-analysis was performed to clarify the impact of heparanase mRNA and protein on clinicopathological parameters in gastric cancer. Combined ORs with 95%CIs were calculated by Revman 5.0, and publication bias testing was performed by stata12.0. Results: A total of 27 studies which included 3,891 gastric cancer patients were combined in the final analysis. When stratifying the studies by the pathological variables of heparanase mRNA expression, the depth of invasion (633 patients) (OR=4.96; 95% CI=2.38-1.37; P<0.0001), lymph node metastasis (639 patients) (OR=6.22; 95%CI=2.70-14.34, P<0.0001), and lymph node metastasis (383 patients) (OR=6.85; 95% CI=2.04-23.04; P=0.002) were all significant. When stratifying the studies by the pathological variables of heparanase protein expression, this was the case for depth of invasion (1250 patients) (OR=2.76; 95% CI=1.52-5.03; P=0.0009), lymph node metastasis (1178 patients) (OR=4.79 ; 95% CI=3.37-6.80, P<0.00001), tumor size (727 patients) (OR=2.06 ; 95% CI=1.31-3.23; P=0.002) (OR=2.61; 95% CI=2.09-3.27; P=0.000), and TNM stage (1233 patients) (OR=6.85; 95% CI=2.04-23.04; P=0.002). Egger's tests suggested publication bias for depth of invasion, lymph node metastasis, lymph node metastasis and tumor size of heparanase mRNA and protein expression. Conclusions: This meta-analysis suggests that higher heparanase expression in gastric cancer is associated with clinicopathologic features of depth of invasion, lymph node metastasis and TNM stage at mRNA and protein levels, and of tumor size only at the protein level. Egger's tests suggested publication bias for these clinicopathologic features of heparanase mRNA and protein expression, and which may be caused by shortage of relevant studies. As a result, although abundant reports showed heparanase may be associated with clinicopathologic features in gastric cancer, this meta-analysis indicates that more strict studies were needed to evaluate its clinicopathologic significance.

• International Journal of Highway Engineering
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• v.17 no.2
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• pp.107-122
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• 2015

PURPOSES : The use of virtual driving tests to determine actual road driving behavior is increasing. However, the results indicate a gap between real and virtual driving under same road conditions road based on ergonomic factors, such as anxiety and speed. In the future, the use of virtual driving tests is expected to increase. For this reason, the purpose of this study is to analyze the gap between real and virtual driving on same road conditions and to use a calibration formula to allow for higher reliability of virtual driving tests. METHODS : An intelligent driving recorder was used to capture real driving. A driving simulator was used to record virtual driving. Additionally, a virtual driving map was made with the UC-Win/Road software. We gathered data including geometric structure information, driving information, driver information, and road operation information for real driving and virtual driving on the same road conditions. In this study we investigated a range of gaps, driving speeds, and lateral positions, and introduced a calibration formula to the virtual record to achieve the same record as the real driving situation by applying the effects of the main causes of discrepancy between the two (driving speed and lateral position) using a linear regression model. RESULTS: In the virtual driving test, driving speed and lateral position were determined to be higher and bigger than in the real Driving test, respectively. Additionally, the virtual driving test reduces the concentration, anxiety, and reality when compared to the real driving test. The formula includes four variables to produce the calibration: tangent driving speed, curve driving speed, tangent lateral position, and curve lateral position. However, the tangent lateral position was excluded because it was not statistically significant. CONCLUSIONS: The results of analyzing the formula from MPB (mean prediction bias), MAD (mean absolute deviation) is after applying the formula to the virtual driving test, similar to the real driving test so that the formula works. Because this study was conducted on a national, two-way road, the road speed limit was 80 km/h, and the lane width was 3.0-3.5 m. It works in the same condition road restrictively.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.18 no.7
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• pp.1777-1783
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• 2014

In this paper, we designed and fabricated a high-speed semiconductor sensor for use in power control devices and analyzed the characteristics with pulsed radiation tests. At first, radiation sensitive circular Si PIN diodes with various diameters(0.1 mm ~5.0 mm) were designed and fabricated using Si epitaxial wafer, which has a $42{\mu}m$ thick intrinsic layer. The reverse leakage current of the diode with a radius of 2 mm at a reverse bias of 30 V was about 20.4 nA. To investigate the characteristic responses of the developed diodes, the pulsed gamma-radiation tests were performed with the intensity of 4.88E8 rad(Si)/sec. From the test results showing that the output currents and the rising speeds have a linear relationship with the area of the sensors, we decided that the optimal condition took place at a 2 mm diameter. Next, for the selected 2 mm diodes, dose rate tests with a range of 2.47E8 rad(Si)/sec to 6.21E8 rad(Si)/sec were performed. From the results, which showed linear characteristics with the radiation intensity, a large amount of photocurrent over 60mA, and a high speed response under 350ns without saturation, we can conclude that the our developed PIN diode can be a good candidate for the sensor of power control devices.