• Journal of the Society of Naval Architects of Korea
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• v.60 no.1
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• pp.31-37
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• 2023

In the present study, a method of performing cavitation erosion test directly on the anodized surface of the rudder model is proposed, not applying ink or paint on its surface. An image processing technique is newly developed to quantitatively evaluate the erosion damages on the rudder model surface after erosion test. The preprocessing saturation image, image smoothing, adaptive hysteresis thresholding and eroded area detection algorithms are in the image processing program. The rudder cavitation erosion tests are conducted in the rudder deflection angle range of 0° to -4°, which is used to maintain a straight course at the highest speed of the targeted navy ship. In the case of the conventional flat-type full-spade rudder currently being used in the target ship, surface erosion can occur on the model rudder surface in the above rudder deflection angle range. The bubble type of cavitation occurs on rudder surface, which is estimated to be the main reason of erosion damage on the rudder surface.

• 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.

• Journal of radiological science and technology
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• v.40 no.2
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• pp.261-267
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• 2017

The study has attempted to evaluate and compare the image evaluation and exposure dose by respectively applying filter back projection (FBP), the existing test method, and adaptive statistical iterative reconstruction (ASIR) with different values of tube voltage during the low dose computed tomography (LDCT). With the image reconstruction method as basis, chest phantom was utilized with the FBP and ASIR set at 10%, 20% respectively, and the change of tube voltage (100 kVp, 120 kVp). For image evaluation, back ground noise, signal-noise ratio (SNR) and contrast-noise ratio (CNR) were measured, and, for dose assessment, CTDIvol and DLP were measured respectively. In terms of image evaluation, there was significant difference in ascending aorta (AA) SNR and inpraspinatus muscle (IM) SNR with the different amount of tube voltage (p < 0.05). In terms of CTDIvol, the measured values with the same tube voltage of 120 kVp were 2.6 mGy with no-ASIR and 2.17 mGy with 20%-ASIR respectively, decreased by 0.43 mGy, and the values with 100 kVp were 1.61 mGy with no-ASIR and 1.34 mGy with 20%-ASIR, decreased by 0.27 mGy. In terms of DLP, the measured values with 120 kVp were $103.21mGy{\cdot}cm$ with no-ASIR and $85.94mGy{\cdot}cm$ with 20%-ASIR, decreased by $17.27mGy{\cdot}cm$ (about 16.7%), and the values with 100 kVp were $63.84mGy{\cdot}cm$ with no-ASIR and $53.25mGy{\cdot}cm$ with 20%-ASIR, a decrease by $10.62mGy{\cdot}cm$ (about 16.7%). At lower tube voltage, the rate of dose significantly decreased, but the negative effects on image evaluation was shown due to the increase of noise.

• The Korean Journal of Nuclear Medicine
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• v.32 no.6
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• pp.525-533
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• 1998

Purpose: Radiation adaptive response in human peripheral lymphocytes and mouse bone marrow cells was investigated using both metaphase analysis and micronucleus assay. We assessed the correlation between both tests. Materials and Methods: Two groups of the human peripheral lymphocytes and mouse bone marrow cells were exposed to low dose (conditioning dose, 0,18 Gy) or high dose (challenging dose, 2 Gy) ${\gamma}$-rays. The other 4 groups were exposed to low dose followed by high dose after several time intervals (4, 7, 12, and 24 hours, respectively). The frequencies of chromosomal aberrations in metaphase analysis and micronuclei in micronucleus assay were counted. Results: Chromosomal aberrations and micronuclei of preexposed group were lower than those of the group only exposed to high dose radiation. Maximal reduction in frequencies of chromosomal aberrations were observed in the group to which challenging dose was given at 7 hour after a conditioning dose (p<0.001). Metaphase analysis and micronucleus assay revealed very good correlation in both human lymphocytes and mouse bone marrow cells (r=0.98, p<0.001 ; r=0.99, p=0.001, respectively). Conclusion: Radiation adaptive response could be induced by low dose irradiation in both human lymphocytes and mouse bone marrow cells. There was a significant correlation between metaphase analysis and micronucleus assay.

• Journal of the Korean Society of Food Science and Nutrition
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• v.40 no.12
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• pp.1700-1707
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• 2011

This study evaluated the effect of multigrain supplementation on exercise-related changes in running time and glycogen storage capacity of male SD rats engaged in treadmill exercise. Thirty-six 6-week-old rats were divided into six groups: normal (Nor) fed normal feed, control (Con) fed with 20% normal feed and 80% milled rice, test group one (GI) fed with multigrain feed I, test group two (GII) fed with multigrain feed II, test group three (GIII) fed with multigrain feed III, and test group four (GIV) fed with multigrain feed IV. Endurance tests by treadmill machine were administered after 24 days of multigrain feed supplementation and adaptive training. Running time was extended and glycogen storage capacity increased in the multigrain-treated group compared to the non-treated group. Also, the fatigue indicators of inorganic phosphorous, CPK, and lactate concentration were all reduced in the multigrain feed group compared to the control group after 25 min and/or exhausted exercise. But there was no difference in GOP, GTP, lactate, or LDH concentrations between the groups. Our results demonstrated that endurance improved with multigrain feed in rats. Specifically, running time, glycogen storage capacity, inorganic phosphorous, CPK, and lactate serum concentration increased. Importantly, the improvements in endurance brought about in the GII group fed with waxy barley was the greatest among the experimental groups.

• Research in Community and Public Health Nursing
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• v.13 no.1
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• pp.89-97
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• 2002

Purpose: The purpose of this study is to explore the validity of the application of the Denver II developmental screening test to Korean children. This screening test. which was developed and standardized in United States. was designed to screen for developmental delay in Korea. and to compare the levels of development of Korean children with the development of children from the U.S. Method: Quota sampling. NP To facilitate field sampling. the age range used from 0 to 6 years old. was split into 10 different age groups. Sample size was estimated according to residence. 1.054 children were recruited from Seoul's metropolitan. urban and rural areas. NP To fill the quota established. the Recruitment and testing of children was done at public health centers, pediatric outpatient clinics of general hospitals and a child care center. The 25, 50, 75 and 90 percentiles were identified by using logistic regression analysis and were calculated as norms. The items in which the ages of both 50 and 90 percent passing differed more than 20 percent by the calculation was identified for comparison. NP Result: There were significant differences found in 45 items between Korean children and the children from the City of Denver as it relates to age differences. 90% of the sample passed items among 125 items from 4 sectors, e.g., personal- social. fine motor adaptive, language, and gross motor sectors. Korean children were found to be advanced in 9 items, whereas there were significant differences found in 38 items in our comparison of the two countries for age differences when 50% of sample pass items. Korean children were found to be advanced in 16 items. NP Conclusion: The result showed that there was a discrepancy in the developmental norms. It could be explained by the differences in the developmental environment. including child rearing patterns and ethnicity. Therefore, a restandardization of the Denver Screening Test is necessary as it relates to its application on Korean children. This restandardization is necessary in order to avoid both under and over-referrals of children with developmental abnormality. The modification of items in the language sector is especially suggested.

• Journal of Broadcast Engineering
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• v.23 no.3
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• pp.351-360
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• 2018

Human emotion recognition is a research topic that is receiving continuous attention in computer vision and artificial intelligence domains. This paper proposes a method for classifying human emotions through multiple neural networks based on multi-modal signals which consist of image, landmark, and audio in a wild environment. The proposed method has the following features. First, the learning performance of the image-based network is greatly improved by employing both multi-task learning and semi-supervised learning using the spatio-temporal characteristic of videos. Second, a model for converting 1-dimensional (1D) landmark information of face into two-dimensional (2D) images, is newly proposed, and a CNN-LSTM network based on the model is proposed for better emotion recognition. Third, based on an observation that audio signals are often very effective for specific emotions, we propose an audio deep learning mechanism robust to the specific emotions. Finally, so-called emotion adaptive fusion is applied to enable synergy of multiple networks. The proposed network improves emotion classification performance by appropriately integrating existing supervised learning and semi-supervised learning networks. In the fifth attempt on the given test set in the EmotiW2017 challenge, the proposed method achieved a classification accuracy of 57.12%.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.4
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• pp.51-61
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• 2004

In the dental field, the 3D tooth model in which each tooth can be manipulated individually is an essential component for the simulation of orthodontic surgery and treatment. To reconstruct such a tooth model from CT slices, we need to define the accurate boundary of each tooth from CT slices. However, the global threshold method, which is commonly used in most existing 3D reconstruction systems, is not effective for the tooth segmentation in the CT image. In tooth CT slices, some teeth touch with other teeth and some are located inside of alveolar bone whose intensity is similar to that of teeth. In this paper, we propose an image segmentation algorithm based on B-spline curve fitting to produce smooth tooth regions from such CT slices. The proposed algorithm prevents the malfitting problem of the B-spline algorithm by providing accurate initial tooth boundary for the fitting process. This paper proposes an optimal threshold scheme using the intensity and shape information passed by previous slice for the initial boundary generation and an efficient B-spline fitting method based on genetic algorithm. The test result shows that the proposed method detects contour of the individual tooth successfully and can produce a smooth and accurate 3D tooth model for the simulation of orthodontic surgery and treatment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.12A
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• pp.2027-2035
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• 2001

In this paper, we present an audio stream delivery using the AMR (Adaptive Multi-Rate) coder that was adopted by ETSI and 3GPP as a standard vocoder for next generation IMT-2000 service in which includes combined sender (FEC) and receiver reconstruction technique in the Internet. By use of the media-specific FEC scheme, the possibility to recover lost packets can be much increased due to the addition of repair data to a main data stream, by which the contents of lost packets can be recovered. The AMR codec is based on the code-excited linear predictive (CELP) coding model. So we use a frame erasure concealment for CELP-based coders. The proposed scheme is evaluated with ITU-T G.729 (CS-ACELP) coder and AMR - 12.2 kbit/s through the SNR (Signal to Noise Ratio) and the MOS (Mean Opinion Score) test. The proposed scheme provides 1.1 higher in Mean Opinion Score value and 5.61 dB higher than AMR - 12.2 kbit/s in terms of SNR in 10% packet loss, and maintains the communicab1e quality speech at frame erasure rates lop to 20%.

• Journal of the Korean association of regional geographers
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• v.22 no.1
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• pp.251-266
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• 2016

Intelligent interpolation methods such as dasymetric mapping are considered to be the best way to disaggregate zone-based population data by observing and utilizing the internal variation within each source zone. This research reviews the advantages and problems of the dasymetric mapping method, and presents a geographically weighted regression (GWR) based method to take into consideration the spatial heterogeneity of population density - land cover relationship. The locally adaptive intelligent interpolation method is able to make use of readily available ancillary information in the public domain without the need for additional data processing. In the case study, we use the preclassified National Land Cover Dataset 2011 to test the performance of the proposed method (i.e. the GWR-based multi-class dasymetric method) compared to four other popular population estimation methods (i.e. areal weighting interpolation, pycnophylactic interpolation, binary dasymetric method, and globally fitted ordinary least squares (OLS) based multi-class dasymetric method). The GWR-based multi-class dasymetric method outperforms all other methods. It is attributed to the fact that spatial heterogeneity is accounted for in the process of determining density parameters for land cover classes.