• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.6C
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• pp.339-347
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• 2008

The penetration of the probe produces the excess pore pressure due to the disturbance. The objective of this study is to evaluate the disturbance zone by using the dissipation of the excess pore water pressure, which was generated due to the penetration of the penetrometer with different size. The CPT, DMT and FVP (Field Velocity Probe) are adopted for in-situ tests. The tests are carried out in the construction site of north container pier of Busan new port, Korea where is accelerating the consolidation settlement using plastic board drains (PBD) and surcharges by crushed gravels. The coefficient of consolidation $(C_h)$ and soil properties are deduced by the laboratory test. The in-site tests are performed after the predrilling the surcharge zone at the point of 90% degree of consolidation. To minimize the penetration effect, the horizontal distance between penetration tests is 3m, the change of the pore pressure is monitored at the fixed depth of 24m. The coefficient of consolidation $(C_h)$ and the $t_{50}s$ are calculated based on the laboratory test and the in-situ data, respectively. The equvalent radi based on the $t_{50}$ shows that the FVP and the DMT produce the smallest and the greatest equivalent radi, respectively.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.202-202
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• 2022

Recently days, soybean production in paddy field is increasing, from 4,422 ha in 2016 to 10,658 ha in 2021 in Korea. It is easy for Phytophthora stem and root rot (PSR) occurring in paddy field condition, when it is poorly drained soils with a high clay content, and temporary flooding and ponding. Therefore PSR resistant soybean cultivar is required. The objective of this study is to identify QTL region and candidate genes relating to PSR resistance of the race in main soybean cultivation area in Korea. 210 soybean materials including cultivars and germplasm were used for inoculation and genome-wide association study (GWAS). Inoculation was conducted using stem-scar method with 2 replications in 2-year for the race 3053 from Kimje and 3617 from Andong. 210 materials were genotyped with Soya SNP 180K chip, and structure analysis and association mapping were conducted with QTLMAX V2. The results of inoculation showed that survival ratio ranged from 0% to 96.7% and mean 9.7% for 3053 and ranged from 0% to 100% and mean 7.6% for 3617. Structure analysis showed linkage disequillibrium (LD) was decayed below r²=0.5 at 335kb of SNP distance. Significant SNPs (LOD>7.0) were identified in Chr 1, 2, 3, 4, 5, 11, 14, 15 for 3053 and Chr 1, 2, 3, 7, 10, 14 for 3617. Especially, LD blocks (AX-90455181;15,056,628bp~AX-90475572;15,298,872bp) in Chr 2 for 3053 and 3067 were duplicated. 29 genes were identified on these genetic regions including Glyma.02gl47000 relating to ribosome recycling factor and defense response to fungus in Soybase.

• Journal of IKEEE
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• v.27 no.4
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• pp.486-493
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• 2023

In this paper, we propose an automatic hand gesture area extraction and recognition technique using FMCW radar-based point cloud and LSTM. The proposed technique has the following originality compared to existing methods. First, unlike methods that use 2D images as input vectors such as existing range-dopplers, point cloud input vectors in the form of time series are intuitive input data that can recognize movement over time that occurs in front of the radar in the form of a coordinate system. Second, because the size of the input vector is small, the deep learning model used for recognition can also be designed lightly. The implementation process of the proposed technique is as follows. Using the distance, speed, and angle information measured by the FMCW radar, a point cloud containing x, y, z coordinate format and Doppler velocity information is utilized. For the gesture area, the hand gesture area is automatically extracted by identifying the start and end points of the gesture using the Doppler point obtained through speed information. The point cloud in the form of a time series corresponding to the viewpoint of the extracted gesture area is ultimately used for learning and recognition of the LSTM deep learning model used in this paper. To evaluate the objective reliability of the proposed technique, an experiment calculating MAE with other deep learning models and an experiment calculating recognition rate with existing techniques were performed and compared. As a result of the experiment, the MAE value of the time series point cloud input vector + LSTM deep learning model was calculated to be 0.262 and the recognition rate was 97.5%. The lower the MAE and the higher the recognition rate, the better the results, proving the efficiency of the technique proposed in this paper.

• Animal Bioscience
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• v.37 no.5
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• pp.795-806
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• 2024

Objective: Karan Fries (KF), a high-producing composite cattle was developed through crossing indicine Tharparkar cows with taurine bulls (Holstein Friesian, Brown Swiss, and Jersey), to increase the milk yield across India. This composite cattle population must maintain sufficient genetic diversity for long-term development and breed improvement in the coming years. The level of linkage disequilibrium (LD) measures the influence of population genetic forces on the genomic structure and provides insights into the evolutionary history of populations, while the decay of LD is important in understanding the limits of genome-wide association studies for a population. Effective population size (N_e) which is genomically based on LD accumulated over the course of previous generations, is a valuable tool for e valuation of the genetic diversity and level of inbreeding. The present study was undertaken to understand KF population dynamics through the estimation of N_e and LD for the long-term sustainability of these breeds. Methods: The present study included 96 KF samples genotyped using Illumina HDBovine array to estimate the effective population and examine the LD pattern. The genotype data were also obtained for other crossbreds (Santa Gertrudis, Brangus, and Beefmaster) and Holstein Friesian cattle for comparison purposes. Results: The average LD between single nucleotide polymorphisms (SNPs) was r² = 0.13 in the present study. LD decay (r² = 0.2) was observed at 40 kb inter-marker distance, indicating a panel with 62,765 SNPs was sufficient for genomic breeding value estimation in KF cattle. The pedigree-based N_e of KF was determined to be 78, while the N_e estimates obtained using LD-based methods were 52 (SNeP) and 219 (genetic optimization for N_e estimation), respectively. Conclusion: KF cattle have an N_e exceeding the FAO's minimum recommended level of 50, which was desirable. The study also revealed significant population dynamics of KF cattle and increased our understanding of devising suitable breeding strategies for long-term sustainable development.

• Korean Journal of Radiology
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• v.22 no.12
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• pp.1974-1984
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• 2021

Objective: This study aimed to compare the efficacy between no-touch (NT) radiofrequency ablation (RFA) and conventional RFA using twin internally cooled wet (TICW) electrodes in the bipolar mode for the treatment of small hepatocellular carcinomas (HCC). Materials and Methods: In this single-center, two-arm, parallel-group, prospective randomized controlled study, we performed a 1:1 random allocation of eligible patients with HCCs to receive NT-RFA or conventional RFA between October 2016 and September 2018. The primary endpoint was the cumulative local tumor progression (LTP) rate after RFA. Secondary endpoints included technical conversion rates of NT-RFA, intrahepatic distance recurrence, extrahepatic metastasis, technical parameters, technical efficacy, and rates of complications. Cumulative LTP rates were analyzed using Kaplan-Meier analysis and the Cox proportional hazard regression model. Considering conversion cases from NT-RFA to conventional RFA, intention-to-treat and as-treated analyses were performed. Results: Enrolled patients were randomly assigned to the NT-RFA group (37 patients with 38 HCCs) or the conventional RFA group (36 patients with 38 HCCs). Among the NT-RFA group patients, conversion to conventional RFA occurred in four patients (10.8%, 4/37). According to intention-to-treat analysis, both 1- and 3-year cumulative LTP rates were 5.6%, in the NT-RFA group, and they were 11.8% and 21.3%, respectively, in the conventional RFA group (p = 0.073, log-rank). In the as-treated analysis, LTP rates at 1 year and 3 years were 0% and 0%, respectively, in the NT-RFA group sand 15.6% and 24.5%, respectively, in the conventional RFA group (p = 0.004, log-rank). In as-treated analysis using multivariable Cox regression analysis, RFA type was the only significant predictive factor for LTP (hazard ratio = 0.061 with conventional RFA as the reference, 95% confidence interval = 0.000-0.497; p = 0.004). There were no significant differences in the procedure characteristics between the two groups. No procedure-related deaths or major complications were observed. Conclusion: NT-RFA using TICW electrodes in bipolar mode demonstrated significantly lower cumulative LTP rates than conventional RFA for small HCCs, which warrants a larger study for further confirmation.

• Korean Journal of Radiology
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• v.22 no.11
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• pp.1850-1857
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• 2021

Objective: The purpose of this study was to assess whether a deep learning (DL) algorithm could enable simultaneous noise reduction and edge sharpening in low-dose lumbar spine CT. Materials and Methods: This retrospective study included 52 patients (26 male and 26 female; median age, 60.5 years) who had undergone CT-guided lumbar bone biopsy between October 2015 and April 2020. Initial 100-mAs survey images and 50-mAs intraprocedural images were reconstructed by filtered back projection. Denoising was performed using a vendor-agnostic DL model (ClariCT.AI^TM, ClariPI) for the 50-mAS images, and the 50-mAs, denoised 50-mAs, and 100-mAs CT images were compared. Noise, signal-to-noise ratio (SNR), and edge rise distance (ERD) for image sharpness were measured. The data were summarized as the mean ± standard deviation for these parameters. Two musculoskeletal radiologists assessed the visibility of the normal anatomical structures. Results: Noise was lower in the denoised 50-mAs images (36.38 ± 7.03 Hounsfield unit [HU]) than the 50-mAs (93.33 ± 25.36 HU) and 100-mAs (63.33 ± 16.09 HU) images (p < 0.001). The SNRs for the images in descending order were as follows: denoised 50-mAs (1.46 ± 0.54), 100-mAs (0.99 ± 0.34), and 50-mAs (0.58 ± 0.18) images (p < 0.001). The denoised 50-mAs images had better edge sharpness than the 100-mAs images at the vertebral body (ERD; 0.94 ± 0.2 mm vs. 1.05 ± 0.24 mm, p = 0.036) and the psoas (ERD; 0.42 ± 0.09 mm vs. 0.50 ± 0.12 mm, p = 0.002). The denoised 50-mAs images significantly improved the visualization of the normal anatomical structures (p < 0.001). Conclusion: DL-based reconstruction may enable simultaneous noise reduction and improvement in image quality with the preservation of edge sharpness on low-dose lumbar spine CT. Investigations on further radiation dose reduction and the clinical applicability of this technique are warranted.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.157-172
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• 2024

Autonomous driving technology, when commercialized, has the potential to improve the safety, mobility, and environmental performance of transportation networks. However, safe autonomous driving may be hindered by poor sensor performance and limitations in long-distance detection. Therefore, cooperative autonomous driving that can supplement information collected from surrounding vehicles and infrastructure is essential. In addition, since HDVs, AVs, and CAVs have different ranges of perceivable information and different response protocols, countermeasures are needed for mixed traffic that occur during the transition period of autonomous driving technology. There is a lack of research on traffic flow optimization that considers the penetration rate of autonomous vehicles and the different characteristics of each road segment. The objective of this study is to develop weights based on safety, operational, and environmental factors for each infrastructure control use case and autonomous vehicle MPR. To develop an integrated evaluation index, infra-guidance AHP and hybrid AHP weights were combined. Based on the results of this study, it can be used to give right of way to each vehicle to optimize mixed traffic.

• The korean journal of orthodontics
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• v.54 no.1
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• pp.48-58
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• 2024

Objective: To quantify the effects of midline-related landmark identification on midline deviation measurements in posteroanterior (PA) cephalograms using a cascaded convolutional neural network (CNN). Methods: A total of 2,903 PA cephalogram images obtained from 9 university hospitals were divided into training, internal validation, and test sets (n = 2,150, 376, and 377). As the gold standard, 2 orthodontic professors marked the bilateral landmarks, including the frontozygomatic suture point and latero-orbitale (LO), and the midline landmarks, including the crista galli, anterior nasal spine (ANS), upper dental midpoint (UDM), lower dental midpoint (LDM), and menton (Me). For the test, Examiner-1 and Examiner-2 (3-year and 1-year orthodontic residents) and the Cascaded-CNN models marked the landmarks. After point-to-point errors of landmark identification, the successful detection rate (SDR) and distance and direction of the midline landmark deviation from the midsagittal line (ANS-mid, UDM-mid, LDM-mid, and Me-mid) were measured, and statistical analysis was performed. Results: The cascaded-CNN algorithm showed a clinically acceptable level of point-to-point error (1.26 mm vs. 1.57 mm in Examiner-1 and 1.75 mm in Examiner-2). The average SDR within the 2 mm range was 83.2%, with high accuracy at the LO (right, 96.9%; left, 97.1%), and UDM (96.9%). The absolute measurement errors were less than 1 mm for ANS-mid, UDM-mid, and LDM-mid compared with the gold standard. Conclusions: The cascaded-CNN model may be considered an effective tool for the auto-identification of midline landmarks and quantification of midline deviation in PA cephalograms of adult patients, regardless of variations in the image acquisition method.

• Korean Journal of Radiology
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• v.24 no.4
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• pp.349-361
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• 2023

Objective: To quantitatively assess the pulmonary vasculature using non-contrast computed tomography (CT) in patients with chronic thromboembolic pulmonary hypertension (CTEPH) pre- and post-treatment and correlate CT-based parameters with right heart catheterization (RHC) hemodynamic and clinical parameters. Materials and Methods: A total of 30 patients with CTEPH (mean age, 57.9 years; 53% female) who received multimodal treatment, including riociguat for ≥ 16 weeks with or without balloon pulmonary angioplasty and underwent both non-contrast CT for pulmonary vasculature analysis and RHC pre- and post-treatment were included. The radiographic analysis included subpleural perfusion parameters, including blood volume in small vessels with a cross-sectional area ≤ 5 mm² (BV5) and total blood vessel volume (TBV) in the lungs. The RHC parameters included mean pulmonary artery pressure (mPAP), pulmonary vascular resistance (PVR), and cardiac index (CI). Clinical parameters included the World Health Organization (WHO) functional class and 6-minute walking distance (6MWD). Results: The number, area, and density of the subpleural small vessels increased after treatment by 35.7% (P < 0.001), 13.3% (P = 0.028), and 39.3% (P < 0.001), respectively. The blood volume shifted from larger to smaller vessels, as indicated by an 11.3% increase in the BV5/TBV ratio (P = 0.042). The BV5/TBV ratio was negatively correlated with PVR (r = -0.26; P = 0.035) and positively correlated with CI (r = 0.33; P = 0.009). The percent change across treatment in the BV5/TBV ratio correlated with the percent change in mPAP (r = -0.56; P = 0.001), PVR (r = -0.64; P < 0.001), and CI (r = 0.28; P = 0.049). Furthermore, the BV5/TBV ratio was inversely associated with the WHO functional classes I-IV (P = 0.004) and positively associated with 6MWD (P = 0.013). Conclusion: Non-contrast CT measures could quantitatively assess changes in the pulmonary vasculature in response to treatment and were correlated with hemodynamic and clinical parameters.

• Korean Journal of Radiology
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• v.23 no.11
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• pp.1044-1054
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• 2022

Objective: This study aimed to investigate whether a deep learning reconstruction (DLR) method improves the image quality, stent evaluation, and visibility of the valve apparatus in coronary computed tomography angiography (CCTA) when compared with filtered back projection (FBP) and hybrid iterative reconstruction (IR) methods. Materials and Methods: CCTA images of 51 patients (mean age ± standard deviation [SD], 63.9 ± 9.8 years, 36 male) who underwent examination at a single institution were reconstructed using DLR, FBP, and hybrid IR methods and reviewed. CT attenuation, image noise, signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and stent evaluation, including 10%-90% edge rise slope (ERS) and 10%-90% edge rise distance (ERD), were measured. Quantitative data are summarized as the mean ± SD. The subjective visual scores (1 for worst -5 for best) of the images were obtained for the following: overall image quality, image noise, and appearance of stent, vessel, and aortic and tricuspid valve apparatus (annulus, leaflets, papillary muscles, and chordae tendineae). These parameters were compared between the DLR, FBP, and hybrid IR methods. Results: DLR provided higher Hounsfield unit (HU) values in the aorta and similar attenuation in the fat and muscle compared with FBP and hybrid IR. The image noise in HU was significantly lower in DLR (12.6 ± 2.2) than in hybrid IR (24.2 ± 3.0) and FBP (54.2 ± 9.5) (p < 0.001). The SNR and CNR were significantly higher in the DLR group than in the FBP and hybrid IR groups (p < 0.001). In the coronary stent, the mean value of ERS was significantly higher in DLR (1260.4 ± 242.5 HU/mm) than that of FBP (801.9 ± 170.7 HU/mm) and hybrid IR (641.9 ± 112.0 HU/mm). The mean value of ERD was measured as 0.8 ± 0.1 mm for DLR while it was 1.1 ± 0.2 mm for FBP and 1.1 ± 0.2 mm for hybrid IR. The subjective visual scores were higher in the DLR than in the images reconstructed with FBP and hybrid IR. Conclusion: DLR reconstruction provided better images than FBP and hybrid IR reconstruction.