• Journal of the Korean Society of Marine Environment & Safety
• /
• v.25 no.2
• /
• pp.139-150
• /
• 2019

Though, fishing vessel accidents account for 70 % of all maritime accidents in Korean waters, most research has focused on identifying causes and developing mitigation policies in an attempt to reduce this rate. However, predicting and evaluating accident risk needs to be done before the implementation of such reduction measures. For this reasons, we havve performed a risk analysis to calculate the risk of accidents and propose a risk criteria matrix with 4 quadrants, within one of which forecasted risk is plotted for the relative comparison of risks. For this research, we considered 9 types of fishing vessel accidents as reported by Korea Maritime Safety Tribunal (KMST). Given that no risk evaluation criteria have been established in Korea, we established a two-dimensional frequency-consequence grid consisting of four quadrants into which paired frequency and consequence for each type of accident are presented. With the simple structure of the evaluation model, one can easily verify the effect of frequency and consequence on the resulting risk within each quadrant. Consequently, these risk evaluation results will help a decision maker employ more realistic risk mitigation measures for accident types situated in different quadrants. As an application of the risk evaluation matrix, accident types were further analyzed using accident causes including human error (factor) and appropriate risk reduction options may be established by comparing the relative frequency and consequence of each accident cause.

• Membrane Journal
• /
• v.29 no.3
• /
• pp.173-182
• /
• 2019

Much research has been made for finding new and eco-friendly alternative sources of energy to solve the problems related with the pollution caused by emissions of greenhouse gases such as carbon dioxide as the use of fossil fuels increases worldwide. Among them, fuel cells draws particular interests as an eco-friendly energy generator because only water is obtained as a by-product. Anion exchange membrane-based alkaline fuel cell (AEMFC) that uses anion exchange membrane as an electrolyte is of increased interest recently because of its advantages in using low-cost metal catalyst unlike the PEMFC (potton exchange membrane fuel cell) due to the high-catalyst activity in alkaline conditions. The main properties required as an anion exchange membrane are high hydroxide conductivity and chemical stability at high pH. Recently we reported a chemically crosslinked poly(2-dimethyl-1,4-phenylene oxide) (PPO) by reacting PPO with N,N,N',N'-tetramethyl-1,6-hexanediamine as novel anion exchange membranes. In the current work, we further developed the same crosslinked polymer but having enhanced physicochemical properties, including higher conductivity, increased mechanical and dimensional stabilities by using the PPO with a higher molecular weight and also by increasing the crosslinking density. The obtained polymer membrane also showed a good cell performance.

• Science of Emotion and Sensibility
• /
• v.24 no.2
• /
• pp.65-74
• /
• 2021

With recent innovations in the ICT industry, the demand for wearable sensing devices to recognize and respond to biological signals has increased. In this study, a three-dimensional (3D) spacer fabric was embedded in a single-wall carbon nanotube (SWCNT) dispersive solution through a simple penetration process to develop a monolayer piezoresistive pressure sensor. To induce electrical conductivity in the 3D spacer fabric, samples were immersed in the SWCNT dispersive solution and dried. To determine the electrical properties of the impregnated specimen, a universal testing machine and multimeter were used to measure the resistance of the pressure change. Moreover, to examine the changes in the electrical properties of the sensor, its performance was evaluated by varying the concentration, number of penetrations, and thickness of the specimen. Samples that penetrated twice in the SWCNT distributed solution of 0.1 wt% showed the best performance as sensors. The 7-mm thick sensors showed the highest GF, and the 13-mm thick sensors showed the widest operating range. This study confirms the effectiveness of the simple process of fabricating smart textile sensors comprising 3D spacer fabrics and the excellent performance of the sensors.

• Journal of the Korean Geotechnical Society
• /
• v.36 no.12
• /
• pp.107-116
• /
• 2020

The compaction grouting technique is widely used to improve the liquefaction resistance of loose sands that are liquefaction-prone. Particularly, the horizontal injection of compaction grout is proposed for the liquefiable ground with an overlying structure as it does not allow the vertical compaction grouting. However, there has been limited number of researches on the horizontal compaction grouting. Therefore, this study explores the grout bulb shape and expansion direction in loose sand. A series of scaled two-dimensional experiments on the horizontal compaction grouting was conducted varying the overburden stress. The results show that the grout bulb grows in an elliptical shape though its directivity of major axis changes with the overburden effective stress and relative density. The grout bulb expands faster in a horizontal direction under a low overburden stress with a small relative density. The higher overburden stress and the greater relative density cause the more circular shape with the faster expansion in a vertical direction. The presented finding is expected to contribute to accurate and efficient design of the horizontal compaction grouting method.

• Journal of Platform Technology
• /
• v.8 no.3
• /
• pp.10-21
• /
• 2020

Partial discharge occurs a lot in high-voltage power equipment such as switchgear, transformers, and switch gears. Partial discharge shortens the life of the insulator and causes insulation breakdown, resulting in large-scale damage such as a power outage. There are several types of partial discharge that occur inside the product and the surface. In this paper, we design a predictive model that can predict the pattern and probability of occurrence of partial discharge. In order to analyze the designed model, learning data for each type of partial discharge was collected through the UHF sensor by using a simulator that generates partial discharge. The predictive model designed in this paper was designed based on CNN during deep learning, and the model was verified through learning. To learn about the designed model, 5000 training data were created, and the form of training data was used as input data for the model by pre-processing the 3D raw data input from the UHF sensor as 2D data. As a result of the experiment, it was found that the accuracy of the model designed through learning has an accuracy of 0.9972. It was found that the accuracy of the proposed model was higher in the case of learning by making the data into a two-dimensional image and learning it in the form of a grayscale image.

• The Journal of Engineering Geology
• /
• v.32 no.2
• /
• pp.221-239
• /
• 2022

Unknown geotechnical characteristics are key challenges in the design of piles for the plant, civil and building works. Although the N-values which were read through the standard penetration test are important, those N-values of the whole area are not likely acquired in common practice. In this study, the N-value is predicted by means of regression analysis with artificial intelligence (AI). Big data is important to improve learning performance of AI, so circular augmentation method is applied to build up the big data at the current study. The optimal model was chosen among applied AI algorithms, such as artificial neural network, decision tree and auto machine learning. To select optimal model among the above three AI algorithms is to minimize the margin of error. To evaluate the method, actual data and predicted data of six performed projects in Poland, Indonesia and Malaysia were compared. As a result of this study, the AI prediction of this method is proven to be reliable. Therefore, it is realized that the geotechnical characteristics of non-boring points were predictable and the optimal arrangement of structure could be achieved utilizing three dimensional N-value distribution map.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.67 no.1
• /
• pp.67-75
• /
• 2022

Roots play important roles in water and nutrient uptake and in response to various environmental stresses. Investigating diversification of cultivars through root phenotyping is important for crop improvement in adzuki beans. Therefore, we analyzed the morphological and architectural root traits of 22 adzuki bean cultivars using 2-dimensional (2D) root imaging. Plants were grown in plastic tubes [6 cm (diameter) × 40 cm (height)] in a greenhouse from July 25^th to August 28^th. When the plants reached the 2^nd or 3^rd trifoliate leaf stage, the roots were removed and washed with tap water to remove soil particles. Clean root samples were scanned, and the scanned images were analyzed using the WinRHIZO Pro software. The cultivars were analyzed based on six root phenotypes [total root length (TRL), surface area (SA), average diameter (AD), and number of tips (NT) were included as root morphological traits (RMT); and link average length (LAL) and link average diameter (LAD) were included as root architectural traits (RAT)]. According to the analysis of variance (ANOVA), a significant difference was observed between the cultivars for all root morphological traits. Distribution analysis demonstrated that all root traits except LAL followed a normally distributed curve. In the correlation test, the most important morphological trait, TRL, showed a strong positive correlation with SA (r = 0.97^***) and NT (r = 0.94^***). In comparison, between RMT and RAT, TRL showed a significantly negative correlation with LAL (r = -0.50^***); however, TRL did not show a correlation with LAD. Based on RMT and RAT, we identified the cultivars that ranked 5% from the top and bottom. In particular, the cultivar "IT 236657" showed the highest TRL, SA, and NT, while the cultivar "IT 236169" showed the lowest values for TRL, SA, and NT. In addition, the coefficient of variance for the six tested root traits ranged from (14.26-40%) which suggested statistical variability in root phenotypes among the 22 adzuki bean varieties. Thus, this study will help to select target root traits for the adzuki bean breeding program in the future, generating climate-resilient adzuki beans, especially for drought stress, and may be useful for developing biotic and abiotic stress-tolerant cultivars based on better root trait attributes.

• Journal of Biomedical Engineering Research
• /
• v.43 no.5
• /
• pp.341-352
• /
• 2022

Medical image segmentation is the most important task in radiation therapy. Especially, when segmenting medical images, the liver is one of the most difficult organs to segment because it has various shapes and is close to other organs. Therefore, automatic segmentation of the liver in computed tomography (CT) images is a difficult task. Since tumors also have low contrast in surrounding tissues, and the shape, location, size, and number of tumors vary from patient to patient, accurate tumor segmentation takes a long time. In this study, we propose a method algorithm for automatically segmenting the liver and tumor for this purpose. As an advantage of setting the boundaries of the tumor, the liver and tumor were automatically segmented from the CT image using the 2D CoordConv DeepLab V3+ model using the CoordConv layer. For tumors, only cropped liver images were used to improve accuracy. Additionally, to increase the segmentation accuracy, augmentation, preprocess, loss function, and hyperparameter were used to find optimal values. We compared the CoordConv DeepLab v3+ model using the CoordConv layer and the DeepLab V3+ model without the CoordConv layer to determine whether they affected the segmentation accuracy. The data sets used included 131 hepatic tumor segmentation (LiTS) challenge data sets (100 train sets, 16 validation sets, and 15 test sets). Additional learned data were tested using 15 clinical data from Seoul St. Mary's Hospital. The evaluation was compared with the study results learned with a two-dimensional deep learning-based model. Dice values without the CoordConv layer achieved 0.965 ± 0.01 for liver segmentation and 0.925 ± 0.04 for tumor segmentation using the LiTS data set. Results from the clinical data set achieved 0.927 ± 0.02 for liver division and 0.903 ± 0.05 for tumor division. The dice values using the CoordConv layer achieved 0.989 ± 0.02 for liver segmentation and 0.937 ± 0.07 for tumor segmentation using the LiTS data set. Results from the clinical data set achieved 0.944 ± 0.02 for liver division and 0.916 ± 0.18 for tumor division. The use of CoordConv layers improves the segmentation accuracy. The highest of the most recently published values were 0.960 and 0.749 for liver and tumor division, respectively. However, better performance was achieved with 0.989 and 0.937 results for liver and tumor, which would have been used with the algorithm proposed in this study. The algorithm proposed in this study can play a useful role in treatment planning by improving contouring accuracy and reducing time when segmentation evaluation of liver and tumor is performed. And accurate identification of liver anatomy in medical imaging applications, such as surgical planning, as well as radiotherapy, which can leverage the findings of this study, can help clinical evaluation of the risks and benefits of liver intervention.

• Journal of Periodontal and Implant Science
• /
• v.52 no.4
• /
• pp.338-350
• /
• 2022

Purpose: Various studies have investigated 3-dimensional (3D)-printed implants using Ti6Al-4V powder; however, multi-root 3D-printed implants have not been fully investigated. The purpose of this study was to explore the stability of multirooted 3D-printed implants with lattice and solid structures. The secondary outcomes were comparisons between the 2 types of 3D-printed implants in micro-computed tomographic and histological analyses. Methods: Lattice- and solid-type 3D-printed implants for the left and right mandibular third premolars in beagle dogs were fabricated. Four implants in each group were placed immediately following tooth extraction. Implant stability measurement and periapical X-rays were performed every 2 weeks for 12 weeks. Peri-implant bone volume/tissue volume (BV/TV) and bone mineral density (BMD) were measured by micro-computed tomography. Bone-to-implant contact (BIC) and bone area fraction occupancy (BAFO) were measured in histomorphometric analyses. Results: All 4 lattice-type 3D-printed implants survived. Three solid-type 3D-printed implants were removed before the planned sacrifice date due to implant mobility. A slight, gradual increase in implant stability values from implant surgery to 4 weeks after surgery was observed in the lattice-type 3D-printed implants. The marginal bone change of the surviving solid-type 3D-printed implant was approximately 5 mm, whereas the value was approximately 2 mm in the lattice-type 3D-printed implants. BV/TV and BMD in the lattice type 3D-printed implants were similar to those in the surviving solid-type implant. However, BIC and BAFO were lower in the surviving solid-type 3D-printed implant than in the lattice-type 3D-printed implants. Conclusions: Within the limits of this preclinical study, 3D-printed implants of double-rooted teeth showed high primary stability. However, 3D-printed implants with interlocking structures such as lattices might provide high secondary stability and successful osseointegration.

• Economic and Environmental Geology
• /
• v.55 no.5
• /
• pp.541-550
• /
• 2022

A pre-existing landform is created by weathering and erosion along the bedrock fault and the weak zone. A neotectonic landform is formed by neotectonic movements such as earthquakes, volcanoes, and Quaternary faults. It is difficult to clearly distinguish the landform in the actual field because the influence of the tectonic activity in the Korean Peninsula is relatively small, and the magnitude of surface processes (e.g., erosion and weathering) is intense. Thus, to better understand the impact of tectonic activity and distinguish between pre-existing landforms and neotectonic landforms, it is necessary to understand the development process of pre-existing landforms depending on the bedrock characteristics. This study used a two-dimensional numerical landscape evolution model (LEM) to study the spatio-temporal development of landscape according to the different erodibility under the same factors of climate and the uplift rate. We used hill-slope indices (i.e., relief, mean elevation, and slope) and channels (i.e., longitudinal profile, normalized channel steepness index, and stream order) to distinguish the difference according to different bedrocks. As a result of the analysis, the terrain with high erosion potential shows low mean elevation, gentle slope, low stream order, and channel steepness index. However, the value of the landscape with low erosion potential differs from that with high erodibility. In addition, a knickpoint came out at the boundary of the bedrock. When researching the actual topography, the location around the border of difference in bedrock has only been considered a pre-existing factor. This study suggested that differences in bedrock and various topographic indices should be comprehensively considered to classify pre-existing and active tectonic topography.