• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.2
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• pp.29-43
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• 2019

The calibration of microscopic traffic simulation models has received much attention in the simulation field. Although no standard has been established for it, a genetic algorithm (GA) has been widely employed in recent literature because of its high efficiency to find solutions in such optimization problems. However, the performance still falls short in simulation analyses to support fast decision making. This paper proposes a new calibration procedure using a dual GA and central composite design (CCD) in order to improve the efficiency. The calibration exercise goes through three major sequential steps: (1) experimental design using CCD for a quadratic response surface model (RSM) estimation, (2) 1st GA procedure using the RSM with CCD to find a near-optimal initial population for a next step, and (3) 2nd GA procedure to find a final solution. The proposed method was applied in calibrating the Gipps car-following model with respect to maximizing the likelihood of a spacing distribution between a lead and following vehicle. In order to evaluate the performance of the proposed method, a conventional calibration approach using a single GA was compared under both simulated and real vehicle trajectory data. It was found that the proposed approach enhances the optimization speed by starting to search from an initial population that is closer to the optimum than that of the other approach. This result implies the proposed approach has benefits for a large-scale traffic network simulation analysis. This method can be extended to other optimization tasks using GA in transportation studies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.204-210
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• 2019

In case of a fire inside a tunnel, unlike ordinary roads, it is very difficult for a driver to obtain visibility, and a large accident is highly likely to occur. In this study, the smoke behavior, visible distance, and CO concentration of a jet fan were analyzed using the NIST fire simulation (FDS). All analyses were set to HRRPUA (Heat Release Rate Per Area) 3.6MW/m and all the analysis times were set to 600s. In all analyses by CFD, the results were confirmed at y=30m and y=110m, and smoke behavior analysis, visible range analysis, and carbon monoxide concentration were confirmed according to the diameter and flow rate. As the size and flow rate of the jet fan increased, the visibility distance was high at y=30m, and the concentration of carbon monoxide was also confirmed to be 0 ppm. Therefore, proper setting of the jet fan diameter and flow rate will be an excellent solution for fires in tunnels, and taking refuge at upstream area of a re-ventilated fan can reduce the number of casualties.

• Journal of the Korean Electrochemical Society
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• v.22 no.3
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• pp.87-103
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• 2019

Nonaqueous organic electrolyte solution in commercially available lithium-ion batteries, due to its flammability, corrosiveness, high volatility, and thermal instability, is demanding to be substituted by safer solid electrolyte with higher cycle stability, which will be utilized effectively in large-scale power sources such as electric vehicles and energy storage system. Of various types of solid electrolytes, composite solid electrolytes with polymer matrix and active inorganic fillers are now most promising in achieving higher ionic conductivity and excellent interface contact. In this review, some kinds and brief history of solid electrolyte are at first introduced and consequent explanations of polymer solid electrolytes and inorganic solid electrolytes (including active and inactive fillers) are comprehensively carried out. Composite solid electrolytes including these polymer and inorganic materials are also described with their electrochemical properties in terms of filler shapes, such as particle (0D), fiber (1D), plane (2D), and solid body (3D). In particular, in all-solid-state lithium batteries using lithium metal anode, the interface characteristics are discussed in terms of cathode-electrolyte interface, anode-electrolyte interface, and interparticle interface. Finally, current requisites and future perspectives for the composite solid electrolytes are suggested by help of some decent reviews recently reported.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.412-419
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• 2019

Negative space in the discipline of art defines the space around and between the subject of an image. The use of negative space is an element of artistic composition, since it is occasionally used to artistic effect as the "real" subject of an image. In painting, it is a technique that negatively touches the background of an object to be expressed, so that it gives a feeling of unique texture and silhouette by touching unnecessary parts while leaving necessary parts. As in art, negative space in a design can also be useful to identify an image of infeasible design ranges with a straightforward view. Similarity between two disciplines leads to the introduction of the negative space concept for design space exploration. A rough design space exploration using statistics and visual analytics may support more efficient decision-making, and can provide meaningful insights into the direction of early-phase system design. For this, the approach guarantees dynamic interactions between visualized information and human cognitive systems. Visual analytics is useful to summarize complex and large-scale data. It is useful for identifying feasible design spaces, as well as for avoiding infeasible spaces or highly risky spaces. This paper investigates the possible use of the negative space concept by using an application example.

• Smart Media Journal
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• v.8 no.1
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• pp.74-81
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• 2019

Recently, machine learning technology has had a significant impact on society, particularly in the medical, manufacturing, marketing, finance, broadcasting, and agricultural aspects of human lives. In this paper, we study how to apply machine learning techniques to foods, which have the greatest influence on the human survival. In the field of Smart Farm, which integrates the Internet of Things (IoT) technology into agriculture, we focus on optimizing the crop growth environment by monitoring the growth environment in real time. KT Smart Farm Solution 2.0 has adopted machine learning to optimize temperature and humidity in the greenhouse. Most existing smart farm businesses mainly focus on controlling the growth environment and improving productivity. On the other hand, in this study, we are studying how to apply machine learning with respect to harvest time so that we will be able to harvest fruits of the highest quality and ship them at an excellent cost. In order to apply machine learning techniques to the field of smart farms, it is important to acquire abundant voluminous data. Therefore, to apply accurate machine learning technology, it is necessary to continuously collect large data. Therefore, the color, value, internal temperature, and moisture of greenhouse-grown fruits are collected and secured in real time using color, weight, and temperature/humidity sensors. The proposed FPSML provides an architecture that can be used repeatedly for a similar fruit crop. It allows for a more accurate harvest time as massive data is accumulated continuously.

• Membrane Journal
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• v.31 no.5
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• pp.343-350
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• 2021

In this study the suction pressure was measured with respect to operational time by submersing the multi-bore capillary membrane module in membrane bioreactor(MBR). The hexagonal shape capillary module which has the nominal pore size of 0.2 ㎛, outer diameter of 6.4 or 4.2 mm was immersed in MLSS 8,000 mg/L active sludge aqueous solution, and confirmed changes with respect to permeation flux and air flow rate. It was operated by the filtration/relaxation(FR), FR with backwashing(FR/BW), and sinusoidal flux continuous operation(SFCO) modes. The suction pressure for the SFCO and FR modes was lower at 30 and 50 L/m²·hr, respectively. In addition, the suction pressure of the module with a small outer diameter was relatively low. The suction pressure of a large outer diameter was greatly increased, but it could be reduced by more than 40% by backwashing.

• Journal of the Korean Geosynthetics Society
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• v.18 no.3
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• pp.33-44
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• 2019

Clinker layer is a stratum structure distributed in volcanic area such as Jeju Island. The clinker layers were formed in between the repetitive action of eruption and solidification of lava flows. Since the clinker layer contains a large amount of voids accompanied by the lava gas ejection process, there is a possibility of inducing overall stability of the ground due to the low stiffness and strength of the clinker layer. Therefore, in this study, site investigation was carried out at both ends of the 00 bridge where the clinker layers exist. And, based on the ground survey results, the behavior of shallow foundations was analyzed numerically. In addition, the improved shallow foundation behavior in grouting substitution using the chemical injection method of the clinker layer was compared with the shallow foundation behavior in the ground, and the grouting substitution efficiency of each layer was analyzed. As a result, the bearing capacity, the replacement efficiency and elastic settlement were different according to the presence or absence of the sediment layer. This is because the sediment layer has a lower stiffness and density than the clinker layer.

• Journal of the Korean Society of Radiology
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• v.14 no.7
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• pp.899-906
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• 2020

The WSS lateral examination is important for diagnosing spinal disorders. Recently, long-length detectors for large-area diagnose have been popularized to effectively reduce the exposure dose and examination time. It can be applied very efficiently to examinations of patients with high risk of falls, children, and adolescents. However, since the image is acquired through a single irradiation, the volume of cervical vertebra is relatively smaller than the lumbar due to the geometrical anatomy of the spine. Therefore, this study intends to fabricate an additional filter using 3D printing technology and copper filament to obtain uniform image quality in the WSS lateral examination and to analyze the results. 3D printing technology is able to easily print a desired shape, so it is widely used in the entire industrial field, and recently, a copper filament has been developed to confirm the possibility as an additional filter. In the WSS lateral examination, CNR and SNR were excellently measured when the additional filter was applied, confirming the possibility of using the additional filter.

• Journal of Korea Water Resources Association
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• v.54 no.3
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• pp.181-190
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• 2021

In this study, a large-scale levee breach experiment from lateral overflow was conducted to verify the effect of the new reinforcement method applied to the levee's surface. The new method could prevent levee failure and minimize damage caused by overflow in rivers. The levee was designed at the height of 2.5 m, a length of 12 m, and a slope of 1:2. A new material mixed with biopolymer powder, water, weathered granite, and loess in an appropriate ratio was sprayed on the levee body's surface at a thickness of about 5 cm, and vegetation recruitment was also monitored. At the Andong River Experiment Center, a flow (4 ㎥/s) was introduced from the upstream of the A3 channel to induce the lateral overflow. The change of lateral overflow was measured using an acoustic doppler current profiler in the upstream and downstream. Additionally, cameras and drones were used to analyze the process of the levee breach. Also, a new method using 3D point cloud for calculating the surface loss rate of the levee over time was suggested to evaluate the performance of the levee reinforcement method. It was compared to existing method based on image analysis and the result was reasonable. The proposed 3D point cloud methodology could be a solution for evaluating the performance of levee reinforcement methods.

• Tunnel and Underground Space
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• v.31 no.1
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• pp.10-24
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• 2021

Rock mass classification for construction of underground facilities is essential to secure their stabilities. Therefore, the reliable values for rock mass classification from the precise information on rock discontinuities are most important factors, because rock mass discontinuities can affect exclusively on the physical and mechanical properties of rock mass. The conventional classification operation for rock mass has been usually performed by hand mapping. However, there have been many issues for its precision and reliability; for instance, in large-scale survey area for regional geological survey, or rock mass classification operation by non-professional engineers. For these reasons, automated rock mass classification using LiDAR becomes popular for obtaining the quick and precise information. But there are several suggested algorithms for analyzing the rock mass discontinuities from point cloud data by LiDAR scanning, and it is known that the different algorithm gives usually different solution. Also, it is not simple to obtain the exact same value to hand mapping. In this paper, several discontinuity extract algorithms have been explained, and their processes for extracting rock mass discontinuities have been simulated for real rock bench. The application process for several algorithms is anticipated to be a good reference for future researches on extracting rock mass discontinuities from digital point cloud data by laser scanner, such as LiDAR.