• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.91-98
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• 2023

The amount of power generation of a solar plant has a high correlation with weather conditions, geographical conditions, and the installation conditions of solar panels. Previous studies have found the elements which impacts the amount of power generation. Some of them found the optimal conditions for solar panels to generate the maximum amount of power. Considering the realistic constraints when installing a solar power plant, it is very difficult to satisfy the conditions for the maximum power generation. Therefore, it is necessary to know how sensitive the solar power generation amount is to factors affecting the power generation amount, so that plant owners can predict the amount of solar power generation when examining the installation of a solar power plant. In this study, we propose a polynomial regression analysis method to analyze the relationship between solar power plant's power generation and related factors such as weather, location, and installation conditions. Analysis data were collected from 10 solar power plants installed and operated in Daegu and Gyeongbuk. As a result of the analysis, it was found that the amount of power generation was affected by panel type, amount of insolation and shade. In addition, the power generation was affected by interaction of the installation angle and direction of the panel.

• Explosives and Blasting
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• v.41 no.3
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• pp.62-72
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• 2023

The aging of plant structures due to industrialization in the 1970s has increased the demand for blast demolition. While blasting can reduce exposure to environmental pollution by shortening the demolition period, improper blasting design and construction plans pose significant safety risks. Thus, it is vital to consider optimal blasting demolition conditions and other factors through collapse behavior simulation. This study utilizes a 3-D combined finite-discrete element method (FDEM) code-based 3-D DFPA to simulate the collapse of a chimney structure in a thermal power plant in Seocheon, South Korea. The collapse behavior from the numerical simulation is compared to the actual structure collapse, and the numerical simulation result presents good agreement with the actual building demolition. Additionally, various numerical simulations have been conducted on the chimney models to analyze the impact of the duct size in the pre-weakening area. The no-duct, duct, and double-area duct models were compared in terms of crack pattern and history of Z-axis displacement. The findings show that the elapse-time for demolition decreases as the area of the duct increases, causing collapse to occur quickly by increasing the load-bearing area.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.2
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• pp.119-125
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• 2023

In this study, we photograph driving obstacle objects such as crosswalks, side spheres, manholes, braille blocks, partial ramps, temporary safety barriers, stairs, and inclined curb that hinder or cause inconvenience to the movement of the vulnerable using electric mobility aids. We develop an optimal AI model that classifies photographed objects and automatically recognizes them, and implement an algorithm that can efficiently determine obstacles in front of electric mobility aids. In order to enable object detection to be AI learning with high probability, the labeling form is labeled as a polygon form when building a dataset. It was developed using a Mask R-CNN model in Detectron2 framework that can detect objects labeled in the form of polygons. Image acquisition was conducted by dividing it into two groups: the general public and the transportation weak, and image information obtained in two areas of the test bed was secured. As for the parameter setting of the Mask R-CNN learning result, it was confirmed that the model learned with IMAGES_PER_BATCH: 2, BASE_LEARNING_RATE 0.001, MAX_ITERATION: 10,000 showed the highest performance at 68.532, so that the user can quickly and accurately recognize driving risks and obstacles.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.27-33
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• 2023

Recently, water shortages have occurred due to climate change, and the need for water management of agricultural water has increased due to the occurrence of algal blooms in reservoirs. Existing algae prevention is operated by putting many people on site and misses the optimal spraying time due to movement through boats. In order to solve this problem, it is necessary to block contamination in advance and move within time to uniformly spray complex microorganisms uniformly. Control drones are used for pesticide spraying and can be applied to algae prevention work by utilizing control drones. In this paper, basic research for the establishment of a marine control system was conducted for application to the reservoir environment, and as one of the results, the characteristics of a drone nozzle, a core technology that can be used for control drones, were calculated. In particular, it was found that the existing agricultural control drones had a disadvantage that the concentration was non-uniform within the suggested spraying interval, and to compensate for this, nozzle positioning and nozzle spraying uniformity were calculated. Based on the experimental results, we develop a core algorithm for establishing an algal bloom monitoring system in the reservoir environment and propose a precision control technology that can be used for marine control work in the future.

• Korean journal of applied entomology
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• v.62 no.4
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• pp.333-343
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• 2023

King oyster mushrooms are one of the major fresh agricultural products which their exports are increasing every year in Korea. Lycoriella ingenua, is notorious insect pest in agriculture, especially in mushroom production. Larvae of L. ingenua cause mainly direct crop damage and adults are vectors of several dangerous fungal pathogens. In this study, the effects of electron beam, X-ray, and gamma-ray irradiation on the development and reproduction of L. ingenua were evaluated. In addition, to find the optimal dose to control L. ingenua in a box filled with king oyster mushrooms, an empirical experiment was conducted for each radiation. As a result, the development and reproduction of L. ingenua were inhibited at 50 Gy for all electron beam, X-ray, and gamma-ray irradiation. Additionally, at the top, middle, and bottom of the export box filled with king oyster mushrooms, the development and reproduction of L. ingenua were inhibited by electron beam with 150 Gy, X-ray with 100 Gy, and gamma-ray with 50 Gy. These results can be provided as basic data for establishing an integrated quarantine management system when exporting mushrooms. It will also contribute to the safety of agricultural products and the strengthening of export competitiveness.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.2
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• pp.106-118
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• 2024

Interest in personal mobility has increased with the growing significance of first-mile and last-mile connectivity in smart mobility services. This study aims to propose a methodology for setting the service area of free-floating personal mobility sharing services and determining the optimal fleet size for the selected shared service area to address first-mile and last-mile challenges. We utilize population data, smart card data, and building data. Additionally, we estimate latent demand by incorporating age-specific and distance-specific utilization rates based on personal mobility device data. Along with the latent demand, we determine the service area based on locations of transit stops and buildings. We apply the proposed methodology to Yeongjong Island, Incheon. As a result, dense residential areas and popular beachside locations are designated as personal mobility sharing service areas. The fleet size for personal mobility in the dense residential service area is determined to be 1,022 units, while the fleet size for the beachside service area is set at 269 units.

• Tunnel and Underground Space
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• v.34 no.3
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• pp.231-247
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• 2024

In the field of high-level radioactive waste disposal targeting deep rock environments, hydraulic characteristic information serves as the most important key factor in selecting relevant disposal sites, detailed design of disposal facilities, derivation of optimal construction plans, and safety evaluation during operation. Since various rock types are mixed and distributed in a small area in Korea, it is important to conduct preliminary work to analyze the hydrogeological characteristics of rock aquifers for various rock types and compile the resulting data into a database. In this paper, we obtained hydraulic conductivity data, which is the most representative field hydraulic characteristic of a high-depth volcanic bedrock aquifer, and also analyzed and evaluated the field data. To acquire field data, we used a high-performance hydraulic testing system developed in-house and applied standardized test methods and investigation procedures. In the process of hydraulic characteristic data analysis, hydraulic conductivity values were obtained for each depth, and the pattern of groundwater flow through permeable rock joints located in the test section was also evaluated. It is expected that the series of data acquisition methods, procedures, and analysis results proposed in this report can be used to build a database of hydraulic characteristics data for high-depth rock aquifers in Korea. In addition, it is expected that it will play a role in improving technical know-how to be applied to research on hydraulic characteristic according to various bedrock types in the future.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.163-171
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• 2024

Structural health monitoring for ships and offshore structures is important in various aspects. Ships and offshore structures are continuously exposed to various environmental conditions, such as waves, wind, and currents. In the event of an accident, immense economic losses, environmental pollution, and safety problems can occur, so it is necessary to detect structural damage or defects early. In this study, structural response data of multi-linked floating offshore structures under various wave load conditions was calculated by performing fluid-structure coupled analysis. Furthermore, the order reduction method with distortion base mode was applied to the structures for predicting the structural response by using the results of numerical analysis. The distortion base mode order reduction method can predict the structural response of a desired area with high accuracy, but prediction performance is affected by sensor arrangement. Optimization based on a genetic algorithm was performed to search for optimal sensor arrangement and improve the prediction performance of the distortion base mode-based reduced-order model. Consequently, a sensor arrangement that predicted the structural response with an error of about 84.0% less than the initial sensor arrangement was derived based on the root mean squared error, which is a prediction performance evaluation index. The computational cost was reduced by about 8 times compared to evaluating the prediction performance of reduced-order models for a total of 43,758 sensor arrangement combinations. and the expected performance was overturned to approximately 84.0% based on sensor placement, including the largest square root error.

• Land and Housing Review
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• v.15 no.2
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• pp.73-87
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• 2024

To evaluate the efficiency of commuting patterns, various commuting indicators such as excess commute and commuting potential utilized have been developed and used. It is crucial to calculate these indicators reasonably to reveal the differences in commuting patterns among metropolitan areas and to consider these in the process of formulating commuting policies. However, commuting indicators are generally calculated at the administrative district level, and thus, they are not free from the problem of the modifiable areal unit problem (MAUP). This issue can undermine the rationality of comparing commuting efficiency between metropolitan areas, making it necessary to handle the calculation of commuting indicators carefully. Therefore, this study utilises Monte Carlo Simulation to calculate optimal, actual, and maximum commuting distances, and thereby presents the excess commute and the commuting potential utilized. To apply Monte Carlo Simulation to the context of South Korea, a constrained Monte Carlo Simulation is conducted, where residential and workplace locations used in the simulation are selected based on the actual locations of buildings. The analysis is conducted on 13 metropolitan areas with established metropolitan plans using the 2016 Household Travel Survey data. The commuting indicators calculated through the simulation showed minimal differences compared to the results obtained through conventional methods. The comparison of commuting efficiency among metropolitan areas revealed that even if the degree of spafial balance between residential and workplace locations is similar, the actual commuting patterns can differ significantly. It is suggested that further research considering characteristics such as the area of each metropolitan region will be necessary in the future.

• Information Systems Review
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• v.19 no.2
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• pp.21-35
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• 2017

The advancement of IT and the "Fourth Industrial Revolution" blurred the boundary between industries. The importance of strategic cooperation between enterprises is emphasized. IT companies must consider their existing business areas and create new territories to drive changes in the industry. They must also secure their competitive edge and manage economic costs to enable them to compete with their global counterparts. By utilizing their resources effectively, these firms can create value through inter-firm cooperation. This study analyzes the collaborative network of global IT companies using social network analysis and examines the effect of this network on firm performance. Collaborative linkages and betweenness centrality, which represent the bridging position of a firm in a network, significantly affect firm performance. This result highlights the importance of the structural position of a firm in a cooperative network of IT companies. This study also characterizes clusters in a network of IT companies. Most of these clusters comprise a combination of IT companies in diverse IT industries. These clusters suggest that these companies engage in multilateral cooperation without boundaries to maximize their business capabilities. This study offers practical implications for establishing a cooperative strategy and framework that can capture business trends in the IT industry from a macroscopic view. This study also visualizes collaborative networks in a multifaceted way using social network analysis to provide researchers and business practitioners with an informative viewpoint.