• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.5
• /
• pp.118-127
• /
• 2021

Recently, the public's interest in the air environment has increased, and public health is threatened by fine particulate matter. Furthermore, the government continues efforts to improve air quality by expanding the monitoring of air pollutants and reinforcing environmental standards. Since air quality differs depending on the region in the Korean Peninsula, it is currently necessary to identify the cause and search for influencing factors. In this study, the atmospheric environment and regional differences in cities located in the Chungnam Province were observed. As a research method, regression analysis was performed for weather conditions, such as temperature, wind speed, precipitation, and season and targeted at air pollutants, such as SO₂, NO₂, CO, O₃, PM₁₀, and PM_2.5, as well as heavy metals contained in particulate matter, such as Pb, Cd, Cr, Cu, Ni, As, Mn, Fe, Al, Ca, and Mg. In the case of PM₁₀, the concentrations of Mn(0.4884) in Cheonan, CO(0.3329) in Dangjin, and Mg(0.5691) in Seosan were highest. In the case of PM_2.5, Cheonan NO₂(0.4759), Dangjin CO(0.4128), and Seosan NO₂(0.3715) were significantly affected. In summary, the influencing factors vary according to the region in Chungnam province in terms of air quality, and there is a difference in the degree of contribution. Therefore, it is considered that the Korean government's management of air quality is required for each region.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.5
• /
• pp.334-342
• /
• 2021

In Korea, the training is performed through independent environments without interoperability among L-V-C systems. In the L system, training for large units is limited due to civil complaints at the training grounds and road restrictions. The V system is insufficient in training related to tactical training, and the C system lacks practicality due to a lack of combat friction elements. To achieve synchronicity and integration training between upper and lower units, it is necessary to establish a system to ensure integrated training for each unit by interoperating the currently operating L, V, and C systems. The interoperability between the C-C system supports Korea-US Combined Exercise. On the other hand, the actual development of the training system through the interoperability of L, V, and C has not been made. Although efforts are being made to establish the L, V, and C system centering on the Army, the joint composite battlefield and LVC integrated architecture technology are not yet secured. Therefore, this paper proposes a new plan for the future training system by designing and implementing the LVC integrated architecture technology, which is the core technology that can build the L-V-C interoperability training system. In conclusion, a division-level L-V-C interoperability training system can be established in the future by securing the LVC integrated architecture technology.

• Journal of the Korea Society of Computer and Information
• /
• v.27 no.2
• /
• pp.171-177
• /
• 2022

In this paper, we propose a service method that can provide insight into multi-source agricultural data, way to cluster environmental factor which supports data analysis according to time flow, and curate crop environmental factors. The proposed curation service consists of four steps: collection, preprocessing, storage, and analysis. First, in the collection step, the service system collects and organizes multi-source agricultural data by using an OpenAPI-based web crawler. Second, in the preprocessing step, the system performs data smoothing to reduce the data measurement errors. Here, we adopt the smoothing method for each type of facility in consideration of the error rate according to facility characteristics such as greenhouses and open fields. Third, in the storage step, an agricultural data integration schema and Hadoop HDFS-based storage structure are proposed for large-scale agricultural data. Finally, in the analysis step, the service system performs DTW-based time series classification in consideration of the characteristics of agricultural digital data. Through the DTW-based classification, the accuracy of prediction results is improved by reflecting the characteristics of time series data without any loss. As a future work, we plan to implement the proposed service method and apply it to the smart farm greenhouse for testing and verification.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.50 no.12
• /
• pp.889-898
• /
• 2022

In this paper, parallel computing method on the three-dimensional electromagnetic field is proposed. The present electromagnetic scattering analysis is conducted based on the time-harmonic vector wave equation and the finite element method. The edge-based element and 2^nd -order absorbing boundary condition are used. Parallelization of the elemental numerical integration and the matrix assemblage is accomplished by allocating the partitioned finite element subdomain for each processor. The graph partitioning library, METIS, is employed for the subdomain generation. The large sparse matrix computation is conducted by MUMPS, which is the parallel computing library based on the multi-frontal method. The accuracy of the present program is validated by the comparison against the Mie-series analytical solution and the results by ANSYS HFSS. In addition, the scalability is verified by measuring the speed-up in terms of the number of processors used. The present electromagnetic scattering analysis is performed for a perfect electric conductor sphere, isotropic/anisotropic dielectric sphere, and the missile configuration. The algorithm of the present program will be applied to the finite element and tearing method, aiming for the further extended parallel computing performance.

• Journal of the Korea Society for Simulation
• /
• v.32 no.3
• /
• pp.23-31
• /
• 2023

Software development involves a series of stages, including requirements analysis, design, implementation, unit testing, and integration testing, similar to those used in the system engineering process. This study utilized MathWorks' model-based design platform to develop multi-function radar software and evaluated its feasibility and efficiency. Because the development of conventional radar software is performed by a unit algorithm rather than in an integrated form, it requires additional efforts to manage the integrated software, such as requirement analysis and integrated testing. The mode-based platform applied in this paper provides an integrated development environment for requirements analysis and allocation, algorithm development through simulation, automatic code generation for deployment, and integrated requirements testing, and result management. With the platform, we developed multi-level models of the multi-function radar software, verified them using test harnesses, managed requirements, and transformed them into hardware deployable language using the auto code generation tool. We expect this Model-based integrated development to reduce errors from miscommunication or other human factors and save on the development schedule and cost.

• Journal of the Korean Geotechnical Society
• /
• v.26 no.3
• /
• pp.59-68
• /
• 2010

Systematic risk management is necessary in grand scaled urban construction because of the existence of complicated and various risk factors. Problems of obstructions, adjacent structures, safety, environment, traffic and geotechnical properties need to be solved because urban construction is progressed in limited space not as general earthwork. Therefore the establishment of special risk management system is necessary to manage not only geotechnical properties but also social and cultural uncertainties. This research presents the technique analysis by the current state of risk management technique. Risk factors were noticed and the importance of each factor was estimated through survey. The systemically categorized database was established. Risk extraction module, matrix and score module were developed based on the database. Expected construction budget and time distribution can be computed by Monte Carlo analysis of probabilities and influences. Construction budgets and time distributions of before and after response can be compared and analyzed 80 the risks are manageable for entire whole construction time. This system will be the foundation of standardization and integration. Procurement, efficiency improvement, effective time and resource management are available through integrated management technique development and application. Conclusively decrease in cost and time is expected by systemization of project management.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
• /
• v.6 no.8
• /
• pp.63-72
• /
• 2016

The main purpose of this study was to empirically validate whether a factor in reducing youth externalizing problem behaviors impact analysis and affection between father and youth self-esteem externalizing problem behavior through effective regulation. The survey was conducted by the researcher who visits the school to collect the sample data by random sampling method on 336 male students at D area. After delating the 38 insincere questionnaires, final 298 data were analyzed. Using SPSS 21.0, the simple correlational analysis was conducted to decide the relationship among the variables and in order to know the reciprocal model, hierarchical multiple regression analysis was implemented. The results showed the esteem and the affection his father on a statistically significant effect on youth externalizing problem behavior, father attachment had the effect of regulating the relationship between self-esteem and externalizing problem behavior. Through these results through the self-esteem Improvement Plan of the Father and the love of young people and to promote a proposal for reducing externalizing problem behavior.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.22 no.3
• /
• pp.38-50
• /
• 2023

Recent advances in artificial intelligence (AI) technology have enabled the integration of AI technology into image sensors, such as Closed-Circuit Television (CCTV), to detect specific traffic incidents. However, most incident detection methods have been carried out using fixed equipment. Therefore, there have been limitations to incident detection for all roadways. Nevertheless, the development of mobile image collection and analysis technology, such as image sensors and edge-computing, is spreading. The purpose of this study is to estimate the reducing effect of the incident detection time according to the introduction level of mobile image collection and analysis equipment (or connected vehicles). To carry out this purpose, we utilized data on the number of incidents collected by the Suwon branch of the Gyeongbu expressway in 2021. The analysis results showed that if the market penetration rate (MPR) of connected vehicles is 4% or higher for two-lane expressway and 3% or higher for three-lane expressways, the incident detection time was less than one minute. Furthermore, if the MPR is 0.4% or higher for two-lane expressways and 0.2% or higher for three-lane expressways, the incident detection time decreased compared to the average incident detection time announced by the Korea Expressway Corporation for both two-lane and three-lane expressways.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.43 no.6
• /
• pp.689-693
• /
• 2023

Domestic bridges with a service life of more than 30 years are expected to account for approximately 54% of all bridges within the next 10 years. As bridges rapidly deteriorate, it is necessary to establish an appropriate maintenance plan. Recent domestic and international research have focused on the integration of BIM to digitize bridge maintenance information and then enhance accessibility and usability of the information. Accordingly, this study developed a BIM-FEM interoperability algorithm for bridge decks to convert maintenance information into data and efficiently manage the history of maintenance. After creating an initial crack BIM based on an exterior damage map, bridge specification and damage information were linked to a numerical analysis that performs damage analysis considering damage scenarios and design loads. The spread of cracks obtained from the analysis results were updated into the BIM. Based on the damage spread information on the BIM, an automated technology was also developed to assess both the current and future condition ratings of the bridge deck. This approach can enable an efficient maintenance of the deck using the history data from bridge inspection and diagnosis as well as future information on cracks and defects. The expected early detection and prevention would ultimately improve the lifespan and safety of bridges.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.44 no.1
• /
• pp.63-73
• /
• 2024

Autonomous vehicles at Levels 3 to 5, currently under global research and development, seek to replace the driver's perception, judgment, and control processes with various sensors integrated into the vehicle. This integration enables artificial intelligence to autonomously perform the majority of driving tasks. However, autonomous vehicles currently obtain temporary driving permits, allowing them to operate on roads if they meet minimum criteria for autonomous judgment abilities set by individual countries. When autonomous vehicles become more widespread in the future, it is anticipated that buyers may not have high confidence in the ability of these vehicles to avoid hazardous situations due to the limitations of temporary driving permits. In this study, we propose a method for grading the judgment abilities of autonomous vehicles based on a driving simulator experiment comparing and evaluating drivers' abilities to avoid hazardous situations. The goal is to derive evaluation criteria that allow for grading based on specific scenarios and to propose a framework for grading autonomous vehicles. Thirty adults (25 males and 5 females) participated in the driving simulator experiment. The analysis of the experimental results involved K-means cluster analysis and independent sample t-tests, confirming the possibility of classifying the judgment abilities of autonomous vehicles and the statistical significance of such classifications. Enhancing confidence in the risk-avoidance capabilities of autonomous vehicles in future hazardous situations could be a significant contribution of this research.