• Journal of The Geomorphological Association of Korea
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• v.17 no.3
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• pp.59-75
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• 2010

In this study, location evaluation of the natural environment of ports in the Joseon Dynasty was carried out to investigate the outport of east coast for the conquest of Usanguk. As a result of study, there were 55 ports and naval stations in the Joseon Dynasty, including the Yeongokpo, Aninpo, Samcheokpo, Susanpo, and Wolsongpo. As a result of the restoration work in the sea level that was done in the sixth century, the sea level at that time was about 1m higher than that at present. In terms of the location type, three types were identified via natural-environment analysis. Location type I consists of a total of 21 ports suitable for defense due to the sand spit in all the sides and because it is located in the bay of small and medium rivers. Location type II is composed of 22 ports close to the open seas, and location type III consists of a total of 12 ports centering on the bay. A total of nine ports satisfied the location factor in the shortest distance analysis(targeting location type I), 15 ports in the slope analysis, 13 ports in the hinterland analysis, 13 ports in the visibility analysis, and 11 ports in the ocean current analysis. It was found in the final evaluation that the I level regions consist of two ports(Obunjin and Mangyangjin). Obunjin has a location characteristic that is advantageous for defense and that makes it suitable to serve as an anchorage harbor for a large-scale fleet as its water level is deep and as it has a wide embayment. In conclusion, Obunjin is considered the outport that has the highest possibility of serving as Isabu's departure port for the conquest of Usanguk.

• Korea Trade Review
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• v.41 no.1
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• pp.91-116
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• 2016

This study proposes a research model to investigate the effect of ICT on national culture and values. Why should we research the relationship between ICT and culture? We do this to shed light on the cultural framework and find areas for further research. This research has found that the development of Information Communication Technology(ICT) has proved to have a positive effect on the quality of individualism (B0.603), there is a decrease in power distance index(B-0.331)and a correlation between individualism and wealth. Also, the development of Information Communication Technology(ICT) has proved to have a positive effect on the quality of Long Term Orientation. As for adoption and use of ICT, the role of culture is important for many reasons. First of all, we can recognize the importance of national culture and organizational culture in establishing the ability of the overall culture to adapt, efficiently merging with different cultures and overcoming potential obstacles of these tasks. This is the evidence supporting the current theory. Our research shows that development of technology highly influences deep human values. Furthermore, the data points used in this research are from World Economic Forum, World Development Indicator and International Telecommunication Union. In order to understand and develop social evolution and progress, we tried to use data that is fair and verifiable.

• The Journal of Engineering Geology
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• v.33 no.2
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• pp.307-322
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• 2023

Rock-mass grouting plays a crucial role in the construction of dams and deep caverns, effectively preventing seepage in the foundations, enhancing stability, and mitigating hazards. Most rock grouting is affected by hydrogeological and rock engineering indices such as rock quality designation (RQD), rock mass quality (Q-value), geological strength index (GSI), joint spacing (Js), joint aperture (Ap), lugeon value (Lu), secondary permeability index (SPI), and coefficient of permeability (K). Therefore, accurate geological analysis of basic rock properties and guidelines for grouting construction are essential for ensuring safe and effective grouting design and construction. Such analysis has been applied in dam construction sites, with a particular focus on the geological characteristics of bedrock and the development of prediction methods for grout take. In South Korea, many studies have focused on grout injection materials and construction management techniques. However, there is a notable lack of research on the analysis of hydrogeological and rock engineering information for rock masses, which are essential for the development of appropriate rock grouting plans. This paper reviews the current state of research into the correlation between the grout take with important hydrogeological and rock engineering indices. Based on these findings, future directions for the development of rock grouting research in South Korea are discussed.

• The Journal of Bigdata
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• v.7 no.2
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• pp.31-41
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• 2022

Steel is one of the most fundamental components to mechanical industry. However, the quality of products are greatly impacted by the surface defects in the steel. Thus, researchers pay attention to the need for surface defects detector and the deep learning methods are the current trend of object detector. There are still limitations and rooms for improvements, for example, related works focus on developing the models but don't take into account real-time application with practical implication on industrial settings. In this paper, a real-time application of steel surface defects detection based on YOLOv4 is proposed. Firstly, as the aim of this work to deploying model on real-time application, we studied related works on this field, particularly focusing on one-stage detector and YOLO algorithm, which is one of the most famous algorithm for real-time object detectors. Secondly, using pre-trained Yolov4-Darknet platform models and transfer learning, we trained and test on the hot rolled steel defects open-source dataset NEU-DET. In our study, we applied our application with 4 types of typical defects of a steel surface, namely patches, pitted surface, inclusion and scratches. Thirdly, we evaluated YOLOv4 trained model real-time performance to deploying our system with accuracy of 87.1 % mAP@0.5 and over 60 fps with GPU processing.

• The Journal of Bigdata
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• v.8 no.1
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• pp.99-109
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• 2023

Recently, not only in Korea but also around the world, we have been experiencing constant disasters such as typhoons, wildfires, and heavy rains. The property damage caused by typhoons and heavy rain in South Korea alone has exceeded 1 trillion won. These disasters have resulted in significant loss of life and property damage, and the recovery process will also take a considerable amount of time. In addition, the government's contingency funds are insufficient for the current situation. To prevent and effectively respond to these issues, it is necessary to collect and analyze accurate data in real-time. However, delays and data loss can occur depending on the environment where the sensors are located, the status of the communication network, and the receiving servers. In this paper, we propose a two-stage hybrid situation analysis and prediction algorithm that can accurately analyze even in such communication network conditions. In the first step, data on river and stream levels are collected, filtered, and refined from diverse sensors of different types and stored in a bigdata. An AI rule-based inference algorithm is applied to analyze the crisis alert levels. If the rainfall exceeds a certain threshold, but it remains below the desired level of interest, the second step of deep learning image analysis is performed to determine the final crisis alert level.

• The Journal of the Convergence on Culture Technology
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• v.9 no.2
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• pp.357-366
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• 2023

In the purpose of this study, the college textbooks of self-narrative writing and examples of classroom practice are analyzed to find a way to educate it. The self- narrative writing subject with a learning of recognization, expression, and communication with oneself, emphasizes the necessity when they become college students through entrance exam-oriented education. The research methods are as follows. Firstly, three university textbooks which include a section on self-narrative writing were compared and analyzed. The analysis highlights the needs for a textbook covering self-narrative writing more extensively and comprehensively as what is offered by the existing textbooks is limited in facilitating students to fully develop the ability of self-reflection, which should be dealt as a long-term goal. Secondly, the current discussion on self-narrative writing and examples of real classroom practice were analyzed. It shows that a step-by-step approach is required to encourage the practice of deep self-reflection to be incorporated into writing. In addition, during the writing process, various correction and feedback activities should be carried out on a macro level and gradually while the communication and feedback should take place not only between a teacher and students, but also among students. As a result, it is expected that this study will help establish a teaching model of self-narrative writing by seeking complementary points and educational directions for self-narrative writing.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.6
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• pp.30-38
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• 2023

As the number of old buildings subject to safety inspection increases, the burden on designated institutions and management entities that are responsible for safety management is increasing. Accordingly, when selecting buildings subject to safety inspection, appropriate safety inspection standards and appropriate technology are essential. The current safety inspection standards for old buildings give low scores when it is difficult to confirm damage such as cracks in structural members due to finishing materials. This causes the evaluation results to be underestimated regardless of the actual safety status of the structure, resulting in an increase in the number of aging buildings subject to safety inspection. Accordingly, this study proposed a thermal imaging technique, a non-destructive and non-contact inspection, to detect cracks inside finishing materials. A concrete specimen was produced to observe cracks inside the finishing material using a thermal imaging camera, and thermal image data was measured by exciting a heat source on the concrete surface and cracked area. As a result of the measurement, it was confirmed that it was possible to observe cracks inside the finishing material with a width of 0.3mm, 0.5mm, and 0.7mm, but it was difficult to determine the cracks due to uneven temperature distribution due to surface peeling and peeling of the wallpaper. Accordingly, as a result of performing data analysis by deriving the amplitude and phase difference of the thermal image data, clear crack measurement was possible for 0.5mm and 0.7mm cracks. Based on this study, we hope to increase the efficiency of field application and analysis through the development of technology using big data-based deep learning in the diagnosis of internal crack damage in finishing materials.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.755-770
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• 2023

Due to recent severe climate change, abnormal weather phenomena, and other factors, the frequency and magnitude of natural disasters are increasing. The need for disaster management using artificial satellites is growing, especially during large-scale disasters due to time and economic constraints. In this study, we have summarized the current status of next-generation medium-sized satellites and microsatellites in operation and under development, as well as trends in satellite imagery analysis techniques using a large volume of satellite imagery driven by the advancement of the space industry. Furthermore, by utilizing satellite imagery, particularly focusing on recent major disasters such as floods, landslides, droughts, and wildfires, we have confirmed how satellite imagery can be employed for damage analysis, thereby establishing its potential for disaster management. Through this study, we have presented satellite development and operational statuses, recent trends in satellite imagery analysis technology, and proposed disaster response strategies that utilize various types of satellite imagery. It was observed that during the stages of disaster progression, the utilization of satellite imagery is more prominent in the response and recovery stages than in the prevention and preparedness stages. In the future, with the availability of diverse imagery, we plan to research the fusion of cutting-edge technologies like artificial intelligence and deep learning, and their applicability for effective disaster management.

• The Transactions of the Korea Information Processing Society
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• v.13 no.6
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• pp.284-290
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• 2024

Speech emotion recognition (SER) is a technique that is used to analyze the speaker's voice patterns, including vibration, intensity, and tone, to determine their emotional state. There has been an increase in interest in artificial intelligence (AI) techniques, which are now widely used in medicine, education, industry, and the military. Nevertheless, existing researchers have attained impressive results by utilizing acted-out speech from skilled actors in a controlled environment for various scenarios. In particular, there is a mismatch between acted and spontaneous speech since acted speech includes more explicit emotional expressions than spontaneous speech. For this reason, spontaneous speech-emotion recognition remains a challenging task. This paper aims to conduct emotion recognition and improve performance using spontaneous speech data. To this end, we implement deep learning-based speech emotion recognition using the VGG (Visual Geometry Group) after converting 1-dimensional audio signals into a 2-dimensional spectrogram image. The experimental evaluations are performed on the Korean spontaneous emotional speech database from AI-Hub, consisting of 7 emotions, i.e., joy, love, anger, fear, sadness, surprise, and neutral. As a result, we achieved an average accuracy of 83.5% and 73.0% for adults and young people using a time-frequency 2-dimension spectrogram, respectively. In conclusion, our findings demonstrated that the suggested framework outperformed current state-of-the-art techniques for spontaneous speech and showed a promising performance despite the difficulty in quantifying spontaneous speech emotional expression.

• Convergence Security Journal
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• v.24 no.2
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• pp.181-188
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• 2024

Amid global geopolitical crises that are heightening tensions worldwide, the importance of national security is being reevaluated. Consequently, South Korea is gaining attention in the global defense market due to its superior technology, competitive pricing, and rapid delivery capabilities. The increasing international demand for defense materials offers opportunities for the development of the domestic defense industry and has the potential to lead to long-term defense strategies and an expansion of exports. In particular, the development of future advanced weapons systems and the expansion of defense exports are likely to be possible through a deep understanding of the international political and economic situation and proactive defense diplomacy. This study analyzes the impact of current global geopolitical crises on Korea's defense industry and presents effective strategies based on these findings, including innovative improvements to defense acquisition systems and the discovery of overseas defense cooperation partners to strengthen defense exports. This strategic approach aims to balance domestic consumption with exports, enhance military strength, and improve the country's standing in the international community. Therefore, efforts are needed to ensure the sustainable growth of the defense industry, enabling South Korea to achieve economies of scale and play a pivotal role in the global defense industry.