• 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.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.5
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• pp.217-228
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• 2023

Video instance segmentation is an intelligent visual task with high complexity because it not only requires object instance segmentation for each image frame constituting a video, but also requires accurate tracking of instances throughout the frame sequence of the video. In special, human instance segmentation in drama videos has an unique characteristic that requires accurate tracking of several main characters interacting in various places and times. Also, it is also characterized by a kind of the class imbalance problem because there is a significant difference between the frequency of main characters and that of supporting or auxiliary characters in drama videos. In this paper, we introduce a new human instance datatset called MHIS, which is built upon drama videos, Miseang, and then propose a novel video data augmentation method, CDVA, in order to overcome the data imbalance problem between character classes. Different from the previous video data augmentation methods, the proposed CDVA generates more realistic augmented videos by deciding the optimal location within the background clip for a target human instance to be inserted with taking rich spatio-temporal context embedded in videos into account. Therefore, the proposed augmentation method, CDVA, can improve the performance of a deep neural network model for video instance segmentation. Conducting both quantitative and qualitative experiments using the MHIS dataset, we prove the usefulness and effectiveness of the proposed video data augmentation method.

• Women's Studies Review
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• v.26 no.1
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• pp.3-39
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• 2009

Philosophical counseling, established by Achenbach in 1981, began as "philosophical practice" and emerged only recently as a new field of philosophy in its own right. It attempts, by recasting the philosopher as a counselor, to bring philosophy back from academia and recover the ancient notion of "doing philosophy," in a real-life context. Furthermore, it allows clients who are at a critical moment in their life a chance to revive their authentic selves and empowers them to pursue their own path. By engaging with philosophical counseling, clients are more likely to realize their hopes for their lives by examining their lives thoroughly and facing them anew. This paper first attempts to investigate philosophical counseling services for Korean women and to outline a new model of counseling based on the combination of two models of counseling, philosophical counseling and feminist counseling. In the second chapter, it seeks to introduce the history and characteristics of philosophical counseling and in the third chapter, the history and characteristics of feminist counseling are investigated, focusing on a counseling-activity entitled "Telephone for Women." Finally, in the fourth chapter, a comparative study is made by identifying the common aspects of each counseling type, in order to promote the shared outlooks of both counseling models. Although these two models of counseling emerged from different historical, social, and cultural contexts, they were founded according to four common beliefs, which are as follows: first, a focus on the importance of "practice," second, the establishment of an equal relationship between the counselor and the client, third, the importance of counselors listening attentively to the client and opening themselves up, fourth, the encouragement of clients becoming truly themselves and self-educated. Therefore, the writer believes that these two models of counseling are both aiming at the realization of an authentic "human life." It is hoped that philosophical counseling will give Korean women an opportunity to maintain a dialogue that will improve their "well-being" in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.212-215
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• 2022

In the era of so-called digital transformation today, the need for the construction and utilization of big data in various fields has increased. Today, a lot of data is produced and stored in a digital device and media-friendly manner, but the production and storage of data for a long time in the past has been dominated by print books. Therefore, the need for Optical Character Recognition (OCR) technology to utilize the vast amount of print books accumulated for a long time as big data was also required in line with the need for big data. In this study, a system for digitizing the structure and content of a document object inside a scanned book image is proposed. The proposal system largely consists of the following three steps. 1) Recognition of area information by document objects (table, equation, picture, text body) in scanned book image. 2) OCR processing for each area of the text body-table-formula module according to recognized document object areas. 3) The processed document informations gather up and returned to the JSON format. The model proposed in this study uses an open-source project that additional learning and improvement. Intelligent OCR proposed as a system in this study showed commercial OCR software-level performance in processing four types of document objects(table, equation, image, text body).

• Journal of Environmental Impact Assessment
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• v.32 no.6
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• pp.503-515
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• 2023

The disconnection and fragmentation of ecological spaces that occur during the development process pose a significant threat to biodiversity. Urban center areas with high development pressure are particularly susceptible to low connectivity due to a scarcity of ecological space. This issue tends to be more pronounced in larger cities.To address this challenge, continuous efforts are needed to assess and improve the current state of ecological space connectivity at the level of individual projects and urban management. However, there is a lack of discussion regarding the analysis and improvement of ecological connectivity in metropolitan cities In line with this objective, this study evaluated the connectivity of ecological spaces in the city centers of Seoul, Busan, Daegu, Incheon, Gwangju, Daejeon, and Ulsan. The evaluation revealed that city centers exhibited lower connectivity of ecological spaces compared to their peripheries or the overall city. In addition, in the ecological network analysis that reflected regional characteristics, such as the species distribution model conducted on Daejeon, 510 optimal paths connecting forests of more than 1ha were derived. This study is significant as an example of deriving an ecological network based on regional characteristics, including quantitative figures necessary for establishing goals to improve urban ecological connectivity and biodiversity. It is anticipated that the results can be utilized to propose directions for enhancing ecological connectivity in environmental impact assessments or urban management and to establish an evaluation framework.

• Journal of Industrial Convergence
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• v.21 no.9
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• pp.41-48
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• 2023

Recently, there has been a sharp increase in the damages caused by ransomware across various sectors of society, including individuals, businesses, and nations. Ransomware is a malicious software that infiltrates user computer systems, encrypts important files, and demands a ransom in exchange for restoring access to the files. Due to its diverse and sophisticated attack techniques, ransomware is more challenging to detect than other types of malware, and its impact is significant. Therefore, there is a critical need for accurate detection and mitigation methods. To achieve precise ransomware detection, an inference engine of a detection system must possess knowledge of ransomware features. In this paper, we propose a model to extract and classify the characteristics of ransomware for accurate detection of ransomware, calculate the similarity of the extracted characteristics, reduce the dimension of the characteristics, group the reduced characteristics, and classify the characteristics of ransomware into attack tools, inflow paths, installation files, command and control, executable files, acquisition rights, circumvention techniques, collected information, leakage techniques, and state changes of the target system. The classified characteristics were applied to the existing ransomware to prove the validity of the classification, and later, if the inference engine learned using this classification technique is installed in the detection system, most of the newly emerging and variant ransomware can be detected.

• Journal of the Korean Association of Geographic Information Studies
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• v.27 no.2
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• pp.61-77
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• 2024

The purpose of this study was to develop a method for rapidly diagnosing urban thermal comfort using Unmanned Aerial Vehicle (UAV) based data. The research was conducted at Changwon National University's College of Engineering site and Yongji Park, both located in Changwon, Gyeongsangnam-do. Baseline data were collected using field measurements and UAVs. Specifically, the study calculated field measurement-based thermal comfort indices PET and UTCI, and used UAVs to create and analyze vegetation index (NDVI), sky view factor (SVF), and land surface temperature (LST) images. The results showed that UAV-predicted PET and UTCI had high correlations of 0.662 and 0.721, respectively, within a 1% significance level. The explanatory power of the prediction model was 43.8% for PET and 52.6% for UTCI, with RMSE values of 6.32℃ for PET and 3.16℃ for UTCI, indicating that UTCI is more suitable for UAV-based thermal comfort evaluation. The developed method offers significant time-saving advantages over traditional approaches and can be utilized for real-time urban thermal comfort assessment and mitigation planning

• Journal of Korean Tunnelling and Underground Space Association
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• v.25 no.6
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• pp.541-554
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• 2023

The utilization of underground spaces in relation to tunnels and energy/waste storage is on the rise. To ensure the stability of underground spaces, it is crucial to reinforce rock fractures and discontinuities. Discontinuities, such as joints, can weaken the strength of the rock and lead to groundwater inflow into underground spaces. In order to enhance the strength and stability of the area around these discontinuities, rock grouting techniques are employed. However, during rock grouting, it is impossible to visually confirm whether the grouting material is being smoothly injected as intended. Without proper injection, the expected increases in strength, durability, and degree of consolidation may not be achieved. Therefore, it is necessary to predict in advance whether the grouting material is being injected as designed. In this study, we aimed to assess the injection performance based on injection variables such as the water/cement mixture ratio, injection pressure, and injection flow using UDEC (Universal Distinct Element Code) numerical program. Additionally, numerical results were validated by the lab experiment. The results of this study are expected to help optimize variables such as injection material properties, injection time, and pump pressure in the grouting design in the field.

• Information Systems Review
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• v.22 no.3
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• pp.59-80
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• 2020

Excellent FinTech firms create value by finding customer needs or addressing customer problems to provide customers with differentiated solutions through information technologies and organizational innovation capability. Accordingly, the survival and growth of FinTech firms rely on the innovation performance for solving customer problems. This study assumes that IT relatedness and entrepreneurial culture play a mediating role in the relationship between service orientation and innovation performance. To examine it, designed and demonstrated is a structural model from the perspective of dynamic organizational capability. The results show that IT relatedness and entrepreneurial culture play a mediating role between service orientation and innovation performance. Although IT relatedness and entrepreneurial culture were partial mediators in each divided model, the integration model showed there was no direct effect of service orientation on innovation performance. The practical implication is that FinTech companies need to understand customer problems accurately, set up appropriate service goals and align all strategies to achieve them. With these strategic alignments, higher innovation performance can be achieved by enabling IT resources and capabilities to be actively utilized in all functions of the organization and institutionalizing the entrepreneurial culture.

• Journal of the Korea Society for Simulation
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• v.33 no.2
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• pp.37-44
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• 2024

The Korean Helicopter Development Program has successfully introduced the Surion helicopter, a versatile multi-domain operational aircraft that replaces the aging UH-1 and 500MD helicopters. Specifically designed for maneuverability, the Surion plays a crucial role in low-altitude tactical maneuvers for personnel transportation and specific missions, emphasizing the helicopter's survivability. Despite the significance of its low-altitude tactical maneuver capability, there is a notable gap in research focusing on multi-mission tactical maneuvers that consider the risk factors associated with deploying the Surion in the presence of enemy air defenses. This study addresses this gap by exploring a method to enhance the Surion's low-altitude maneuvering paths, incorporating information about enemy air defenses. Leveraging the Proximal Policy Optimization (PPO) algorithm, a reinforcement learning-based approach, the research aims to optimize the helicopter's path planning. Visualized experiments were conducted using a Surion model implemented in the Unity environment and ML-Agents library. The proposed method resulted in a rapid and stable policy convergence for generating optimal maneuvering paths for the Surion. The experiments, based on two key criteria, "operation time" and "minimum damage," revealed distinct optimal paths. This divergence suggests the potential for effective tactical maneuvers in low-altitude situations, considering the risk factors associated with enemy air defenses. Importantly, the Surion's capability for remote control in all directions enhances its adaptability in complex operational environments.