• KIPS Transactions on Software and Data Engineering
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• v.12 no.5
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• pp.199-206
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• 2023

The current software becomes the huge size of source codes. Therefore it is increasing the importance and necessity of static analysis for high-quality product. With static analysis of the code, it needs to identify the defect and complexity of the code. Through visualizing these problems, we make it guild for developers and stakeholders to understand these problems in the source codes. Our previous visualization research focused only on the process of storing information of the results of static analysis into the Database tables, querying the calculations for quality indicators (CK Metrics, Coupling, Number of function calls, Bad-smell), and then finally visualizing the extracted information. This approach has some limitations in that it takes a lot of time and space to analyze a code using information extracted from it through static analysis. That is since the tables are not normalized, it may occur to spend space and time when the tables(classes, functions, attributes, Etc.) are joined to extract information inside the code. To solve these problems, we propose a regularized design of the database tables, an extraction mechanism for quality metric indicators inside the code, and then a visualization with the extracted quality indicators on the code. Through this mechanism, we expect that the code visualization process will be optimized and that developers will be able to guide the modules that need refactoring. In the future, we will conduct learning of some parts of this process.

• Convergence Security Journal
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• v.23 no.2
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• pp.27-36
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• 2023

In recent years, ransomware attacks have become more organized and specialized, with the sophistication of attacks targeting specific individuals or organizations using tactics such as social engineering, spear phishing, and even machine learning, some operating as business models. In order to effectively respond to this, various researches and solutions are being developed and operated to detect and prevent attacks before they cause serious damage. In particular, honeypots can be used to minimize the risk of attack on IT systems and networks, as well as act as an early warning and advanced security monitoring tool, but in cases where ransomware does not have priority access to the decoy file, or bypasses it completely. has a disadvantage that effective ransomware response is limited. In this paper, this honeypot is optimized for the user environment to create a reliable real-time dynamic honeypot file, minimizing the possibility of an attacker bypassing the honeypot, and increasing the detection rate by preventing the attacker from recognizing that it is a honeypot file. To this end, four models, including a basic data collection model for dynamic honeypot generation, were designed (basic data collection model / user-defined model / sample statistical model / experience accumulation model), and their validity was verified.

• Journal of Korea Entertainment Industry Association
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• v.13 no.8
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• pp.619-626
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• 2019

This study was conducted to investigate the effects of a participatory rehabilitation program on sit-rise and rise-to-walk test performances, and perception and motor skills in adults with medically vulnerable individuals and, adults with developmental disabilities in particular. Seventeen adults with developmental disabilities participated in a participatory rehabilitation program using resistance bands and exercise balls, for 60 minutes once weekly over 13 weeks. Their performances were measured before and immediately after the intervention, and 12 weeks after. The findings were as follows. In the sit-rise test, the number of times rising from sitting posture increased after the intervention versus before, but the difference was not statistically significant. In the rise-to-walk test, the performance showed statistically significant difference over time, and the post-hoc test showed a significant effect after the intervention versus before. There was no significant difference in perception and motor skills. In sum, the participatory rehabilitation program positively influenced dynamic balancing related to functional activities but had no significant effect on perception and motor skills, which is related to motor control and motor learning. It is suggested that to increase the participation in community activities, reduce fall risk, and improve dynamic balancing abilities in adults with developmental disabilities, participatory rehabilitation programs should be utilized to promote the physical wellbeing.

• Journal of Korea Entertainment Industry Association
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• v.13 no.6
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• pp.187-202
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• 2019

The main goal of this study is to investigate influence of trust in physical education (PE) teachers and immersion experience in PE classes on attitude and satisfaction during PE classes. Total 863 middle school students in Gwang-ju metropolitan area were recruited by utilizing a convenience sampling method. All data were analyzed by using SPSS statistic program ver. 25.0 (frequency analysis, exploratory factor analysis, reliability analysis, correlation analysis, multiple regression analysis). Alpha was set at 0.05. The results of this study is summarized as in the following. First, all sub-factors of trust in the PE teachers partially positively or negatively influence sub-factors of attitude during PE classes. Second, sub-factors of satisfaction during PE classes were partially positively affected to trust in the PE teachers. Third, Attitude during PE Classes were found to have partial positive influence on immersion experience in PE classes. Fourth, sub-factors of immersion experience in PE classes have partial positive effect on the sub-factors of satisfaction during PE classes. Thus, in order to the positive attitude and greater satisfaction during PE classes, it is important to establish the trust of PE teachers through maintaining interaction with students, constructing better systemic class, and creating the class conditions based on considering students' ability. In addition, in order to enhance immersion experiences of students during PE classes, it is necessary to set up learning goals and tasks based on ability of students, to study various teaching method, and to make only focusing on the performance based PE classes without grading.

• Journal of Korea Entertainment Industry Association
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• v.13 no.8
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• pp.131-142
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• 2019

This paper is intended to examine and analyze the new Chinese words as the result of culture content. The development of the Korean entertainment industry has created a Korean wave around the world. Through this, many Korean words, Internet vocabulary, and cultural concepts have begun to enter China. Among them, there are many new words that have appeared on the Chinese Internet due to the culture content. As the number of Korean fans and Korean learners increases, new words on the Internet are widely used. The new Chinese words, which are influenced by Korean cultural content, are considered an important part of new Chinese vocabulary. To accurately recognize and understand this, first of all six categories of the new Chinese words were analyzed, which were figurative meaning, substitution, loan of foreign words, abbreviation, compound word, derivation. This formulation also works on the Chinese words with the influence of cultural content. There are three types of the Internet new words form Korean cultural. Which were new words in Chinese characters, new words in alphabets, extended meanings. And had analyzed new words through the acquisition of new meanings. Also took specific news titles and songs according to each category. Through new Chinese words, The influence of cultural content had been confirmed. It is expected that these new Chinese words enrich Chinese vocabulary, also help to facilitate communication. And these new Chinese words are often used in public media or in everyday life. We should recognize the existence of these new Chinese words, and have an accurate perception of them.

• Korean Journal of Social Welfare Studies
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• v.42 no.3
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• pp.183-206
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• 2011

This study examined the longitudinal relationship between academic achievement and school satisfaction using a data of the Seoul Panel Study of Children(SPSC). Fully autoregressive cross-lagged analysis and multi-group comparison were performed to measure the longitudinal relationship between two constructs as well as differences between poverty and non-poverty groups. The results showed that both academic achievement and school satisfaction were stable over time in non-poverty group. Academic achievement at the 4th grade significantly affected the school satisfaction at the 6th grade and it subsequently affected on the academic achievement at the 8th grade in non-poverty group. In contrast, academic achievement was not consistent over time in poverty group. Only the school satisfaction at the 6th grade affected the academic achievement at the 8th grade. The findings of this study have various practical implication for school interventions. It is more important to keep supporting the children to maintain the level of academic achievement in non-poverty group. While, in poverty group, it is essential to make school satisfaction and academic motivation increase with school attachment programs.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.953-964
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• 2023

Climate change is undeniably the most urgent challenge that humanity faces today. Despite this, the level of public awareness and understanding of climate change remains insufficient, indicating a need for more proactive education and the development of supportive content. In particular, it is crucial to intensify climate change education during elementary and secondary schooling when values and ethical consciousness begin to form. However, there is a significant lack of age-appropriate, experiential educational content. To address this, our study has developed an innovative 3D simulator, enabling learners to indirectly experience the effects of climate change, specifically sea-level rise. This simulator considers not only sea-level rise caused by climate change but also storm surges, which is a design based on the analysis of long-term wave observation big data. To make the simulator accessible and engaging for students, we utilized the 'Unity' game engine. We further propose using this simulator as a part of a comprehensive educational program on climate change.

• Journal of Practical Engineering Education
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• v.14 no.3
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• pp.479-489
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• 2022

In order to understand how to increase the use of virtual training content at K University's online lifelong education institute, this study examined the use experience, content recognition, field practice replacement, and requirements, focusing on the examples of operating institutions. To this end, 12 institutions that operated virtual training contents distributed by the K University Online Lifelong Education Center in 2020 were selected for in-depth interviews and qualitative analysis was conducted on the interviews of 11 institutions. As a result of the analysis, first, the experience of using the contents of the virtual training operating institution was aimed at changing the educational environment, supplementing theoretical learning, and improving the sense of practice. Second, according to a survey on the recognition of virtual training content, if the importance and utilization of the content are high, it can be replaced by on-site practice in non-face-to-face classes, such as experiences of facilities and equipment, attracting interest and attention. Third, in many cases, the perception of replacement for field practice is not unreasonable to use as a pre-training material for field practice, but it is difficult to replace field practice. Fourth, content quality improvements can be summarized as content quality improvement, content access and manipulation improvement, dedicated device development, training for instructors, and curriculum systematization. Fifth, institutional requirements include improving the quality of virtual training content itself, equipment support, curriculum systemization and characterization, systematic curriculum and detailed content sharing, detailed guidance on using virtual training content, introducing how to use content, and recruiting instructors. This study is meaningful in that it sought ways to improve the utilization of virtual training content based on the perception of virtual training content operating institutions.

• Journal of the Korea Computer Graphics Society
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• v.29 no.5
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• pp.11-20
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• 2023

In this paper, we propose a novel deep learning-based motion reconstruction approach that facilitates the generation of full-body motions, including finger motions, while also enabling the online adjustment of motion generation delays. The proposed method combines the Vive Tracker with a deep learning method to achieve more accurate motion reconstruction while effectively mitigating foot skating issues through the use of an Inverse Kinematics (IK) solver. The proposed method utilizes a trained AutoEncoder to reconstruct character body motions using tracker data in real-time while offering the flexibility to adjust motion generation delays as needed. To generate hand motions suitable for the reconstructed body motion, we employ a Fully Connected Network (FCN). By combining the reconstructed body motion from the AutoEncoder with the hand motions generated by the FCN, we can generate full-body motions of characters that include hand movements. In order to alleviate foot skating issues in motions generated by deep learning-based methods, we use an IK solver. By setting the trackers located near the character's feet as end-effectors for the IK solver, our method precisely controls and corrects the character's foot movements, thereby enhancing the overall accuracy of the generated motions. Through experiments, we validate the accuracy of motion generation in the proposed deep learning-based motion reconstruction scheme, as well as the ability to adjust latency based on user input. Additionally, we assess the correction performance by comparing motions with the IK solver applied to those without it, focusing particularly on how it addresses the foot skating issue in the generated full-body motions.

• Journal of IKEEE
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• v.27 no.4
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• pp.486-493
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• 2023

In this paper, we propose an automatic hand gesture area extraction and recognition technique using FMCW radar-based point cloud and LSTM. The proposed technique has the following originality compared to existing methods. First, unlike methods that use 2D images as input vectors such as existing range-dopplers, point cloud input vectors in the form of time series are intuitive input data that can recognize movement over time that occurs in front of the radar in the form of a coordinate system. Second, because the size of the input vector is small, the deep learning model used for recognition can also be designed lightly. The implementation process of the proposed technique is as follows. Using the distance, speed, and angle information measured by the FMCW radar, a point cloud containing x, y, z coordinate format and Doppler velocity information is utilized. For the gesture area, the hand gesture area is automatically extracted by identifying the start and end points of the gesture using the Doppler point obtained through speed information. The point cloud in the form of a time series corresponding to the viewpoint of the extracted gesture area is ultimately used for learning and recognition of the LSTM deep learning model used in this paper. To evaluate the objective reliability of the proposed technique, an experiment calculating MAE with other deep learning models and an experiment calculating recognition rate with existing techniques were performed and compared. As a result of the experiment, the MAE value of the time series point cloud input vector + LSTM deep learning model was calculated to be 0.262 and the recognition rate was 97.5%. The lower the MAE and the higher the recognition rate, the better the results, proving the efficiency of the technique proposed in this paper.