• Journal of IKEEE
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• v.26 no.3
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• pp.341-348
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• 2022

Wi-Fi Sensing, which uses Wi-Fi technology to sense the surrounding environments, has strong potentials in a variety of sensing applications. Recently several advanced deep learning-based solutions using CSI (Channel State Information) data have achieved high performance, but it is still difficult to use in practice without explicit data collection, which requires expensive adaptation efforts for model retraining. In this study, we propose a Channel State Information Automatic Labeling System (CALS) that automatically collects and labels training CSI data for deep learning-based Wi-Fi sensing systems. The proposed system allows the CSI data collection process to efficiently collect labeled CSI for labeling for supervised learning using computer vision technologies such as object detection algorithms. We built a prototype of CALS to demonstrate its efficiency and collected data to train deep learning models for detecting the presence of a person in an indoor environment, showing to achieve an accuracy of over 90% with the auto-labeled data sets generated by CALS.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.11
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• pp.513-520
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• 2021

Recently, research on edutech, which combines education and technology in the e-learning field called learning, education and training, has been actively conducted, but it is still insufficient to collect and utilize data tailored to individual learners based on learning activity data that can be automatically collected from digital devices. Therefore, this study attempts to detect questions in textbooks or problem papers using artificial intelligence computer vision technology that plays the same role as human eyes. The textbook or questionnaire item detection model proposed in this study can help collect, store, and analyze offline learning activity data in connection with intelligent education services without digital conversion of textbooks or questionnaires to help learners provide personalized learning services even in offline learning.

• Atmosphere
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• v.33 no.2
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• pp.297-306
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• 2023

Celebrating its 60th anniversary, this study suggests the future vision of the Korean Meteorological Society (KMS) for the next 60 years. The vision is "to advance atmospheric science and technology that contributes to human society as well as protect people from not only climate change risks but also weather, climate, and environmental disasters". Based on the suggestions from its members, this study proposes the KMS future development plan as follows. The first plan is to strengthen in leading the development and growth of atmospheric sciences in Korea, especially to improve weather, climate, and environment forecasts and to reduce uncertainty in future climate projections. The second is to enhance interaction not only among its members in academy, Korea Meteorological Administration and related organizations, meteorological industry, and science communicators but also with other related fields such as energy, water resources, agriculture, fishery, and forestry. The third is to enhance in nurturing young scientists by supporting domestic and international networks and training the state-of-the-art sciences, and to create opportunities for young scientists to advance into a wider field. The last is to expand its international activities for solving the challenges facing mankind, such as climate change risks and weather, climate, and environment disasters. The KMS should also continue the efforts to establish an integrative platform for leading fundamental and interdisciplinary research in weather, climate, and environment.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.3
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• pp.411-425
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• 2023

Today, AI (Artificial Intelligence) technology is widely used in various fields, performing classification and regression tasks according to the purpose of use, and research is also actively progressing. Especially in the field of security, unexpected threats need to be detected, and unsupervised learning-based anomaly detection techniques that can detect threats without adding known threat information to the model training process are promising methods. However, most of the preceding studies that provide interpretability for AI judgments are designed for supervised learning, so it is difficult to apply them to unsupervised learning models with fundamentally different learning methods. In addition, previously researched vision-centered AI mechanism interpretation studies are not suitable for application to the security field that is not expressed in images. Therefore, In this paper, we use a technique that provides interpretability for detected anomalies by searching for and comparing optimization references, which are the source of intrusion attacks. In this paper, based on reference, we propose additional logic to search for data closest to real data. Based on real data, it aims to provide a more intuitive interpretation of anomalies and to promote effective use of an anomaly detection model in the security field.

• Journal of Korea Society of Industrial Information Systems
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• v.29 no.1
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• pp.91-105
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• 2024

Car accidents occur as a result of collisions between vehicles, leading to both vehicle damage and personal and material losses. This study developed a vehicle accident detection model based on 2,550 image frames extracted from car accident videos uploaded to YouTube, captured by CCTV. To preprocess the data, bounding boxes were annotated using roboflow.com, and the dataset was augmented by flipping images at various angles. The You Only Look Once version 8 (YOLOv8) model was employed for training, achieving an average accuracy of 0.954 in accident detection. The proposed model holds practical significance by facilitating prompt alarm transmission in emergency situations. Furthermore, it contributes to the research on developing an effective and efficient mechanism for vehicle accident detection, which can be utilized on devices like smartphones. Future research aims to refine the detection capabilities by integrating additional data including sound.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.146-155
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• 2020

This study was conducted from December 26, 2018 to January 4, 2019 in order to analyze the effects of hospital internal marketing on job performance and loyalty based on nurses' perception. The participants were 250 nurses at general hospitals located in Gyeonggi-do. The results of this study are as follows: First, internal marketing in hospitals had a statistically significant effect on organizational and future vision, education and training systems, communication, organizational attributes, and job performance (F=29.118, p<.001). The training system, organizational and future vision, compensation and welfare system, and work management environment were found to have a statistically significant effect (F=38.671, p <.001) on loyalty, and the effect of job performance on loyalty was statistically significant (F=87.324, p<.001). Second, the relationship between hospital internal marketing based on nurses' perception and loyalty was found to have a statistically significant positive (+) effect on stage 1 job performance (p<.001) and a statistically significant positive effect on stage 2 loyalty (+) (P <.001). The third-level internal marketing regression coefficient was significant, and job performance was also significant (P <.001). Based on these results, there is a need for hospital management to strengthen internal marketing in order to increase performance level and loyalty among nurses.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.701-715
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• 2021

The drastic advance of recent deep learning technologies is heavily dependent on training datasets which are essential to train models by themselves with less human efforts. In comparison with the work to design deep learning models, preparing datasets is a long haul; at the moment, in the domain of vision intelligent, datasets are still being made by handwork requiring a lot of time and efforts, where workers need to directly make labels on each image usually with GUI-based labeling tools. In this paper, we overview the current status of vision datasets focusing on what datasets are being shared and how they are prepared with various labeling tools. Particularly, in order to relieve the repetitive and tiring labeling work, we present an interactive smart image annotating system with which the annotation work can be transformed from the direct human-only manual labeling to a correction-after-checking by means of a support of automatic labeling. In an experiment, we show that automatic labeling can greatly improve the productivity of datasets especially reducing time and efforts to specify regions of objects found in images. Finally, we discuss critical issues that we faced in the experiment to our annotation system and describe future work to raise the productivity of image datasets creation for accelerating AI technology.

• Journal of Practical Engineering Education
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• v.15 no.3
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• pp.681-701
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• 2023

The purpose of this study is propose performance indicators analysis and development plans for K University professional graduate school for the training of human resource professionals. Specifically, the main research includes the derivation of performance indicators for K University's professional graduate school, PR plan, academic establishment plan, name change, vision proposal, and curriculum improvement plan for each major. To this end, a survey was conducted on a total of 132 current and former students of K University's professional graduate school. FGI was also conducted with 29 participants. The results of the research are as follows. In the case of key performance indicators, 15 indicators were proposed, taking into account previous research, the characteristics of professional graduate school, surveys, and FGI surveys. Promotion should be continuous, not one-time, and the advantages and benefits of the graduate school should be actively informed to target customers. The proposed name of the professional association is the Korean Association for Employment and Vocational Competency Development. It was found that operating as a convergence society and focusing on convergence research were appropriate. The names of K University's professional graduate school were HR (Human Resources), HRD, and employment and vocational competency development graduate school. As for the vision, it was suggested that a balance between identity and differentiation is needed to flexibly respond to new changes while maintaining existing strengths. As for the proposed improvement of the curriculum by major, it is proposed to reform in a stepwise and gradual manner while maintaining the existing framework to some extent rather than being radical.

• Journal of dental hygiene science
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• v.17 no.1
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• pp.1-11
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• 2017

There are 82 dental hygiene departments and clinical training institutes across the country with a very wide range of clinical practice content and evaluation methods, making standardization difficult. Therefore, there is a need to establish a standard protocol outlining clinical practice content and evaluation methods for systematic and efficient operation of clinical practice. Thus, this study attempted to propose such a protocol for standardization of dental hygiene clinical practice in dental clinics and hospitals to examine the contents of clinical practice by reviewing relevant literature, and relating it to professional practice within the dental hygienic curriculum to facilitate enhancement of expertise. Clinical practice content was extracted from 74 cases, and was consisted of classifying mandatory and optional clinical practice, training time, and activity methods for each component. To standardize effective clinical practice, it is necessary to organize the components acquired in the course of clinical dentistry training in line with their arrangement on each university's curriculum, in order to learn all components step by step. To do this, it is necessary to present a standardized clinical practice protocol and a organic cooperation between educational institutions and clinical training institutions.

• The Korean Journal of Elementary Counseling
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• v.7 no.1
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• pp.205-226
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• 2008

The purpose of the study you have seen is to verify the effectiveness of existing quantitative research and to put the Empathy Training Program to practical use for participating children. From looking into this, the changes in empathic understanding that came to light in relationships between teacher and children and children and children are sure to have that effect. For this work, I established the following subject of inquiry: What kind of changing processes can be seen in the empathic understanding of participating children in the Empathy Training Program? To resolve the above line of inquiry, six female sixth grade elementary school students were chosen and they progressed through twelve sessions of the Empathy Training Program. The children were given a sentence completion exam, recognition work, neat writing exam and a school adaptation exam both before and after participation in the program, making data for analysis. To analyze, first, participants had one or two meetings of forty to fifty minutes each. Progress through the program's curriculum was recorded and through the repeating and copying method, to be sure participating children's empathic understanding was revealed, empathic language and behavior was routinely chosen. Next, according the above criteria I looked into visible changes of the participating children's empathic expressions, classifying and analyzing changes in empathic understanding and six instances of common changes in the emphatic understanding of the participants relationships were analyzed and put together. Next I will summarize the findings we have seen in this research: First, if we look into changes in common empathic understanding from the beginning, using the criteria of empathic language, each individual showed understanding at the beginning and passed and progressed through stages of care, insight and emotional expressions. Second, when we looked at the criteria of empathic behavior from the beginning to the end, one's line of vision and ability to concentrate one's attention was connected. Next, the act of nodding one's head looked like a brief nod at first but at the end, it was not just a simple nod but rather they could feel deep empathy. The condition and substance of the facial expression was seen to match and at the very end the child was expressive and stretched out arms to hold and pat the other person and the act of holding hands could also be seen. Among lots of empathic behavior the final stage was shown by half of the children. Third, from the first stage to the last stage there were many cases revealed. The more the children went the more complete their empathic language became. Their vocabulary increased and became more diverse with empathic actions. Also, when comparing actions and expressions from the beginning with the end, visible expressions became more natural and sincere at the end. The result of the research we have seen is that through receiving experience of empathic understanding, participating children showed a sense of self-confidence and they looked to make peaceful expressions while not being aggressive or defensive about problems. In addition, from understanding empathic expressions, participating children's relationships felt closer. This outcome within this group in this case will be applied and the formation of empathic understanding can be used by the children internally to solve their own problems, acquire close relationships with their teachers and others. It will also contribute to smooth classroom management.