• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.139-143
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• 2021

본 논문에서는 꾸준히 연구되어 오던 이미지 복원 문제에서 초해상화와 인페인팅이라는 복합적 이미지 복원을 동시에 처리하는 해결 방법을 제안한다. 초해상화는 국지적 픽셀 정보를 이용하여 고해상도의 영상을 복원하고, 인페인팅은 이미지 전체 정보를 활용하여 영상 내 비어 있는 영역을 생성해야 하므로, 이러한 두 가지 영상 복원 기법을 동시에 수행하는 것은 상당히 어려운 문제이다. 그렇기에 인페인팅과 초해상화는 이미지 복원에서 널리 활용되는 기술인 만큼 동시에 해결할 수 있는 기법에 대한 수요는 있음에도 지금까지 거의 연구되지 않았다. 본 논문은 초해상화 및 인페인팅 합동 처리에 있어 복합적인 정보를 모두 다뤄야하는 네트워크가 서로의 성능을 저하시키지 않도록 개략적 복원 네트워크 (Coarse network), 디테일 복원 네트워크 (Refinement network), 초해상화 네트워크 (SR network)로 분리하여 초해상화 및 인페인팅 합동 처리를 수행하며, 각 단계마다 결과 영상을 얻어 스케일 별 정답 영상과 손실함수를 계산하여 복합적인 성능을 올릴 수 있는 방법을 제시한다. 또한 순차적 단일 모델에 비하여 인페인팅과 초해상화를 합동 학습하는 제안 모델이 개선된 화질의 결과 영상을 획득할 수 있다는 것을 실험적으로 보인다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2020.11a
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• pp.205-207
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• 2020

This paper proposes a novel deep learning-based method to upsample a depth map. Most conventional methods estimate high-resolution depth map by modifying pixel value of given depth map using high-resolution color image and low-resolution depth map. However, these methods cause under- or over-shooting problems that restrict performance improvement. To overcome these problems, the proposed method iteratively performs grid warping scheme which shifts pixel values to restore blurred image for estimating high-resolution depth map. Experimental results show that the proposed method improves both quantitative and visual quality compared to the existing method.

• International Journal of Computer Science & Network Security
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• v.23 no.7
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• pp.131-140
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• 2023

Network security situational awareness systems helps in better managing the security concerns of a network, by monitoring for any anomalies in the network connections and recommending remedial actions upon detecting an attack. An Intrusion Detection System helps in identifying the security concerns of a network, by monitoring for any anomalies in the network connections. We have proposed a CRF based IDS system using genetic search feature selection algorithm for network security situational awareness to detect any anomalies in the network. The conditional random fields being discriminative models are capable of directly modeling the conditional probabilities rather than joint probabilities there by achieving better classification accuracy. The genetic search feature selection algorithm is capable of identifying the optimal subset among the features based on the best population of features associated with the target class. The proposed system, when trained and tested on the bench mark NSL-KDD dataset exhibited higher accuracy in identifying an attack and also classifying the attack category.

• Journal of Internet Computing and Services
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• v.19 no.6
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• pp.41-51
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• 2018

Recently, in the field of video surveillance, deep learning based learning method is applied to intelligent video surveillance system, and various events such as crime, fire, and abnormal phenomenon can be robustly detected. However, since occlusion occurs due to the loss of 3d information generated by projecting the 3d real-world in 2d image, it is need to consider the occlusion problem in order to accurately detect the object and to estimate the pose. Therefore, in this paper, we detect moving objects by solving the occlusion problem of object detection process by adding depth information to existing RGB information. Then, using the convolution neural network in the detected region, the positions of the 14 keypoints of the human joint region can be predicted. Finally, in order to solve the self-occlusion problem occurring in the pose estimation process, the method for 3d human pose estimation is described by extending the range of estimation to the 3d space using the predicted result of 2d keypoint and the deep neural network. In the future, the result of 2d and 3d pose estimation of this research can be used as easy data for future human behavior recognition and contribute to the development of industrial technology.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.302-314
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• 2024

Purpose: This study proposes a fall detection model based on a top-down deep learning pose estimation model to automatically determine falls of multiple workers in an underground utility tunnel, and evaluates the performance of the proposed model. Method: A model is presented that combines fall discrimination rules with the results inferred from YOLOv8-pose, one of the top-down pose estimation models, and metrics of the model are evaluated for images of standing and falling two or fewer workers in the tunnel. The same process is also conducted for a bottom-up type of pose estimation model (OpenPose). In addition, due to dependency of the falling interference of the models on worker detection by YOLOv8-pose and OpenPose, metrics of the models for fall was not only investigated, but also for person. Result: For worker detection, both YOLOv8-pose and OpenPose models have F1-score of 0.88 and 0.71, respectively. However, for fall detection, the metrics were deteriorated to 0.71 and 0.23. The results of the OpenPose based model were due to partially detected worker body, and detected workers but fail to part them correctly. Conclusion: Use of top-down type of pose estimation models would be more effective way to detect fall of workers in the underground utility tunnel, with respect to joint recognition and partition between workers.

• Journal of the Korean earth science society
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• v.39 no.2
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• pp.178-192
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• 2018

The purposes of this study were to develop and apply on learning on geological field trip utilizing the social construction of scientific model. We developed field trip places by considering not only Orion (1993)'s novelty space but also the achievement standards of 2015 national curriculum. The subjects of the study were 8 in the 'G' science gifted education center. We conducted a study using the theme of 'How was formed Mt. Gwanak?' on 5 lessons including a series of 2 field trip lessons and 3 lessons utilizing the social construction of scientific model. Students participated in pre- and post-test on the understanding of scientific knowledge about formation of mountain. Semi-structured interview was used to analyze students' learning about geological field trip in terms of affective domain. Results were as follows. First, there were 2 places of upper-stream valley and down-stream valley separately. They contained outcrops gneiss, granite, joint in the valley, xenolith, fault plane, mineral in the valley. Second, pre- and post-test and semi-structure interview were analyzed in terms of what scientific knowledge students learned about and how Mt. Gwanak was formed. Seven students explained that Mt. Gwanak was volcano during pretest. Seven students described how granite was formed to form Mt. Gwanak. They also understood geological time scale, i.e., metamorphic rock. Third, the geological field trip was effective to low achievement geoscience students as they engaged in the activities of field trip. Using positive responses on affective learning was effective on learning on geological field trip when utilizing the social construction of scientific model. This study suggests that teachers use an example 'model' on geoscience education. This study also suggests that teachers apply the social construction of scientific model to geological field trip.

• Asia pacific journal of information systems
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• v.22 no.2
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• pp.39-69
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• 2012

With the advent of communication technologies including electronic collaborative tools and conferencing systems provided over the Internet, virtual collaboration is becoming increasingly common in organizations. Virtual collaboration refers to an environment in which the people working together are interdependent in their tasks, share responsibility for outcomes, are geographically dispersed, and rely on mediated rather than face-to face, communication to produce an outcome. Research suggests that new sets of individual skill, knowledge, and ability (SKAs) are required to perform effectively in today's virtualized workplace, which is labeled as individual virtual competence. It is also argued that use of online social networking sites may influence not only individuals' daily lives but also their capability to manage their work-related relationships in organizations, which in turn leads to better performance. The existing research regarding (1) the relationship between virtual competence and task performance and (2) the relationship between online networking and task performance has been conducted based on different theoretical perspectives so that little is known about how online social networking and virtual competence interplay to predict individuals' task performance. To fill this gap, this study raises the following research questions: (1) What is the individual virtual competence required for better adjustment to the virtual collaboration environment? (2) How does online networking via diverse social network service sites influence individuals' task performance in organizations? (3) How do the joint effects of individual virtual competence and online networking influence task performance? To address these research questions, we first draw on the prior literature and derive four dimensions of individual virtual competence that are related with an individual's self-concept, knowledge and ability. Computer self-efficacy is defined as the extent to which an individual beliefs in his or her ability to use computer technology broadly. Remotework self-efficacy is defined as the extent to which an individual beliefs in his or her ability to work and perform joint tasks with others in virtual settings. Virtual media skill is defined as the degree of confidence of individuals to function in their work role without face-to-face interactions. Virtual social skill is an individual's skill level in using technologies to communicate in virtual settings to their full potential. It should be noted that the concept of virtual social skill is different from the self-efficacy and captures an individual's cognition-based ability to build social relationships with others in virtual settings. Next, we discuss how online networking influences both individual virtual competence and task performance based on the social network theory and the social learning theory. We argue that online networking may enhance individuals' capability in expanding their social networks with low costs. We also argue that online networking may enable individuals to learn the necessary skills regarding how they use technological functions, communicate with others, and share information and make social relations using the technical functions provided by electronic media, consequently increasing individual virtual competence. To examine the relationships among online networking, virtual competence, and task performance, we developed research models (the mediation, interaction, and additive models, respectively) by integrating the social network theory and the social learning theory. Using data from 112 employees of a virtualized company, we tested the proposed research models. The results of analysis partly support the mediation model in that online social networking positively influences individuals' computer self-efficacy, virtual social skill, and virtual media skill, which are key predictors of individuals' task performance. Furthermore, the results of the analysis partly support the interaction model in that the level of remotework self-efficacy moderates the relationship between online social networking and task performance. The results paint a picture of people adjusting to virtual collaboration that constrains and enables their task performance. This study contributes to research and practice. First, we suggest a shift of research focus to the individual level when examining virtual phenomena and theorize that online social networking can enhance individual virtual competence in some aspects. Second, we replicate and advance the prior competence literature by linking each component of virtual competence and objective task performance. The results of this study provide useful insights into how human resource responsibilities assess employees' weakness and strength when they organize virtualized groups or projects. Furthermore, it provides managers with insights into the kinds of development or training programs that they can engage in with their employees to advance their ability to undertake virtual work.

• Journal of Korean Home Economics Education Association
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• v.31 no.4
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• pp.129-147
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• 2019

This study aimed at exploring the influence of 'Healthy couple relationship' education on the relationship formation competencies and marriage values of high school students. To achieve the research objective, the 'Healthy couple relationship' lesson plan developed by the author was executed in two high schools for eight weeks from September 1 to November 3, 2018 from which the effects were analyzed. The results are as follows. First, the 'healthy couple relationship' education for high school students has been effective in improving their relationship performance, which is a part of the home economics curriculum. In S high school, the paired t-test of pre-/post-test comparison results showed statistically significant differences in the areas of 'communication', 'conflict resolution' and 'relationship formation performance'. For Sejong City campus-type joint curriculum group, where Wilcoxson signed-rank test was applied due to small sample size, showed that the overall scores as well as all the subsections of 'relationship formation performance' (i.e., 'communication', 'self-understanding', 'conflict resolution', and 'empathy') have improved, although not statistically significant. Second, the 'Healthy couple relationship' education for high school students had positive effects on the marriage values of high school students. In S high school, students' perception of marriage values rendered a statistically significant positive change, while in campus-type joint curriculum in Sejong City, no statistical significance was detected. In conclusion, the 'Healthy couple relationship' education can help high school students build positive values by cultivating their 'relationship formation competence', which is a part of the competencies listed in home economics curriculum, and also broaden their understanding of marriage, by acquiring knowledge and skills to build healthy couple relationships, and learning to implement the knowledge and skills in their own lives.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.10
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• pp.723-730
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• 2013

This paper presents the design of an arm gesture recognition system using Kinect sensor. A variety of methods have been proposed for gesture recognition, ranging from the use of Dynamic Time Warping(DTW) to Hidden Markov Models(HMM). Our system learns a unique HMM corresponding to each arm gesture from a set of sequential skeleton data. Whenever the same gesture is performed, the trajectory of each joint captured by Kinect sensor may much differ from the previous, depending on the length and/or the orientation of the subject's arm. In order to obtain the robust performance independent of these conditions, the proposed system executes the feature transformation, in which the feature vectors of joint positions are transformed into those of angles between joints. To improve the computational efficiency for learning and using HMMs, our system also performs the k-means clustering to get one-dimensional integer sequences as inputs for discrete HMMs from high-dimensional real-number observation vectors. The dimension reduction and discretization can help our system use HMMs efficiently to recognize gestures in real-time environments. Finally, we demonstrate the recognition performance of our system through some experiments using two different datasets.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.17-24
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• 2022

The article proves that the main goal of informatization of higher education institutions in the EU countries is to improve the quality of education of future specialists by introducing digital educational resources into the education process. The main tasks of informatization of education are defined. Digital educational resources are interpreted as a set of data in digital form that is applicable for use in the learning process; it is an information source containing graphic, text, digital, speech, music, video, photo and other information aimed at implementing the goals and objectives of modern education; educational resources on the Internet, electronic textbooks, educational programs, electronic libraries, etc. The creation of digital educational resources is defined as one of the main directions of informatization of all forms and levels of Education. Types of digital educational resources by educational functions are considered. The factors that determine the effectiveness of using digital educational resources in the educational process are identified. The use of digital educational resources in the training of future specialists in the EU countries is considered in detail. European countries note that digital educational resources in professional use allow you to implement a fundamentally new approach to teaching and education, which is based on broad communication, free exchange of opinions, ideas, information of participants in a joint project, on a completely natural desire to learn new things, expand their horizons; is based on real research methods (scientific or creative laboratories), allowing you to learn the laws of nature, the basics of techniques, technology, social phenomena in their dynamics, in the process of solving vital problems, features of various types of creativity in the process of joint activities of a group of participants; promotes the acquisition by teachers of various related skills that can be very useful in their professional activities, including the skills of using computer equipment and various digital technologies.