• Journal of Internet of Things and Convergence
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• v.8 no.5
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• pp.119-125
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• 2022

With the recent increase in dementia patients due to aging, measures to prevent their wandering behavior and disappearance are urgently needed. To solve this problem, various authentication methods and location detection techniques have been introduced, but the security problem of personal authentication and a system that can check indoor and outdoor overall was lacking. In order to solve this problem, various authentication methods and location detection techniques have been introduced, but it was difficult to find a system that can check the security problem of personal authentication and indoor/outdoor overall. In this study, we intend to propose a system that can identify personal authentication, basic health status, and overall location indoors and outdoors by using wristband-type wearable devices in a private blockchain environment. In this system, personal authentication uses ECG, which is difficult to forge and highly personally identifiable, Bluetooth beacon that is easy to use with low power, non-contact and automatic transmission and reception indoors, and DGPS that corrects the pseudorange error of GPS satellites outdoors. It is intended to detect wandering behavior and abnormal signs by locating the patient. Through this, it is intended to contribute to the prompt response and prevention of disappearance in case of wandering behavior and abnormal symptoms of dementia patients living at home or in nursing homes.

• Journal of Korean Elementary Science Education
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• v.40 no.4
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• pp.460-479
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• 2021

The crisis of the COVID-19 pandemic has caused significant changes in education systems worldwide, including in Korea. Due to COVID-19's social distancing policies, the education system was suddenly switched to distance learning, resulting in many problems in primary schools without preparation. The purpose of this study was to investigate a teacher's awareness of science education techniques, responses to issues in science classes, including inquiry activities, advantages and disadvantages, and roles after experiencing distance learning. Survey and focus interviews were conducted for primary school teachers who had previously participated in distance learning, such as online content classes and real-time interactive classes. The study findings showed three conclusions: 1) Primary school teachers conducted one-way and interactive lectures in online classes. It is vital to improve a teacher's digital literacy to improve other teaching methods such as investigation and discussion in online classes. 2) Primary school teachers acknowledged the challenges of field feedback, inquiry item preparations, and safety in inquiry activities of science classes, by providing individual experimental packages and videos and using online discussion and feedback among teacher - student and student - student interactions. 3) Primary school teachers recognized that various types of classes using IT devices and individualized learning were possible as advantages of distance learning. As for disadvantages, it was acknowledged that inquiry activities, cooperative learning, immediate feedback, and interaction among students were challenging. Furthermore, learning gaps were wider in distance learning.

• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.665-672
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• 2023

Purpose: Underground utility tunnel is facility that is jointly house infrastructure such as electricity, water and gas in city, causing condensation problems due to lack of airflow. This paper aims to prevent electricity leakage fires caused by condensation by detecting whether the control panel door in the underground utility tunnel is open using a deep learning model. Method: YOLO, a deep learning object recognition model, is trained to recognize the opening and closing of the control panel door using video data taken by a robot patrolling the underground utility tunnel. To improve the recognition rate, image augmentation is used. Result: Among the image enhancement techniques, we compared the performance of the YOLO model trained using mosaic with that of the YOLO model without mosaic, and found that the mosaic technique performed better. The mAP for all classes were 0.994, which is high evaluation result. Conclusion: It was able to detect the control panel even when there were lights off or other objects in the underground cavity. This allows you to effectively manage the underground utility tunnel and prevent disasters.

• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.498-509
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• 2023

Purpose: This paper proposes a method detecting the falling of a maintenance worker in the underground utility tunnel, by applying deep learning techniques using CCTV video, and evaluates the applicability of the proposed method to the worker monitoring of the utility tunnel. Method: Each rule was designed to detect the falling of a maintenance worker by using the inference results from pre-trained YOLOv5 and OpenPose models, respectively. The rules were then integrally applied to detect worker falls within the utility tunnel. Result: Although the worker presence and falling were detected by the proposed model, the inference results were dependent on both the distance between the worker and CCTV and the falling direction of the worker. Additionally, the falling detection system using YOLOv5 shows superior performance, due to its lower dependence on distance and fall direction, compared to the OpenPose-based. Consequently, results from the fall detection using the integrated dual deep learning model were dependent on the YOLOv5 detection performance. Conclusion: The proposed hybrid model shows detecting an abnormal worker in the utility tunnel but the improvement of the model was meaningless compared to the single model based YOLOv5 due to severe differences in detection performance between each deep learning model

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.407-418
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• 2023

The Multi-Object Goal Visual Navigation(MultiOn) is a visual navigation task in which an agent must visit to multiple object goals in an unknown indoor environment in a given order. Existing models for the MultiOn task suffer from the limitation that they cannot utilize an integrated view of multimodal context because use only a unimodal context map. To overcome this limitation, in this paper, we propose a novel deep neural network-based agent model for MultiOn task. The proposed model, MCFMO, uses a multimodal context map, containing visual appearance features, semantic features of environmental objects, and goal object features. Moreover, the proposed model effectively fuses these three heterogeneous features into a global multimodal context map by using a point-wise convolutional neural network module. Lastly, the proposed model adopts an auxiliary task learning module to predict the observation status, goal direction and the goal distance, which can guide to learn the navigational policy efficiently. Conducting various quantitative and qualitative experiments using the Habitat-Matterport3D simulation environment and scene dataset, we demonstrate the superiority of the proposed model.

• Journal of Platform Technology
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• v.11 no.2
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• pp.26-38
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• 2023

This paper is a study on a transport robot capable of autonomously driving to a destination using a QR code in an indoor environment. The transport robot was designed and manufactured by attaching a lidar sensor so that the robot can maintain a certain distance during movement by detecting the distance between the camera for recognizing the QR code and the left and right walls. For the location information of the delivery robot, the QR code image was enlarged with Lanczos resampling interpolation, then binarized with Otsu Algorithm, and detection and analysis were performed using the Zbar library. The QR code recognition experiment was performed while changing the size of the QR code and the traveling speed of the transport robot while the camera position of the transport robot and the height of the QR code were fixed at 192cm. When the QR code size was 9cm × 9cm The recognition rate was 99.7% and almost 100% when the traveling speed of the transport robot was less than about 0.5m/s. Based on the QR code recognition rate, an experiment was conducted on the case where the destination is only going straight and the destination is going straight and turning in the absence of obstacles for autonomous driving to the destination. When the destination was only going straight, it was possible to reach the destination quickly because there was little need for position correction. However, when the destination included a turn, the time to arrive at the destination was relatively delayed due to the need for position correction. As a result of the experiment, it was found that the delivery robot arrived at the destination relatively accurately, although a slight positional error occurred while driving, and the applicability of the QR code-based destination self-driving delivery robot was confirmed.

• Journal of Korea Entertainment Industry Association
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• v.13 no.4
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• pp.165-172
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• 2019

Signs of the street and scenes of the nature(tree) popping up like a still screen in a monotonously repeated routine, as if waiting for something by chance, characters appearing and disappearing without special meaning, advise you to get away from cliché meetings and breakups while repeating it. The images of people returning to their places without presenting any conclusions highlights the coincidences and unexpectedness of everyday life, but are so familiar that it is easy to be overlooked, it brings us to experience the potential of everyday unfamiliarity in such moments. The actor's performance, which deviates from the practice of well-organized characters, is improvised (unplanned and uncoordinated) emphasized on the scene and expresses the everyday nature of his differentiated character freely like the reality as if he were locked up in a film structure but not confined to it, and as if he got used to the everyday life. Also the repeated words and actions of characters, and unpredictable changes of emotions, centered by the encounters and conversations of this film of Hong Sang-soo, everything that is presented in the background of everyday life in its form, let's us pay attention to the meaning and what to be found in the film. In addition, director Hong Sang-soo, who creates a story after selecting actors to reproduce this daily process in a realistic manner, sets new relationships between the characters and the actors, presenting a new method of realistic expression, through the actor who repeatedly appears in the film. This study analyzes the everyday characters and acting of the film based on director Hong Sang-soo's directing style.

• Knowledge Management Research
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• v.24 no.1
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• pp.1-29
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• 2023

The COVID-19 pandemic has accelerated digital transformation across all industries and daily life. Edutech is spreading in the education field, also bringing changes in university education. Non-face-to-face online-only classes at universities have spread after the COVID-19 pandemic physical distancing started. Online-only or real-time online classes showed diverse educational imitations. 'Metaverse' started to attract attention as a learning space and community activity support platform that may solve the limitations of online education and communication. It is time to prepare an introduction strategy for the actual application of education using metaverse. This study, first, by examining previous studies and cases of metaverse application, and second, establishing a metaverse introduction framework based on the technology lifecycle model and the innovation diffusion theory. Finally, we provide an introduction strategy in steps, a specialized introduction plan according to the main users is established and presented as a scenario. We expect that this study will provide the theoretical background of the new technology introduction and the spread of metaverse research. Also, we present an efficient introduction strategy, the basis for a service model, and a practical basis for the university's value-added strategy.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.249-256
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• 2022

Various studies are being actively conducted to show that the real-time visualization technology that combines BIM (Building Information Modeling) and AR (Augmented Reality) helps to increase construction management decision-making and processing efficiency. However, when large-capacity BIM data is projected into AR, there are various limitations such as data transmission and connection problems and the image cut-off issue. To improve the high efficiency of visualizing, a mesh optimization algorithm based on the k-nearest neighbors (KNN) classification framework to reconstruct BIM data is proposed in place of existing mesh optimization methods that are complicated and cannot adequately handle meshes with numerous boundaries of the 3D models. In the proposed algorithm, our target BIM model is optimized with the Unity C# code based on triangle centroid concepts and classified using the KNN. As a result, the algorithm can check the number of mesh vertices and triangles before and after optimization of the entire model and each structure. In addition, it is able to optimize the mesh vertices of the original model by approximately 56 % and the triangles by about 42 %. Moreover, compared to the original model, the optimized model shows no visual differences in the model elements and information, meaning that high-performance visualization can be expected when using AR devices.

• The Journal of Korean Society for Radiation Therapy
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• v.26 no.2
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• pp.297-303
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• 2014

Purpose : The purpose of this study is reproducibility evaluation of deep inspiration breath-hold(DIBH) technique by respiration data and heart position analysis in radiation therapy for Left Breast cancer patients. Materials and Methods : Free breathing(FB) Computed Tomography(CT) images and DIBH CT images of three left breast cancer patients were used to evaluate the heart volume and dose during treatment planing system( Eclipse version 10.0, Varian, USA ). The signal of RPM (Real-time Position Management) Respiratory Gating System (version 1.7.5, Varian, USA) was used to evaluate respiration stability of DIBH during breast radiation therapy. The images for measurement of heart position were acquired by the Electronic portal imaging device(EPID) cine acquisition mode. The distance of heart at the three measuring points(A, B, C) on each image was measured by Offline Review (ARIA 10, Varian, USA). Results : Significant differences were found between the FB and DIBH plans for mean heart dose (6.82 vs. 1.91 Gy), heart $V_{30}$ (68.57 vs. $8.26cm^3$), $V_{20}$ (76.43 vs. $11.34cm^3$). The standard deviation of DIBH signal of each patient was ${\pm}0.07cm$, ${\pm}0.04cm$, ${\pm}0.13cm$, respectively. The Maximum and Minimum heart distance on EPID images were measured as 0.32 cm and 0.00 cm. Conclusion : Consequently, using the DIBH technique with radiation therapy for left breast cancer patients is very useful to establish the treatment plan and to reduce the heart dose. In addition, it is beneficial to using the Cine acquisition mode of EPID for the reproducibility evaluation of DIBH.