• Journal of Digital Convergence
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• v.14 no.5
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• pp.273-281
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• 2016

The issue about the safety management of gas related work has been studied toward a direction to utilize IoT system recently. For this purpose, the matters of user's demand has been deduced through the literature survey, field survey, and professional consultation, by studying the characteristics of worker, work, and work site. In summary, these are the demands for mobile App, 1)a clear arrangement of contents, 2)a design with high readability, 3)a design with low death, 4) securing of user's accessibility, 5)an effective information transmission plan in the work section where it is impossible to operate the mobile device, 6)an activation of alarm function at the section of high working error, 7)a fast two-way transmission and receipt of safety inspection matter needed at work, 8)a selection of images and contents that can guide the situation to the worker in case of accident, 9)an alarm function for the degree of danger in an area of worker's location. Based on these, a basic design of safety application for gas related work has been proposed, that can secure the user accessibility.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.67-74
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• 2016

Drone images with high spatial resolution are emerging as an alternative to previous studies with extraction limits in high density forests. Individual tree in the dense forests were extracted from drone images. To detect the individual tree extracted through the image segmentation process, the image segmentation results were compared between the combination of DSM and all R,G,B band and the combination of DSM and R,G,B band separately. The changes in the tree density of a deciduous forest was experimented by time and image. Especially the image of May when the forests are dense, among the images of March, April, May, the individual tree extraction rate based on the trees surveyed on the site was 50%. The analysis results of the width of crown showed that the RMSE was less than 1.5m, which was the best result. For extraction of the experimental area, the two sizes of medium and small trees were extracted, and the extraction accuracy of the small trees was higher. The forest tree volume and forest biomass could be estimated if the tree height is extracted based on the above data and the DBH(diameter at breast height) is estimated using the relational expression between crown width and DBH.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.4
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• pp.509-517
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• 2020

This study evaluated the importance of technical characteristics in manufacturing street furniture using 3D printing technology to suggest the direction of development of high priority 3D printing technology. The importance was analyzed by the QFD, quantified by scores and the priority of the items was summarized. As a result, the 'output size', 'shrinkage of material', and 'output angle' were derived as technical elements that should be prioritized in development and research. For verification, the design of atypical street furniture was made into a large 3D printed output and the development direction was suggested by applying the technical elements of priority during the manufacturing process. Street furniture should be designed based on functionality and stability, as well as economic efficiency, productivity, and aesthetics. Therefore, the 'output size' ensured stability by minimizing the division of parts, and the 'contractability of materials' satisfied the aesthetic and productivity by minimizing the error of form. Finally, the 'output angle' was verified by improving the quality of the output and selecting an angle with efficient and structural stability through various output angles.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.245-251
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• 2021

As the trend of steadily increasing the number of single or double household, there is a growing demand to see who is the outsider visiting the home during the free time. Various models of face recognition technology have been proposed through many studies, and Harr Cascade of OpenCV and Hog of Dlib are representative open source models. Among the two modes, Dlib's Hog has strengths in front of the indoor and at a limited distance, which is the focus of this study. In this paper, a face recognition visitor access system based on Dlib was designed and implemented. The whole system consists of a front module, a server module, and a mobile module, and in detail, it includes face registration, face recognition, real-time visitor verification and remote control, and video storage functions. The Precision, Specificity, and Accuracy according to the change of the distance threshold value were calculated using the error matrix with the photos published on the Internet, and compared with the results of previous studies. As a result of the experiment, it was confirmed that the implemented system was operating normally, and the result was confirmed to be similar to that reported by Dlib.

• Journal of Navigation and Port Research
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• v.47 no.1
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• pp.10-17
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• 2023

A series of studies on the development of autonomous surface ships have been promoted in domestic and foreign countries. One of the main technologies for the development of autonomous ships is path-following control, which is closely related to securing the safety of ships at sea. In this regard, the path-following performance of an autonomous ship should be first evaluated at the design stage. The main aim of this study was to develop a visual and quantitative evaluation method for the path-following control performance of an autonomous ship at the design stage. This evaluation technique was developed using a computational fluid dynamics (CFD)-based path-following control model together with a line-of-sight (LOS) guidance algorithm. CFD software was utilized to visualize waves around the ship, performing path-following control for visual evaluation. In addition, a quantitative evaluation was carried out using the difference between the desired and estimated yaw angles, as well as the distance difference between the planned and estimated trajectories. The results demonstrated that the ship experienced large deviations from the planned path near the waypoints while changing its course. It was also found that the fluid phenomena around the ship could be easily identified by visualizing the flow generated by the ship. It is expected that the evaluation method proposed in this study will contribute to the visual and quantitative evaluation of the path-following performance of autonomous ships at the design stage.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.1
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• pp.94-106
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• 2020

Recently, the radio navigation method utilizing the GPS(Global Positioning System) satellite information is widely used as the method to measure the position of objects. As GPS applications become wider and fields based on various positioning information emerge, new methods for achieving higher accuracy are required. In the case of autonomous vehicles, the INS(Inertial Navigation System) using the IMU(Inertial Measurement Unit), and the DR(Dead Reckoning) algorithm using the in-vehicle sensor, are used for the purpose of preventing degradation of accuracy of the GPS and to measure the position in the shadow area. However, these positioning methods have many elements of problems due not only to the existence of various shaded areas such as building areas that are continually enlarged, tunnels, underground parking lots and but also to the limitations of accumulation-based location estimation methods that increase in error over time. In this paper, an efficient positioning method in a large underground parking space using Fingerprint method is proposed by placing the AP(Access Points) and directional antennas in the form of four anchors using WLAN, a popular means of wireless communication, for positioning the vehicle in the GPS shadow area. The proposed method is proved to be able to produce unchanged positioning results even in an environment where parked vehicles are moved as time passes.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.1
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• pp.470-477
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• 2013

The aim of this study is to suggest a detection method of water surface location and its evaluation results of application for same vertical position in two successive images with time interval including both staff gauge and water surface. A specific rectangular inspection area is defined from the top of watermark and then the correlation coefficients for the inspection area of the same position of two images with short time interval is calculated. Accordingly, it is possible to identify differences between changing area and fixed area of pixel density by the water flow. The photographs taken in the laboratory were analyzed in order to validate the proposed technique. As the result of the experiment, it is identified that characteristic of correlation coefficients depends on the size of the inspection area. In the case that the inspection area is within the entire width of the watermark, water surface characteristic according to correlation coefficients is clearly noticeable. Thus, it is identified that the proposed technique can be utilized to search water surfaces. Besides, using corelation analysis of two images with time interval, it is identified that error range between 10 and 42cm was reduced in the level of 2.6cm or less in the contaminated photo of existing image stage gauge. Therefore, it is expected that the suggested method can be utilized to enhance image stage gauge performance improving the previous water surface detection method.

• The Journal of the Convergence on Culture Technology
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• v.8 no.1
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• pp.227-238
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• 2022

This study is the case of non-face-to-face teaching-learning in the subject of "Research and Guidance on Early Childhood Materials" in the pre-child teacher training program. The study conducted a non-face-to-face teaching-learning model for 18 students at B University in region C who took lectures on 'Research and Guidance on Early Childhood Materials' in the first semester of 2021. As a non-face-to-face teaching-learning model, it consisted of video lectures, real-time zoom classes, and various forms of 'communication' through frequent feedback and interaction and 'participation'. As a teaching-learning strategy for the participation of pre-service early childhood teachers, comment on questions related to early childhood materials, in-depth reflection on early childhood materials through writing reflective journals and observation reports, and step-by-step presentation of making childhood materials plans, processes, and results were carried out. As a result of exploring the experience of making early childhood materials for pre-service early childhood teachers, factors such as "growth experience through trial and error," "thinking from child's point of view", "Increase efficiency and reduce burden through communication", "Process rather than result" and "The importance of communication and interaction in non-face-to-face classes"

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.34 no.4
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• pp.109-118
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• 2022

The data of the missing section among the vertex surface sea temperature observation data was imputed using the Bidirectional Recurrent Neural Network(BiRNN). Among artificial intelligence techniques, Recurrent Neural Networks (RNNs), which are commonly used for time series data, only estimate in the direction of time flow or in the reverse direction to the missing estimation position, so the estimation performance is poor in the long-term missing section. On the other hand, in this study, estimation performance can be improved even for long-term missing data by estimating in both directions before and after the missing section. Also, by using all available data around the observation point (sea surface temperature, temperature, wind field, atmospheric pressure, humidity), the imputation performance was further improved by estimating the imputation data from these correlations together. For performance verification, a statistical model, Multivariate Imputation by Chained Equations (MICE), a machine learning-based Random Forest model, and an RNN model using Long Short-Term Memory (LSTM) were compared. For imputation of long-term missing for 7 days, the average accuracy of the BiRNN/statistical models is 70.8%/61.2%, respectively, and the average error is 0.28 degrees/0.44 degrees, respectively, so the BiRNN model performs better than other models. By applying a temporal decay factor representing the missing pattern, it is judged that the BiRNN technique has better imputation performance than the existing method as the missing section becomes longer.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.11-17
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• 2022

In this paper, a model that can increase the efficiency of work in arranging interior furniture by applying augmented reality technology was studied. In the existing system to which augmented reality is currently applied, there is a problem in that information is limitedly provided depending on the size and nature of the company's product when outputting the image of furniture. To solve this problem, this paper presents an AR labeling algorithm. The AR labeling algorithm extracts feature points from the captured images and builds a database including indoor location information. A method of detecting and learning the location data of furniture in an indoor space was adopted using the CNN technique. Through the learned result, it is confirmed that the error between the indoor location and the location shown by learning can be significantly reduced. In addition, a study was conducted to allow users to easily place desired furniture through augmented reality by receiving detailed information about furniture along with accurate image extraction of furniture. As a result of the study, the accuracy and loss rate of the model were found to be 99% and 0.026, indicating the significance of this study by securing reliability. The results of this study are expected to satisfy consumers' satisfaction and purchase desires by accurately arranging desired furniture indoors through the design and implementation of AR labels.