• Journal of the Korean Society of Marine Environment & Safety
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• v.21 no.6
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• pp.689-695
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• 2015

The offshore plant crews that were commissioned in the commercial startup phase boarded the offshore plant in two shifts until the end of the project. The crews who were hired by the owner side stayed in the original offshore plant during the project. However, most of the offshore plant commissioned members who were dispatched from the shipyard were accommodated in the offshore accommodation barge. For this reason, they were exposed to many accidents since there are a lot of people staying in a small space. This study suggested a method for improving survival rate at offshore accommodation barge in terms of life safety. It is assumed that the fire accident among unfortunate events which take place in the offshore accommodation barge mainly occurred. So, this study analyzed the safety evacuation for offshore plant employees using fire simulation model based on both domestic and international law criteria. In particular, When fire occurs in the offshore accommodation barge, the periodically well trained crews are followed safety evacuation procedure. whereas many employees who have different background such as various occupations, cultural differences, races and nationality can be commissioned with improper evacuation behaviors. As a result, the risk will be greater than normal situation due to these inappropriate behaviors. Therefore, This study analyzed the Required Safe Escape Time (RSET) and Available Safe Escape Time (ASET). Also it was suggested the improvement of structure design and additional arrangement of safety equipment to improve the survival rate of the residents in offshore accommodation barge.

• Journal of the Korea Society of Computer and Information
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• v.25 no.6
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• pp.109-117
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• 2020

An edutainment system aims to help learners to recognize problems effectively, grasp and classify important information needed to solve the problems and convey the contents of what they have learned. Edutainment contents can be usefully applied to education and training in the both scientific and industrial areas. Our present work proposes an edutainment system that can be applied to a drug discovery process including virtual screening by using intuitive multi-modal interfaces. In this system, a stereoscopic monitor is used to make three-dimensional (3D) macro-molecular images, with supporting multi-modal interfaces to manipulate 3D models of molecular structures effectively. In this paper, our system can easily solve a docking simulation function, which is one of important virtual drug screening methods, by applying gaming factors. The level-up concept is implemented to realize a bio-game approach, in which the gaming factor depends on number of objects and users. The quality of the proposed system is evaluated with performance comparison in terms of a finishing time of a drug docking process to screen new inhibitors against target proteins of human immunodeficiency virus (HIV) in an e-drug discovery process.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.37 no.1
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• pp.68-75
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• 2019

This study aims to look at the application methods of landscape architecture in response to the 4th Industrial Revolution. The results of the analysis of trends in the 4th Industrial Revolution and the subsequent search for application methods to the field of landscape architecture are as follows. First, the 4th Industrial Revolution means innovative change based on digital technology and seeks to create value based on intelligent information technology, and continuous growth is being made through innovation. This requires expertise to collect large amounts of information and creatively rework it, and a strategy to flexibly cope with changes in the times. Second, the status of technological use in response to the 4th Industrial Revolution in the field of landscape architecture is generalizing the establishment of precise analysis results such as survey technology and global mapping using drones, three-dimensional design simulation, and VR. In the field of traditional landscape architecture, efforts are made to obtain accurate fact-finding data on landscape site components. Third, the application methods in the field of landscape science according to the 4th Industrial Revolution in the future are required to supply precision technology and supply programs in the technology sector, and to provide a shared platform. In addition, a systemically standardized process will need to be established for this. In addition, educational efforts should be continued to professional manpower training and provide economic support for the development of technologies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.65-73
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• 2021

This study aimed to provide the basic data for the development of a simulation training program for new infectious diseases by analyzing the knowledge and educational needs of 119 paramedics regarding COVID-19 infection control. Data was obtained through a structured questionnaire survey of 186 paramedics from November 15th to 30th 2020. The study showed that 98 of the 119 paramedic subjects (52.7%) had not been educated regarding COVID-19. The knowledge level was 18.21±1.98 out of 25 points, with environmental control securing the lowest correct answers. The highest need for education was in the areas of prevention of transmission and spread, and employee safety control. The total average for educational needs was 3.81±.28 (4 point scale) with the highest educational need in the area of prevention of the spread and dispersion of the disease and employee safety management. There was a statistically significant difference in the knowledge of the general characteristics according to gender (t=-1.999, p=.047) and the educational demand was related to career (t=-1.999, p=.047) and, education levels (t=2.336, p=.021). Accordingly, it is necessary to plan a new infectious disease simulation education program that addresses the low-scoring areas and items with high educational needs which include the propagation path and spread prevention, environmental management, and employee safety management as per the findings of this study.

• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.488-498
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• 2021

This study applied Flipped Learning teaching and learning method to Basics Cooking Practice Subject using YouTube. The purpose of this study is to investigate whether the curriculum is properly progressing by grasping the effects of before and after learning and analyzing learners' subjectivity through the learning process. The investigation period was conducted from August 01, 2020 to September 10, 2020. According to the research design of Q Methodology, it was divided into five stages: Q sample selection, P sample selection, Q sorting, coding and recruiting, conclusion and discussion. As a result of the analysis, the first type (N=5): Prior Learning effect, the second type (N=7): Simulation practice effect, and the third type (N=3): self-efficacy effect. As a result, by applying the flipped learning teaching method of the Basics Cooking Practice Subject using YouTube, positive effects such as inducing interest in the class and increasing confidence were found in active learners, but some learners lacked understanding of the system of the class operation method. However, the lack of number of training sessions compared to other subjects is considered to be a solution to be solved later.

• The Journal of the Convergence on Culture Technology
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• v.7 no.3
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• pp.509-515
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• 2021

This study analyzes the efficient floor layout plan of classrooms for securing evacuation stability in school in case of fire by using the Pathfinder simulation program. Efficient evacuation methods and safety were evaluated by analyzing REST (Required Safe Egress Time) according to the allocation of personnel by floor targeting a high school 5-story building equipped with a ramp and stairs. The current status of personnel assignments exceeded the Required Safe Egress Time(RSET), resulting in a problem with evacuation safety. When students were placed on the 3rd, 4th, and 5th floors, the result was that the time exceeded RSET the most. When students were placed on the 1st, 2nd, and 3rd floors, the result was that they completed evacuation in the shortest time, less than RSET. In the current state, when evacuation was guided by designating an evacuation exit depending on the location, the result of shortening RSET was obtained. As a result, it is effective to put the students on the lower floors when placing students in high-rise school buildings in terms of evacuation safety, and in the preliminary training, it is required to designate evacuation exits so that they can use the nearest exit for each location in case of a fire. As a future research project, additional research is needed on the RSET when a fire occurs in a specific location according to whether the automatic fire door at that location is opened or closed.

• Journal of the Korea Society for Simulation
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• v.31 no.1
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• pp.11-18
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• 2022

Recently, research to classify human activity using imagery has been actively conducted for the purpose of crime prevention and facility safety in public places and facilities. In order to improve the performance of human activity classification, most studies have applied deep learning based-transfer learning. However, despite the increase in the number of backbone network models that are the basis of deep learning as well as the diversification of architectures, research on finding a backbone network model suitable for the purpose of operation is insufficient due to the atmosphere of using a certain model. Thus, this study applies the transfer learning into recently developed deep learning backborn network models to build an intelligent system that classifies human activity using imagery. For this, 12 types of active and high-contact human activities based on sports, not basic human behaviors, were determined and 7,200 images were collected. After 20 epochs of transfer learning were equally applied to five backbone network models, we quantitatively analyzed them to find the best backbone network model for human activity classification in terms of learning process and resultant performance. As a result, XceptionNet model demonstrated 0.99 and 0.91 in training and validation accuracy, 0.96 and 0.91 in Top 2 accuracy and average precision, 1,566 sec in train process time and 260.4MB in model memory size. It was confirmed that the performance of XceptionNet was higher than that of other models.

• Journal of the Korean Society of Radiology
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• v.16 no.6
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• pp.697-702
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• 2022

For imaging in positron emission tomography(PET), it is necessary to measure the position of the scintillation pixel interacting with the gamma rays incident on the detector. To this end, in the conventional system, a flood image of the scintillation pixel is obtained, the imaged area of each scintillation pixel is separated, and the position of the scintillation pixel is specified and acquired as a digital signal. In this study, a deep learning method was applied based on the signal formed by the photosensor of the detector, and a method was developed to directly acquire a digital signal without going through various procedures. DETECT2000 simulation was performed to verify this and evaluate the accuracy of position measurement. A detector was constructed using a 6 × 6 scintillation pixel array and a 4 × 4 photosensor, and a gamma ray event was generated at the center of the scintillation pixel and summed into four channels of signals through the Anger equation. After training the deep learning model using the acquired signal, the positions of gamma-ray events that occurred in different depth directions of the scintillation pixel were measured. The results showed accurate results at every scintillation pixel and position. When the method developed in this study is applied to the PET detector, it will be possible to measure the position of the scintillation pixel with a digital signal more conveniently.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.6
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• pp.124-131
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• 2017

Recently, drone is extending its range of usability. For example, the delivery, agriculture, industry, and entertainment area take advantage of drone mobilities. To control real drones, it needs huge amount of drone control training steps. However, it is risky; falling down, missing, destroying. The virtual drone system can avoid such risks. We reason that what kinds of technologies are required for building the virtual drone system. First, it needs that the virtual drone authoring tool that can assemble drones with the physical restriction in the virtual environment. We suggest that the drone assembly method that can fulfill physical restrictions in the virtual environment. Next, we introduce the virtual drone simulator that can simulate the assembled drone moves physically right in the virtual environment. The simulator produces a high quality rendering results more than 60 frames per second. In addition, we develop the physics engine based on SILS(Software in the loop simulation) framework to perform more realistic drone movement. Last, we suggest the virtual drone controller that can interact with real drone controllers which are commonly used to control real drones. Our virtual drone system earns 7.64/10.0 user satisfaction points on human test: the test is done by one hundred persons.

• Journal of KIISE:Computing Practices and Letters
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• v.9 no.3
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• pp.322-331
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• 2003

As the complexity of a 3D game is increased by various factors of the game scenario, it has a problem for controlling the interrelation of the game objects. Therefore, a game system has a necessity of the coordination of the responses of the game objects. Also, it is necessary to control the behaviors of animations of the game objects in terms of the game scenario. To produce realistic game simulations, a system has to include a structure for designing the interactions among the game objects. This paper presents a method that designs the dynamic control mechanism for the interaction of the game objects in the game scenario. For the method, we suggest a game agent system as a framework that is based on intelligent agents who can make decisions using specific rules. Game agent systems are used in order to manage environment data, to simulate the game objects, to control interactions among game objects, and to support visual authoring interface that ran define a various interrelations of the game objects. These techniques can process the autonomy level of the game objects and the associated collision avoidance method, etc. Also, it is possible to make the coherent decision-making ability of the game objects about a change of the scene. In this paper, the rule-based behavior control was designed to guide the simulation of the game objects. The rules are pre-defined by the user using visual interface for designing their interaction. The Agent State Decision Network, which is composed of the visual elements, is able to pass the information and infers the current state of the game objects. All of such methods can monitor and check a variation of motion state between game objects in real time. Finally, we present a validation of the control method together with a simple case-study example. In this paper, we design and implement the supervised classification systems for high resolution satellite images. The systems support various interfaces and statistical data of training samples so that we can select the most effective training data. In addition, the efficient extension of new classification algorithms and satellite image formats are applied easily through the modularized systems. The classifiers are considered the characteristics of spectral bands from the selected training data. They provide various supervised classification algorithms which include Parallelepiped, Minimum distance, Mahalanobis distance, Maximum likelihood and Fuzzy theory. We used IKONOS images for the input and verified the systems for the classification of high resolution satellite images.