• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.209-218
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• 2021

First principle-based modeling studies have been performed to improve the heat exchange efficiency of ORV and optimize operation, but the heat transfer coefficient of ORV is an irregular system according to time and location, and it undergoes a complex modeling process. In this study, FNN, LSTM, and AutoML-based modeling were performed to confirm the effectiveness of data-based modeling for complex systems. The prediction accuracy indicated high performance in the order of LSTM > AutoML > FNN in MSE. The performance of AutoML, an automatic design method for machine learning models, was superior to developed FNN, and the total time required for model development was 1/15 compared to LSTM, showing the possibility of using AutoML. The prediction of NG and seawater discharged temperatures using LSTM and AutoML showed an error of less than 0.5K. Using the predictive model, real-time optimization of the amount of LNG vaporized that can be processed using ORV in winter is performed, confirming that up to 23.5% of LNG can be additionally processed, and an ORV optimal operation guideline based on the developed dynamic prediction model was presented.

• 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 Society of Disaster Information
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• v.18 no.1
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• pp.146-153
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• 2022

Purpose: In the case of domestic port facilities, port structures that have been in use for a long time have many problems in terms of safety performance and functionality due to the enlargement of ships, increased frequency of use, and the effects of natural disasters due to climate change. A big data analysis method was studied to develop an approximate model that can predict the aging pattern of a port facility based on the maintenance history data of the port facility. Method: In this study, member-level maintenance history data for caisson-type quay walls were collected, defined as big data, and based on the data, a predictive approximation model was derived to estimate the aging pattern and deterioration of the facility at the project level. A state-based aging pattern prediction model generated through Gaussian process (GP) and linear interpolation (SLPT) techniques was proposed, and models suitable for big data utilization were compared and proposed through validation. Result: As a result of examining the suitability of the proposed method, the SLPT method has RMSE of 0.9215 and 0.0648, and the predictive model applied with the SLPT method is considered suitable. Conclusion: Through this study, it is expected that the study of predicting performance degradation of big data-based facilities will become an important system in decision-making regarding maintenance.

• Journal of the Korea Institute of Building Construction
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• v.23 no.4
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• pp.417-428
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• 2023

The demolition of domestic infrastructures mirrors other significant construction initiatives in presenting a markedly high accident rate. A comprehensive investigation into the origins of such accidents is crucial for the prevention of future incidents. Upon detailed inspection, the causes of demolition construction accidents are multifarious, encompassing unsafe worker behavior, hazardous conditions, psychological and physical states, and site management deficiencies. While statistics relating to demolition construction accidents are consistently collated and reported, there exists an exigent need for a more foundational cause categorization system based on accident type. Drawing from Heinrich's Domino Theory, this study classifies the origins of accidents(unsafe behavior, unsafe conditions) and human errors(human factors) as per the type of accidents experienced during demolition construction. In this study, a three-step model of QFD-FMEA(Quality Function Deployment - Failure Mode Effect Analysis) is employed to systematically categorize accident causes according to the types of accidents that occur during demolition construction. The QFD-FMEA method offers a technique for cause classification at each stage of the demolition process, including direct causes(unsafe behavior, unsafe environment), and human errors(human factors) through a tri-stage process. The results of this accident cause classification can serve as safety knowledge and reference checklists for accident prevention efforts.

• Korean Security Journal
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• no.59
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• pp.37-69
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• 2019

According to viewpoints of researchers and stakeholders, various opinions can be suggested on self-governing police system. Therefore, success of Korean self-governing police system will be defending on how to balance among conflicting values such as Empowerment, Political neutrality, Financial issues, Comprehensive competence in maintaining public safety. Before the launching of self-governing police system nation-wide, the experience of Jeju provincial police will be valuable model case. In specific, enlargement of work scope of self-governing police in Jeju province which has been introduced since last year will be a useful reference. There is more pessimism about self-governing police of Jeju province so far. However, this perspective is mostly based on the issue regarding hardwares such as manpower, equipment, law and organization. Issues regarding softwares such as organizational culture, operation system and work process need more attention to evaluate self-governing police system properly. To mark the first year after enlargement of work scope of Jeju police, this study demonstrate the overall result and implications of self-governing police of Jeju province based on documents, statistics, reports and media reports. In result, several preconditions are needed to implement the self-governing police system nation-wide successfully. 1. Strengthen the link between local government and local police 2. Establish the foundation for collaboration of state and local police 3. Enhance the aspect of citizen autonomy in local level 4. Reinforcing the capability of handling situation of state and local police 5. Invigorating the inter-organizational working group to operate self-governing police system effectively. The self-governing police system is unclosed topic to discuss. After this study, in-depth studies should be followed with more resources. Particularly, additional perspective including redundancy and equity need to be considered regarding self-governing police. By getting with the changes of macroscopic trends - lowbirth and aging, the fourth industrial revolution and possible reunification of north and south Koreas - these studies should suggest the long-term blueprint of self-governing police system of Korea.

• Journal of Astronomy and Space Sciences
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• v.22 no.3
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• pp.329-352
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• 2005

Long term observations of full-disk Lyman-o irradiance have been made by the instruments on various satellites. In addition, several sounding rockets dating back to the 1950s and up through the present have measured the $Lyman-{\alpha}$ irradiance. Previous full disk $Lyman-{\alpha}$ images of the sun have been very interesting and useful scientifically, but have been only five-minute 'snapshots' obtained on sounding rocket flights. All of these observations to date have been snapshots, with no time resolution to observe changes in the chromospheric structure as a result of the evolving magnetic field, and its effect on the Lyman-o intensity. The $Lyman-{\alpha}$ Imaging Solar Telescope(LIST) can provide a unique opportunity for the study of the sun in the $Lyman-{\alpha}$ region with the high time and spatial resolution for the first time. Up to the 2nd year development, the preliminary design of the optics, mechanical structure and electronics system has been completed. Also the mechanical structure analysis, thermal analysis were performed and the material for the structure was chosen as a result of these analyses. And the test plan and the verification matrix were decided. The operation systems, technical and scientific operation, were studied and finally decided. Those are the technical operation, mechanical working modes for the observation and safety, the scientific operation and the process of the acquired data. The basic techniques acquired through the development of satellite based solar telescope are essential for the construction of space environment forecast system in the future. The techniques which we developed through this study, like mechanical, optical and data processing techniques, could be applied extensively not only to the process of the future production of flight models of this kind, but also to the related industries. Also, we can utilize the scientific achievements which are obtained throughout the project And these can be utilized to build a high resolution photometric detectors for military and commercial purposes. It is also believed that we will be able to apply several acquired techniques for the development of the Korean satellite projects in the future.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.32 no.1
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• pp.65-73
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• 2019

In order to increase the production efficiency of the ship and shorten the production cycle, it is important to evaluate the accuracy of the ship components efficiently during the drying cycle. The accuracy control of the block is important for shortening the ship process, reducing the cost, and improving the accuracy of the ship. Some systems have been developed and used mainly in large shipyards, but in some cases, they are measured and managed using conventional measuring instruments such as tape measure and beam, optical instruments as optical equipment, In order to perform accuracy control, these tools and equipment as well as equipment for recording measurement data and paper drawings for measuring the measurement position are inevitably combined. The measured results are managed by the accuracy control system through manual input or recording device. In this case, the measurement result is influenced by the work environment and the skill level of the worker. Also, in the measurement result management side, there are a human error about the lack of the measurement result creation, the lack of the management sheet management, And costs are lost in terms of efficiency due to consumption. The purpose of this study is to improve the working environment in the existing accuracy management process by using the augmented reality technology to visualize the measurement information on the actual block and to obtain the measurement information And a smart management system based on augmented reality that can effectively manage the accuracy management data through interworking with measurement equipment. We confirmed the applicability of the proposed system to the accuracy control through the prototype implementation.

• Food Science and Industry
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• v.55 no.2
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• pp.188-202
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• 2022

In the insect industry, as the scope of application of insects is expanded from pet insects and natural enemies to feed, edible and medicinal insects, the demand for quality control of insect raw materials is increasing, and interest in securing the safety of insect products is increasing. In the process of expanding the industrial scale, controlling the temperature and humidity and air quality in the insect breeding room and preventing the spread of pathogens and other pollutants are important success factors. It requires a controlled environment under the operating system. European commercial insect breeding facilities have attracted considerable investor interest, and insect companies are building large-scale production facilities, which became possible after the EU approved the use of insect protein as feedstock for fish farming in July 2017. Other fields, such as food and medicine, have also accelerated the application of cutting-edge technology. In the future, the global insect industry will purchase eggs or small larvae from suppliers and a system that focuses on the larval fattening, i.e., production raw material, until the insects mature, and a system that handles the entire production process from egg laying, harvesting, and initial pre-treatment of larvae., increasingly subdivided into large-scale production systems that cover all stages of insect larvae production and further processing steps such as milling, fat removal and protein or fat fractionation. In Korea, research and development of insect smart factory farms using artificial intelligence and ICT is accelerating, so insects can be used as carbon-free materials in secondary industries such as natural plastics or natural molding materials as well as existing feed and food. A Korean-style customized breeding system for shortening the breeding period or enhancing functionality is expected to be developed soon.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.7
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• pp.846-853
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• 2016

This study prioritizes Noxious Liquid Substances (NLS) transported by sea via a risk-based database containing 596 chemicals to prepare against NLS incidents. There were 158 chemicals transported in Korean waters during 2014 and 2015, which were prioritized, and then chemicals were grouped into four categories (with rankings of 0-3) based on measures for preparedness against incident. In order to establish an effective preparedness system against NLS spill incidents on a national scale, a compiling process for NLS chemicals ranked 2~3 should be carried out and managed together with an initiative for NLS chemicals ranked 0-1. Also, it is advisable to manage NLS chemicals ranked 0-1 after considering the characteristics of NLS specifically transported through a given port since the types and characteristics of NLS chemicals relevant differ depending on the port. In addition, three designated regions are suggested: 1) the southern sector of the East Sea (Ulsan and Busan); 2) the central sector of the South Sea (Gwangyang and Yeosu); and 3) the northern sector of the West Sea (Pyeongtaek, Daesan and Incheon). These regions should be considered special management sectors, with strengthened surveillance and the equipment, materials and chemicals used for pollution response management schemes prepared in advance at NLS spill incident response facilities. In the near future, the risk database should be supplemented with specific information on chronic toxicity and updated on a regular basis. Furthermore, scientific ecotoxicological data for marine organisms should be collated and expanded in a systematic way. A system allowing for the identification Hazardous and Noxious Substances (HNS) should also be established, noting the relevant volumes transported in Korean waters as soon as possible to allow for better management of HNS spill incidents at sea.

• Journal of Internet Computing and Services
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• v.14 no.1
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• pp.15-22
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• 2013

WAVE(Wireless Access for Vehicular Environment) is new concepts and Vehicles communications technology using for ITS(Intelligent Transportation Systems) service by IEEE standard 802.11p. Also it increases the efficiency and safety of the traffic on the road. However, the efficiency of Scrambler bit computational algorithms of OFDM modulation in WAVE systems will fall as it is not able to process in parallel in terms of hardware and software. This paper proposes an algorithm to configure 64-bits matrix table in scambler bit computation as well as an algorithm to compute 64-bits matrix table and input data in parallel. The proposed algorithm on this thesis is executed using 64-bits matrix table. In the result, the processing speed for 1 and 1000 times is improved about 40.08% ~ 40.27% and processing rate per sec is performed more than 468.35 compared to bit operation scramble. And processing speed for 1 and 1000 times is improved about 7.53% ~ 7.84% and processing rate per sec is performed more than 91.44 compared to 32-bits operation scramble. Therefore, if the 64 bit-CPU is used for 64-bits executable scramble algorithm, it is improved more than 40% compare to 32-bits scrambler.