• KSCE Journal of Civil and Environmental Engineering Research
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• v.38 no.6
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• pp.793-800
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• 2018

It is necessary to determine an optimal design frequency for establishing stable flood control against frequent flood disasters. Depending on the importance of river and regional characteristics, design return periods are suggested from at least 50 years up to 200 years for river design. However, due to the wide range of applications, it is not desirable to reflect the geographical and flood control characteristics of river. In this study, Bayes theory was applied to seven evaluation factors to determine the optimal design return period of rivers in Chungcheongnam-do; urbanization flooded area, watershed area, basin coefficient, slope, water system and stream order, range of backwater effect, abnormal rainfall occurrence frequency. The potential flood damage (PFD) capacity was estimated considering climate change and the appropriate design return period was determined by analyzing the capacity of each district. We compared the design return periods of 382 rivers in Chungcheongnam-do with the existing design return periods. The number of rivers that were upgraded from the existing return period were 65, which have relatively large flooding areas and have large PFDs. Whereas, the number of rivers that were downgraded were 169.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.18 no.5
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• pp.126-141
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• 2019

One of the Cooperative Intelligent Transportation System(C-ITS) priority services is collision prevention support service. Several studies have considered V2I2V communication-based collision prevention support services using Artificial Neural Networks(ANN). However, such services still show some issues due to a low penetration of C-ITS devices and large delay, particularly when loading massive traffic data into the server in the C-ITS center. This study proposes the Artificial Neural Network-based Collision Warning Service(ACWS), which allows upstream vehicle to update pre-determined weights involved in the ANN by using real-time sectional traffic information. This research evaluates the proposed service with respect to various penetration rates and delays. The evaluation result shows the performance of the ACWS increases as the penetration rate of the C-ITS devices in the vehicles increases or the delay decreases. Furthermore, it reveals a better performance is observed in more advanced ANN model-based ACWS for any given set of conditions.

• Journal of Korean Society of Forest Science
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• v.100 no.4
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• pp.664-671
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• 2011

Random Walk Model can predict the sediment areas of debris flow but it must be extracted three parameters fitted topographical environment. This study developed the method to extract the optimal values of three parameters - Once flowing volume, Stopping slope and Gravity weight - for Random Walk Model. And the extracted parameters were validated by aerial photographs of the debris flowed area. To extract the optimal parameters was randomly performed, limiting the range values of three parameters and developing an accuracy decision method that is called the rate of concordance. The set of the optimal parameters was decided on highest the rate of concordance and a consistency. As a result, the optimal parameters in Bonghwa county were showed that the once flowing volume is $1.0m^3$, the stopping slope is $4.2^{\circ}$ and the gravity weight is 2 when the rate of concordance is -0.2. The validating result of the optimal parameters showed closely that the rate of concordance is average -0.2.

• Journal of Digital Convergence
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• v.18 no.12
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• pp.87-95
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• 2020

The Incheon airport is a gateway to and from the Republic of Korea and has a great influence on the image of the country. Therefore, it is necessary to predict the number of airport passengers in the long term in order to maintain the quality of service at the airport. In this study, we compared the predictive performance of various time series models to predict the air passenger demand at Incheon Airport. From 2002 to 2019, passenger data include trend and seasonality. We considered the naive method, decomposition method, exponential smoothing method, SARIMA, PROPHET. In order to compare the capacity and number of passengers at Incheon Airport in the future, the short-term, mid-term, and long-term was forecasted by time series models. For the short-term forecast, the exponential smoothing model, which weighted the recent data, was excellent, and the number of annual users in 2020 will be about 73.5 million. For the medium-term forecast, the SARIMA model considering stationarity was excellent, and the annual number of air passengers in 2022 will be around 79.8 million. The PROPHET model was excellent for long-term prediction and the annual number of passengers is expected to be about 99.0 million in 2024.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.671-678
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• 2021

In a previous study, technology protection levels were set on a qualitative basis. That study lacked quantitative standards, so here, we conduct a study to complement the previous study and to present an objective standard. This paper provides a method of setting a technical protection level that applies statistical analysis. To set the technology protection level, statistical analysis of six technical survey items is performed first. Second, the technical survey items are analyzed by AHP to quantify the opinions of experts in order to derive weights for each technical survey item. Finally, by using the normal distribution scatter map and median calculation method, the technology protection level is selected in three stages using the final detailed factor technology score reflecting the weight. The technology protection level methodology developed through this study is the first methodology with objectivity that can evaluate defense technology by level. If this methodology is applied in practice, it is believed that it will provide a scientific and quantitative technology value judgment criterion when setting the technology protection level in the future.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.4
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• pp.542-548
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• 2022

In order to reduce marine accidents, each contracting Government needs to implement the instruments enacted and amended by the International Maritime Organization (IMO). The III Code requires each administration of the government to have a system for improvement through periodic review and evaluation and to include performance indicators in its evaluation methods. Thus, each IMO Member State needs to develop its own performance indicators. The purpose of this paper is to develop and present an evaluation model using the Balanced Scorecard (BSC) and Key Performance Indicators (KPI) in order to quantify and evaluate the level of implementation of the instruments by the administrations. From the perspective of 'III-BSC', which applies the BSC concept to the III code requirements, the Critical Success Factors (CSF) that must be secured to achieve the established vision were drawn up, and candidate KPIs for each evaluation area were developed to measure the derived key success factors and an initial study model was designed composed of four levels. The validity of the KPIs was verified and the study model was finalized using the survey design using the SMART technique. Furthermore, based on the developed study model, an evaluation model for the implementation of the BSC-based IMO instruments was developed by deriving the weights of elements for each level through AHP analysis. The developed evaluation model is expected to contribute toward improving the administrations' level of implementation of the IMO instruments as a tool for quantitatively grasping the level of performance of the implementation.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.83-101
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• 2021

This study is to investigate, using AHP, what technologies should be applied first to Korean SMEs in order to respond to the 4th industrial revolution and change to a smart enterprise. To this end, technologies related to the 4th industrial revolution and smart factory are synthesized, and the classification criteria of Dae-Hoon Kim et al. (2019) are applied, but additional opinions of experts are collected and related technologies are converted to artificial intelligence (AI), Big Data, and Cloud Computing. As a base technology, mobile, Internet of Things (IoT), block chain as hyper-connected technology, unmanned transportation (autonomous driving), robot, 3D printing, drone as a convergence technology, smart manufacturing and logistics, smart healthcare, smart transportation and smart finance were classified as smart industrial technologies. As a result of confirming the priorities for technical use by AHP analysis and calculating the total weight, manufacturing companies have a high ranking in mobile, artificial intelligence (AI), big data, and robots, while service companies are in big data and robots, artificial intelligence (AI), and smart healthcare are ranked high, and in all companies, it is in the order of big data, artificial intelligence (AI), robot, and mobile. Through this study, it was clearly identified which technologies should be applied first in order to respond to the 4th industrial revolution and change to a smart company.

• Journal of the Korea Organic Resources Recycling Association
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• v.30 no.2
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• pp.29-42
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• 2022

The government promotes the 2050 carbon-neutral policy. Therefore, the concern to convert livestock manure into energy is increasing for the reduction of greenhouse gases generated in the livestock industry sector. In this study, the economic feasibility of the livestock manure solid fuel power generation facility, which is a major consumer of livestock manure solid fuel, was assessed to expand the demand for livestock manure solid fuel. The production cost of livestock manure solid fuel showed the lowest production cost of 97.4 thousand won/ton when dried using solid fuel at a 200 ton/day scale bio-drying facility. The livestock manure solid fuel power generation facility showed economic feasibility at a REC weight of 1.5 in the case of the bio-drying facility, so it was necessary to set a REC weight of 1.5 or more to expand the demand for livestock manure solid fuel. The conversion of livestock manure into solid fuel has various environmental benefits, such as the reduction of greenhouse gases and the effect of reducing non-point pollutants in the water system. Therefore, in order to expand livestock manure solid fuel production facility, it was required to review the feasibility including various environmental benefits.

• Smart Media Journal
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• v.11 no.10
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• pp.65-75
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• 2022

Deep learning is used as a creative tool that could overcome the limitations of existing analysis models and generate various types of results such as text, image, and music. In this paper, we propose a method necessary to preprocess audio data using the Niko's MIDI Pack sound source file as a data set and to generate music using Bi-LSTM. Based on the generated root note, the hidden layers are composed of multi-layers to create a new note suitable for the musical composition, and an attention mechanism is applied to the output gate of the decoder to apply the weight of the factors that affect the data input from the encoder. Setting variables such as loss function and optimization method are applied as parameters for improving the LSTM model. The proposed model is a multi-channel Bi-LSTM with attention that applies notes pitch generated from separating treble clef and bass clef, length of notes, rests, length of rests, and chords to improve the efficiency and prediction of MIDI deep learning process. The results of the learning generate a sound that matches the development of music scale distinct from noise, and we are aiming to contribute to generating a harmonistic stable music.

• Journal of the Korea institute for structural maintenance and inspection
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• v.27 no.3
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• pp.1-11
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• 2023

After the collapse of the Seongsu Bridge in the 1990s in Korea, attention was focused on the maintenance of facilities. The government has established various policies since the enactment of the Act in 1995 until recently. In general, safety inspections are performed to evaluate the safety grade of facilities, and facilities are maintained and managed by performing repairs and reinforcements for defects. However, since the budget is limited, it is impossible to carry out repair and reinforcement projects for all defects. It is necessary to prioritize repair and reinforcement measures. Then, the priority index (PI) is presented considering the importance of members, the seriousness of defects, and economic feasibility. In this index, the degree of influence can be adjusted within the range of 50 to 100% according to the expert's subjective judgment, and the same weight is set for some specific members. Also, the effect through repair and reinforcement is not taken into account decisively, and most of them have a limit in which priority is determined by economic feasibility. Therefore, in this study, through several case studies, problems with the priority index were reviewed and an equation was presented to improve them.