• Journal of Korea Port Economic Association
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• v.34 no.3
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• pp.133-158
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• 2018

The role and ratio of national vessels in the global container shipping market have reduced significantly due to the bankruptcy of Hanjin Shipping in early 2017. All import-export companies, as well as container ports in Korea, are facing a crisis. The Trump's tariff and trade battles have had a negative impact on the increase in the North American cargo. However, Chinese and Japanese container shipping companies, which merged with domestic container shipping companies, and mega carriers such as Maersk and CMA CGM have benefited from the decline in shipping supplies due to the collapse of Hanjin Shipping, the world's 10th largest container carrier in Korea. The import/export freight trade in Korea is witnessing the increasing stronghold of foreign carriers. This scenario is expected to weaken Korea's negotiation powers with overseas shipping companies in domestic ports, such as Busan and Kwangyang, thereby making it more challenging to attract shipping carriers. This study compares the global container-shipping network in 2007 and 2017 by combining the network topology of the social network analysis and the economics of the liner shipping connectivity index (LSCI) and the container port connectivity index (CPCI) analysis. The findings of this study are that the role of the ports across the world can be identified, and CPCI has a high correlation with the centrality index and freight volume data. These findings can contribute toward the utilization of the meaning of the necessary centrality index without an additional centrality analysis. This study can be applied not only to the call strategy of container carriers but also to the alliance and development strategy of Korean ports.

• Journal of the Korean Society of Marine Environment & Safety
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• v.23 no.6
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• pp.739-745
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• 2017

Many studies have been conducted to reduce environmental pollution by ships and reduce fuel consumption. As part of this effort, research on power conversion systems through DC distribution systems that link renewable energy with conventional power grids has been pursued as well. The diode rectifiers currently used include many lower harmonics in the input current of the load and distort supply voltage to lower the power quality of the whole system. This distortion of voltage waveforms causes the malfunctions of generators, load devices and inverter pole switching elements, resulting in a large number of switching losses. In this paper, a controller is presented to improve DC output waveforms, the input Power Factor and the THD of an AFE type PWM rectifier used for PLL. DC output voltage waveforms have been improved, and the input Power Factor can now be matched to the unit power factor. In addition, the THD of the input power supply has been proven by simulation to comply with the requirements of IEEE Std514-2014.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.93-103
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• 2019

In metropolitan cities have been reorganizing the routes of the city buses periodically due to changes in the spatial structure and traffic pattern and the lack of supply due to new developments. However, there is a lack of system to comprehensively evaluate the routes. Even if the evaluation index is not clearly defined, it may not be reasonable. Therefore, it is difficult to set the improvement direction when the bus route is reorganized. In this study, the existing evaluation indexes were reviewed and further investigation was conducted on the problematic indexes. In particular, the degree of curvature has been used as a very important index in the evaluation of the route system, but the existing curvature based curvature has a limitation in considering the traffic characteristics of individual users. For this purpose, a virtual city bus network was set up and the degree of curvature was calculated and compared based on the point - based curvature and stopping point based on individual user O/D. In this study, it is considered that more efficient and practical analysis and evaluation are possible in the evaluation of the city bus route system through the curvature considering the individual user O/D based on the stopping point. It is expected that it will be used at the time of reorganization of city bus route performed by individual local governments in the future.

• Journal of the Korean Society of Mineral and Energy Resources Engineers
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• v.55 no.6
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• pp.553-563
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• 2018

In this study, the location conditions and optimal technologies required for creating urban municipalities that can utilize the space in an abandoned mine area, where there is no infrastructure related to recycling wastes and valuable metals, are investigated. The urban mining industry deals with mineral resources through the processing of high value-added industrial by-products and wastes, and it is a useful linkage industry for the development of mineral resources and prevention of mining hazards. Urban mining technologies targeted at the abandoned mine area constitute screening, extraction, and smelting for recycling waste products. By analyzing the technologies available, an industrial network can be developed for recycling waste batteries and catalysts, which are promising raw materials. It is also important to establish an appropriate location for related industries that can generate value-added resources, rather than the resource supply and demand conditions seen in general urban mines. In order to overcome the accessibility and infrastructure limitations, the economic foundation of the abandoned mine area should consider the linkage of raw material supply, key technologies for recycling useful mineral resources that are derived from urban mines, spatial and site conditions, and industrial characteristics.

• Korean Chemical Engineering Research
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• v.59 no.2
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• pp.191-199
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• 2021

A distillation column, which is a main facility of the chemical process, separates the desired product from a mixture by using the difference of boiling points. The distillation process requires the optimization and the prediction of operation because it consumes much energy. The target process of this study is difficult to operate efficiently because the composition of feed flow is not steady according to the supplier. To deal with this problem, we could develop a data-driven model to predict operating conditions. However, data preprocessing is essential to improve the predictive performance of the model because the raw data contains outlier and noise. In this study, after optimizing the predictive model based long-short term memory (LSTM) and Random forest (RF), we used a low-pass filter and one-class support vector machine for data preprocessing and compared predictive performance according to the method and range of the preprocessing. The performance of the predictive model and the effect of the preprocessing is compared by using R2 and RMSE. In the case of LSTM, R2 increased from 0.791 to 0.977 by 23.5%, and RMSE decreased from 0.132 to 0.029 by 78.0%. In the case of RF, R2 increased from 0.767 to 0.938 by 22.3%, and RMSE decreased from 0.140 to 0.050 by 64.3%.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.688-701
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• 2020

This study analyzes the characteristics and change factors of technological cooperation networks in the automotive industry. Using Social Network Analysis (SNA) of 112,009 autonomous driving-related patents filed from 2000 to 2017 by major automotive firms in the world, we investigate the structure of the technological cooperation network. Network characteristics such as density are analyzed through structural characteristic analysis among the network analysis indicators. The structural characteristics of the technology cooperation network are confirmed through analysis of status characteristic indicators, such as the degree of centrality, betweenness centrality, and closeness centrality. Results show that car makers such as Toyota and Hyundai Motors, as well as parts suppliers such as Bosch and Continental, have high-performance technology developments related to autonomous driving. The structural characteristics of the network show that companies participating in cooperative networks for autonomous driving technology development have increased in number and are diversified, and all of the status characteristics indicators have decreased. This can be interpreted as an increasing number of horizontal and complementary forms of technological cooperation between firms. In addition, it was confirmed that the number of participants in the field of autonomous driving technology has increased, and the networks have become more complex.

• Journal of Korean Society of Disaster and Security
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• v.13 no.4
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• pp.75-92
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• 2020

In most cases of the water balance analysis, the return flow ratio for each water supply was uniformly determined and applied, so it has been contained a problem that the volume of available water would be incorrectly calculated. Therefore, sewage and wastewater among the return water were focused in this study and the data-driven model was developed to forecast the outflow from the sewage treatment plant. The forecasting results of LSTM (Long Short-Term Memory), GRU (Gated Recurrent Units), and SVR (Support Vector Regression) models, which are mainly used for forecasting the time series data in most fields, were compared with the observed data to determine the optimal model parameters for forecasting outflow. As a result of applying the model, the root mean square error (RMSE) of the GRU model was smaller than those of the LSTM and SVR models, and the Nash-Sutcliffe coefficient (NSE) was higher than those of others. Thus, it was judged that the GRU model could be the optimal model for forecasting the outflow in sewage treatment plants. However, the forecasting outflow tends to be underestimated and overestimated in extreme sections. Therefore, the additional data for extreme events and reducing the minimum time unit of input data were necessary to enhance the accuracy of forecasting. If the water use of the target site was reviewed and the additional parameters that could reflect seasonal effects were considered, more accurate outflow could be forecasted to be ready for climate variability in near future. And it is expected to use as fundamental resources for establishing a reasonable river water management system based on the forecasting results.

• The Journal of the Convergence on Culture Technology
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• v.8 no.2
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• pp.343-348
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• 2022

This study aims to analyze the user experience of unmanned checkout counters perceived by consumers using SNS big data. For this study, blogs, news, intellectuals, cafes, intellectuals (tips), and web documents were analyzed on Naver and Daum, and 'unmanned checkpoints' were used as keywords for data search. The data analysis period was selected as two years from January 1, 2020 to December 31, 2021. For data collection and analysis, frequency and matrix data were extracted through Textom, and network analysis and visualization analysis were conducted using the NetDraw function of the UCINET 6 program. As a result, the perception of the checkout counter was clustered into accessibility, usability, continuous use intention, and others according to the definition of consumers' experience factors. From a supplier's point of view, if unmanned checkpoints spread indiscriminately to solve the problem of raising the minimum wage and shortening working hours, a bigger employment problem will arise from a social point of view. In addition, institutionalization is needed to supply easy and convenient unmanned checkout counters for the elderly and younger generations, children, and foreigners who are not familiar with unmanned calculation.

• Journal of the Korea Society for Simulation
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• v.18 no.3
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• pp.13-21
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• 2009

The sensor nodes that form a wireless sensor network must perform both routing and sensing roles, since each sensor node always has a regular energy drain. The majority of sensors being used in wireless sensor networks are either unmanned or operated in environments that make them difficult for humans to approach. Furthermore, since many wireless sensor networks contain large numbers of sensors, thus requiring the sensor nodes to be small in size and cheap in price, the amount of power that can be supplied to the nodes and their data processing capacity are both limited. In this paper, we proposes the WSN(Wireless Sensor Network) algorithm which is applied sensor node that has low power consumption and efficiency measurement. Moreover, the efficiency routing protocol is proposed in this paper. The proposed algorithm reduces power consumption of sensor node data communication. It has not researched in LEACH(Low-Energy Adaptive Clustering Hierarchy) routing protocol. As controlling the active/sleep mode based on the measured data by sensor node, the energy consumption is able to be managed. In the event, the data is transferred to the local cluster head already set. The other side, this algorithm send the data as dependent on the information such as initial and present energy, and the number of rounds that are transformed into cluster header and then transferred. In this situation, the assignment of each node to cluster head evenly is very important. We selected cluster head efficiently and uniformly distributed the energy to each cluster node through the proposed algorithm. Consequently, this caused the extension of the WSN life time.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.30 no.5D
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• pp.533-540
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• 2010

Dam is very important facility in water supply and flood control. Therefore study needs to analyze reservoir capacity accurately to manage Dam efficiently. This study compared time series reservoir capacity using multi-dimensional spatial information to Chungju Dam reservoir and major conclusions are as follows. First, LiDAR and multi beam echo sounder survey were carried out in land zone and water zone of Dam reservoir area. And calibration process was performed to enhance the accuracy of survey data and it could be constructed that multi dimensional spatial information which was clearly satisfied with the standard of tolerance error by validation with ground control points. Reservoir capacity by water level was calculated using triangle irregular network from detailed topographic data that was constructed by linked with airborne LiDAR and multi beam echo sounder data, and curve equation of reservoir capacity was developed through regression analysis in 2008. In the comparison of the reservoir capacity of 2008 with those of 1986 and 1996, the higher water level goes, total reservoir capacity of 2008 showed decrease because of the increase of sediment in reservoir. Also, erosion and sediment area could be analyzed through calculating the reservoir capacity by the range of water level. Especially the range of water level as 130.0~135.0 which is the upper part of average water level, showed the highest erosion characteristics during 1986~2008 and 1996~2008 and it is considered that the erosion of reservoir slant by heavy rainfall is major reason.