• The Journal of Bigdata
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• v.8 no.2
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• pp.165-175
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• 2023

LNG is a representative imported cargo at Incheon Port and has a relatively high contribution to the increase/decrease in overall cargo volume at Incheon Port. In addition, in the view point of nationwide, LNG is the one of the most important key resource to supply the gas and generate electricity. Thus, it is very essential to identify the factors that have impact on the demand fluctuation and build the appropriate forecasting model, which present the basic information to make balance between supply and demand of LNG and establish the plan for power generation. In this study, different to previous research based on macroscopic annual data, the weekly demand of LNG is converted from the cargo volume unloaded by LNG carriers. We have identified the periodicity and correlations among internal and external factors of demand variability. We have identified the input factors for predicting the LNG demand such as seasonality of weekly cargo volume, the peak power demand, and the reserved capacity of power supply. In addition, in order to predict LNG demand, considering the characteristics of the data, time series prediction with weekly LNG cargo volume as a dependent variable and prediction through an artificial neural network model were made, the suitability of the predictions was verified, and the optimal model was established through error comparison between performance and estimates.

• The Korean Journal of Emergency Medical Services
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• v.26 no.1
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• pp.21-36
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• 2022

Purpose: This descriptive research study aimed to investigate the knowledge and perception of the natural disaster medical system by relevant disaster medical response teams in Jeonnam region, and provide baseline data for a disaster education program based on analysis of priorities of educational demand. Methods: Online questionnaires were distributed to 200 research participants including paramedics from five fire stations in J province, 22 public health centers, two disaster base hospitals, ERU (Emergency Response Units), and DMAT (Disaster Medical Assistance Team). The questionnaires elicited basic information about respondents, their knowledge and perception on disaster preparation and response, cooperation system, and educational and training needs. Results: The top priority items selected were: other disasters for paramedics, first aid for the rapid response team, and command system for DMAT. Conclusion: Customized education and training programs must be developed to suit each organizational need. Detailed operational guidelines must be established and with them a unified educational curriculum should be put into practice.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.02a
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• pp.73-81
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• 2004

National Geographic Information Institute (NGII) in Korea, through National Geographic Information System (NGIS) Program, has prepared to generate and disseminate digital elevation data for Korea. This is a pilot research to propose a policy for generation, maintenance, and supply of Korea Digital Elevation Data (KDED). Customer demands for accuracy and resolution of DEM was surveyed through questionnaire. In order to investigate the quality, the technical efficiency and the production cost, a tentative DEM in a small test site was generated based on digital topographic maps (original paper map scale 1 :5,000), analytical plotter, and LIDAR. Accuracy standard for KDED was derived based on source data and generation methods. As results of this research, we recommend uniformly spaced grid model for KDED. Its preferable grid space is 5m in urban and its vicinity; and 10m in field and mountainous area. LIDAR has been valuated as a proper KDED generation method fulfilling customers demand for the accuracy.

• Journal of the Korea Society for Simulation
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• v.8 no.4
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• pp.109-124
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• 1999

The major objective of this research is to design and build the variable structure DEVS modeling & simulation framework. To do this, we have proposed the direct message passing mechanism between the model and its simulator to deal with the structural demand from the model during the simulation. In this approach, four types of basic messages are introduced for the vertical(creation/deletion of the child) and horizontal(creation/deletion of the brother) structural changes. Proposed methodology has been successfully applied to the multi-processor system and the forest fire information system.

• The Journal of Information Systems
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• v.31 no.3
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• pp.19-45
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• 2022

Purpose Since COVID-19, the demand for online class platforms has increased. However, those platforms have not been clearly defined, and related research is also limited. In the context of the knowledge marketplace (KMs), this study examined the effects of class information and trust in creators on class preferences from the perspective of consumption value theory. Design/methodology/approach By establishing a web crawler through Python, this study collected 1,174 class data in Korea's leading knowledge marketplace, Class 101, focusing on diverse class-related information and the number of Instagram followers for individual class creators. Based on class information, this research analyzed the effects of consumers' utilitarian value, social value, and hedonic value on class preference. In addition, this study examined whether consumers' trust in creators moderates the relationship between class information and class preference. Findings According to analysis results, it was found that the higher the consumers' consumption value for each class on KMs, the more positive their preference for the class. Also, it was confirmed that consumers' trust in creators moderates the relationship between class information and class preference.

• Journal of Internet Computing and Services
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• v.16 no.5
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• pp.29-38
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• 2015

The Energy Storage System stores electricity for later use. This system can store electricity from legacy electric power systems or renewable energy systems into a battery device when demand is low. When there is high electricity demand, it uses the electricity previously stored and enables efficient energy usage and stable operation of the electric power system. It increases the energy usage efficiency, stabilizes the power supply system, and increases the utilization of renewable energy. The recent increase in the global interest for efficient energy consumption has increased the need for an energy storage system that can satisfy both the consumers' demand for stable power supply and the suppliers' demand for power demand normalization. In general, an energy storage system consists of a Power Conditioning System, a Battery Management System, a battery cell and peripheral devices. The specifications of the subsystems that form the energy storage system are manufacturer dependent. Since the core component interfaces are not standardized, there are difficulties in forming and operating the energy storage system. In this paper, the design of the profile structure for energy storage system and realization of private profiling system for energy storage system is presented. The profiling system accommodates diverse component settings that are manufacturer dependent and information needed for effective operation. The settings and operation information of various PCSs, BMSs, battery cells, and other peripheral device are analyzed to define profile specification and structure. A profile adapter software that can be applied to energy storage system is designed and implemented. The profiles for energy storage system generated by the profile authoring tool consist of a settings profile and operation profile. Setting profile consists of configuration information for energy device what composes energy saving system. To be more specific, setting profile has three parts of category as information for electric control module, sub system, and interface for communication between electric devices. Operation profile includes information in relation to the method in which controls Energy Storage system. The profiles are based on standard XML specification to accommodate future extensions. The profile system has been verified by applying it to an energy storage system and testing charge and discharge operations.

• The Journal of Bigdata
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• v.3 no.2
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• pp.59-70
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• 2018

In order to provide stable district heat supplying service to the certain limited residential area, it is the most important to forecast the short-term future demand more accurately and produce and supply heat in efficient way. However, it is very difficult to develop a universal heat demand forecasting model that can be applied to general situations because the factors affecting the heat consumption are very diverse and the consumption patterns are changed according to individual consumers and regional characteristics. In particular, considering all of the various variables that can affect heat demand does not help improve performance in terms of accuracy and versatility. Therefore, this study aims to develop a demand forecasting model using deep learning based on only limited information that can be acquired in real time. A demand forecasting model was developed by learning the artificial neural network of the Tensorflow using past data consisting only of the outdoor temperature of the area and date as input variables. The performance of the proposed model was evaluated by comparing the accuracy of demand predicted with the previous regression model. The proposed heat demand forecasting model in this research showed that it is possible to enhance the accuracy using only limited variables which can be secured in real time. For the demand forecasting in a certain region, the proposed model can be customized by adding some features which can reflect the regional characteristics.

• Proceedings of the KSR Conference
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• 2003.05a
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• pp.133-138
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• 2003

The Korean high speed railway is scheduled to open in 2004. For railway-based integrated transfer system, it is essential to develop intermodal information system for easy and better transfer to other travel modes. An understanding of mode choices by KTX passengers is crucial for the intermodal transportation planning. Recent development of Intelligent Transportation System made it possible for railroad users to access the information in a cabin or waiting areas at the station. Development of intermodal transportation information system will influence the relative demand for traveling by train from competing other transportation mode. The research is focused on a general overview of the ITS with an emphasis on intermodal transportation information system.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.742-743
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• 2017

The smart factory market is expected to show high growth rate in the future, supported by demand for manufacturing innovation in order to overcome structural low growth. Especially in the future manufacturing industry, robots are combined with IT, becoming the most important core technology. In this paper, we proposed and implemented state information classification method for IoT-based robot control in smart manufacturing environment.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.103-119
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• 2022

The purpose of this study is to propose a plan to establish a system that can maximize the effectiveness of disaster safety training. A review of previous studies and analysis of current status cases was conducted to examine the current level of data, systems, demand technologies, laws, and systems for related fields. A disaster safety training system linking digital twin and extended reality technology was proposed, and a study on the construction plan was conducted for this. It is hoped that the results of this study can contribute to the advancement of the disaster safety training system and reduce disaster damage.