• Journal of the Korea Society of Computer and Information
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• v.14 no.12
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• pp.41-53
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• 2009

In this paper, we propose the system structure and technologies to implement a business model for an intelligent traffic facility management system based on ubiquitous technology. The business model includes the service functions, service structure, business process, and demand and supply relationship among the participants in this model. We also propose an approach to implementing the model. This includes the network, infrastructure and platform to be used for system composition. We then present the results from an analysis by comparison of different technologies and an adequate technology structure. Finally, this paper may present guidelines to managing traffic facilities.

• Korean Journal of Artificial Intelligence
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• v.12 no.1
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• pp.17-24
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• 2024

This paper introduces a novel approach to time-series estimation for energy load forecasting within Virtual Power Plant (VPP) systems, leveraging advanced artificial intelligence (AI) algorithms, namely Long Short-Term Memory (LSTM) and Seasonal Autoregressive Integrated Moving Average (SARIMA). Virtual power plants, which integrate diverse microgrids managed by Energy Management Systems (EMS), require precise forecasting techniques to balance energy supply and demand efficiently. The paper introduces a hybrid-method forecasting model combining a parametric-based statistical technique and an AI algorithm. The LSTM algorithm is particularly employed to discern pattern correlations over fixed intervals, crucial for predicting accurate future energy loads. SARIMA is applied to generate time-series forecasts, accounting for non-stationary and seasonal variations. The forecasting model incorporates a broad spectrum of distributed energy resources, including renewable energy sources and conventional power plants. Data spanning a decade, sourced from the Korea Power Exchange (KPX) Electrical Power Statistical Information System (EPSIS), were utilized to validate the model. The proposed hybrid LSTM-SARIMA model with parameter sets (1, 1, 1, 12) and (2, 1, 1, 12) demonstrated a high fidelity to the actual observed data. Thus, it is concluded that the optimized system notably surpasses traditional forecasting methods, indicating that this model offers a viable solution for EMS to enhance short-term load forecasting.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.8
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• pp.2399-2416
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• 2024

The current automotive industry is transitioning from Internal Combustion Engine (ICE) vehicles to Electric Vehicles (EVs), adopting a mixed assembly production approach to respond to fluctuating demand. While mixed assembly production offers the advantages of lower investment costs and flexibility in responding to changing demands, the supply of EV components requires more extensive provisioning compared to ICE vehicle components, potentially leading to unexpected issues such as congestion of transport vehicles. This study proposes a digital twin system architecture that uses Discrete Event Simulation (DES) and Business Intelligence (BI) tools to specifically address logistics challenges. The proposed architecture facilitates real-time, data-driven decision making across three layers; Data source, Simulation, and BI. It was implemented in factories engaged in the mixed assembly production of ICE and EV vehicles. The simulation challenges involve a tier 1 vendor supplying parts to Korean automobile manufacturers that produce both ICE and EV parts. A total of 240 scenarios were created to run the simulations. The deployment of the proposed architecture demonstrates its capability to quickly respond to diverse experimental situations and promptly identify potential issues.

• Korean Chemical Engineering Research
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• v.55 no.3
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• pp.332-340
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• 2017

This study aims to propose a new optimization-based approach for design and analysis of the stand-alone hybrid energy supply system using renewable energy sources (RES). In the energy supply system, we include multiple energy production technologies such as Photovoltaics (PV), Wind turbine, and fossil-fuel-based AC generator along with different types of energy storage and conversion technologies such as battery and inverter. We then select six different regions of Korea to represent various characteristics of different RES potentials and demand profiles. We finally designed and analyzed the optimal RES stand-alone energy supply system in the selected regions using multiobjective optimization (MOOP) technique, which includes two objective functions: the minimum cost and the minimum $CO_2$ emission. In addition, we discussed the feasibility and expecting benefits of the systems by comparing to conventional systems of Korea. As a result, the region of the highest RES potential showed the possibility to remarkably reduce $CO_2$ emissions compared to the conventional system. Besides, the levelized cost of electricity (LCOE) of the RES-based energy system is identified to be slightly higher than conventional energy system: 0.35 and 0.46 $/kWh, respectively. However, the total life-cycle emission of $CO_2$ ($LCE_{CO2}$) can be reduced up to 470 g$CO_2$/kWh from 490 g$CO_2$/kWh of the conventional systems.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 1995.12a
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• pp.9-21
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• 1995

A planning support system enhances our ability to use water capacity expansion as an urban growth management strategy. This paper reports the development of capacity expansion modeling of water supply as part of the continuing development of such a planning support system (PEGASUS: Planning Environment for Generation and Analysis of Spatial Urban Systems) to incorporate water supply, This system is designed from the understanding that land use and development drive the demand for infrastructure and infrastructure can have a significant influence on the ways in which land is developed and used. Capacity expansion Problems of water supply can be solved in two ways: 1) optimal control theory, and 2) mixed integer nonlinear programming (MINLP). Each method has its strengths and weaknesses. In this study the MINLP approach is used because of its strength of determining expansion sizing and timing simultaneously. A dynamic network optimization model and a water-distribution network analysis model can address the dynamic interdependence between water planning and land use planning. While the water-distribution network analysis model evaluates the performance of generated networks over time, the dynamic optimization model chooses alternatives to meet expanding water needs. In addition, the user and capacity expansion modeling-to-generate-alternatives (MGA) can generate alternatives. A cost benefit analysis module using a normalization technique helps in choosing the most economical among those alternatives. GIS provide a tool for estimating the volume of demanded water and showing results of the capacity expansion model.

• Spatial Information Research
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• v.22 no.5
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• pp.65-75
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• 2014

Bus headway plays an important role not only in determining the passenger waiting time and bus service quality, but also in influencing the bus operation cost and passenger demand. Previous research on headway control has considered only an hourly difference in the distribution of ridership between peak and non-peak hours. However, this approach is too simple to help manage ridership demand fluctuations in a short time scale; thus passengers' waiting cost will be generated when ridership demand exceeds the supply of bus services. Moreover, bus ridership demand varies by station location and traffic situation. To address this concern, we propose a headway control algorithm for minimizing the waiting time cost by using Smart Card data. We also provide proof of the convergence of the algorithm to the desired headway allocation using a set of preconditions of political waiting time guarantees and available fleet constraints. For model verification, the data from the No. 143 bus line in Seoul were used. The results show that the total savings in cost totaled approximately 600,000 won per day when we apply the time-value cost of waiting time. Thus, we can expect that cost savings will be more pronounced when the algorithm is applied to larger systems.

• Journal of National Security and Military Science
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• s.5
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• pp.241-280
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• 2007

This study examines the relationship of the industry-specific factors that effect innovation of manufacturing technology and the market share within the defense industry. Since the establishment of the basic defense industry framework in 1973, there were numerous interactions of the industry-specific factors of the defense industry structure with the technological innovation and market organization of the defense industry. During last three decades, the domestic defense industry has achieved the considerable level but the framework of the basic system has not developed much in areas of the military science and the defense manufacturing technology. Industry-specific factors were formed in the process and appeared in a variety of behavioral characteristics as subsystems. Currently, there IS a growing trend where the management of defense industry is gradually deteriorating due to limitation of the domestic industry-specific factor (e.g. defense technologies, amount of demand, etc.). If there is a prominent imbalance of the industry-specific factors. it can trigger the potential problem of conflict, lack of cooperation and control, slowing the growth of the manufacturing technology thereby diminishing the market and deteriorating the defense supply/demand relationship. In a research conducted by Joe S. Bain, Bain analyzed the relationship of the traditional industrial organization where industry-specific factor(S) not only impacts the conductor(C). And, conductor(C) influences the shaping of the performance(P) of relationship of the traditional industrial organization. Consequently, the researcher has identified the demand monopoly, barriers to entry, and market competition with comparison of defense industry issues. These defense issues were three industry-specific factors identified, which are 1) The demand monopoly and The entry barriers to new market competition, 2) the industrial technical factor to a production technical competitiveness and a market sharing competitiveness, 3) the probability factor to revolution for military affairs(RMA) and a R&D production. According to baseline with these factors, the following research model is established from the special companies group(Group A), the systematization companies group(Group B), and the general companies group(Group 0. The hypothesis is that if there are more industry-specific factors, then there will be more relationships of defense industry relation statutes. This research is an empirical study on the relationship that the industry specific factors effects the innovation of manufacturing technology and the shaping of the market in the defense industry. Moreover, the existing models to evaluate the industry specific factors of the defense industry IS much to be desired with the controlled statistical analysis of the result. It is vital to study on current situation with suggesting alternative strategy to the efficient strategy. The descriptive analysis approach analysis is conducted with SPSSWIN to conduct reliability test, factor analysis, correlation analysis, cross-tabulation analysis, one-way ANOVA, and multiple regression analysis. However, there were some limitations of the survey such as the rigidity of concept about the technical factors and various market management factors. The wishes is that the decision-maker could be utilized these defence industrial factors to formulate efficient defence policy and strategy in the future.

• International Journal of Computer Science & Network Security
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• v.21 no.11
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• pp.345-353
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• 2021

Cloud computing represent a new era of computing that's forms through the combination of service-oriented architecture (SOA), Internet and grid computing with virtualization technology. Virtualization is a concept through which every cloud is enable to provide on-demand services to the users. Most IT service provider adopt cloud based services for their users to meet the high demand of computation, as it is most flexible, reliable and scalable technology. Energy based performance tradeoff become the main challenge in cloud computing, as its acceptance and popularity increases day by day. Cloud data centers required a huge amount of power supply to the virtualization of servers for maintain on- demand high computing. High power demand increase the energy cost of service providers as well as it also harm the environment through the emission of CO₂. An optimization of cloud computing based on energy-performance tradeoff is required to obtain the balance between energy saving and QoS (quality of services) policies of cloud. A study about power usage of resources in cloud data centers based on workload assign to them, says that an idle server consume near about 50% of its peak utilization power [1]. Therefore, more number of underutilized servers in any cloud data center is responsible to reduce the energy performance tradeoff. To handle this issue, a lots of research proposed as energy efficient algorithms for minimize the consumption of energy and also maintain the SLA (service level agreement) at a satisfactory level. VM (virtual machine) consolidation is one such technique that ensured about the balance of energy based SLA. In the scope of this paper, we explore reinforcement with fuzzy logic (RFL) for VM consolidation to achieve energy based SLA. In this proposed RFL based active VM consolidation, the primary objective is to manage physical server (PS) nodes in order to avoid over-utilized and under-utilized, and to optimize the placement of VMs. A dynamic threshold (based on RFL) is proposed for over-utilized PS detection. For over-utilized PS, a VM selection policy based on fuzzy logic is proposed, which selects VM for migration to maintain the balance of SLA. Additionally, it incorporate VM placement policy through categorization of non-overutilized servers as- balanced, under-utilized and critical. CloudSim toolkit is used to simulate the proposed work on real-world work load traces of CoMon Project define by PlanetLab. Simulation results shows that the proposed policies is most energy efficient compared to others in terms of reduction in both electricity usage and SLA violation.

• The Journal of Industrial Distribution & Business
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• v.11 no.3
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• pp.39-50
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• 2020

Purpose: Agriculture, which is heavily influenced by climate conditions, is one of the industries most affected by climate change. In this respect, various studies on the impact of climate change on the agricultural market have been conducted. Since climate change is a long-term phenomenon for more than a decade, long-term projections of agricultural prices as well as climate variables are needed to properly analyze the impact of climate change on the agricultural market. However, these long-term price projections are often major constraints on studies of climate changes. The purpose of this study is to analyze the impacts of climate changes on the Korean onion market using ex-post analysis approach in order to avoid the difficulties of long-term price projections. Research design, data and methodology: This study develops an annual dynamic partial equilibrium model of Korean onion market. The behavioral equations of the model were estimated by OLS based on the annual data from 1988 to 2018. The modelling system is first simulated to have actual onion market conditions from 2014 to 2018 as a baseline and then compared it to the scenario assuming the climatic conditions under RCP8.5 over the same period. Scenario analyses were simulated by both comparative static and dynamic approach to evaluate the differences between the two approaches. Results: According to the empirical results, if the climate conditions under RCP8.5 were applied from 2014 to 2018, the yield of onion would increase by about 4%, and the price of onion would decrease from 3.7% to 17.4%. In addition, the average price fluctuation rate over the five years under RCP8.5 climate conditions is 56%, which is more volatile than 46% under actual climate conditions. Empirical results also show that the price decreases have been alleviated in dynamic model compared with comparative static model. Conclusions: Empirical results show that climate change is expected to increase onion yields and reduce onion prices. Therefore, the appropriate countermeasures against climate change in Korean onion market should be found in the stabilization of supply and demand for price stabilization rather than technical aspects such as the development of new varieties to increase productivity.

• Journal of the Society of Disaster Information
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• v.1 no.1
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• pp.27-42
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• 2005

Recently the demand for civil security and security guards shows rapid growth. However the supply and training system have some limitations. Educational and training systems for civil body and security guards are in the basic level and private organizations trained the professional work force. So this paper is showing what a social dominant factor and a divice of development of the private security. Capitalism is based on a material desire of the human being. the social control of capital value and the management of capital ability reflects the actual condition of the capitalism well. The unconstrained growing and the expansion of capitalism, it finally lost social meaning and an importance of human being element and the safety of the civilian life, began to threat the security of citizen by forming over the material center structure of society. Improving human life quality and material richness on their life leads positive factor of capitalism whereas is causing several crimes through the society which is being threatened around a human being life for a negative factor of the capitalism. Therefore capitalistic social system has offered both a positive factor 'growing' and 'richness' and that of a negative 'structural poverty' and 'lack of security' and they have been remaining the assignment of capitalism 'poverty' and 'security' by settlement in the society for a extremely phenomenon of both sides. In Korea because their recognition of the study approach and the social safety for social security control function is still staying first step and our daily life is annoying from various threat of the society. many studies and the realistic necessity of experience related with social security is being studied. In addition. The development possibility of the civil guard and defense at the civil field which will be keep the social security has a wide position but its study approach and realistic comprehension is still in insufficient condition.