• Proceedings of the KSR Conference
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• 2008.06a
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• pp.1612-1627
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• 2008

Dwelling time is one of the factors that influence in rail. Current research in dwelling time has been focusing on railways, the state of the research in high-speed rail's dwelling time is not complete. Dwelling time is consisted of time to open door, time to get into and out of vehicle and time of the departure it takes after the passenger's door was closed, it was affected by various factors such as congestion's degree in vehicle, the number of persons that get into and out of vehicle, congestion's degree in station. In order to analyze theses, we need data analysis such as the number of persons that get into and out of vehicle, congestion's degree in station, congestion's degree in vehicle, but the congestion's degree and passenger's distribution chart in vehicle is excluded in this research due to difficulty of gathering data, and thus we will develop forecasting models through high-speed rail's demand most affected by the dwelling time.

• Journal of Climate Change Research
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• v.8 no.3
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• pp.265-273
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• 2017

Recently the Paris Climate Change Accord has been officially put into effect, making global efforts to implement Greenhouse Gas (GHG) reductions, and also International environmental regulations in the automotive sector will be further strengthened. The electric vehicle, which minimizes the particulate matter generated by existing internal combustion engine automobiles, is evaluated as a representative eco-friendly automobile. However, charging the battery of an electric vehicle is not fully environment-friendly if it is fueled by electricity that is being generated by fossil fuels as an energy source. The energy generated by the photovoltaic power generation system, which is an infinite clean energy, can be used to charge an electric vehicle's battery. Currently, shortage of charging facilities, time of charging, and high battery prices are the problem of activating the supply of electric vehicles. This study is to build a conjunction between the EVBSS (Electric Vehicle Battery Supply System) and ESS (Energy Storage System), which can quickly supply the photovoltaic charged battery to the required demand. If the charged battery in the Battery Swapping Station (BSS) is swapped swiftly, it will dramatically shorten the waiting time for charging the battery. As a result, if the battery is rented when it is needed, electric vehicles can be sold without the cost of a battery, which accounts for a large portion of the total cost, then the supply of electric vehicles are expected to expand. Furthermore, it will be an important alternative to maneuver climate change by minimizing GHG emissions from internal combustion engine vehicles.

• Journal of Internet Computing and Services
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• v.20 no.2
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• pp.51-59
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• 2019

In this paper, we analyzed the relationship between charging operation system and electricity charges connected with charging infrastructure among data of many demonstration projects focused on electric vehicles recently. At this point in time, due to the rapid increase in demand for the electric charging infrastructure that will take place in the future, we can prepare for an upcoming era in the sense of forecasting the demand value. At the same time, demonstrating and modeling optimized system modeling centering on sites is a prerequisite. The modeling based on the existing small - scale simulation and the design of the operating system are based on the data linkage analysis. In this paper, we implemented a new optimized system modeling and introduced it as a standard format to analyze time - dependent time - divisional data for each vehicle and user in each point and node. In order to verify the efficiency of the optimization based on the data linkage analysis for the actual implemented electric car charging infrastructure and operation system.

• Journal of the Korea Institute of Military Science and Technology
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• v.13 no.4
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• pp.594-600
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• 2010

In this paper, we introduced non-parametric statisticals method that could analyse the field data and proposed application ways such as repair-part demand forcasting, MTBF estimation and trend analysis, identity comparison with two populations using the analytical results. In addition, we applied that to real field data which has been collected for about ten years from K series tracked vehicle. After that, we compared the results with those using traditional parametric statistical method, and verified the usability of them.

• Electronics and Telecommunications Trends
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• v.36 no.3
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• pp.1-11
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• 2021

In this study, we analyze the automotive chip ecosystem that recently caused the global supply shortage, and attempt to derive policy implications for us from the conclusion. Automotive chips are critical parts that control various systems so that a vehicle can drive itself or operate with electricity. The current shortage in supply and demand for automotive chips is due to the inconsistency between supply and demand between automotive chip companies and car manufacturers. To promote the automotive chip industry, new investment incentives, tax cuts, and human resource training are needed.

• Journal of Surface Science and Engineering
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• v.57 no.1
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• pp.31-37
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• 2024

The surge in demand for lithium is primarily fueled by the expanding electric vehicle market, the necessity for renewable energy storage, and governmental initiatives aimed at achieving carbon neutrality. This study proposes a straightforward method for lithium extraction utilizing cellulose nanofiber (CNF) via a vacuum filtration process. This approach yields a porous CNF film, showcasing its potential utility as a lithium extractor and indicator. Given its abundance and eco-friendly characteristics, cellulose nanofiber (CNF) emerges as a material offering both economic and environmental advantages over traditional lithium extraction techniques. Hence, this research not only contributes to lithium recovery but also presents a sustainable solution to meet the growing demand for lithium in energy storage technologies.

• Journal of Advanced Marine Engineering and Technology
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• v.34 no.3
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• pp.376-382
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• 2010

These days, a study on 'Unmanned Surface Vehicle (USV)' has made very active progress in many countries. Even if it is being expected that there will be a great demand of USV for wide field, such as military operation, private sector, and etc., the study of USV in Korea is still at an early stage. For this reason, we have made a very small USV which is composed of dual mode (autonomous and remote control). The TCP/IP communication is applied to the USV.

• International Journal of Automotive Technology
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• v.7 no.5
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• pp.565-570
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• 2006

The development of a light-weight vehicle is in great demand for enhancement of fule efficiency and dynamic performance. The vehicle weight can be reduced effectively by using lightweight materials such as aluminum and magnesium. However, if such materials are used in vehicles, there are often instances when different materials such as aluminum and steel need to be joined to each other. The conventional joining method, namely resistance spot welding, cannot be used in joining different materials. Self-piercing rivet(SPR) and adhesive bonding, however, are good alternatives to resistance spot welding. This paper is concerned with the crushing test of double hat-shaped member made by resistance spot welding, SPR and adhesive bonding. Various parameters of crashworthiness are analyzed and evaluated. Based on these results, the applicability of SPR and adhesive bonding are proposed as an alternative to resistance spot welding.

• Journal of the Korean Society of Propulsion Engineers
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• v.14 no.3
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• pp.79-86
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• 2010

The characteristics and classification of UAV power plants were studied. The energy source for electric generation and power source for internal combustion engine for UAVs were compared. The advantage and drawbacks of power plants were analyzed respectively and the performance demand condition was suggested for next generation UAV power plant finally.

• Journal of Electrical Engineering and Technology
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• v.8 no.1
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• pp.1-10
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• 2013

The power industry is currently facing many challenges, due to the new environment created by the introduction of smart grid technologies. In particular, the large-scale deployment of electric vehicles (EVs) may have a significant impact on demand for electricity and, thereby, influence generation and transmission system planning. However, it is difficult to deal with uncertainties in EV charging loads using deterministic planning methods. This paper presents a two-stage stochastic decomposition method with Latin-hyper rectangle sampling (LHRS) to solve the integrated generation and transmission planning problem incorporating EV deployment. The probabilistic distribution of EV charging loads is estimated by Latin-hyper rectangle sampling (LHRS) to enhance the computational performance of the proposed method. Numerical results are presented to show the effectiveness of the proposed method.