• New & Renewable Energy
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• v.5 no.4
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• pp.68-73
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• 2009

국가 에너지 안보 확보와 친환경적이고 지속적인 '저탄소 녹색성장'의 기반을 마련한다는 측면에서 신재생에너지 분야의 인력양성은 시급하고도 중요한 당면 과제이다. 본 연구에서는 신재생에너지인력양성이 원활하게 공급되지 않았을 경우 발생할 수 있는 인력공급지장효과를 분석하기 위하여 산업연관분석의 공급유도모형을 유도하고 2006년 신재생에너지 인력양성사업 배출인원을 기준으로 실증분석을 실시하였다. 또한 공급유도형의 감응도 계수와 영향력계수 분석을 통해 신재생에너지 관련 사업과 타 산업 간의 전후방연쇄효과를 비교분석하였다. 연구 수행 결과 신재생에너지 관련 산업의 평균 영향력계수는 1.37, 평균 감응도 계수는 0.96으로 최종 수요적 제조업의 성격을 띠고 있는 것으로 나타났다. 또한, 2006년 신재생에너지 인력양성사업에 의해 배출된 336명의 인력이 공급되지 않았을 경우 공급지장비용은 총 230억이며, 8개 신재생에너지원 중 태양열과 연료전지에 인력 공급지장비용이 타 에너지원에 비해 상대적으로 높은 것으로 분석되었다. 산업분류 기준으로는 일반목적용 기계 산업과 전기기계 장치 산업이 신재생 에너지 인력공급 장애에 따른 지장비용이 높은 것으로 분석되었다.

• The Journal of Society for e-Business Studies
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• v.17 no.2
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• pp.105-114
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• 2012

Recently, global warming, energy shortage, and environmental disruption have been serious problems in every nation. It became more and more important to reduce the emission of CO2 and to use of energy efficiently. Smart grid was also introduced using the rapidly developing information technology. It deployed the mutual communication concept between customers and the suppliers in the electricity supply. There were increasing demands to adopt the smart meter and to present incentive for efficient energy usage in many developed countries. The objective of this research was to develop the optimal real time pricing model which maximized the profit of the power retailer and reduced the usage of energy. The simulation study was given to show the usefulness of the model. Simulation considered the customer demand response rate and price elasticity rate. The price elasticity rate was compared in the condition of fixed value according to time and variable value according to the customers. The optimal price model could maximize the profit of the power retailer and reduce the energy usage of the consumers.

• Journal of the Korean Chemical Society
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• v.55 no.2
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• pp.157-162
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• 2011

In the present study, we developed a portable GC module for real-time, quantitative determinations of gas mixtures in air sample. Capillary or packed column was coiled together with a heater wire and thermocouple in a small case. Together with the small and light weight sensors and valves as well as the rechargeable carrier gas canister, which permits collection and separation of samples, this system can determine the components of complex mixtures of air contaminants at low concentrations with a duty cycle of 10 min. When measured the various samples with a FID and TCD, the system showed, for a capillary column, a good resolution (R=8.3), high sensitivity, reproducibility, and linear dynamic range greater than three orders of magnitude. These results indicate that the portable GC module is expected to be used for a wide range of applications, particularly for in situ environmental monitoring, chemical processes, and regulation of contaminant emission.

• Journal of the Korea Society of Computer and Information
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• v.15 no.8
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• pp.157-161
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• 2010

Most of air pollution in a metropolis is the result of exhaust gas emissions from automotive vehicles, and the world-wide regulation against environmental pollution is becoming more strict. Moreover the demand on development and supply of an environment-friendly automobile is increasing and the market share about that is expected to grow rapidly in this time of high oil price. The secondary batteries the most important component to store the electrical energy in hybrid electric vehicle. It needs to the higher power characteristics to emit the energy instantaneous. In this paper, we proposed the system to monitor reliably the charge and discharge states of the secondary batteries for hybrid electric vehicle. The material is about SW and HW module the software and hardware module mounted on the charge and discharge system and the monitoring system to control the charge and discharge performance effectively.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.2
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• pp.161-168
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• 2018

In this study, IT based traceability system which is able to measure weight and moisture content of grain in the post-harvest process of intake, drying, storage and milling was developed in RPC(Rice processing complex). Measured information of weight, moisture content, yield, loss and quality was saved in the DB sever. Simultaneously, lot No. was generated and connecting to quality and traceability information. Also, automatic control system with MMI(Man Machine Interface) and yield and inventory control system(YICS) for grain was developed for the traceability system by applying the TCP/IP communication. In addition, simulation of system was performed for evaluation in RPC.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.6
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• pp.1-6
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• 2020

Road movement pollutant air environment big data is a link between real-time traffic data such as vehicle type, speed, and load using AVC, VDS, WIM, and DTG, which are always traffic volume survey equipment, and road shape (uphill, downhill, turning section) data using GIS. It consists of traffic flow data. Also, unlike general data, a lot of data per unit time is generated and has various formats. In particular, since about 7.4 million cases/hour or more of large-scale real-time data collected as detailed traffic flow information are collected, stored and processed, a system that can efficiently process data is required. Therefore, in this study, an open source-based data parallel processing performance optimization study is conducted for the visualization of big data in the air environment of road transport pollution.

• Journal of Internet Computing and Services
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• v.24 no.5
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• pp.107-120
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• 2023

The public bicycle of Seoul, Ttareungyi, was launched at October 2015 to reduce traffic and carbon emissions in downtown Seoul and now, 2023 Oct, the cumulative number of user is upto 4 million and the number of bike is about 43,000 with about 2700 stations. However, super growth of Ttareungyi has caused the several problems, especially demand/supply mismatch, and thus the Seoul citizen has been complained about out of stock. In this point, this study conducted a real time demand forecasting model to prevent stock out bike at stations. To develop the model, the research team gathered the rental·return transaction data of 20,000 bikes in whole 1600 stations for 2019 year and then analyzed bike usage, user behavior, bike stations, and so on. The forecasting model using machine learning is developed to predict the amount of rental/return on each bike station every hour through daily learning with the recent 90 days data with the weather information. The model is validated with MAE and RMSE of bike stations, and tested as a prototype service on the Seoul Bike Management System(Mobile App) for the relocation team of Seoul City.

• Journal of the Korea Organic Resources Recycling Association
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• v.13 no.3
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• pp.105-118
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• 2005

This study examined the improvements of existing food waste statistics system using a sample survey, which estimated the total food waste generation in 4 areas(High, Middle, Middle and Low, and Low population density), and a survey, which was aimed at forming a basis for modeling 112 local governments, were conducted. Currently, the methods for collecting the statistical data are summarized as five types. In high population density areas, the type based on examining the recycling facilities was found to be a more general way of estimating population centers higher than low population density areas. It was found that numerous low population density areas estimated their food waste production according to its generation per capita. It was also found that the findings of sample survey were 10%~40% higher than the existing statistical data and Non-separated collected food waste appears to be the main factor.

• Journal of Engineering Education Research
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• v.13 no.3
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• pp.11-17
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• 2010

Korea plans to be the world's first country to transform its electricity network into "smart grids," which use information and operational technologies to help to facilitate the reduction of carbon emissions, make more efficient use of existing infrastructure/resources through meeting customer demand/less generation, and support renewable resources with real time monitoring and controls. In this situation, universities do the needful on priority to nurture smart grid engineers who will be responsible for state-of-the-art technologies as today's electric grid transitions to a digital network. This paper thus attempts to permanently turn out high-quality human resources in electrical engineering by fleshing out strategies for training smart electric grid engineers, based on lessons from a national undertaking of nurturing qualified power IT engineers starting on February 1 of 2007.

• Smart Media Journal
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• v.13 no.1
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• pp.18-23
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• 2024

Power efficiency management in smart farms is important due to its link to climate change. As climate change negatively impacts agriculture, future agriculture is expected to utilize smart farms to minimize climate impacts, but smart farms' power consumption may exacerbate the climate crisis due to the current electricity production system. Therefore, it is essential to efficiently manage and optimize the power usage of smart farms. In this study, we propose a system that monitors the power usage of smart farm equipment in real time and predicts the power usage one hour later using GRU. CT sensors are installed to collect power usage data, which are analyzed to detect and prevent abnormal patterns, and combined with IoT technology to efficiently manage and monitor the overall power usage. This helps to optimize power usage, improve energy efficiency, and reduce carbon emissions. The system is expected to improve not only the energy management of smart farms, but also the overall efficiency of energy use.