• Journal of Korea Technology Innovation Society
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• v.21 no.3
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• pp.1155-1178
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• 2018

Future automobiles are evolving into movable living spaces capable of eco-friendly autonomous driving. The role of electrically processing, controlling, and commanding various information in the vehicle is essential. It is expected that the automotive semiconductor will play a key role in the future automobile such as self-driving and eco-friendly automobile. In order to foster the automotive semiconductor industry, it is necessary to grasp technology trends and to acquire technology and quality that reflects the requirements in advance, thereby achieving technological innovation with industrial competitiveness. However, there is a lack of systematic analysis of technology trends to date. In this study, we analyzed the technology trends of automotive semiconductors using patent analysis and topic model, and confirmed technologies such as electric cars, driving assistance, and digital manufacturing. The technology trends showed that element technology and technical characteristics change according to technology convergence, market needs, and government regulations. Through this research, it is expected that it will help to make R&D policy for automotive semiconductor industry and to make decision for industrial technology strategy establishment. In addition, it is expected that it will be used effectively in detail research direction and patent strategy establishment by providing detailed classification of technology and trend analysis result of technology.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1059-1065
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• 2011

In line with the expansion of electric railway, reducing carbon emission and optimal train operation are required by economical, eco-friendly and efficient management. Most of the energy consumption in electric railway is consumed by train operation. So it is important that minimize the energy consumption in train operation. An analysis of the operation performance of the new model vehicle which in South Korea, Korail introduced shows that the energy consumption is different in line with the skill level of the engine driver. In this study, the know-how of train operation of a skilled engine driver is systematized by using artificial intelligence, and the technique which supports engine drivers with train operation was offered. As a result of applying in South Korea, the Gyeongbu line by using simulation, it confirmed that the maximum 20% can reduce the energy consumption in comparison with unskilled engine drivers in case of applying the Expert System.

• 한국방재학회:학술대회논문집
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• 2007.02a
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• pp.399-402
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• 2007

This project is the 1st. stage for the foreshore reclamation at Jang-Hang area and its scope is to construct a seawall as outer facilities, road adjacent to the seawall and drainage gate. for the safe protections of the facilities at the reclaimed land hereafter, we adopted the mild slope rubble mound type for the seawall structure which was excellent in interrupting the wave overtopping, as a result of numerical & hydraulic model test about alternative 4 sections. For the flooding prevention of the reclaimed land, we planned the drainage system that could make the flood water level lower than the reclaimed land level. Also, we planned the eco-friendly waterfront area with 8 nature themes through the whole seawall sections.

• Journal of Korea Multimedia Society
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• v.22 no.12
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• pp.1491-1499
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• 2019

Insufficient sleep time and bad sleep quality causes many illnesses and it's research became more and more important. The most common method for measuring sleep quality is the polysomnography(PSG). The PSG is a test used to diagnose sleep disorders. The most common PSG data is obtained from the examiner, which attaches several sensors on a body and takes sleep overnight. However, most of the sleep stage classification in PSG are low accuracy of the classification. In this paper, we have studied algorithm for sleep level classification based on machine learning which can replace PSG. EEG, EOG, and EMG channel signals are studied and tested by using CNN algorithm. In order to compensate the performance, a mixed model using both CNN and DNN models is designed and tested for performance.

• 한국신재생에너지학회:학술대회논문집
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• 2011.05a
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• pp.134.1-134.1
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• 2011

As eco-friendly energy is in the spotlight, lots of countries are out to develop and disseminate renewable energy. However, Korea still remains in relative newcomer position for renewable energy. To overcome the present condition, it is necessary to carry out a study of establishment of renewable energy policy that is appropriate the present situation of Korea from examples of advanced countries. Among several renewable energies, wind energy is known to be the most reliable energy. Germany that has increased the share of wind energy in total energy supply is a representative leading country for wind energy. Therefore wind energy policy in Germany will be a role model for that in Korea. In this study, as a research of portfolio for wind energy policy of advanced countries, a wide survey for current status of wind energy and energy policy in Germany is carried out.

• Journal of Hydrogen and New Energy
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• v.26 no.2
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• pp.156-163
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• 2015

The fuel cells have been investigated in the applications of marine as the high efficient and eco-friendly power generating systems. In this study, modeling of IR Type molten carbonate fuel cell (Internal Reforming Type molten carbonate fuel cell) has been developed to analyze the feasibility of thermal energy utilization. The model is developed under Aspen plus and used for the study of system performances over regarding fuel types. The simulation results show that the efficiency of MCFC system based on NG fuel is the highest. Also, it is also verified that the steam reforming is suitable as pre-reforming for diesel fuel.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.309-312
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• 2016

Green Internet of Things (IoT) is the study and practice of eco-friendly sustainable computing. The basic goal of green computing is to reduce the use of materials and maximize energy efficiency with reliable and secure communications. The paper presents various technologies and issues regarding green IoT. It also studies the green Information and Communication Technology (ICT) such as green M2M, green Cloud Computing (CC), and green Data Center (DC). In addition, this paper mentions about the reliability in IoT Communication and and issues to achieve green IoT communication by applying efficient activity scheduling technique for energy saving. Finally, we propose the green IoT-Home Service (GIHS) model which provides efficient energy management in home automation system.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2004.03a
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• pp.318-319
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• 2004

This paper shows an application of single crystal metals and Single Shell Polymer Concentrator (SSPC) to Solar Thermal Propulsion (STP). Based on it, we fabricated a breadboard model of STP system (STP-BBM) for microsatellites. We also proposed Eco-Friendly End-of-Life De-Orbiting (EFELDO) by using such a high performance STP system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.3
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• pp.1011-1015
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• 2013

The demand of bike increases eco-friendly as the mean of transportation but domestic production basis becomes sluggish. In this study, the design analysis of horizontal and vertical frame is performed on the model which is proposed as the bike of new concept in conjunction with public transport system. As the result, the structural analysis is conducted on the main frame of urban bike used with cast magnesium alloy. As the vertical load of 150 kg is applied, the design technology insures that maximum stress less than 70 MPa is obtained.

• Journal of the Korean Society of Visualization
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• v.19 no.1
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• pp.57-61
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• 2021

In order to determine erythrocyte sedimentation rate (ESR) indicating acute phase inflammation, a Westergren method has been widely used because it is cheap and easy to be implemented. However, the Westergren method requires quite a long time for 1 hour. In this study, a gated recurrent unit (GRU) neural network was used to reduce measurement time of ESR evaluation. The sedimentation sequences of the erythrocytes were acquired by the camera and data processed through image processing were used as an input data into the neural network models. The performance of a proposed models was evaluated based on mean absolute error. The results show that GRU model provides best accurate prediction than others within 30 minutes.