• Korea Journal of Geothermal Energy
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• v.11 no.2
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• pp.32-39
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• 2015

• Journal of Korea Spatial Information System Society
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• v.12 no.1
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• pp.1-9
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• 2010

Recently, wireless sensor networks(WSNs) technology has been considered as one of the most critical issues in the ubiquitous computing age. The sensor nodes have limited battery power, so they should consume low energy through their operation for the long-lasting lifetime. Therefore, it is essential to use energy efficient routing protocol. For this, we propose a location-based energy-efficient routing protocol which constructs the energy efficient route by considering the quantity of Energy consumed. In addition, we propose a route reconstruction algorithm to handle the disconnection of message transmission. Finally, we show from performance analysis using TOSSIM that our protocol outperforms the existing location based routing protocols in terms of energy efficiency.

• Proceeding of EDISON Challenge
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• 2016.03a
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• pp.32-36
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• 2016

단일금속 나노입자에 비해 나노합금입자는 발광이나 촉매력과 같은 여러 특징들이 더 뛰어나게 나타난다고 잘 알려져 있다. 이에 따라 실험적인 연구뿐 아니라 이론적으로도 나노합금입자의 특성과 구조를 밝히려는 노력이 이루어지고 있다. 그러나 대부분의 연구는 자유공간을 상정하여 진행되고 있어, 갇힌 공간 속의 입자에 대한 연구는 부족한 실정이다. 이러한 배경으로 본 연구에서는 Sutton-Chen (SC) 포텐셜을 주요 이론으로 하여, 복제교환분자동력학(replica exchange molecular dynamics, REMD) 모의실험을 통해 가두는 공간의 크기에 따라 금-팔라듐 나노합금입자(Au17Pd17)의 구조와 특성이 어떻게 달라지는지 EDISON에 등록된 metal_alloy 프로그램(molecular dynamics simulation of metal alloy nano-cluster)을 사용해 살펴보았다. 결과적으로 입자가 상전이 이전의 낮은 온도에서 존재하면, 둘러싼 공간의 크기와 무관하게 안정한 구조의 중심에 항상 팔라듐 원자가 위치한다는 것이 확인되었다. 또, 가두는 공간의 크기마다 상전이가 일어나는 온도 구간의 차이가 나타났으며, 작은 공간에 갇힌 입자일수록 입자의 최대 직경이 작아지면서 상대적으로 높은 에너지를 가지는 구조를 형성하였다. 이는 입자가 존재하는 공간이 좁을수록 에너지의 증가를 통하면서 최대한 공간을 활용할 수 있는 구조를 선택하는 것으로 보인다.

• The Magazine for Energy Service Companies
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• s.79
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• pp.12-19
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• 2012

본고에서는 ESCO 시장이 성장하기 위하여 건물부문 대상을 1만$m^2$이상 대형건물, 에너지다소비건물, 소규모 건물로 설정하여 정책 및 제도 개선방안을 모색한다. 이를 위해 각각의 개별적인 건물에너지 효율개선사업이 아닌, 유형별, 공간별로 집단화하여 ESCO사업으로 추진하고, ESCO에 대한 홍보와 관심을 유도하기 위한 시범사례를 구축 및 확산하기 위하여 해외사례와 시사점을 제시한다.

• Journal of the Korean Association of Geographic Information Studies
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• v.14 no.3
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• pp.22-35
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• 2011

Incheon Bay has a suitable condition for tidal power generation due to the high tidal range by topographical effect. Therefore a study on the technology development for tidal energy utilization has been promoted since 2006. It is needed to deduce optimal alternatives to determine the suitable location of facilities for tidal power generation and to reduce the environmental damage from development. In order to carry out efficiently this mission, spatial information system is essential to manage and use various spacial elements related to the development and conservation. In this study, for the development of tidal energy, spatial data could be defined as three kinds of dataset. Fundamental dataset is defined as spatial data such as tide, tidal current, wave, erosion and sedimentation. Framework dataset is composed of topographical map, facility map and bathymetry. The reference dataset is composed of marine ecology and environment having the characteristics of thematic map. This study is mainly aimed at establishing methodology of conceptual spatial data modeling classifying as essential data model and optional data model through the definition of the components of spatial data.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.1
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• pp.55-59
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• 2010

Most applications for solar-powered wireless sensor networks are usually deployed in remote areas without a continuous connection to the external networks and a regular maintenance by an administrator. In this case, sensory data has to be stored in the network as much as possible until it is uploaded by the data mule. For this purpose, a balanced data distribution over the network should be performed, and this can be achieved efficiently by taking the amount of available energy and storage into account, in the system layer of each node. In this paper, we introduce a simple but very efficient data distribution algorithm, by which each solar-powered node utilizes the harvested energy and the storage space maximally. This scheme running on each node determines the amount of energy which can be used for a data distribution as well as the amount of data which should be transferred to each neighbor, by using the local information of energy and storage status.

• Electric Engineers Magazine
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• s.372
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• pp.10-11
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• 2013

연일 무더위가 이어지던 2011년 9월 15일, 전력수요가 예상치를 훌쩍 뛰어넘어 전국적인 대정전 사태를 겪었다. 이후에도 크고 작은 사고들이 일어났다. 이렇게 전기와 같은 에너지 수급에 어려움이 생기면서 대체에너지로서의 신재생에너지의 중요성이 점차 커지고 있다. 그렇다면 우리는 이런 신재생에너지에 대해 얼마나 알고 있을까? 서울 상암동 월드컵 경기장 평화의 공원 인근에 에너지의 중요성을 알리고 체험을 해볼 수 있는 복합문화공간인 서울에너지드림센터에 그 답이 있다.

• Spatial Information Research
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• v.21 no.2
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• pp.23-33
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• 2013

W ith the recent advancement of IoT (Internet of Things) technology, there has been much interest in the spatial query processing which energy-efficiently acquires sensor readings from sensor nodes inside specified geographical area of interests. Therefore, various kinds of spatial query processing algorithms and distributed spatial indexing methods have been proposed. They can minimize energy consumption of sensor nodes by reducing wireless communication among them using in-network spatial filtering technology. However, they cannot optimize multiple spatial queries which w ill be w idely used in IoT, because most of them have focused on a single spatial query optimization. Therefore, we propose a new multiple spatial query optimization algorithm which can energy-efficiently process multiple spatial queries in a sensor network. The algorithm uses a concept of 'query merging' that performs the merged set after merging multiple spatial queries located at adjacent area. Here, our algorithm makes a decision on which is better between the merged and the separate execution of queries. For such the decision making, we additionally propose the cost estimation method on the spatial query execution. Finally, we analyze and clarify our algorithm's distinguished features using the spatial indexing methods of GR-tree, SPIX, CPS.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.464-477
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• 2022

DFN (discrete fracture network) models that take account of spatial variability and correlation between rock fractures have been demanded for analysis of fractured rock mass behavior for wide areas with high reliability, such as that of underground nuclear waste repositories. In this regard, this report describes the spatial distribution characteristics of fracture networks, and the DFN modeling methodologies that aim to represent such characteristics. DFN modeling methods have been proposed to represent the spatial variability of rock fractures by defining fracture domains (Darcel et al., 2013) and the spatial correlation among fractures by genetic modeling techniques that imitate fracture growth processes (Davy et al., 2013, Libby et al., 2019, Lavoine et al., 2020).These methods, however, require further research for their application to field surveys and for modeling in-situ rock fracture networks.

• Korean Journal of Construction Engineering and Management
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• v.20 no.3
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• pp.105-112
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• 2019

Due to abnormal high temperature, electric power demand has exceeded the backup power reserved for emergency case, hence, resulting in a major power outage. In today's overcrowded cities, the unexpected disruption in energy supply and demand is a major threat to the enormous economic damage and urban malfunctions. Existing methods for estimating the demand of the emergency power source do not lend themselves to predict the actual demand in the spatial dimension of the city. In addition, the reserve power is arbitrarily distributed in the case of emergency. This paper presents a method that predicts the emergency power demand using the spatial distribution of emergency power demand by applying the daily energy consumption intensity and emergency power demand according to urban spatial information and building use.