• Journal of Institute of Control, Robotics and Systems
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• v.14 no.1
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• pp.1-6
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• 2008

The ubiquitous sensor network technique is widely applied to variety of information fields such as home automations, logistics, traffic controls, public administrations, health and environment monitoring and etc. It is particularly useful in the areas where energy consumption is minimal and where continuous monitoring of the surrounding environments, which generates streams of data, are required. In this study, we have designed and implemented a living environment automatic control system which collects the streams of temperature, humidity, light and noise data of a simulated house setting in real-time fashion, then controls the home environment based on the collected data according to the users favorites. In order to differentiate the proposed system from the currently existing similar system, we have demonstrated not only the feasibility of collecting data using sensor network in the controlled environment but also the ability to control the various household equipments through wireless communications.

• Journal of the Korean housing association
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• v.23 no.5
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• pp.75-86
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• 2012

The primary purpose of this study is to prove the relationship between housing environment and mental health with depression and self-esteem in the republic of Korea. The raw data of 10,608 respondents, was gathered from the 4th wave of Korea Welfare Panel Study (KoWePS) in 2009. Some variables related to housing environment and mental health were selected in KoWePS' data. Data was analyzed by SPSS 19.0 and AMOS 17.0. The major results are as follow: 1) Householder economic variables significantly relate to housing environment and resident mental health. 2) Housing environment variables are significantly related to resident mental health, and these variables explain 4.3% of depression and 6.7% of self-esteem. 3) Throughout path analysis of economic, housing environment, and mental health variables, housing environment variable is a parameter. In conclusion, these results show that better quality of housing environment would contribute to the residents' better mental health.

• Korean Journal of Computational Design and Engineering
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• v.2 no.1
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• pp.44-52
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• 1997

A design process is difficult to describe comprehensively because a design problem has a multi-disciplinary nature and the design itself evolves as solutions are attempted by the designer. The process of design has been investigated in this paper with the purpose of characterizing the role that a system of this kind may have. In defining the system, an approach has been used that privileges the relationships with the existing CAD tools based on data exchange standards in course of definition today. Integrated design environment normally consists of a centralized data model a data management system and a set of CAD tools. In this study, all further investigations are directed towards the data management system, as one of the main components of the proposed environment. Moreover, product modeling, as a prerequisite for the data management core, is taken into special consideration.

• Journal of Information Technology Applications and Management
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• v.26 no.5
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• pp.57-65
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• 2019

Recommendation Systems are information technologies that E-commerce merchants have adopted so that online shoppers can receive suggestions on items that might be interesting or complementing to their purchased items. These systems stipulate valuable assistance to the user's purchasing decisions, and provide quality of push service. Traditionally, Recommendation Systems have been designed using a centralized system, but information service is growing vast with a rapid and strong scalability. The next generation of information technology such as Cloud Computing and Big Data Environment has handled massive data and is able to support enormous processing power. Nevertheless, analytic technologies are lacking the different capabilities when processing big data. Accordingly, we are trying to design a conceptual service model with a proposed new algorithm and user adaptation on dynamic recommendation service for big data environment.

• Journal of Software Assessment and Valuation
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• v.17 no.1
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• pp.59-66
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• 2021

Recently, conceptual information model is changing fast, and these changes are coming about as a result of individual tendency, social cultural, new circumstances and societal shifts within big data environment. Despite the data is growing more and more, now is the time to commit ourselves to the development of renewable, invaluable information of social/live commerce. Because we have problems with various insoluble data, we propose about deep learning prediction model-based object classification in social commerce of big data environment. Accordingly, it is an increased need of social commerce platform capable of handling high volumes of multiple items by users. Consequently, responding to rapid changes in users is a very significant by deep learning. Namely, promptly meet the needs of the times, and a widespread growth in big data environment with the goal of realizing in this paper.

• International conference on construction engineering and project management
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• 2013.01a
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• pp.169-172
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• 2013

Building Information Modeling (BIM) is an effective decision-making platform that helps to save project cost and enhance quality of construction. By generating and linking a wide variety of objects data, BIM can be effectively utilized, and it should be ensured that object properties maintain consistency throughout the project period of design, estimates, construction, maintenance and repair. This study examined how to utilize BIM data in a construction project, by linking cost and schedule data in web environment, to better utilize the information and maintain consistency of the BIM information. To do so, the model integrated WBS data and CBS data, linked them with BIM model to realize 5D simulation in web environment. As a result, cost and schedule data could be simultaneously acquired, and object properties-cost, schedule, location-as well. These are expected to contribute to developing a BIM-based automatic data-processing system in web environment.

• Journal of the Architectural Institute of Korea Planning & Design
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• v.36 no.5
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• pp.53-58
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• 2020

The purpose of this study is to build a database of Spatial information Bigdata of cities using satellite images and spatial information, and to examine the correlations with the surface temperature. Using architectural structure and usage in building information, DEM and Slope topographical information for constructed with 300 × 300 mesh grids for Busan. The satellite image is used to prepare the Normalized Difference Built-up Index (NDBI), Normalized Difference Vegetation Index (NDVI), Bare Soil Index (BI), and Land Surface Temperature (LST). In addition, the building area in the grid was calculated and the building ratio was constructed to build the urban environment DB. In architectural structure, positive correlation was found in masonry and concrete structures. On the terrain, negative correlations were observed between DEM and slope. NDBI and BI were positively correlated, and NDVI was negatively correlated. The higher the Building ratio, the higher the surface temperature. It was found that the urban environment DB could be used as a basic data for urban environment analysis, and it was possible to quantitatively grasp the impact on the architecture and urban environment by adding local meteorological factors. This result is expected to be used as basic data for future urban environment planning and disaster prevention data construction.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.9B
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• pp.1066-1072
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• 2011

Cloud Computing Environment provides users with a blue print of IT Utopia with virtualization; unbounded computing power and data storage free from the cost and the responsibility of maintenance for the IT resources. But, there are several issues to be addressed for the Cloud Computing Environment to be realized as the blue print because users cannot control the IT resources provided by the Cloud Computing Environment but can only use them. One of the issues is how to secure and to trust data in the Cloud Computing Environment. In this paper, an efficient and practical trust assurance of data with provenance in Cloud Computing Environment.

• Journal of the Korea Society for Simulation
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• v.22 no.2
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• pp.53-62
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• 2013

Cloud environment is one in the field of distributed computing and it consists of physical nodes and virtual nodes. In distributed cloud environment, an optimal path search is that each node to perform a search for an optimal path. Synchronization of each node is required for the optimal path search via fast data transmission because of real-time environment. Therefore, a quantization technique is required in order to guarantee QoS(Quality of Service) and search an optimal path. The quantization technique speeds search data transmission of each node. So a main server can transfer data of real-time environment to each node quickly and the nodes can perform to search optimal paths smoothly. In this paper, we propose the quantization technique to solve the search problem. The quantization technique can reduce the total data transmission. In order to experiment the optimal path search system which applied the quantized data transmission, we construct a simulation of cloud environment. Quantization applied cloud environment reduces the amount of data that transferred, and then QoS of an application for the optimal path search problem is guaranteed.

• Journal of Korean Society on Water Environment
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• v.28 no.6
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• pp.819-832
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• 2012

HSPF model based on BASINS was applied for the Hwaseong Reservoir watershed (HRW) to evaluate the feasibility of water quality management. The watershed was divided into 45 sub-basins considering various watershed environment. Streamflow was calibrated based on the measured meteorological data, discharge data of treatment plants and observed streamflow data for 2010 year. Then the model was calibrated against the field measurements of water qualities, including BOD, T-N and T-P. In most cases, there were reasonable agreements between observed and predicted data. The validated model was used to analyze the characterization of pollutant load from study area. As a result, Non-point source pollutant loads during the rainy season was about 66~78% of total loads. In rainy-season, water quality parameters depended on precipitation and pollutant loads patterns, but their concentration were not necessarily high during the rainy season, and showed a decreasing trend with increasing water flow. As another result of evaluation for load duration curves, in order to improve water qualities to the satisfactory level, the watershed managements considering both time-variant and pollution sources must be required in the HRW. Overall, it was found that the model could be used conveniently to assess watershed characteristics and pollutant loads in watershed scale.