• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2008.04a
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• pp.386-392
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• 2008

The purpose of this study is to clarify playground types by characteristics of playground environment in child care facilities, to analyze the needs and estimation of users according to playground types. The subjects of this study were care-givers, who assist outdoor play activities of children and manage safety in playground, to estimate adequateness of playground's environment to children's outdoor plays and to report needs. The data were collected by field measurement survey for clarification playground environments in 21 child care facilities and structured-questionnaire for estimation and needs of 181 care-givers in them. The major results showed the following. 1) The playgrounds were clarified to five type according to number of child and size of playground. The five types include A-type as large-scale facility/small-size playground, B-type as small-scale facility/large-size playground, C-type as small-scale facility/small-size playground, D-type as middle-scale facility/large-size playground, and E-type as large-scale facility/large-size playground. 2) The adequateness of playground environment of D-type were estimate higher than others. C-type were estimated lower than other types in size and outdoor play areas organization of playground. 3) The care-givers in D-type and E-type wanted to install various play equipments, but the care-giver in C-type didn't wanted to install play equipment. 4) The various outdoor play areas were needed in D-type.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.1
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• pp.253-258
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• 2014

In smartphone sensing which monitors various social phenomena of the individuals by using embedded sensors, managing metadata is one of the important issue to process large-scale data, improve the data quality, and share collected data. In this paper, we proposed a document clustering scheme for the large-scale metadata management architecture which is designed as a hybrid back-end consisting of a cluster head and member nodes to reduce the server-side overhead. we also verified that the proposed scheme is more efficient than the distance based clustering scheme in terms of the server-side overhead through simulation results.

• Communications for Statistical Applications and Methods
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• v.26 no.4
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• pp.411-430
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• 2019

Tumor development is driven by complex combinations of biological elements. Recent advances suggest that molecularly distinct subtypes of breast cancers may respond differently to pathway-targeted therapies. Thus, it is important to dissect pathway disturbances by integrating multiple molecular profiles, such as genetic, genomic and epigenomic data. However, missing data are often present in the -omic profiles of interest. Motivated by genomic data integration and imputation, we present a new statistical framework for pathway significance analysis. Specifically, we develop a new strategy for imputation of missing data in large-scale genomic studies, which adapts low-rank, structured matrix completion. Our iterative strategy enables us to impute missing data in complex configurations across multiple data platforms. In turn, we perform large-scale pathway analysis integrating gene expression, copy number, and methylation data. The advantages of the proposed statistical framework are demonstrated through simulations and real applications to breast cancer subtypes. We demonstrate superior power to identify pathway disturbances, compared with other imputation strategies. We also identify differential pathway activity across different breast tumor subtypes.

• Journal of Korean Tunnelling and Underground Space Association
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• v.9 no.4
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• pp.343-349
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• 2007

The reduced scale fire test provides basic data but it is not enough to analysis real fire problem directly because there is no exact analogy theory between a real fire and the reduced scale model. Therefore we have developed the large scale calorimeter in order to the real scale fire test. This advanced large scale calorimeter used for physical properties such as a heat release rate, based upon consumption of $O_2$ method. Using this large scale calorimeter, we cameo out the real scale vehicle fire test in order to evaluation for heat release rate. We obtained the calculated result for HRR $2.3{\sim}3.4\;MW$ and this result is very similar to the PIARC candidate HRR. It is approve that this facility has the reliability and it is capable of applying to the advance fire research in the future.

• Journal of KIISE
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• v.42 no.1
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• pp.114-121
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• 2015

Large-scale wireless sensor networks are constructed by using a large number of sensor nodes that are non-uniformly deployed over a wide area. As a result, the data collected by the sensor nodes are similar to that from one another since a high density of the sensor nodes may cause an overlap. As a result of the characteristics of the traffic, data is collected from a plurality of sensor nodes by a sink node, and when the sensor nodes transmit their collected data to the sink node, the sensor nodes around the sink node have a higher amount of traffic than the sensor nodes far away from the sink node. Thus, the former sensor encounter bottlenecks due to traffic congestion and have an energy hole problem more often than the latter ones, increasing energy consumption. This paper proposes a congestion control scheme that considers traffic flows in order to control traffic congestion of the sensor nodes that are non-uniformly deployed over a large-scale wireless sensor network.

• Journal of KIISE
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• v.43 no.5
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• pp.553-561
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• 2016

Several machine learning techniques are able to automatically populate ontology data from web sources. Also the interest for large scale ontology reasoning is increasing. However, there is a problem leading to the speculative result to imply uncertainties. Hence, there is a need to consider the reliability problems of various data obtained from the web. Currently, large scale ontology reasoning methods based on the trust value is required because the inference-based reliability of quantitative ontology is insufficient. In this study, we proposed a large scale OWL Horst reasoning method based on a confidence value using spark, a distributed in-memory framework. It describes a method for integrating the confidence value of duplicated data. In addition, it explains a distributed parallel heuristic algorithm to solve the problem of degrading the performance of the inference. In order to evaluate the performance of reasoning methods based on the confidence value, the experiment was conducted using LUBM3000. The experiment results showed that our approach could perform reasoning twice faster than existing reasoning systems like WebPIE.

• Journal of Information Processing Systems
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• v.17 no.1
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• pp.37-50
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• 2021

Query applications based on nested data, the most commonly used form of data representation on the web, especially precise query, is becoming more extensively used. MapReduce, a distributed architecture with parallel computing power, provides a good solution for big data processing. However, in practical application, query requests are usually concurrent, which causes bottlenecks in server processing. To solve this problem, this paper first combines a column storage structure and an inverted index to build index for nested data on MapReduce. On this basis, this paper puts forward an optimization strategy which combines query execution service tree and frequent sub-query trajectory to reduce the response time of frequent queries and further improve the efficiency of multi-user concurrent queries on large scale nested data. Experiments show that this method greatly improves the efficiency of nested data query.

• Fire Science and Engineering
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• v.22 no.1
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• pp.37-44
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• 2008

The reduced scale fire test provides basic data but it is not enough to analysis real fire problem directly because there is no exact analogy theory between a real fire and the reduced scale model. Therefore, we have developed the 10 MW large scale calorimeter in order to real scale fire test. This advanced large scale calorimeter used for physical properties such as a heat release rate, based upon consumption of $O_2$ method. Using the heptane pool fire, we carried out the calibration in order to evaluation for heat release rate. It is approve that this facility has the reliability and it is capable of applying to the advance fire research in the future.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.3
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• pp.857-872
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• 2014

Recent researches reveal that great benefit can be achieved for data gathering in wireless sensor networks (WSNs) by employing mobile data collectors. In order to balance the energy consumption at sensor nodes and prolong the network lifetime, a multi-track large-scale mobile data collection mechanism (MTDCM) is proposed in this paper. MTDCM is composed of two phases: the Energy-balance Phase and the Data Collection Phase. In this mechanism, the energy-balance trajectories, the sleep-wakeup strategy and the data collection algorithm are determined. Theoretical analysis and performance simulations indicate that MTDCM is an energy efficient mechanism. It has prominent features on balancing the energy consumption and prolonging the network lifetime.

• Journal of KIBIM
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• v.6 no.3
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• pp.24-33
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• 2016

Planning occurs from day-to-day, small-scale decisions to large-scale infrastructure investment decisions. For that reason, various attempts have been made to appropriately assist decision-making process and its optimization. Lately, initiation of a large amount of data, also known as big data has received great attention from diverse disciplines because of versatility and adoptability in its use and possibility to generate new information. Accordingly, implementation of big data and other information management systems, such as geographic information systems (GIS) and building information modeling (BIM) have received enough attention to establish each of its own profession and other associated activities. In this extent, this study illustrates a series of big data implementation cases that can provide a lesson to urban planning domain. In specific, case studies analyze how data was used to extract the most optimized solution and what aspects could be helpful in relation to planning decisions. Also, important notions about GIS and its application in various urban cases are examined.