• 한국연소학회:학술대회논문집
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• 2014.11a
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• pp.15-16
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• 2014

With the increasing trend in CFB(Circulating Fluidized Bed) boiler scale, the EHE(External Heat Exchanger) must be adopted to the large-scale boilers to recover insufficient heat transfer surface. In this study, the numerical analysis model for EHE in commercial 300MWe CFB boiler was developed with the inclusion of mechanistic model, which enables the heat transfer prediction. Finally, the calculated absorbed heat and derived heat transfer coefficient are evaluated through the verification with experimental data.

• 한국연소학회:학술대회논문집
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• 2012.04a
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• pp.35-36
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• 2012

Part load operation usually covers large periods of the total operation time on the economic ground and electricity demand in small-scale boilers. Performance analysis of part load behavior is very important for the purpose of boiler operation optimization. A simple thermal calculation approach is applied to predict performance of a pilot-scale circulating fluidized bed (CFB) boiler at part load operation. Verification has been carried out by comparing between calculation results an operation data of the boiler.

• Journal of the Korea Society for Simulation
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• v.10 no.3
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• pp.95-103
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• 2001

Rendering of 3D terrain data in real-time is difficult because of its large scale. So, it is necessary to use level-of-detail(LOD) that uses fewer data, but makes almost similar image to the original. We present an algorithm for real-time LOD generation and rendering of 3D terrain data. The algorithm applies wavelet transform to the terrain data, and then generates quadtree based view-dependent LOD using wavelet coefficients that are the output of wavelet transform. It also uses frame-to-frame coherence and view culling for high frame rates.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4B
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• pp.329-334
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• 2006

The spatial variability of the L- and C- band large scale remotely sensed soil moisture data, obtained during the Southern Great Plain 1999 Experiment (SGP'99), was characterized. The results demonstrate that soil moisture data using L-band show the break in statistical symmetry (multiscaling behavior) with the variation of scale of observation, which is similar to that of the soil property such as sand content. Also, soil moisture data using C-band show single scaling behavior with the variation of scale of observation, which is similar to that of the vegetation condition. The results should be considered during downscaling the Global soil moisture data using AMSR instrument.

• ETRI Journal
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• v.45 no.4
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• pp.557-569
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• 2023

Traditional deterministic channel modeling is accurate in prediction, but due to its complexity, improving computational efficiency remains a challenge. In an alternative approach, we investigated a multilayer artificial neural network (ANN) to predict large-scale and small-scale channel characteristics in metro tunnels. Simulated high-precision training datasets were obtained by combining measurement campaign with a ray tracing (RT) method in a metro tunnel. Performance on the training data was used to determine the number of hidden layers and neurons of the multilayer ANN. The proposed multilayer ANN performed efficiently (10 s for training; 0.19 ms for prediction), and accurately, with better approximation of the RT data than the single-layer ANN. The root mean square errors (RMSE) of path loss (2.82 dB), root mean square delay spread (0.61 ns), azimuth angle spread (3.06°), and elevation angle spread (1.22°) were impressive. These results demonstrate the superior computing efficiency and model complexity of ANNs.

• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.755-768
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• 2017

As Big Data becomes the core of the fourth industrial revolution, big data-based processing and analysis capabilities are expected to influence the company's future competitiveness. Comparative studies of RHadoop and RHIPE that integrate R and Hadoop environment, have not been discussed by many researchers although RHadoop and RHIPE have been discussed separately. In this paper, we constructed big data platforms such as RHadoop and RHIPE applicable to large scale data and implemented the machine learning algorithms such as multiple regression and logistic regression based on MapReduce framework. We conducted a study on performance and scalability with those implementations for various sample sizes of actual data and simulated data. The experiments demonstrated that our RHadoop and RHIPE can scale well and efficiently process large data sets on commodity hardware. We showed RHIPE is faster than RHadoop in almost all the data generally.

• The Journal of the Korea Contents Association
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• v.22 no.3
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• pp.500-512
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• 2022

Post-Occupancy Evaluation (POE), which is one of the construction environment evaluation methods, is a series of processes that ask about the functional requirements and satisfaction of an object from a life cycle perspective such as design/construction/residence. However, there are no POE research activities targeting large-scale units. On the other hand, large-scale third-phase new towns are being developed. Therefore, this study conducted a post-residence evaluation (POE) research activity in a large-scale unit (Multifunctional Administrative City). The procedure of this study is to conduct a literature survey on the current status and implications of the multi-functional administrative city area, and based on the research data, derive the Happy City evaluation index for the major issues and special issues of the Happy City. Afterwards, 450 questionnaires were conducted for the residents of Happy City, and POE analysis was performed on the derived data for each module. And based on the analysis results, implications such as problems and improvement points for the current status of the Happy City were derived. This can be used as a basis for the expansion of a large-scale new city into a self-sufficient city, and it can be used as a basic data for the development and improvement of a happy city that meets social needs in the future.

• Journal of Distribution Science
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• v.21 no.5
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• pp.101-111
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• 2023

Purpose: The purpose of this paper is to examine the effect of the VKOSPI index on short-term stock returns after a large-scale stock price shock of individual stocks of firms in the distribution industry in Korea. Research design, data, and methodology: This study investigates the effect of the change of the VKOSPI index or investor mood on abnormal returns after the event date from January 2004 to July 2022. The significance of the abnormal return, which is obtained by subtracting the rate of return estimated by the market model from the rate of actual return on each trading day after the event date, is determined based on T-test and multifactor regression analysis. Results: In Korea's distribution industry, the simultaneous occurrence of a bad investor mood and a large stock price decline, leads to stock price reversals. Conversely, the simultaneous occurrence of a good investor mood and a large-scale stock price rise leads to stock price drifts. We found that the VKOSPI index has strong explanatory power for these reversals and drifts even after considering both company-specific and event-specific factors. Conclusions: In Korea's distribution industry-related stock market, investors show an asymmetrical behavioral characteristic of overreacting to negative moods and underreacting to positive moods.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.2-5
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• 2021

With the recent development of the Internet of Things (IoT) technology, various terminals are being connected to the Internet. As a result, the amount of IoT data is also increasing, and an index key that can efficient analyze the large-scale IoT data is proposed. Existing index keys have only time and space information, so if data stored in index tables and instance tables were queried using repetition or join operation, IoT data was embedded in the index key of the proposal to create OLAP-based big tables to minimize the number of repetitions or join times.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.8 no.3
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• pp.229-238
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• 2010

In order to acquire a realistic forecast for the lifetime and post-closure period of the LILW (Low- and Intermediate-Level Radioactive Waste) repository and to establish the overall management plan associated gas issues. it is essential to carry out the long-term experimental research in a similar condition to actual disposal environment. Regarding this, as a part of the following-up actions on a construction and operation license for the first stage of the LILW repository at Gyeongju city, a large-scale in-situ experiment is being planned. For securing basic data on the experiment, the experimental researches related to gas generation previously performed in foreign countries are reviewed in detail. Consequently, it is judged that data on the gas generation experiment in Finland could be practically applied as the benchmark for our large-scale in-situ experiment because the same disposal concept as the Korean repository is adopted and the experiment is performed in a scale large enough to allow the use of regular waste packages.