• International journal of advanced smart convergence
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• v.10 no.4
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• pp.278-288
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• 2021

Recently, IoT systems are cloud-based, so that continuous and large amounts of data collected from sensor nodes are processed in the data server through the cloud. However, in the centralized configuration of large-scale cloud computing, computational processing must be performed at a physical location where data collection and processing take place, and the need for edge computers to reduce the network load of the cloud system is gradually expanding. In this paper, a cluster system consisting of 6 inexpensive Raspberry Pi boards was constructed to perform fast data processing. And we propose "Kubernetes cluster system(KCS)" for processing large data collection and analysis by model distribution and data pipeline method. To compare the performance of this study, an ensemble model of deep learning was built, and the accuracy, processing performance, and processing time through the proposed KCS system and model distribution were compared and analyzed. As a result, the ensemble model was excellent in accuracy, but the KCS implemented as a data pipeline proved to be superior in processing speed..

• Journal of the Korean Institute of Gas
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• v.1 no.1
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• pp.56-63
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• 1997

This paper presents a hybrid network model(HY-PIPENET) implementing a minimum cost spanning tree(MCST) network algorithm to be able to determine optimum path and constrained derivative(CD) method to select optimum Pipe diameter. The HY-PIPENET has been validated with the published data of 6-node/7-pipe network. Networking system and also this system has been optimized with MCST-CD method. As a result, it was found that the gas can be sufficiently supplied at the lower pressure with the smaller diameters of pipe compared to the original system in 6-node/7-pipe network. Hence, the construction cost was reduced about $40\%$ in the optimized system. The hybrid networking model has been also applied to a complicated domestic gas pipeline network in metropolitan area, Korea. In this simulation, parametric study was peformed to understand the role of each individual parameter such as source pressure, flow rate, and pipe diameter on the optimized network. From the results of these simulations, we have proposed the optimized network as tree-type structure with optimum pipe diameter and source pressure in metropolitan area, Korea, however, this proposed system does not consider the environmental problems or safety concerns.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.12 s.243
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• pp.1291-1298
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• 2005

Since the interior shape of a pressure regulator is complex and the change of fluid resistance at each operation condition is rapid and big, the pressure regulator can become the major factor that causes big loss in pipelines. So the suitable pressure regulator modeling by each operation condition is important to obtain reliable results especially in small scale pipeline network analysis. And in order to prevent the condensation and freezing problems, it is needed to confirm both whether temperature recovery is achieved after passing by the pressure regulator's narrow neck and how much amount of low temperature area that can cause condensate accumulation is distributed by various PCV models at every inlet-outlet pressure ratio. In this research, the numerical model resembling P company pressure regulator that is used widely for high pressure range in commercial, is adopted as the base model of CFD analysis to investigate pressure regulator's flow characteristics at each pressure ratio. Additionally it is also introduced to examine pressure regulator's critical flow characteristics and possibility of condensation or freezing at each pressure ratio. Furthermore, the comparison between the results of CFD analysis and the results of analytic solution obtained by compressible fluid-dynamics theory is attempted to validate the results of CFD modeling in this study and to estimate the accuracy of theoretical approach at each pressure ratio too.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.29 no.12 s.243
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• pp.1299-1306
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• 2005

The suitable pressure regulator modeling at each opening ratio and pressure ratio is very important to obtain reliable results, especially in small scale pipeline network analysis such as a pressure regulator system. And it is needed to confirm both whether temperature recovery is achieved after passing by the pressure regulator's narrow neck and how much amount of low temperature area that can cause condensate accumulation is distributed by various PCV models and driving conditions. In this research, the numerical model resembling P company pressure regulator that is used widely for high pressure range in commercial, is adopted as the base model of CFD analysis to investigate pressure regulator's flow characteristics at each pressure ratio and opening ratio. And it is also introduced to examine pressure regulator's critical flow characteristics and possibility of condensation or freezing at each pressure ratio and opening ratio. Additionally, the comparison between the results of CFD analysis and the results of analytic solution obtained by compressible fluid-dynamics theory is attempted to validate the results of CFD modeling in this study and to estimate the accuracy of theoretical approach at each pressure ratio and opening ratio too.

• 한국전산유체공학회:학술대회논문집
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• 2000.10a
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• pp.101-108
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• 2000

Pipe network analysis is analyze all of it about pressure and volume flow rate through that are pipeline, junction, regulator and valve etc. In this study is compare TVD with MOC method for analysis of unsteady compressible flow in pipelines. Then, we calculated unsteady compressible flow for pipe network that periodic volume flow rate conditions.

• Journal of Ocean Engineering and Technology
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• v.11 no.4
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• pp.152-158
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• 1997

An analyzing method for pressure fluctuations in oil hydraulic pipe network was developed in this study. The object pipe network has multi-branch configuration, and the pipelines of it are composed of steel tubes, flexible hoses. Also, accumulators, orifices and lumped oil volume components are attached on it. Transfer matrix method, in other words impedance method, was used for the analysis. The reliability and usefulness of the analyzing method were confirmed by investigation computed results and experimental results got in this study.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.9
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• pp.3583-3597
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• 2020

In this paper, a parallel deep learning model using a convolutional neural network and a dilated convolutional neural network is proposed to classify Alzheimer's disease with high accuracy in PET/CT images. The developed model consists of two pipelines, a conventional CNN pipeline, and a dilated convolution pipeline. An input image is sent through both pipelines, and at the end of both pipelines, extracted features are concatenated and used for classifying Alzheimer's disease. Complimentary abilities of both networks provide better overall accuracy than single conventional CNNs in the dataset. Moreover, instead of performing binary classification, the proposed model performs three-class classification being Alzheimer's disease, mild cognitive impairment, and normal control. Using the data received from Dong-a University, the model performs classification detecting Alzheimer's disease with an accuracy of up to 95.51%.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.47 no.11
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• pp.97-104
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• 2010

This paper presents a high performance 32-bit single core AES architecture. The proposed architecture employs a 5-stage pipeline: four stages in the ShiftRows/InvShiftRows module, and one stage in the MixColumn/InvMixColumn module. Circuit size reduction has been achieved through merging of the shift rows and inverse shift rows. The mix column and inverse mix column share the same resources. Three 32-bit registers replace the conventional ten 32-bit registers in the RCON architecture. The proposed architecture has been implemented in Verilog HDL, and yields 415 Mbits/s throughput with the circuit size of 13764 gate equivalents on the 0.18um CMOS process technology. This high performance architecture is suitable for wireless network router applications.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.12 no.20
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• pp.47-53
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• 1989

This paper presents an algorithm CAPFACT to evaluate the reliability of a capacitated two terminal network such as a communication network, a power distribution network, and a pipeline network. The network is good(working) if and only if it is possible to transmit successfully the required system capacity from one specified terminal to the other. This paper defines new Capacitated series-parallel reduction to be applied to a series-parallel structure of the network. New Capacitated factoring method is applied to a non-series-parallel structure. The method is based on the factoring theorem given by Agrawal and Barlow. According to the existing studies on the reliability evaluation of the network that the capacity is not considered, the factoring method using reduction is efficient. The CAPFACT is more efficient than Aggarwal algorithm which enumerated and combined the paths. The efficiency is proved by the result of testing the number of operations and cpu time on FORTRAN compiler of VAX-11/780 at Hanyang University.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.04a
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• pp.305-308
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• 1996

An analyzing method for pressure fluctuation in oil hydraulic pipe network was developed in this study. The object pipe network has multi-branch configuration, and the pipeline of it is composed of steel tubes, flexible hoses. Also, accumulators, orifices and lumped oil volume components are attached on it. Transfer matrix method, in other words impedance method, was used for the analysis. The reliablity and usefulness of the analyzing method was confirmed by comparing and investigating computed results and experimental results got in this study.