• International Journal of Fluid Machinery and Systems
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• v.4 no.4
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• pp.367-374
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• 2011

Water hammer pumps can effectively use the water hammer phenomenon in long-distance pipeline networks that include pumps and allow fluid transport without drive sources, such as electric motors. The results of experiments that examined the effect of the geometric form of water hammer pumps by considering their major dimensions have been reported. In addition, a paper has also been published analyzing the water hammer phenomenon numerically by using the characteristic curve method for comparison with experimental results. However, these conventional studies have not fully evaluated the pump performance in terms of pump head and flow rate, common measures indicating the performance of pumps. Therefore, as a first stage for the understanding of water hammer pump performance in comparison with the characteristics of typical turbo pumps, the previous paper experimentally examined how the hydrodynamic characteristics were affected by the inner diameter ratio of the drive and lifting pipes, the form of the air chamber, and the angle of the drive pipe. To understand the behavior of the components attached to the valve chamber and the air chamber that affects the performance of water hammer pumps, the previous study also determined the relationship between the water hammer pump performance and temporal changes in valve chamber and air chamber pressures according to the air chamber capacity. For the geometry of components attached to the drain valve, which is another major component of water hammer pumps, this study experimentally examines how the water hammer pump performance is affected by the length of the spring and the angle of the drain pipe.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.5
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• pp.61-70
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• 2004

The operation mode of neural network is divided into learning and recognition process. Learning is updating process of weight until neural network archives target result from input pattern. Recognition is arithmetic process of input pattern and weight. Traditional inner product process is focused to improve processing speed and hardware complexity. There is no hardware architecture to distinguish between loaming and recognition mode of neural network. In this paper we propose the new architecture of low power inner product processor for reconfigurable neural network. The proposed architecture is similar with bit-serial inner product processor on learning mode. It have several advantages which are fast processing base on bit-level, suitability of hardware implementation and pipeline architecture to compute data. And proposed architecture minimizes active units and reduces consumption power on recognition mode. Result of simulation shows that active units is depend on bit representation of weight, but we can reduce active units about 50 precent.

• Journal of Korean Society of Environmental Engineers
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• v.36 no.9
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• pp.614-623
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• 2014

Customers water quality complaints by foreign substance in local water service can be able to call the main cause bring the distrust for tap water and inhibiting the rate of drinking water. In this study, foreign substances were collected in the target region. Foreign objects were subjected to qualitative and quantitative analysis of compounds and elements components to reveal the cause of detection. Also, resolve the complaints by foreign substance and improve the reliability for tap water providing high quality water supply scheme. Collected substances at the water quality complaint area were included in inorganic compounds due to internal corrosion and aging pipeline, as well as organic compounds containing a large amount of carbon (C) and oxygen (O) component. To decide and reduce for foreign substance, objective assessment of pipe condition in target area was required.

• Journal of Korea Multimedia Society
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• v.16 no.12
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• pp.1427-1438
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• 2013

We have developed a 128-bit stream cipher algorithm composed of the 5-stage pipeline, capable of real-time processing, confidentiality and integrity. The developed stream cipher is a stream cipher algorithm that makes the final 128-bit ciphers through a whitening process after making the ASR 277 bit and SHACAL-2 and applying them to the CFB mode. We have verified the hardware performance of the proposed stream cipher algorithm with Modelsim 6.5d and Quartus II 12.0, and the result shows that the hardware runs at 33.34Mhz(4.27Gbps) at worst case. According to the result, the new cipher algorithm has fully satisfied the speed requirement of wireless Internet and sensor networks, and DRM environment. Therefore, the proposed algorithm with satisfaction of both confidentiality and integrity provides a very useful ideas.

• Journal of Sensor Science and Technology
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• v.8 no.6
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• pp.461-468
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• 1999

In this paper, we have implemented a gas recognition system for classification and identification of explosive gases such as methane, propane, and butane using a sensor array and an artificial neural network. Such explosive gases which can be usually detected in the oil factory and LPG pipeline are very dangerous for a human being. We analyzed the characteristics of a multi-dimensional sensor signals obtained from the nine sensors using the principal component analysis(PCA) technique. Also, we implemented a gas pattern recognizer using a multi-layer neural network with error back propagation learning algorithm, which can classify and identify the sorts of gases and concentrations for each gas. The simulation and experimental results show that the proposed gas recognition system is effective to identify the explosive gases. And also, we used DSP board(TMS320C31) to implement the proposed gas recognition system using the neural network for real time processing.

• Journal of the Korean GEO-environmental Society
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• v.14 no.5
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• pp.15-22
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• 2013

The submarine pipe, which is one of the most important coastal structures, is widely used in the development of coastal and ocean engineering. The scour of the submarine pipe occurs due to the wave and the current according to the state of the sea bed. The scour affects the submarine pipe and causes it to undergo settlement and fatigue. It is difficult to predict the local scour under complicated and various conditions of the coastal environment, even though many researches on the scour of the submarine pipe have been studied in recent years. This study analyzed the scour depth around a submarine pipe by using the Neural Network technique. The back-propagation algorithms was used to train the Neural Network. The 58 simulating experimental data for the performance and validation of the Neural Network technique were analyzed in this study. Then, the regression analysis for the same data was performed in this study to predict and compare with the Neural Network technique for the scour depth.

• Journal of the Korea Computer Graphics Society
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• v.29 no.4
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• pp.17-24
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• 2023

In computer graphics and computer vision research and its applications, various representations of 3D objects, such as point clouds, voxels, or triangular meshes, are used depending on the purpose. The need for animating characters using these representations is also growing. In a typical animation pipeline called skeletal animation, "skinning weight painting" is required to determine how joints influence a vertex on the character's skin. In this paper, we introduce a neural network for automatically performing skinning weight painting for characters represented in various formats. We utilize signed distance fields (SDF) to handle different representations and employ graph neural networks and multi-layer perceptrons to predict the skinning weights for a given point.

• Fire Science and Engineering
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• v.17 no.1
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• pp.8-20
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• 2003

Natural gas has been supplied through underground pipelines and valve stations as a new city gas in Seoul. In contrast to its handiness the natural gas has very substantial hazards due to fires and explosions occurring from careless treatments or malfunctions of the transporting system. The main objectives of this study are to identify major hazards and to perform risk assessments after assessing reliabilities of the composing units in dealing with typical pipeline networks. there-fore two method, fault tree analysis ;1nd event tree analysis, are used here. Random valve stations are selected and considered its situation in location. The value of small leakage, large rupture, and no supply of liquefied natural gas is estimated as that of top event. By this calculation the values of small leakage are 3.29 in I)C valve station, 1.41 in DS valve station, those of large rup-lure are $1.90Times10_{-2}$ in DC valve station, $2.32$\times$10^{-2}$ in DS valve station, and those of no supply of LNG to civil gas company are $2.33$\times$10 ^{-2}$ , $2.89$\times$10^{-2}$ in each valve station. And through minimal cut set we can find the parts that is important and should be more important in overall system. In DC valve station one line must be added between basic event 26,27 because the potential hazard of these parts is the highest value. If it is added the failure rate of no supply of LNG is reduced to one fourth. In DS valve station the failure rate of basic event 4 is 92eye of no supply of LNG. Therefore if the portion of this part is reduced (one line added) the total failure rate can be decreased to one tenth. This analytical study on the risk assessment is very useful to prepare emergency actions or procedures in case of gas accidents around underground pipeline networks and to establish a resolute gas safety management system for loss prevention in Seoul metropolitan area.

• Proceedings of the Korea Water Resources Association Conference
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• 2008.05a
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• pp.500-504
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• 2008

The objective of this paper is to evaluate the feasibility of using an optimization model as a effective way to search conjunctive operation scheme to meet two conditions; one is to minimize the electric cost for pumping and another is to meet the water demand for satisfying customers. The feasibility is confirmed as comparing the best combinations of pumps between multi-regional water supply networks from multiple sources which are obtained through an optimization modeling and EPAnet modeling. KModsim model, a network optimization model, was used to determine conjunctive operation scheme in the pipe system. KModsim, based on Lagrangian Relaxation algorithm, is useful for modeling network system and obtaining simultaneously pump combination and water allocation with given input option such as energy unit cost supplying from a source into a consumer, operating pumping combination. This study develops the procedure of determining optimal conjunctive operation scheme with using KModsim model. As a study region, the water supplying systems of the Geojae-city in the Geongsang Namdo Province was selected and investigated. The EPAnet hydraulic simulation result(Ryu et al, 2007, KSWW) gave input data for optimization model; energy unit price(won/$m^3$), water service available area etc.. It was assured that the combination of pump operation through optimum conjunctive operation is to be optimum scheme to obtain the best economic water allocation with comparison to the hydraulic simulation result such as electric cost and pump combination cases. The results obtained through the study are as follows. First, It was found that a well-allocated water supply scheme, the best combination of pump operation through optimum joint operation, promises to save the electric cost and satisfy all operational goals such as stability and revenues during the period. Second, an application of KModSim, a network model, gave the amount of water allocation from each source to a consumer with consideration of economic supply. Finally, in a service area available to supply through conjunctive operation of existing inter-regional water supply networks within short distance, a conjunctive operation is useful for determining each transmission pipeline's service area and maximizing the effectiveness of optimizations in pumping operation time.

• Journal of Korea Water Resources Association
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• v.46 no.7
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• pp.745-754
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• 2013

The systematic analysis and evaluation of required energy in the processes of drinking water production and supply have attracted considerable interest considering the need to overcome electricity shortage and control greenhouse gas emissions. On the basis of a review of existing research results, a practical method is developed in this study for evaluating energy in water supply networks. The proposed method can be applied to real water supply systems. A model based on the proposed method is developed by combining the hydraulic analysis results that are obtained using the EPANET2 software with a mathematical energy model on the MATLAB platform. It is suggested that performance indicators can evaluate the inherent efficiency of water supply facilities as well as their operational efficiency depending on the pipeline layout, pipe condition, and leakage level. The developed model is validated by applying it to virtual and real water supply systems. It is expected that the management of electric power demand on the peak time of water supply and the planning of an energy-efficient water supply system can be effectively achieved by the optimal management of energy by the proposed method in this study.