• 대한기계학회:학술대회논문집
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• 대한기계학회 2004년도 추계학술대회
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• pp.1448-1453
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• 2004

The major parameters governing the fluid dynamical and thermo-dynamical behavior in the large pipeline network system are friction loss and the pipeline length. But in local pipeline networks and relatively short distance pipeline system, secondary loss and the considerations of the moving states of the fluid machine are also important. One of the major element in local pressure control system is pressure regulator. It causes the variations of the physical properties in that pipeline system. Especially, as there is not enough information to obtain reliable physical property values such as density, temperature etc. at the downstream of the pressure regulator, It is hard to calculate accurate solution in the pipeline network analysis. In this study, some numerical approaches to investigate the critical-flow-characteristics of the pressure regulator have been done and the detail examinations and considerations of the pressure regulator as a pipeline network elements according to the variations of the inlet-outlet pressure ratio have been carried. Finally the flow-flied distributions, relations and critical-flow-characteristics have been studied. in detail and the 1D analytic method to analyze critical pipe flow have been investigated

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1998년도 춘계학술발표회논문집(1)
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• pp.641-646
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• 1998

In order to enhance the dynamic and interactive simulation capability of a system thermal hydraulic code for nuclear power plant, applicability of flow network models in SINDA/FLUIN $T^{™}$ has been tested by modeling feedwater system and coupling to DSNP which is one of a system thermal hydraulic simulation code for a pressurized heavy water reactor. The feedwater system is selected since it is one of the most important balance of plant systems with a potential to greatly affect the behavior of nuclear steam supply system. The flow network model of this feedwater system consists of condenser, condensate pumps, low and high pressure heaters, deaerator, feedwater pumps, and control valves. This complicated flow network is modeled and coupled to DSNP and it is tested for several normal and abnormal transient conditions such turbine load maneuvering, turbine trip, and loss of class IV power. The results show reasonable behavior of the coupled code and also gives a good dynamic and interactive simulation capabilities for the several mild transient conditions. It has been found that coupling system thermal hydraulic code with a flow network code is a proper way of upgrading simulation capability of DSNP to mature nuclear plant analyzer (NPA).

• 전기학회논문지
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• 제56권8호
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• pp.1373-1381
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• 2007

This paper presents a graphical windows-based software for the education and training of transmission network charge. The motivation for the development of the simulator is to provide students with a simple and useable tool for gaining an intuitive feel for transmission network charge. The developed simulator consists of the main module (MMI, GUI), the power flow module (PF), the power flow tracing module (PFT), and usage cost DB module (UCD). Each module has a separate graphical and interactive interfacing window. The developed simulator provides with two power system analysis methods (i.e., DC-PF and Modified DC-PF) and supports the PSS/E input data format to load input data of power system. Also, power flow tracing can be calculate using four methods such as "Felix Wu", "Modified Felix Wu", "DCLF ICRP", and "Reverse MW mile". Results of calculation for transmission usage cost are displayed and compared on the window through the table and/or chart. Therefore, the developed simulator can be utilize as a useful tool for effective education and training of transmission network charge.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.275-280
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• 2005

The principal context of this research is the approach to an artificial neural network algorithm which solves multivariable nonlinear equation systems by estimating the state of line power flow. First a dynamical neural network with feedback is used to find the minimum value of the objective function at each iteration of the state estimator algorithm. In second step a two-layer neural network structures is derived to implement all of the different matrix-vector products that arise in neural network state estimator analysis. For hardware requirements, as they relate to the total number of internal connections, the architecture developed here preserves in its structure the pronounced sparsity of power networks for which state the estimator analysis is to be carried out. A principal feature of the architecture is that the computing time overheads in solution are independent of the dimensions or structure of the equation system. It is here where the ultrahigh-speed of massively parallel computing in neural networks can offer major practical benefit.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2003년도 추계학술발표논문집 (중)
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• pp.639-642
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• 2003

본 논문에서는 청소로봇이 전 청소 영역을 CCPP(Complete Coverage Path Planning)를 이용해 경로를 생성한 후 재 경로계획 시 장애물의 미소한 변화로도 기존에 생성한 전 경로패턴을 바꾸지 않고 수정 할 수 있는 CD(Cell Decomposition)와 FN(Flow Network)을 이용한 CCPP 방식을 제안 하였다. 그리고 제안된 경로 계획에 대해 시뮬레이션으로 결과를 제시하였다.

• 한국통신학회논문지
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• 제10권2호
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• pp.61-68
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• 1985

本 論文에서는 Network flow理論의 한 方法으로 Primal法을 利用하여 流量, 壓力配分의 最適化를 提案하였다. 이 配分制御의 目的은 正常壓力과 最小費用流이며 流量과 壓力問題의 解法은 Primal法을 使用하여 求했다.

• 한국IT서비스학회지
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• 제11권1호
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• pp.247-272
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• 2012

Social Network Service(SNS) is a kind of advanced Internet service that acts as personal media. This study was intended to find out the structural relationships among factors affecting the usage of social network services by extending the Technology Acceptance Model(TAM). For this purpose, the variable 'Flow' was first integrated into the TAM in order to understand the internal motivations of users. And then the external factors of SNS usage were derived from the perspective of users, contents, and media side of SNS, and finally the dependent variable was set with the intention of sustainable use. Then these factors were carefully integrated into a structural model. We expect the findings of this study will be very helpful for the internet marketing professionals, SNS developers, and the others.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 심포지엄 논문집 정보 및 제어부문
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• pp.65-67
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• 2004

Change of state of Channel between two wireless terminals which is caused by noise and multiple environmental conditions for happens frequently from the Wireles Network. So, When it is like that planning a wireless network protocol or performance analysis, it follows to change of state of time-varying channel and packet the analysis against a transmission efficiency is necessary. In this paper, analyzes transmission time of a packet and a packet in a time-varying and packet based Wireless Network. To reflecte the feature of the time-varying channel, we use a Signal Flow Graph model. From the model the mean of transmission time and the mean of queue length of the packet are analyzed in terms of the packet distribution function, the packet transmission service time, and the PER of the time-varying channel.

• International Journal of Reliability and Applications
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• 제2권1호
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• pp.73-80
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• 2001

A network, where links have different capacities, is considered to be in functioning state if a specified amount of flow can be transmitted through the network. In this paper, we consider the measures of importance of a link in such networks. We define the structural importance and reliability importance of a link when the required amount of flow is given. We also present the performability importance, which can be used to determine which links should be improved first in order to make the greatest improvement in the expected maximum flow of network. Numerical examples are presented as well for illustrative purpose.

• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2021년도 추계학술발표대회
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• pp.878-879
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• 2021

Most state-of-the-art CNNs for action recognition are based on a two-stream architecture: RGB frames stream represents the appearance and the optical flow stream interprets the motion of action. However, the cost of optical flow computation is very high and then it increases action recognition latency. We introduce a design strategy for action recognition inspired by a two-stream network and teacher-student architecture. There are two sub-networks in our neural networks, the optical flow sub-network as a teacher and the RGB frames sub-network as a student. In the training stage, we distill the feature from the teacher as a baseline to train student sub-network. In the test stage, we only use the student so that the latency reduces without computing optical flow. Our experiments show that its advantages over two-stream architecture in both speed and performance.