• Nuclear Engineering and Technology
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• 제53권7호
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• pp.2162-2173
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• 2021

In this paper, the coupling of fine-mesh computational fluid dynamics (CFD) thermal-hydraulics (TH) code and neutronics code is achieved using the Ansys Fluent User Defined Function (UDF) for code development, including parallel meshing mapping, data computation, and data transfer. Also, some CFD schemes are designed for mesh mapping and data transfer to guarantee physical conservation in the coupling computation. Because there is no rigorous research that gives robust guidance on the various CFD schemes that must be obtained before the fine-mesh coupling computation, this work presents a quantitative analysis of the CFD meshing and mapping schemes to improve the accuracy of the value and location of key physical prediction. Furthermore, the effect of the sub-pin scale coupling computation is also studied. It is observed that even the pin-resolved coupling computation can also create a large deviation in the maximum value and spatial locations, which also proves the significance of the research on mesh mapping and data transfer for CFD code in a coupling computation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권12호
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• pp.4081-4098
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• 2022

With the aim of tackling the contradiction between computation intensive industrial applications and resource-weak Edge Devices (EDs) in Industrial Internet of Things (IIoT), a novel computation task offloading scheme in SDIN-enabled MEC based IIoT is proposed in this paper. With the aim of reducing the task accomplished latency and energy consumption of EDs, a joint optimization method is proposed for optimizing the local CPU-cycle frequency, offloading decision, and wireless and computation resources allocation jointly. Based on the optimization, the task offloading problem is formulated into a Mixed Integer Nonlinear Programming (MINLP) problem which is a large-scale NP-hard problem. In order to solve this problem in an accessible time complexity, a sub-optimal algorithm GPCOA, which is based on hybrid evolutionary computation, is proposed. Outcomes of emulation revel that the proposed method outperforms other baseline methods, and the optimization result shows that the latency-related weight is efficient for reducing the task execution delay and improving the energy efficiency.

• International Journal of Computer Science & Network Security
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• 제23권8호
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• pp.146-158
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• 2023

Smart City is gaining attention with the advancement of Information and Communication Technology (ICT). ICT provides the basis for smart city foundation; enables us to interconnect all the actors of a smart city by supporting the provision of seamless ubiquitous services and Internet of Things. On the other hand, Crowdsourcing has the ability to enable citizens to participate in social and economic development of the city and share their contribution and knowledge while increasing their socio-economic welfare. This paper proposed a hybrid model which is a compound of human computation, machine computation and citizen crowds. This proposed hybrid model uses knowledge-based crowdsourcing that captures collaborative and collective intelligence from the citizen crowds to form democratic knowledge space, which provision solutions in areas of civic innovations. This paper also proposed knowledge-based crowdsourcing framework which manages knowledge activities in the form of human computation tasks and eliminates the complexity of human computation task creation, execution, refinement, quality control and manage knowledge space. The knowledge activities in the form of human computation tasks provide support to existing crowdsourcing system to align their task execution order optimally.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1990년도 추계학술대회 논문집 학회본부
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• pp.239-243
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• 1990

This paper presents a algorithm to improve accuracy and reliability in state estimation of contaminated bad data. The conventional algorithms for detection of bad data confront the problems of excessive memory requirements and long computation time. In order to overcome measurement compensation approach is proposed to reduce computation time and partitioned measurement error model has the advantage of remarkable reduction in computation time and memory requirements in estimated error computation. The proposed algorithm has been tested for IEEE sample systems, which shows its applicability to on-line power systems.

• Journal of applied mathematics & informatics
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• 제6권2호
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• pp.649-659
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• 1999

This paper presents a parallel implementation of stiff-ness matrix calculation based on the processor farm model on a net-work of workstations running PVM programming environment. As the computational characteristics of stiffnes matrix exhibits good po-tentials for effective prallel computation the performance improve-ment is show to be almost linear with the number of sorkstations involved in the computation.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.2196-2199
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• 2003

With the development of digital signal processor(DSP), digital pulse compressor (DPC) is commonly used in radar systems. A DPC is implemented by using finite impulse response(FIR) filter algorithm in time domain or fast Fourier transform(FFT) algorithm in frequency domain. This paper compares the computation complexity tot these two methods and calculates boundary Fm filter taps that determine which of the two methods is better based on computation amount. Also, it shows that the boundary FIR filter taps for DSP, ADSP21060, and those for computation complexity have similar characteristic.

• 대한전기학회논문지
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• 제40권2호
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• pp.144-153
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• 1991

This paper presents an algorithm to improve accuracy and reliability in the state estimation of contaminated bad data. The conventional algorithms for detection of bad data have the problems of excessive memory requirements and long computation time. In order to overcome these problems, a measurement compensation approach is proposed to reduce computation time, and the partitioned measurement error model has the advantage of remarkable reduction in computation time and memory requirements in estimated error computation. The proposed algorithm has been tested for IEEE sample systems, which shows its applicability to on-line power systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권12호
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• pp.5723-5743
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• 2018

The evolving internet-based services demand high-speed data transmission in conjunction with scalability. The next generation optical network has to exploit artificial intelligence and cognitive techniques to cope with the emerging requirements. This work proposes a novel way to solve the dynamic provisioning problem in optical network. The provisioning in optical network involves the computation of routes and the reservation of wavelenghs (Routing and Wavelength assignment-RWA). This is an extensively studied multi-objective optimization problem and its complexity is known to be NP-Complete. As the exact algorithms incurs more running time, the heuristic based approaches have been widely preferred to solve this problem. Recently the software-defined networking has impacted the way the optical pipes are configured and monitored. This work proposes the dynamic selection of path computation algorithms in response to the changing service requirements and network scenarios. A software-defined controller mechanism with a novel packet matching feature was proposed to dynamically match the traffic demands with the appropriate algorithm. A software-defined controller with Path Computation Element-PCE was created in the ONOS tool. A simulation study was performed with the case study of dynamic path establishment in ONOS-Open Network Operating System based software defined controller environment. A java based NOX controller was configured with a parent path computation element. The child path computation elements were configured with different path computation algorithms under the control of the parent path computation element. The use case of dynamic bulk path creation was considered. The algorithm selection method is compared with the existing single algorithm based method and the results are analyzed.

• 대한수학회지
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• 제52권4호
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• pp.797-819
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• 2015

A trapdoor discrete logarithm group is a cryptographic primitive with many applications, and an algorithm that allows discrete logarithm problems to be solved faster using a pre-computed table increases the practicality of using this primitive. Currently, the distinguished point method and one extension to this algorithm are the only pre-computation aided discrete logarithm problem solving algorithms appearing in the related literature. This work investigates the possibility of adopting other pre-computation matrix structures that were originally designed for used with cryptanalytic time memory tradeoff algorithms to work as pre-computation aided discrete logarithm problem solving algorithms. We find that the classical Hellman matrix structure leads to an algorithm that has performance advantages over the two existing algorithms.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2001년도 춘계학술대회논문집E
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• pp.512-517
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• 2001

In this study, spin-up flows in a rectangular container are analysed by using three-dimensional computation. In the numerical computation, we use the parallel computer system of PC-cluster type. We compared our results with those obtained by two-dimensional computation. Effect of velocity and vorticity on the flow is studied. The result shows that two-dimensional solution is in good agreement with the 3-D result. Attention is given to the region where the 3-D flow is significant.