• Proceedings of the KIEE Conference
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• 2005.07e
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• pp.12-15
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• 2005

The subject of this research is not only to examine effects on electrical wiring that voltage drops make in low voltage load facilities found in apartments, buildings street lightings, factories, and etc, but also to discuss the voltage drops computation program on distributed random loads to optimize their safety and economy.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.6
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• pp.206-219
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• 1996

This paper describes a data structure and evaluation algorithm to improve the perofmrances MOS logic-with-timing simulation in computation and accuracy. In order to efficiently simulate the logic and timing of driver-load networks, (1) a tree data structure to represent the mutual interconnection topology of switches and nodes in the driver-lod network, and (2) an algebraic modeling to efficiently deal with the new represetnation, (3) an evaluation algorithm to compute the linear resistive and capacitive behavior with the new modeling of driver-load networks are developed. The higher modeling presented here supports the structural and functional compatibility with the linear switch-level to simulate the logic-with-timing of digital MOS circuits at a mixed-level. This research attempts to integrate the new approach into the existing simulator RSIM, which yield a mixed-klevel logic-with-timing simulator MIXIM. The experimental results show that (1) MIXIM is a far superior to RSIM in computation speed and timing accuracy; and notably (2) th etiming simulation for driver-load netowrks produces the accuracy ranged within 17% with respect ot the analog simulator SPICE.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.5
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• pp.2403-2407
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• 2012

Finite number of pile elements are considered in load transfer method. And section force and movement of each pile element are computed by considering compatibilities between pile displacement and the load transfer along a pile and between displacement and resistance at the tip of the pile. For the conventional load transfer method, large amount of computations due to iterations are needed. Formulation of finite difference equation from the differential equation which depicts pile behavior under axial loading was accomplished in order to simplify the computation for obtaining pile section forces and displacements. By comparing the results between the simplified computation method and the reported data, there was no difference between the two results.

• Proceedings of the Korean Geotechical Society Conference
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• 2006.03a
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• pp.1287-1294
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• 2006

A pile is compressed with settlements when loading and bearing capacity is altered along relative displacement of pile/soil on settlement and compression. Settlements of pile displaying limit skin friction is different from displaying tip resistance. Therefore, it is an error in traditional method that bearing capacity of pile is estimated from the sum of limit skin fraction and tip resistance. Accordingly, development of design method considering behavior of load-settlement is needed. In this study, we would like to establish the base for development of design method considering bearing capacity altering along displacement on settlement and compression. For this, we established system and substance of design method. And in order to establish relationship of load-settlement of pile on the type of soil, we analyzed and arranged existing database and pile loading test. On design method, settlement is assumed gradually on each capacity level being assumed gradually. Bearing capacity developing on the pile is obtained on each settlement level. Until the obtained bearing capacity will be equal to assumed capacity, this process is continued with increasing settlement. Load-settlement curve for soil classification is sketched in the process computing settlement on assumed capacity. This design method will be materialized by computation program.

• Journal of KIISE:Computer Systems and Theory
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• v.28 no.12
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• pp.632-641
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• 2001

In this paper, we introduce new methods for hiding computation overheads involved in load redistributing for parallel computer of hypercube, mesh and tree topologies. The basic idea is either coalescing some phases of load redistributing to overlap the transfer on different links or dividing each phase into steps to pipeline the transfer of load unit by unit for maximum utilization of links. They proved effective in making links busy transmitting load as soon as possible, hence reducing the computation overheads involved in balancing. Proposed techniques experimented on hypercube, mesh or tree topologies reduce communication overheads by 20% to 50% compared with known methods.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.2
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• pp.189-196
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• 1994

This paper describes a parallel computing algorithm in Gauss elimination of Jacobian matrix to large-scale power system. The structure of Jacobian matrix becomes different according to ordering method of buses. In sequential computation buses are ordered to minimize the number of fill-in in the triangulation of the Jacobian matrix. The proposed method develops the parallelism in the Gauss elimination by using ND(nested dissection) ordering. In this procedure the level structure of the power system network is transformed to be long and narrow by using end buses which results in balance of computing load among processes and maximization of parallel computation. Each processor uses the sequential computation method to preserve the sqarsity of matrix.

• The Journal of the Korea Contents Association
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• v.6 no.12
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• pp.136-146
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• 2006

In Wireless Sensor Network(WSN) a sensor node transfers sensing data to the base-node through multi-hop because of the limited transmission range. Also because of the limited energy of the sensor node, the sensor nodes are required to consume their energy evenly to prolong the lifetime of the network. LMPR is a routing protocol for WSN, LMPR configures the network autonomously based on level which is the depth from the base-node, and distributes the transmission and computation load of the network to each sensor node. This paper implements LMPR on TinyOS and experiments on the performance of LMPR in WSN. As the result, the average of the received rate of LMPR is 91.39% and LMPR distributes the load of the transmission and computation about 4.6 times compare to the shortest cost routing protocol. We expect LMPR evenly distributes the transmission and computation load of the network to each node, and the lifetime of the network will be longer than it used to be.

• Journal of Broadcast Engineering
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• v.10 no.1 s.26
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• pp.83-102
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• 2005

The problem of video scheduling is analyzed in the framework of divisible load scheduling. A divisible load can be divided into any number of fractions (parts) and can be processed/computed independently on the processors in a distributed computing system/network, as there are no precedence relationships. In the video scheduling, a frame can be split into any number of fractions (tiles) and can be processed independently on the processors in the network, and then the results are collected to recompose the single processed frame. The divisible load arrives at one of the processors in the network (root processor) and the results of the computation are collected and stored in the same processor. In this problem communication delay plays an important role. Communication delay is the time to send/distribute the load fractions to other processors in the network. and the time to collect the results of computation from other processors by the root processors. The objective in this scheduling problem is that of obtaining the load fractions assigned to each processor in the network such that the processing time of the entire load is a minimum. We derive closed-form expression for the processing time by taking Into consideration the communication delay in the load distribution process and the communication delay In the result collection process. Using this closed-form expression, we also obtain the optimal number of processors that are required to solve this scheduling problem. This scheduling problem is formulated as a linear pro-gramming problem and its solution using neural network is also presented. Numerical examples are presented for ease of understanding.

• Proceedings of the KIEE Conference
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• 1996.07a
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• pp.68-70
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• 1996

In this paper, an efficient parallel computation method for solving large sparse systems of linear algebraic equations by using Cholesky's method in the finite element method is studied. The methods of minimizing the number of fill-ins in the factorization process of factorization are investigated for minimizing the amount of memory and computation time. The parallel programming is implemented under the PVM(Parallel Virtual Machine) environment. The method of load-distribution is studied for minimizing the computation time and the communication time.

• Proceedings of the IEEK Conference
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• 2000.07a
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• pp.314-317
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• 2000

Cluster system provides attractive scalability in terms of computation power and memory size. With the advances in high speed computer network technology, cluster systems are becoming increasingly competitive compared to expensive parallel machines. In parallel processing program, each task load is difficult to predict before running the program and each task is interdependent each other in many ways. Load imbalancing induces an obstacle to system performance. Most of researches in load balancing were concerned with distributed system but researches in cluster system are few. In cluster system, the dynamic load balancing algorithm which evaluates each processor's load in runtime is purpose that the load of each node are evenly distributed. But, if communication cost or node complexity becomes high, it is not effective method for all nodes to attend load balancing process. In that circumstances, it is good to reduce the number of node which attend to load balancing process. We have modeled cluster systems and proposed marginal dynamic load balancing algorithms suitable for that circumstances.