• Proceedings of the KIPE Conference
• /
• 2000.07a
• /
• pp.290-293
• /
• 2000

In this paper the algorithm which controls output voltage and power factor independently and the algorithm which controls output voltage with fixed unity power factor are compared and analyzed. These algorithms are applied to single-phase AC/DC parallel are applied to single-phase AC/DC parallel converters for a high speed train system. The control characteristic of the algorithms are compared and analyzed with respect to the output voltage and input power factor when system parameters vary.

• Structural Engineering and Mechanics
• /
• v.23 no.4
• /
• pp.325-337
• /
• 2006

A hybrid structural design and optimization methodology that combines the strengths of genetic algorithms, local search techniques, and parallel computing is developed to evolve optimal truss systems in this research effort. The primary objective that is met in evolving near-optimal or optimal structural systems using this approach is the capability of satisfying user-defined design criteria while minimizing the computational time required. The application of genetic algorithms to the design and optimization of truss systems supports conceptual design by facilitating the exploration of new design alternatives. In addition, final shape optimization of the evolved designs is supported through the refinement of member sizes using local search techniques for further improvement. The use of the hybrid approach, therefore, enhances the overall process of structural design. Parallel computing is implemented to reduce the total computation time required to obtain near-optimal designs. The support of human-computer interaction during layout optimization and local optimization is also discussed since it assists in evolving optimal truss systems that better satisfy a user's design requirements and design preferences.

• International Journal of Computer Science & Network Security
• /
• v.21 no.4
• /
• pp.1-8
• /
• 2021

The subject of navigation has drawn a large interest in the last few years. Navigation problem (or path planning) finds the path between two points, source location and destination location. In smart cities, solving navigation problem is essential to all residents and visitors of such cities to guide them to move easily between locations. Also, the navigation problem is very important in case of moving robots that move around the city or part of it to get some certain tasks done such as delivering packages, delivering food, etc. In either case, solution to the navigation is essential. The core to navigation systems is the navigation algorithms they employ. Navigation algorithms can be classified into navigation algorithms that depend on maps and navigation without the use of maps. The map contains all available routes and its directions. In this proposal, we consider the first class. In this paper, we are interested in getting path planning solutions very fast. In doing so, we employ a parallel platform, Reconfigurable mesh (R-Mesh), to compute the path from source location to destination location. R-Mesh is a parallel platform that has very fast solutions to many problems and can be deployed in moving vehicles and moving robots. This paper presents two algorithms for path planning. The first assumes maps with linear streets. The second considers maps with branching streets. In both algorithms, the quality of the path is evaluated in terms of the length of the path and the number of turns in the path.

• 한국전산유체공학회:학술대회논문집
• /
• 2006.05a
• /
• pp.178-181
• /
• 2006

• Proceedings of the KIEE Conference
• /
• 2001.07e
• /
• pp.134-140
• /
• 2001

Parallel processing has the potential to be cost effectively used on computationally intense power system problems. But this technology is not still available is not only parallel computer but also parallel processing scheme. Testing these algorithms to ensure accuracy, and evaluation of their performance is also an issue. Although a significant amount of parallel algorithms of power system problem have been developed in last decade, actual testing on processor architectures lies in the beginning stages. This paper presents the parallel processing algorithm to supply the base being able to treat power flow by newton's method by the distributed memory type parallel computer. This method is to assign and to compute teared blocks of sparse matrix at each parallel processors. The testing to insure accuracy of developed method have been done on serial computer by trying to simulate a parallel environment.

• Proceedings of the IEEK Conference
• /
• 2000.07a
• /
• pp.289-293
• /
• 2000

We propose two new algorithms for parallelism-independent scheduling. The machine code generated from the compiler using these algorithms in its scheduling phase is parallelism-independent code, executable in minimum time regardless of the number of the processors in the parallel computer. Our new algorithms have the following phases: finding the minimum number of processors on which the program can be executed in minimal time, scheduling by an heuristic algorithm for this predefined number of processors, and serialization of the parallel schedule according to the earliest start time of the tasks. At run time tasks are taken from the serialized schedule and assigned to the processor which allows the earliest start time of the task. The order of the tasks decided at compile time is not changed at run time regardless of the number of the available processors which means there is no out-of-order issue and execution. The scheduling is done predominantly at compile time and dynamic scheduling is minimized and diminished to allocation of the tasks to the processors. We evaluate the proposed algorithms by comparing them in terms of schedule length to the CP/MISF algorithm. For performance evaluation we use both randomly generated DAGs (directed acyclic graphs) and DACs representing real applications. From practical point of view, the algorithms we propose can be successfully used for scheduling programs for in-order superscalar processors and shared memory multiprocessor systems. Superscalar processors with any number of functional units can execute the parallelism-independent code in minimum time without necessity for dynamic scheduling and out-of-order issue hardware. This means that the use of our algorithms will lead to reducing the complexity of the hardware of the processors and the run-time overhead related to the dynamic scheduling.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.65 no.3
• /
• pp.171-177
• /
• 2016

Noise problem that occurs in living environment is a big trouble in the economic, social and environmental aspects. In this paper, the filtered-X LMS algorithms, the adjoint LMS algorithms, and the robust adjoint LMS algorithms will be introduced for applications in active noise control(ANC). The filtered-X LMS algorithms is currently the most popular method for adapting a filter when the filter exits a transfer function in the error path. The adjoint LMS algorithms, that prefilter the error signals instead of divided reference signals in frequency band, is also used for adaptive filter algorithms to reduce the computational burden of multi-channel ANC systems such as the 3D space. To improve performance of the adjoint LMS ANC system, an off-line measured transfer function is connected parallel to the LMS filter. This parallel-fixed filter acts as a noise controller only when the LMS filter is abnormal condition. The superior performance of the proposed system was compared through simulation with the adjoint LMS ANC system when the adaptive filter is in normal and abnormal condition.

• The Transactions of the Korean Institute of Electrical Engineers P
• /
• v.51 no.2
• /
• pp.55-59
• /
• 2002

Parallel processing is able to be used effectively on computationally intense power system problems. But this technology is not still available is not only parallel computer but also parallel processing scheme. Testing these algorithms to ensure accuracy, and evaluation of their performance is also an issue. Although a significant amount of parallel algorithms of power system problem have been developed in last decade, actual testing on parallel computer architectures lies in the beginning stages because no clear cut paths. This paper presents Jacobian modeling method to supply the base being able to treat power flow by newton's method by the computer. This method is to assign and to compute teared blocks of sparse matrix at each parallel processors. The testing to insure accuracy of developed method have been done on serial computer by trying to simulate a parallel environment.

• Journal of the Korea Safety Management & Science
• /
• v.3 no.3
• /
• pp.191-200
• /
• 2001

Parallel Genetic Algorithms partition the whole population into several sub-populations and search the optimal solution by exchanging the information each others periodically. Distributed Genetic Algorithm, one of Parallel Genetic Algorithms, divides a large population into several sub-populations and executes the traditional Genetic Algorithm on each sub-population independently. And periodically promising individuals selected from sub-populations are migrated by following the migration interval and migration rate to different sub-populations. In this paper, for the Travelling Salesman Problems, we analyze and compare with Distributed Genetic Algorithms using different Genetic Algorithms and using same Genetic Algorithms on each separated sub-population The simulation result shows that using different Genetic Algorithms obtains better results than using same Genetic Algorithms in Distributed Genetic Algorithms. This results look like the property of rapidly searching the approximated optima and keeping the variety of solution make interaction in different Genetic Algorithms.

• Journal of applied mathematics & informatics
• /
• v.5 no.1
• /
• pp.141-152
• /
• 1998

Based on the geometric representation an efficient al-gorithm is designed to find all articulation points of a permutation graph. The proposed algorithm takes only O(n log n) time and O(n) space where n represents the number of vertices. The proposed se-quential algorithm can easily be implemented in parallel which takes O(log n) time and O(n) processors on an EREW PRAM. These are the first known algorithms for the problem on this class of graph.