• Journal of the Korean Society of Safety
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• v.11 no.2
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• pp.150-159
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• 1996

In this paper, an A-team(Asynchronous Team ) based approach for Reactive power and volage control considering static security assessment in a power system with infrastructural deficiencies is proposed. Reactive power and voltage control problem is the one of optimally establishing voltage level given several constraints such as reactive generation, voltage magnitude, line flow, and other switchable reactive power sources. It can be formulated as a mixed-integer linear programming(MILP) problem without deteriorating of solution accuracy to a certain extent. The security assessment is to estimate the relative robustness of the system in Its present state through the evaluation of data provided by security monitoring. Deterministic approach based on AC load flow calculations is adopted to assess the system security, especially voltage security. A security metric, as a standard of measurement for power system security, producting a set of discrete values rather than binary values, is employed. In order to analyze the above two problems, reactive power/voltage control problem and static security assessment problem, in an integrated fashion for real-time operations, a new organizational structure, called an A-team, is adopted. An A-team is an organization for agents which ale all autonomeus, work in parallel and communicate asynchronously, which is well-suited to the development of computer-based, multi-agent systems for operations. This A-team based approach, although it is still in the beginning stage, also has potential for handling other difficult power system problems.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.3
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• pp.217-222
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• 2016

This study investigates the design, analysis, and implementation of the square-root extended Kalman filter by using an algorithm derived by combining the Potter or Carlson algorithm with the modified Gram-Schmidt algorithm, for sensorless speed control of a permanent-magnet synchronous motor. The sensitivity of the Kalman filter to round-off errors is a well-known problem. A possible way to address this limitation is by combining the square-root concept and Kalman filter that can improve the numerical performance and solve instability-related problems such as divergence. This paper presents the design and analysis of the implementation of such a square-root extended Kalman filter. To demonstrate the performance of the proposed filter, experimental results under several operating conditions, such as high and low speeds, reversal rotation, detuned parameters and load test, have been analyzed. Further, code sizes and operation times have been compared. Experimental results establish the performance of the proposed square-root extended Kalman filter-based estimation technique for sensorless speed control of a permanent-magnet synchronous motor.

• Journal of the Korean School Mathematics Society
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• v.16 no.3
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• pp.561-582
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• 2013

Meanwhile, the meaning has been emphasized in mathematics. But the meaning of meaning had not been clearly defined and the meaning classification had not been reported. In this respect, the meaning was classified as expressive and cognitive. Furthermore, it was reclassified as mathematical situation and real situation. Based on this classification, we investigated how student recognizes the meaning when solving mathematical modeling problem. As a result, we found that the understanding of cognitive meaning in real situation is more difficult than that of the other meaning. And we knew that understanding the meaning in solving of equation, has more difficulty than in expression of equation. Thus, to help students understanding the meaning in the whole process of mathematical modeling, we have to connect real situation with mathematical situation. And this teaching method through unit and measurement, will be an alternative method for connecting real situation and mathematical situation.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.1
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• pp.12-21
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• 2003

In this paper, we propose an on-line scheduling algorithm with the goal of maximizing the total reward of IRIS (Increasing Reward with Increasing Service) real-time tasks that have reward functions and arrive dynamically into the system. We focus on enhancing the performance of scheduling algorithm, which W.: based on the following two main ideas. First, we show that the problem to maximize the total reward of dynamic tasks can also be solved by the problem to find minimum of maximum derivatives of reward functions. Secondly, we observed that only a few of scheduled tasks are serviced until a new task arrives, and the rest tasks are rescheduled with the new task. Based on our observation, the Proposed algorithm doesn't schedules all tasks in the system at every scheduling print, but a part of tasks. The performance of the proposed algorithm is verified through the simulations for various cases. The simulation result showed that the computational complexity of proposed algorithm is$O(N_2)$ in the worst case which is equal to those of the previous algorithms, but close to O(N) on the average.

• Journal of Korea Spatial Information System Society
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• v.11 no.2
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• pp.79-88
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• 2009

The volume of memory to store real-time data stream is varied dynamically. Continuous queries processing the data stream must manage the storage volume dynamically. In previous research, according to current volume of data a general memory manager which allocates and releases memory by a page unit is researched.However, the method frequently executes page allocation and release to store data stream. Moreover, particularly delayed queries can monopolize many of pages because the method directly allocates pages when a query has not enough memory. Focusing on the problems in memory management systems, this research proposes a memory management method which reduces the frequency of allocation and release and uniformly distributes pages for queries. The method can reduce the frequency of allocation and release through allocation based on utilization ratio of pages in each query and prevent memory monopoly through memory allocation which considers query delay.

• The KIPS Transactions:PartD
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• v.10D no.3
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• pp.417-426
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• 2003

The problem of finding clusters in high dimensional data is well known in the field of data mining for its importance, because cluster analysis has been widely used in numerous applications, including pattern recognition, data analysis, and market analysis. Recently, a new framework, projected clustering, to solve the problem was suggested, which first select subdimensions of each candidate cluster and then each input point is assigned to the nearest cluster according to a distance function based on the chosen subdimensions of the clusters. We propose a new algorithm for subdimensional clustering of high dimensional data, each of the three major steps of which partitions the input points into several candidate clutters with proper numbers of points, filters the clusters that can not be useful in the next steps, and then merges the remaining clusters into the predefined number of clusters using a closeness function, respectively. The result of extensive experiments shows that the proposed algorithm exhibits better performance than the other existent clustering algorithms.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.3
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• pp.259-266
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• 2011

We present a new dual sequential approximate optimization (SAO) algorithm called SD-TDQAO (sequential dual two-point diagonal quadratic approximate optimization). This algorithm solves engineering optimization problems with a nonlinear objective and nonlinear inequality constraints. The two-point diagonal quadratic approximation (TDQA) was originally non-convex and inseparable quadratic approximation in the primal design variable space. To use the dual method, SD-TDQAO uses diagonal quadratic explicit separable approximation; this can easily ensure convexity and separability. An important feature is that the second-derivative terms of the quadratic approximation are approximated by TDQA, which uses only information on the function and the derivative values at two consecutive iteration points. The algorithm will be illustrated using mathematical and topological test problems, and its performance will be compared with that of the MMA algorithm.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.15 no.3
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• pp.159-166
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• 2003

In this study, we develop a finite element model to directly solve the Laplace equation while keeping the same computational efficiency as the models based on the extended mild-slope equation which has been widely used for calculation of wave transformation in shallow water. For this, the computational domain is discretized into finite elements with a single layer in the vertical direction. The velocity potential in the element is then expressed in terms of the potentials at the nodes located at water surface, and the Galerkin method is used to construct the numerical model. A common shape function is adopted in horizontal direction, and the cosine hyperbolic function in vertical direction, which describes the vertical behavior of progressive waves. The model was developed for vertical two-dimensional problems. In order to verify the developed model, it is applied to vertical two-dimensional problems of wave reflection and transmission. It is shown that the present finite element model is comparable to the models based on extended mild-slope equations in both computational efficiency and accuracy.

• The Journal of Korean Association of Computer Education
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• v.16 no.4
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• pp.55-62
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• 2013

Most of the APP market today, it is biased in the field of games and entertainment. In contrast, market-share of the educational APP is very low. This phenomenon is due to two major problems. The first is a decrease in the reuse because of the test of simple pattern. The second is difficult to consider user-level range that was learned previously. In this case it is necessary for students to do additional effort. This paper, propose an educational intelligent educational APP to solve the problems described above and shows implementation results. This system analyzes the stored results that have been saved to determine the area of vulnerability. Time-based Re-validation module helps long-term memory of student. The proposed system in this way directly supports self-directed learning. Therefore, the students can be able to relearn weak area autonomously. It results in improved academic achievement.

• Journal of the Korea Society of Computer and Information
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• v.20 no.4
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• pp.95-102
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• 2015

This paper proposes a simple algorithm for circuit minimization. There are currently two effective heuristics for circuit minimization, namely manual Karnaugh maps and computable Quine-McCluskey algorithm. The latter, however, has a major defect: the runtime and memory required grow $3^n/n$ times for every increase in the number of variables n. The proposed algorithm, however, extracts the prime implicants (PI) that cover minterms of a given Boolean function by deriving an implicants table based on frequency. From a set of the extracted prime implicants, the algorithm then eliminates redundant PIs again based on frequency. The proposed algorithm is therefore capable of minimizing circuits polynomial time when faced with an increase in n. When applied to various 3-variable and 4-variable cases, it has proved to swiftly and accurately obtain the optimal solutions.