• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.175-177
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• 2018

This paper proposes an algorithm to speed up block structure partition of quad tree plus binary tree (QTBT) in Joint Exploration Test Model (JEM) encoder. The proposed fast encoding of QTBT block partition employs three spatially neighbor coded blocks, such as left, top-left, and top of current block, to early terminate QTBT block structure pruning. The propose algorithm is organized based on statistical similarity of those spatially neighboring blocks, such as block depths and coded block types, which are coded with overlapped block motion compensation (OBMC) and adaptive multi transform (AMT). The experimental results demonstrate about 30% encoding time reduction with 1.3% BD-rate loss on average compared to the anchor JEM-7.1 software under random access configuration.

• The Journal of Information Technology and Database
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• v.6 no.2
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• pp.71-86
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• 1999

The performance of relational database is measured by the number of disk accesses necessary to transfer data from disk to main memory. The paper proposes to vertically partition relations into fragments and to allow attribute replication to reduce the number of disk accesses. To reduce the computational time, heuristic search method using genetic algorithm is used. Genetic algorithm used employs a rank-based-sharing fitness function and elitism. Desirable parameters of genetic algorithm are obtained through experiments and used to find the solutions. Solutions of attribute replication and attribute non-replication problems are compared. Optimal solutions obtained by branch and bound method and by heuristic solutions(genetic algorithm) are also discussed. The solution method proposed is able to solve large-sized problems within acceptable time limit and shows solutions near the optimal value.

• Convergence Security Journal
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• v.14 no.7
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• pp.59-64
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• 2014

We investigate $p(n){\cdot}2^{O(\sqrt{n})}$ algorithm for 0/1 knapsack problem where x is the total bit length of a list of sizes of n objects. The algorithm is adaptable of method that achieves a similar complexity for the partition and Subset Sum problem. The method can be applied to other optimization or decision problem based on a list of numerics sizes or weights. 0/1 knapsack problem can be used to solve NP-Complete Problems with pseudo-polynomial time algorithm. We try to apply this technique to bio-informatics problem which has pseudo-polynomial time complexity.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2146-2156
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• 2017

When a failure occurs in active distribution system, it will be isolated through the action of circuit breakers and sectionalizing switches. As a result, the network might be divided into several connected components, in which distributed generations could supply power for customers. Aimed at decreasing customer interruption cost, this paper proposes a theoretically optimal island partition model for such connected components, and a simplified but more practical model is also derived. The model aims to calculate a dynamic island partition schedule during the failure recovery time period, instead of a static islanding status. Fluctuation and stochastic characteristics of the renewable distributed generations and loads are considered, and the interruption cost functions of the loads are fitted. To solve the optimization model, a heuristic search algorithm based on the hill climbing method is proposed. The effectiveness of the proposed model and algorithm is evaluated by comparing with an existing static island partitioning model and intelligent algorithms, respectively.

• Journal of Electrical Engineering and information Science
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• v.1 no.1
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• pp.164-172
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• 1996

The partitioning of related objects should be performed before clustering for an efficient access in object-oriented databases. In this paper, a horizontal partition of related objects in object-oriented databases is presented. All subclass nodes in a class inheritance hierarchy of a schema graph are shrunk to a class node in the graph that is called condensed schema graph because the aggregation hierarchy has more influence on the partition than the class inheritance hierarchy. A set function and an accessibility function are defined to find a maximal subset of related objects among the set of objects in a class. A set function maps a subset of the domain class objects to a subset of the range class objects. An accessibility function maps a subset of the objects of a class into a subset of the objects of the same class through a composition of set functions. The algorithm derived in this paper is to find the related objects of a condensed schema graph using accessibility functions and set functions. The existence of a maximal subset of the related objects in a class is proved to show the validity of the partition algorithm using the accessibility function.

• Journal of Korea Multimedia Society
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• v.11 no.7
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• pp.1025-1034
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• 2008

In this paper, we developed GridGML for efficiently supplying a GML and visualizing the map with partitioning map and caching method to a mobile device. In order to overcome the weighting of a file, which is the biggest weakness of a GML, GridGML extracts only the most necessary parts for the visualization of the map among GML attributes, and makes the file light as a class instance by applying an offset value. GridGML manages a partition based on the visualization area of a mobile device to visualize the map to a mobile device in real time, and transmits the partition area by serializing it for the benefit of transmission. Also, the received partition area is compounded in a mobile device and is visualized by being partitioned again as four visible areas based on the display of a mobile device. Then, the area is managed by applying a caching algorithm in consideration of repetitiveness for a received map for the efficient operation of resources. Also, in order to prevent the delay in transmission time as regards the instance density area of the map, an adaptive map partition mechanism is proposed for maintaining the transmission time uniformly.

• ETRI Journal
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• v.21 no.2
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• pp.22-30
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• 1999

In this paper, we derive an efficient parallel algorithm to solve the single function coarsest partition problem. This algorithm runs in O(\log2n) time using O(nlogn) operations on the EREW PRAM with O(n) memory cells used. Compared with the previous PRAM algorithms that consume O(n1+${\varepsilon}$) memory cells for some positive constant ${\varepsilon}\>0$, our algorithm consumes less memory cells without increasing the total number of operations.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1254-1259
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• 2005

In this paper, we proposed a learning algorithm for the neuro-fuzzy modeling using a learning rule to adapt clustering. The proposed algorithm includes the data partition, assigning the rule into the process of partition, and optimizing the parameters using predetermined threshold value in self-constructing algorithm. In order to improve the clustering, the learning method of neuro-fuzzy model is extended and the learning scheme has been modified such that the learning of overall model is extended based on the error-derivative learning. The effect of the proposed method is presented using simulation compare with previous ones.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.2
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• pp.95-101
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• 2005

In this paper, we proposed a learning algorithm for the neuro-fuzzy modeling using a learning rule to adapt clustering. The proposed algorithm includes the data partition, assigning the rule into the process of partition, and optimizing the parameters using predetermined threshold value in self-constructing algorithm. In order to improve the clustering, the learning method of neuro-fuzzy model is extended and the learning scheme has been modified such that the learning of overall model is extended based on the error-derivative learning. The effect of the proposed method is presented using simulation compare with previous ones.

• Journal of the Korea Society of Computer and Information
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• v.20 no.11
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• pp.69-75
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• 2015

This paper suggests heuristic polynomial time algorithm for crew scheduling problem that is a kind of optimization problems. This problem has been solved by linear programming, set cover problem, set partition problem, column generation, etc. But the optimal solution has not been obtained by these methods. This paper sorts transit costs $c_{ij}$ to ascending order, and the task i and j crew paths are merged in case of the sum of operation time ${\Sigma}o$ is less than day working time T. As a result, we can be obtain the minimum number of crews $_{min}K$ and minimum transit cost $z=_{min}c_{ij}$. For the transit cost of specific number of crews $K(K>_{min}K)$, we delete the maximum $c_{ij}$ as much as the number of $K-_{min}K$, and to partition a crew path. For the 5 benchmark data, this algorithm can be gets less transit cost than state-of-the-art algorithms, and gets the minimum number of crews.