• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.8B
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• pp.757-763
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• 2006

In this paper, a novel multiple access scheme using SMA(Split and Merge Algorithm) is proposed to reduce the accessdelay of wireless MAC protocols. The key idea of the SMA is to dynamically split and merge the contending terminals depending on their traffic loads for effective control of access to the channels. The SMA divides the collided terminals into several sub-groups if a collision occurs and merges the idle terminals of the split sub-groups into their original group. The merge algorithm can be used to resolve collision and split operation can be used to dynamic group management. The simulation results indicate that our algorithm may provide a higher throughput and a lower collision rate than the existing algorithms, especially under heavy traffic loads.

• The Korean Journal of Applied Statistics
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• v.17 no.3
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• pp.459-473
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• 2004

It has well known that an exhaustive search algorithm suggested by Breiman et. a1.(1984) has a trend to select the variable having relatively many possible splits as an splitting rule. We propose an algorithm to overcome this variable selection bias problem and then construct unbiased regression trees based on the algorithm. The proposed algorithm runs two steps of selecting a split variable and determining a split rule for binary split based on the split variable. Simulation studies were performed to compare the proposed algorithm with Breiman et a1.(1984)'s CART(Classification and Regression Tree) in terms of degree of variable selection bias, variable selection power, and MSE(Mean Squared Error). Also, we illustrate the proposed algorithm with real data sets.

• Journal of Korea Multimedia Society
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• v.13 no.10
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• pp.1534-1546
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• 2010

In sensor network systems, various hierarchical clustering schemes have been proposed in order to efficiently maintain the energy consumption of sensor nodes. Most of these schemes, however, are hardly applicable in practice since these schemes might produce unbalanced clusters or randomly distributed clusters without taking into account of the distribution of sensor nodes. To overcome the limitations of such hierarchical clustering schemes, we propose a novel scheme called CSM(Clustering using Split & Merge algorithm), which exploits node split and merge algorithm of tree-based indexing structures to efficiently construct clusters. Our extensive performance studies show that the CSM constructs highly balanced clustering in a energy efficient way and achieves higher performance up to 1.6 times than the previous clustering schemes, under various operational conditions.

• Journal of applied mathematics & informatics
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• v.34 no.5_6
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• pp.467-478
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• 2016

In this paper, we propose an Ishikawa-type extra-gradient iterative algorithm for finding a solution of split feasibility, fixed point problems and equilibrium problems of quasi-nonexpansive mappings. It is proven that under suitable conditions, the sequences generated by the proposed iterative algorithms converge weakly to a solution of the split feasibility, fixed point problems and equilibrium problems. An example is given to illustrate the main result of this paper.

• Journal of KIISE:Databases
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• v.30 no.1
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• pp.80-94
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• 2003

In this paper. we propose an enhanced concurrency control algorithm that minimizes the query delay efficiently. The factors that delay search operations and deteriorate the concurrency of index structures are node splits and MBR updates in multi dimensional index structures. In our algorithm, to reduce the query delay by split operations, we optimize exclusive latching time on a split node. It holds exclusive latches not during whole split time but only during physical node split time that occupies small part of whole split time. Also to avoid the query delay by MBR updates we introduce partial lock coupling(PLC) technique. The PLC technique increases concurrency by using lock coupling only in case of MBR shrinking operations that are less frequent than MBR expansion operations. For performance evaluation, we implement the proposed algorithm and one of the existing link technique-based algorithms on MIDAS-III that is a storage system of a BADA-III DBMS. We show through various experiments that our proposed algorithm outperforms the existing algorithm In terms of throughput and response time.

• Journal of Korea Society of Industrial Information Systems
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• v.3 no.1
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• pp.258-268
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• 1998

This paper presents two sequential advanced split and merge algorithms and a parallel image segmentation algorithm based on them. First, the two advanced methods are obtained from the combination of edge detection and classic split and merge to solve the inherent problems of the classical method. Besides, the parallel image segmentation algorithm on mesh-connected MIMD system considers three types in the merge stage to reduce the communication overhead between processors, such as intraprocessor merge, interprocessor with boundary merge, and interprocessor without boundary merge. Finally , we prove that the proposed algorithms achieve the improved performance by implementing them.

• Journal of Korean Society for Geospatial Information Science
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• v.25 no.1
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• pp.29-36
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• 2017

In this paper, we implement a spatial big data analysis prototype based on Spark which is an in-memory system and compares the performance by the spatial split algorithm on this basis. In cluster computing environments, big data is divided into blocks of a certain size order to balance the computing load of big data. Existing research showed that in the case of the Hadoop based spatial big data system, the split method by spatial is more effective than the general sequential split method. Hadoop based spatial data system stores raw data as it is in spatial-divided blocks. However, in the proposed Spark-based spatial analysis system, there is a difference that spatial data is converted into a memory data structure and stored in a spatial block for search efficiency. Therefore, in this paper, we propose an in-memory spatial big data prototype and a spatial split block storage method. Also, we compare the performance of existing spatial split algorithms in the proposed prototype. We presented an appropriate spatial split strategy with the Spark based big data system. In the experiment, we compared the query execution time of the spatial split algorithm, and confirmed that the BSP algorithm shows the best performance.

• The Journal of the Acoustical Society of Korea
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• v.36 no.5
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• pp.300-304
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• 2017

In a cylindrical sonar, a conventional broadband energy detector has limitations in the separation of adjacent targets. In this paper, a broadband detection algorithm using cross-correlation is applied to the cylindrical sonar to improve the bearing resolution. The proposed algorithm uses split beamforming before broadband detection processing using cross-correlation to generate half beams. The time delay obtained from the peak of correlation between half beams is used to estimate the bearing of target. Simulations demonstrate the improved performance of the proposed algorithm against the conventional algorithm.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.10
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• pp.4007-4024
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• 2020

It is tremendously important to construct decision trees to use as a tool for knowledge representation from a given decision table. However, the usual algorithms may split the decision table based on each value, which is not efficient for numerical attributes. The methodology of this paper is to split the given decision table into binary groups as like the CART algorithm, that uses binary split to work for both categorical and numerical attributes. The difference is that it uses split for each attribute established by the directed acyclic graph in a dynamic programming fashion whereas, the CART uses binary split among all considered attributes in a greedy fashion. The aim of this paper is to study the effect of binary splits in comparison with each value splits when building the decision trees. Such effect can be studied by comparing the number of nodes, local and global misclassification rate among the constructed decision trees based on three proposed algorithms.

• Journal of Power Electronics
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• v.18 no.6
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• pp.1720-1728
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• 2018

This paper proposes a novel soft starting algorithm by using PWM inverter technique to control an amplitude of the motor starting current at a single-phase induction motor (SPIM). Traditional SPIM starting methods such as a Split-Phase, Capacitor-Start, Permanent-Split Capacitor (PSC), Capacitor-Start Capacitor-Run (CSCR), basically cannot control the magnitude of starting current due to the fixed system structures. Therefore, in this paper, a soft starting algorithm based on a proportional resonant (PR) control with a variable and constant frequency is proposed to reduce the inrush current and starting up time. In addition, a transition algorithm for operation modes is devised to generate a constant voltage and constant frequency (CVCF). The validity and effectiveness of the proposed soft starting method and transition algorithm are verified through experimental results.