• The Journal of the Korea Contents Association
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• v.9 no.9
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• pp.80-89
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• 2009

A fast and efficient search algorithm to determine an optimal number of clusters in clustering algorithms is presented. The method is based on cluster validity index which is a measure for clustering optimality. As the clustering procedure progresses and reaches an optimal cluster configuration, the cluster validity index is expected to be minimized or maximized. In this Paper, a fast non-exhaustive search method for finding the optimal number of clusters is designed and shown to work well in clustering. The proposed algorithm is implemented with the k-mean++ algorithm as underlying clustering techniques using CB and PBM as a cluster validity index. Experimental results show that the proposed method provides the computation time efficiency without loss of accuracy on several artificial and real-life data sets.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.8
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• pp.637-642
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• 2014

In this paper, we propose a efficient shift index searching algorithm for design of the block LDPC codes. It is combined with the message-passing based cycle search algorithm and ACE algorithm. We can determine the shift indices by ordering of priority factors which are effect on the LDPC code performance. Using this algorithm, we can construct the LDPC codes with low complexity compare to trellis-based search algorithm and save the memory for storing the parity check matrix.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.16 no.7
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• pp.640-650
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• 1991

In the paper, the threepoint search algorithm used direct search method for optimal design is proposed. Proposed algorithm is composed of two iteration procedure to determine the minimum value of performance index. The minumum value of three-point existing in the inner N-order searching is firstly determined and next searching space is then reduced by the result of first procedure. To compute performance index. 3N iteration for a searching is necessary. 3N searching method is also described and confirmed with exception of parameter included multiphicator and divisor. Proposed algorithm have good stability and reliability when performance index is linear or quadratic function.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.5
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• pp.217-224
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• 2002

This paper presents an algorithm to obtain an approximate optimal solution for the service restoration and load balancing of large scale radial distribution system in a real-time operation environment. Since the problem is formulated as a combinatorial optimization problem, it is difficult to solve a large-scale combinatorial optimization problem accurately within the reasonable computation time. Therefore, in order to find an approximate optimal solution quickly, the authors proposed an algorithm which combines optimization technique called cyclic best-first search with heuristic based feeder loadings balance index for computational efficiency and robust performance. To demonstrate the validity of the proposed algorithm, numerical calculations are carried out the KEPCO's 108 bus distribution system.

• Korean Journal of Materials Research
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• v.27 no.6
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• pp.312-317
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• 2017

In the construction of a white LED, the region of the red emission is a very important factor. Red light emitting materials play an important role in improving the color rendering index of commercial lighting. These materials also increase the color gamut of display products. Therefore, the development of novel phosphors with red emission and the study of color tuning are actively underway to improve product quality. In the present study, heuristic algorithms were used to search for phosphors capable of increasing the color rendering index and color gamut. Using a heuristic algorithm, the phosphors that were identified were $SrGe_4O_9:Mn^{4+}$ and $BaGe_4O_9:Mn^{4+}$. Emission spectra study confirmed that these phosphors emit light in the deep red wavelength region, which can fulfill the requirement for the improvement in color rendering index and color gamut for a white LED.

• International Journal of Contents
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• v.1 no.1
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• pp.50-58
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• 2005

Generally, multidimensional data such as image and spatial data require large amount of storage space. There is a limit to store and manage those large amounts of data in single workstation. If we manage the data on parallel computing environment which is being actively researched these days, we can get highly improved performance. In this paper, we propose a parallel multidimensional index structure that exploits the parallelism of the parallel computing environment. The proposed index structure is nP(processor)-nxmD(disk) architecture which is the hybrid type of nP-nD and 1P-nD. Its node structure in-creases fan-out and reduces the height of an index. Also, a range search algorithm that maximizes I/O parallelism is devised, and it is applied to k-nearest neighbor queries. Through various experiments, it is shown that the proposed method outperforms other parallel index structures.

• The KIPS Transactions:PartC
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• v.9C no.1
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• pp.9-16
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• 2002

As existing analog video surveillance systems could save and retrieve data only in a limited space within short distance, it had many constraints in developing into various application systems. However, on the back of development of the Internet and computer technologies, digital video surveillance systems can be controlled from a remote location by web browser without space limits. Moreover, data compression and management technologies with Index Search algorithm make it possible to efficiently handling, storing, and retrieving a large amount of data and further motion detection algorithm enhances a recording speed and efficiency for a practical application, that is, a practical remote recordable video surveillance system using our efficient algorithms as mentioned, called WebCam. The WebCam server system can intelligently record and save video images digitized through efficient database management, monitor and control cameras in a remote place through user authentication, and search logs.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.157-163
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• 2017

The binary and interpolation search algorithms are the most famous among search area algorithms, the former running in $O(log_2n)$ on average, and the latter in $O(log_2log_2n)$ on average and O(n) at worst. Also, the interpolation search use only the probability of key value location without priori information. This paper proposes another search algorithm, which I term a 'hybrid block and interpolation search'. This algorithm employs the block search, a method by which MSB index of a data is determined as a block, and the interpolation search to find the exact location of the key. The proposed algorithm reduces the search range with priori information and search the reduced range with uninformed situation. Experimental results show that the algorithm has a time complexity of $O(log_2log_2n_i)$, $n_i{\simeq}0.1n$ both on average and at worst through utilization of previously acquired information on the block search. The proposed algorithm has proved to be approximately 10 times faster than the interpolation search on average.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1091-1110
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• 2016

Hybrid deployment under current cloud data centers is a combination of online and offline services, which improves the utilization of the cluster resources. However, the performance of the cluster is often affected by the online services in the hybrid deployment environment. To improve the response time of online service (e.g. search engine), an effective scheduling algorithm based on Storm is proposed. At the component level, the algorithm dispatches the component with more influence to the optimal performance node. Inside the component, a reasonable resource allocation strategy is used. By searching the compressed index first and then filtering the complete index, the execution speed of the component is improved with similar accuracy. Experiments show that our algorithm can guarantee search accuracy of 95.94%, while increasing the response speed by 68.03%.

• Steel and Composite Structures
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• v.36 no.1
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• pp.31-45
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• 2020

The purpose of this study is to develop an effective iterative two-stage method (ITSM) for structural damage identification of offshore platform structures. In each iteration, a new damage index, Modal Energy-Based Damage Index (MEBI), is proposed to help effectively locate the potential damage elements in the first stage. Then, in the second stage, the beetle antenna search (BAS) algorithm is used to estimate the damage severity of these elements. Compared with the well-known particle swarm optimization (PSO) algorithm and genetic algorithm (GA), this algorithm has lower computational cost. A modal energy based objective function for the optimization process is proposed. Using numerical and experimental data, the efficiency and accuracy of the ITSM are studied. The effects of measurement noise and spatial incompleteness of mode shape are both considered. All the obtained results show that under these influences, the ITSM can accurately identify the true location and severity of damage. The results also show that the objective function based on modal energy is most suitable for the ITSM compared with that based on flexibility and weighted natural frequency-mode shape.