• Journal of Digital Convergence
• /
• v.15 no.6
• /
• pp.229-236
• /
• 2017

An efficient frequent pattern algorithm is essential for mining association rules as well as many other mining tasks for convergence with its application spread over a very broad spectrum. Models for mining pattern have been proposed using a FP-tree for storing compressed information about frequent patterns. In this paper, we propose a centroid frequent pattern growth algorithm which we called "CAWFP-Growth" that enhances he FP-Growth algorithm by making the center of weights and frequencies for the itemsets. Because the conventional constraint of maximum weighted support is not necessary to maintain the downward closure property, it is more likely to reduce the search time and the information loss of the frequent patterns. The experimental results show that the proposed algorithm achieves better performance than other algorithms without scarifying the accuracy and increasing the processing time via the centroid of the items. The MapReduce framework model is provided to handle large amounts of data via a pseudo-distributed computing environment. In addition, the modeling of the proposed algorithm is required in the fully distributed mode.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.16 no.8
• /
• pp.1789-1798
• /
• 2012

IEEE 802.15.4a standard can provide a variety of location-based services for ZigBee or wireless network applications by adapting the time-of-arrival (TOA) ranging technique. The non-line-of-sight (NLOS) condition is the critical problem in the IEEE 802.15.4a networks, and it can significantly degrade the performance of the TOA-based localization. To enhance the location accuracy due to the NLOS problem, this paper proposes an energy-efficient low complexity localization algorithm. The proposed approach performs the ranging with the multicast method, which can reduce the message overhead due to packet exchanges. By limiting the search region for the location of the node, the proposed approach can enhance the location accuracy. Experimental results show that the proposed algorithm outperforms previous algorithms in terms of the energy consumption and the localization accuracy.

• Journal of Internet of Things and Convergence
• /
• v.2 no.4
• /
• pp.15-20
• /
• 2016

This paper describes the construction of knowledge data retrieval management system based on medical image CT. The developed system is aimed to improve the efficiency of the hospital by reading the medical images using the intelligent retrieval technology and diagnosing the patient 's disease name. In this study, the medical image DICOM file of PACS is read, the image is processed, and feature values are extracted and stored in the database. We have implemented a system that retrieves similarity by comparing new CT images required for medical treatment with the feature values of other CTs stored in the database. After converting 100 CT dicom provided for academic research into JPEG files, Code Book Library was constructed using SIFT, CS-LBP and K-Mean Clustering algorithms. Through the database optimization, the similarity of the new CT image to the existing data is searched and the result is confirmed, so that it can be utilized for the diagnosis and diagnosis of the patient.

• Journal of Broadcast Engineering
• /
• v.16 no.5
• /
• pp.861-872
• /
• 2011

Many fast block-matching algorithms (BMAs) in motion estimation field reduce computational complexity by screening the number of checking points. Although many fast BMAs reduce computations, sometimes they should endure matching errors in comparison with full-search algorithm (FSA). In this paper, a novel fast BMA for constrained one-bit transform (C1BT)-based motion estimation is proposed in order to decrease the calculations of the block distortion measure. Unlike the classical fast BMAs, the proposed algorithm shows a new approach to reduce computations. It utilizes the binomial distribution based on the characteristic of binary plane which is composed of only two elements: 0 and 1. Experimental results show that the proposed algorithm keeps its peak signal-to-noise ratio (PSNR) performance very close to the FSA-C1BT while the computation complexity is reduced considerably.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.35 no.11
• /
• pp.1429-1436
• /
• 2011

In this paper, a new tube-radius-measuring algorithm has been proposed for effectively measuring the radii of small tubes under severe noise conditions that can also perform well when metal scraps that make it difficult to measure the radius correctly are inside the tube hole. In the algorithm, we adopt a fuzzy searching method that searches for the center of the inner circle by using fuzzy parameters for distance and orientation from the initial search point. The proposed algorithm has been implemented and tested on both synthetic and real-world tube images, and the performance is compared to existing circle-detection algorithms, such as the Hough transform and RANSAC methods, to prove the accuracy and effectiveness of the algorithm. From this comparison, it is concluded that the proposed algorithm has excellent performance in terms of measurement accuracy and computation time.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.10
• /
• pp.4738-4753
• /
• 2018

Efficient rendezvous node selection and routing algorithm (RNSRA) for wireless sensor networks with mobile sink that visits rendezvous node to gather data from sensor nodes is proposed. In order to plan an optimal moving tour for mobile sink and avoid energy hole problem, we develop the RNSRA to find optimal rendezvous nodes (RN) for the mobile sink to visit. The RNSRA can select the set of RNs to act as store points for the mobile sink, and search for the optimal multi-hop path between source nodes and rendezvous node, so that the rendezvous node could gather information from sensor nodes periodically. Fitness function with several factors is calculated to find suitable RNs from sensor nodes, and the artificial bee colony optimization algorithm (ABC) is used to optimize the selection of optimal multi-hop path, in order to forward data to the nearest RN. Therefore the energy consumption of sensor nodes is minimized and balanced. Our method is validated by extensive simulations and illustrates the novel capability for maintaining the network robustness against sink moving problem, the results show that the RNSRA could reduce energy consumption by 6% and increase network lifetime by 5% as comparing with several existing algorithms.

• Structural Engineering and Mechanics
• /
• v.61 no.3
• /
• pp.347-357
• /
• 2017

The applications of active control is being more popular nowadays. Several control algorithms have been developed to determine optimum control force. In this paper, a Chaotic Particle Swarm Optimization (CPSO) technique, based on Logistic map, is used to compute the optimum control force of active tendon system. A chaotic exploration is used to search the solution space for optimum control force. The response control of Multi-Degree of Freedom (MDOF) shear buildings, equipped with active tendons, is introduced as an optimization problem, based on Instantaneous Optimal Active Control algorithm. Three MDOFs are simulated in this paper. Two examples out of three, which have been previously controlled using Lattice type Probabilistic Neural Network (LPNN) and Block Pulse Functions (BPFs), are taken from prior works in order to compare the efficiency of the current method. In the present study, a maximum allowable value of control force is added to the original problem. Later, a twenty-story shear building, as the third and more realistic example, is considered and controlled. Besides, the required Central Processing Unit (CPU) time of CPSO control algorithm is investigated. Although the CPU time of LPNN and BPFs methods of prior works is not available, the results show that a full state measurement is necessary, especially when there are more than three control devices. The results show that CPSO algorithm has a good performance, especially in the presence of the cut-off limit of tendon force; therefore, can widely be used in the field of optimum active control of actual buildings.

• The Journal of the Acoustical Society of Korea
• /
• v.20 no.3
• /
• pp.34-41
• /
• 2001

In an IMBE (Improved Multi-band Excitation) speech coder, initial pitch estimation occupies most of the total computing time for the coder due to complex cost function and exhaustive search over candidate pitches. Future frames in initial pitch estimation cause inevitable time delay. Therefore, it is difficult to implement a real-time coder. Furthermore, unvoiced frames use the unnecessary pitch estimation as in the voiced frames. In this paper, each frame is determined voiced or unvoiced by Dyadic Wavelet Transform (DyWT) and, then, initial pitch estimation is performed only for voiced frame. Therefore different pitch estimation algorithms are employed between voiced and unvoiced frames incurring reduced time delay at transmitter and receiver. Simulation result show that the relative complexity of initial pitch estimation is reduced by 23％, and the processing time decreases down to 1/10 ∼ 1/1l of the IMBE coder while speech quality is almost maintained.

• Journal of Intelligence and Information Systems
• /
• v.14 no.4
• /
• pp.201-216
• /
• 2008

Nowadays various new items are available, but limitation of searching effort makes it difficult for customers to search new items which they want to purchase. Therefore new item providers and customers need recommendation systems which recommend right items for right customers. In this research, we focus on the new item recommendation issue, and suggest preference boundary- based procedures which extend traditional content-based algorithm. We introduce the concept of preference boundary in a feature space to recommend new items. To find the preference boundary of a target customer, we suggest heuristic algorithms to find the centroid and the radius of preference boundary. To evaluate the performance of suggested procedures, we have conducted several experiments using real mobile transaction data and analyzed their results. Some discussions about our experimental results are also given with a further research area.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.6 no.2
• /
• pp.1-15
• /
• 1986

The algorithm Proposed utilizes the two-levels technique. In the first level which consists of two phases, the cross-sectional area of the truss member is optimized by transforming the nonlinear problem into SUMT, and solving SUMT utilizing the modified Newton-Rahson method. In the second level, the geometric shape is optimized utilizing the unindirectional search technique of the Powell method which make it possible to minimize only the objective function. The algorithm Proposed in this study is numerically tested for several truss structures with various shapes, loading conditions and design criteria, and compared with the results of the other algorithms to examine its applicability and stability. The numerical comparisons show that the two-Levels algorithm Proposed in this study is safely applicable to any design criteria, and the convergency rate is relathely fast and stable compared with other iteration methods for the geometric optimization of truss structures.