• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.43-48
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• 2013

Adaboost is widely used for Haar-like feature boosting algorithm in Face Detection. It shows very effective performance on single distribution model. But when detecting front and side face images at same time, Adaboost shows it's limitation on multiple distribution data because it uses linear combination of basic classifier. This paper suggest the HDCT, modified decision tree algorithm for Haar-like features. We still tested the performance of HDCT compared with Adaboost on multiple distributed image recognition.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.11B
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• pp.991-1000
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• 2004

This paper presents an application layer multicast tree constructing algorithm to minimize the average time delay from the sender to end-systems for the effective real-time media delivery. Simultaneously, the proposed algorithm takes into account the computing power and the network condition of each end-system as a control variable and thus avoids the undesirable case that loads are concentrated to only several end-systems. The multicast tree is constructed by clustering technique and modified Dijkstra's algorithm in two steps, i.e. tree among proxy-senders and tree in each cluster. By the experimental results, we show that the proposed algorithm can provide an effective solution.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.5A
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• pp.502-510
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• 2011

In this paper, we propose a slot scheduling algorithm for balancing power consumption in tree-based sensor networks. In this type of networks, nodes with lower depths tend to consume more energy than those with higher depths, thereby reducing the life time of the network. The proposed algorithm allocates a series of receiving slots first and then a series of sending slots. This way of slot allocation eases packet aggregation and filtering, and thus reduces traffic load on nodes near a sink. We compare the proposed algorithm and the frame-slot allocation algorithm employed in the TreeMAC by resorting to simulation. The simulation results showed that the proposed approach well achieves the balancing of power consumption.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.4B
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• pp.305-313
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• 2011

This paper presents a P2P (Peer-to-Peer) overlay multicast tree construction algorithm to support stable multimedia service over the Internet. While constructing a multicast tree, it takes into account not only the link delay, but also peer stability. Since peers actually show dynamic and unstable behavior over P2P-based network, it is essential to consider peer stability. Furthermore, the weighting factor between link delay and peer stability is adaptively controlled according to the characteristics of the multicast tree. Basically, Genetic algorithm is employed to obtain a near optimal solution with low computational complexity. Finally, simulation results are provided to show the performance of the proposed algorithm.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.218-223
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• 1995

A new design scheme of a binary decision tree is proposed. In this scheme a binary decision tree is constructed by using genetic algorithm and FCM algorithm. At each node optimal or near-optimal feature or feature subset among all the available features is selected based on fitness function in genetic algorithm which is inversely proportional to classification error, balance between cluster, number of feature used. The proposed design scheme is applied to the handwtitten alphabetic characters. Experimental results show the usefulness of the proposed scheme.

• Journal of applied mathematics & informatics
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• v.7 no.2
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• pp.629-640
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• 2000

this paper present an efficient line-drawing algorithm that reduces the amount of space required, Because of its efficiency , this line-drawing algorithm is faster than the Bresenham algorithm or the recursive bisection method. this efficiency was achieved through a new data structure; namely , the modified segment tree (MST). Using the modified segment tree and the distribution rule suggested in this paper, we dra lines without generating the recursive calls used in [3] and without creating the binary operation used in [4]. we also show that line accuracy improves in proportion to the display resolution . In practice, we can significantly improve the algorithm's performance with respect to time and space, This improvement offer an increase in speed, specially with lines at or near horizontal, diagonal. or vertical ; that is, this algorithm requires the time complexity of (n) and the space complexity O(2k+1), where n is the number of pixels and k is a level of the modified segment tree.

• Journal of Distribution Science
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• v.13 no.6
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• pp.11-15
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• 2015

Purpose - Robot path planning, a constrained optimization problem, has been an active research area with many methods developed to tackle it. This study proposes the use of a Rapidly-exploring Random Tree and Particle Swarm Optimizer algorithm for path planning. Research design, data, and methodology - The grid method is built to describe the working space of the mobile robot, then the Rapidly-exploring Random Tree algorithm is applied to obtain the global navigation path and the Particle Swarm Optimizer algorithm is adopted to obtain the best path. Results - Computer experiment results demonstrate that this novel algorithm can rapidly plan an optimal path in a cluttered environment. Successful obstacle avoidance is achieved, the model is robust, and performs reliably. The effectiveness and efficiency of the proposed algorithm is demonstrated through simulation studies. Conclusions - The findings could provide insights to the validity and practicability of the method. This method makes it is easy to build a model and meet real-time demand for mobile robot navigation with a simple algorithm, which results in a certain practical value for distribution environments.

• Industrial Engineering and Management Systems
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• v.3 no.2
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• pp.123-128
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• 2004

A tree structure model has been proposed for representing the unequal-area facility layout. Each facility has a different rectangular shape specified by its area and aspect ratio. In this layout problem, based on the assumption that the shop floor has enough space for laying out the facilities, no constraint is considered for a shop floor. Objectives are minimizing total part movement between facilities and total rectangular layout area where all facilities and dead spaces are enclosed. Using the genetic code corresponding to two kinds of information, facility sequence and branching positions in the tree structure model, a genetic algorithm has been applied for finding non-dominated solutions in the two-objective layout problem. We use three kinds of crossover (PMX, OX, CX) for the former part of the chromosome and one-point crossover for the latter part. Two kinds of layout problems have been tested by the proposed method. The results demonstrate that the presented algorithm is able to find good solutions in enough short time.

• Journal of Internet Computing and Services
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• v.5 no.5
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• pp.119-127
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• 2004

As, the development of language-based programming environment, a study on incremental parsing has become an essential part. The purpose of this paper is to show the more efficient incremental parsing algorithm than earlier one that demands parsing speed and memorizing space too much. This paper suggests the threaded tree construction algorithm not using stack. In addition, to remove the reparsing process, it proposes the algorithm for creation node and construction incremental threaded tree not using stack.

• International Journal of Computer Science & Network Security
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• v.24 no.6
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• pp.83-88
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• 2024

In this paper we used classification algorithms on social networking. We are proposing, a new classification algorithm called the improved Decision Tree (IDT). Our model provides better classification accuracy than the existing systems for classifying the social network data. Here we examined the performance of some familiar classification algorithms regarding their accuracy with our proposed algorithm. We used Support Vector Machines, Naïve Bayes, k-Nearest Neighbors, decision tree in our research and performed analyses on social media dataset. Matlab is used for performing experiments. The result shows that the proposed algorithm achieves the best results with an accuracy of 84.66%.