• Journal of the Institute of Convergence Signal Processing
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• v.3 no.3
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• pp.14-20
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• 2002

In this paper, we proposed the compression technique of the video data using SPIHT(set partitioning in hierarchical trees) based on wavelet and the multi-stream delivery method for best-effort service as fully utilizing the clients bandwidth over the current Internet. The experiment shows that the proposed method provides about 1.5dB better picture quality without block effects than DCT(discrete consine transform) based coding schemes at the same bit rates because of using the wavelet video coder. In addition, this technique implements the multi-stream transmission based on TCP(transmission control protocol). Thus, it is provided with the best-efforts service which is robust to the network jitter problem, and maximally utilizes the bandwidth of the client's.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.40 no.10
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• pp.24-34
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• 2003

In this paper, we investigated the problems of the offset time based service differentiation scheme for optical burst switching (OBS) networks, and proposed the preemption-based service differentiation scheme which combines a preemption channel selection algorithm and channel partitioning algorithm. The proposed preemption channel selection algorithm minimizes the length of preempted bursts to improve the channel efficiency, while the proposed channel partitioning algorithm controls the degree of service differentiation between service classes. The simulation results showed that the proposed schemes could improve the end-to-end performance and effectively provide controllable service differentiation in the multiple hop network environments.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.935-942
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• 2000

In this paper we introduce a fast simplification algorithm for terrain height fields to produce a triangulated irregular network, based on the greedy insertion algorithm in [1,4,5]. Our algorithm partitions a terrain height data into rectangular blocks with the same size ad simplifies blocks one by one with the greedy insertion algorithm. Our algorithm references only to the points and the triangles withing each current block for adding a point into the triangulation. Therefore, the algorithm runs faster than the greedy insertion algorithm, which references all input points and triangles in the terrain. Our experiment shows that partitioning method runs from 4 to more than 20 times faster, and it approximates test height fields as accurately as the greedy insertion algorithms. Most greedy insertion algorithms suffer from elongated triangles that usually appear near the boundaries. However, we insert the four corner points into each block to produce the base triangulation of the block before the point addition step begins so that elongated triangles could not appear in th simplified terrain.

• Telecommunications review
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• v.24 no.4
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• pp.468-480
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• 2014

The current-generation avionics systems are based on a federated architecture, where an electronic device runs a single software module or application that collaborates with other devices through a network. This architecture makes the internal system architecture very complicate, and gives rise to issues of Size, Weight, and Power (SWaP). In this paper, we show that the partitioning defined by ARINC 653 can efficiently deal with the SWaP issues on small unmanned aerial vehicles, where the SWaP issues are extremely severe. We especially install the integrated mission system on real hexacopter and quadcopter and perform successful flight tests. The presented software technology for integrated mission system and software consolidation methodology can provide a valuable reference for other SWaP sensitive real-time systems.

• Journal of Korean Institute of Industrial Engineers
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• v.16 no.2
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• pp.91-98
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• 1990

This paper studies a heuristic method for the Maximum Origin-Destination Flow Path (MODFP) in an acyclic transportation network. We construct a mathematical formulation for finding the MODFP. Then by applying Benders' partitioning method, we generate two subproblems which should be solved in turn so that they may give an optimal solution. We solve one subproblem by an optimal seeking algorithm and the other by a hueristic method. so that, we finally obtain a good solution. The computational complexity of calculating the optimal solution of the first subproblem is 0(mn) and that of calculating the heuristic solution of the other subproblem is $0(n^2).$ From the computational experiments, we estimated the performance of the heuristic method as being 99.3% and the computing time relative to optimal algorithm as being 28.76%.

• Journal of Industrial Technology
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• v.24 no.A
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• pp.99-107
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• 2004

This paper considers reinforcement learning control with the self-organizing map. Reinforcement learning uses the observable states of objective system and signals from interaction of the system and the environments as input data. For fast learning in neural network training, it is necessary to reduce learning data. In this paper, we use the self-organizing map to parition the observable states. Partitioning states reduces the number of learning data which is used for training neural networks. And neural dynamic programming design method is used for the controller. For evaluating the designed reinforcement learning controller, an inverted pendulum of the cart system is simulated. The designed controller is composed of serial connection of self-organizing map and two Multi-layer Feed-Forward Neural Networks.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1991.10a
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• pp.464-464
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• 1991

We address the problem of designing a physical CATV network with switched-star topology in which the broadband interactive service is provided. There are two types of decision variables: One is where to place conduit paths, and the other is how many cable units to be installed on each link traversed by an established conduit path. Due to the serious drawback of the conventional approach partitioning the problem into two subproblems, the unified approach handled in one setting is used here to attack the whole problem without dividing into two ones. In this paper, we present a mathematical design model and propose an efficient solution method exploiting the nice structure of it. In addition to this physical design, some results on logical network configuration have also been made. Finally, computaional experiments are conducted to illustrate the efficiency of our design approach.

• International Journal of Computer Science & Network Security
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• v.21 no.6
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• pp.237-244
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• 2021

Clustering is a most powerful un-supervised machine learning techniques for division of instances into homogenous group, which is called cluster. This Clustering is mainly used for generating a good quality of cluster through which we can discover hidden patterns and knowledge from the large datasets. It has huge application in different field like in medicine field, healthcare, gene-expression, image processing, agriculture, fraud detection, profitability analysis etc. The goal of this paper is to explore both hierarchical as well as partitioning clustering and understanding their problem with various approaches for their solution. Among different clustering K-means is better than other clustering due to its linear time complexity. Further this paper also focused on data mining that dealing with high-dimensional datasets with their problems and their existing approaches for their relevancy

• Journal of Korea Multimedia Society
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• v.25 no.6
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• pp.783-792
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• 2022

Versatile Video Coding (VVC) is the latest video coding standard, which had been developed by the Joint Video Experts Team (JVET) of ITU-T Video Coding Experts Group (VCEG) and ISO/IEC Moving Picture Experts Group (MPEG) in 2020. Although VVC can provide powerful coding performance, it requires tremendous computational complexity to determine the optimal block structures during the encoding process. In this paper, we propose a fast ternary tree decision method using two neural networks with 7 nodes as input vector based on the multi-layer perceptron structure, names STH-NN and STV-NN. As a training result of neural network, the STH-NN and STV-NN achieved accuracies of 85% and 91%, respectively. Experimental results show that the proposed method reduces the encoding complexity up to 25% with unnoticeable coding loss compared to the VVC test model (VTM).

• International Journal of Computer Science & Network Security
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• v.22 no.5
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• pp.17-24
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• 2022

Hierarchical clustering methods have been proposed for more than sixty years and yet are used in various disciplines for relation observation and clustering purposes. In 1965, divisive hierarchical methods were proposed in biological sciences and have been used in various disciplines such as, and anthropology, ecology. Furthermore, recently hierarchical methods are being deployed in economy and energy studies. Unlike most clustering algorithms that require the number of clusters to be specified by the user, hierarchical clustering is well suited for situations where the number of clusters is unknown. This paper presents an overview of the hierarchical clustering algorithm. The dissimilarity measurements that can be utilized in hierarchical clustering algorithms are discussed. Further, the paper highlights the various and recent disciplines where the hierarchical clustering algorithms are employed.