• The KIPS Transactions:PartA
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• v.11A no.7 s.91
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• pp.547-554
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• 2004

To play back CM (Continuous Media) in online mode, the multimedia system Is required to have a real-time disk scheduling scheme that can efficiently fulfill the strict temporal constraints of serviced CM streams to prevent hiccups. In general, such disk scheduling is performed based on the concept of periodic prefetching since a CM stream has a rather long Playback time. In this paper, we also propose a periodic prefetching scheme that runs by using real-time disk channels, called on-time delivery channels. Since the channels are generated from the bulk-SCAN algorithm and they can be allocated in a very flexible manner based on the EDF (earliest-deadline-first) algorithm, the proposed scheme provides a better Performance in terms of I/O throughput and the average response time, as well as hiccup-free playback of concurrent CM streams. To show that the proposed scheme outperforms other methods, we give some simulation results.

• Journal of the Korea Society for Simulation
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• v.17 no.3
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• pp.75-83
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• 2008

A deadlock is a condition in which the excessive demand for the resources being used by others causes activities to stop and it is one of the important problems in process control system to detect and prevent deadlocks. While the reachability analyze methods or divide subnets for analyzing methods are well used, it requires a lot of times and effects to analyze the detection of the deadlock status. Furthermore, it could not be effective if the model is complex or huge. Therefore, it is necessary to develop a new and more efficient deadlock detection algorithm. In this paper, a deadlock detection conditions after analyzed the Petri Net using the transitive matrix has been proposed to solve these problems. For presenting the results, the suggested deadlock detection algorithm was also adapted to an illustrated FMS (Flexible Manufacturing System) model.

• Journal of Broadcast Engineering
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• v.15 no.5
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• pp.617-630
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• 2010

At 37th VCEG meeting in Jan. 2009, Toshiba proposed Quadtree-based Adaptive Loop Filter (QALF). The basic concept of QALF is to apply Wiener filter to decoded image after the conventional deblocking filter and to represent the filter on/off flag data for each basic filtering unit in a more efficient way of quadtree structure. QALF could enhance the compression performance of around more than 9%, but the structure of one filter for a decoded frame leaves room for further improvement in the sense that optimal filter for one region of a frame could quite different from the optimal filter for other parts of a picture. This paper proposes multiple adaptive loop filters for better utilization of local characteristics of decoded frame to optimize the region-based Wiener filters. Additional filters, proposed in this paper, cover separate spatial area of each decoded frame according to the performance of previously designed filter(s) to provide the flexibility of rate-distortion based selection of the number of filters.

• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1542-1555
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• 1999

This paper proposes an algorithm for class hierarchies which can optimize member data and member function. This algorithm considers single/multiple inheritance, static/dynamic binding, overloading/overriding, pure virtual/virtual function, and constructor on the hierarchy of C++ class. We need to eliminate unused function that possesses many component element, because the program uses a limited of function in class hierarchies. Previous works on slicing mainly focused on selecting output data and including the related program statement. It was consists of structured programming language and also centralized on error detection, maintenance, and flexible testing. In this paper, we extend to the object-oriented language, makes a linked-table for objects to raise the efficiency of information management, and proposes necessary algorithm for optimizing system Through this process, we can obtain the simplification of program code and the progress of system performance by eliminating unused member data and member function.

• KSBB Journal
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• v.17 no.6
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• pp.560-565
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• 2002

A COG(clusters of orthologous groups of proteins) algorithm was used to detect conserved genes within Proteobacteria and to figure out their relationships. Restricting comparison to the sequences of 42 procaryotes, 33 eubacteria and 16 Proteobacteria, the number of conserved genes was increased. All analyzed procaryotes shared 75 COGs. COG0195, COG0358 and COG0528 were only represented by the 42 procaryotes. Sixtyfour COGs were added as conserved genes in 33 eubacteria. Each Proteobacteria group has a unique repertoire of COGs. Metabolic COGs were more diverse in the beta Proteobacteria group than in the other groups. These results could be used to determine the origins and the evolutionary relationships of Proteobacteria. The possibilities of detecting new biological molecules is high in phylogenetically related organisms, hence the identification of useful proteins by using this algorithm is possible.

• Journal of the Korean Data and Information Science Society
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• v.12 no.2
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• pp.1-10
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• 2001

Neural networks we increasingly being seen as an addition to the statistics toolkit which should be considered alongside both classical and modern statistical methods. Neural networks are usually useful for classification and function estimation. In this paper we concentrate on function estimation using neural networks with weight decay factor The use of weight decay seems both to help the optimization process and to avoid overfitting. In this type of neural networks, the problem to decide the number of hidden nodes, weight decay parameter and iteration number of learning is very important. It is called the optimization of weight decay neural networks. In this paper we propose a automatic optimization based on genetic algorithms. Moreover, we compare the weight decay neural network automatically learned according to automatic optimization with ordinary neural network, projection pursuit regression and support vector machines.

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.699-709
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• 2004

XML is increasingly important in data exchange and information management. Starting point for retrieving the structure and integrating the documents efficiently is clustering the documents that have similar structure. The reason is that we can retrieve the documents more flexible and faster than the method treating the whole documents that have different structure. Therefore, in this paper, we propose the similar structure-based incremental clustering method useful for retrieving the structure of XML documents and integrating them. As a novel method, we use a clustering algorithm for transactional data that facilitates the large number of data, which is quite different from the existing methods that measure the similarity between documents, using vector. We first extract the representative structures of XML documents using sequential pattern algorithm, and then we perform the similar structure based document clustering, assuming that the document as a transaction, the representative structure of the document as the items of the transaction. In addition, we define the cluster cohesion and inter-cluster similarity, and analyze the efficiency of the Proposed method through comparing with the existing method by experiments.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.587-598
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• 2002

In multicast environment, the main objective of group key management is to provide security services to group communications by sharing a single group key among all the members of the group and subsequently encrypting and decrypting all the communication messages exchanged among the members of the group. Up to now, there has been no effort to develop group key management mechanism that considers the rate of users' join/leave operations. Hence, in this research, we propose group key management mechanisms that consider the rate of user's join/leave operations. We also define a new tree structure called variable tree which is much more flexible than full regular trees and show that variable trees are more efficient than full regular trees for group key management. Especially, we propose an algorithm that minimizes the necessary number of rekey messages according to the rate of join and leave operations. We also shows that if the rate of leave operation is greater than 50%, then the tree structure with degrees 2 or 3 are the optimal structures.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.10
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• pp.1279-1286
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• 2021

The electrocardiogram (ECG) signal is a good indicator for early diagnosis of heart abnormalities. The ECG signal has a different reference normal signal for each person. And it requires lots of data to diagnosis. In this paper, we propose an adaptive OpenCL-based FPGA-GPU hybrid-layer platform to efficiently accelerate ECG signal diagnosis. As a result of diagnosing 19870 number of ECG signals of MIT-BIH arrhythmia database on the platform, the FPGA accelerator takes 1.15s, that the execution time was reduced by 89.94% and the power consumption was reduced by 84.0% compared to the software execution. The GPU accelerator takes 1.87s, that the execution time was reduced by 83.56% and the power consumption was reduced by 62.3% compared to the software execution. Although the proposed FPGA-GPU hybrid platform has a slower diagnostic speed than the FPGA accelerator, it can operate a flexible algorithm according to the situation by using the GPU.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1688-1696
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• 2020

The paradigm of Internet-of-things(IoT) systems is changing from a cloud-based system to an edge-based system to solve delays caused by network congestion, server overload and security issues due to data transmission. However, edge-based IoT systems have fatal weaknesses such as lack of performance and flexibility due to various limitations. To improve performance, application-specific hardware can be implemented in the edge device, but performance cannot be improved except for specific applications due to a fixed function. This paper introduces a edge-centric metamorphic IoT(mIoT) platform that can use a variety of hardware through on-demand partial reconfiguration despite the limited hardware resources of the edge device, so we can increase the performance and flexibility of the edge device. According to the experimental results, the edge-centric mIoT platform that executes the reconfiguration algorithm at the edge was able to reduce the number of server accesses by up to 82.2% compared to previous studies in which the reconfiguration algorithm was executed on the server.