• Structural Monitoring and Maintenance
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• v.7 no.4
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• pp.345-365
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• 2020

At present, many machine leaning and data mining methods are used for analyzing and predicting structural response characteristics. However, the platform that combines big data analysis methods with online and offline analysis modules has not been used in actual projects. This work is dedicated to developing a multifunctional Hadoop-Spark big data platform for bridges to monitor and evaluate the serviceability based on structural health monitoring system. It realizes rapid processing, analysis and storage of collected health monitoring data. The platform contains offline computing and online analysis modules, using Hadoop-Spark environment. Hadoop provides the overall framework and storage subsystem for big data platform, while Spark is used for online computing. Finally, the big data Hadoop-Spark platform computational performance is verified through several actual analysis tasks. Experiments show the Hadoop-Spark big data platform has good fault tolerance, scalability and online analysis performance. It can meet the daily analysis requirements of 5s/time for one bridge and 40s/time for 100 bridges.

• Journal of information and communication convergence engineering
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• v.21 no.2
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• pp.117-129
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• 2023

High-utility itemset mining (HIUM) has emerged as a key data-mining paradigm for object-of-interest identification and recommendation systems that serve as frequent itemset identification tools, product or service recommendation systems, etc. Recently, it has gained widespread attention owing to its increasing role in business intelligence, top-N recommendation, and other enterprise solutions. Despite the increasing significance and the inability to provide swift and more accurate predictions, most at-hand solutions, including frequent itemset mining, HUIM, and high average- and fast high-utility itemset mining, are limited to coping with real-time enterprise demands. Moreover, complex computations and high memory exhaustion limit their scalability as enterprise solutions. To address these limitations, this study proposes a model to extract high-utility frequent closed itemsets based on an improved cumulative summary list structure (CSLFC-HUIM) to reduce an optimal set of candidate items in the search space. Moreover, it employs the lift score as the minimum threshold, called the cumulative utility threshold, to prune the search space optimal set of itemsets in a nested-list structure that improves computational time, costs, and memory exhaustion. Simulations over different datasets revealed that the proposed CSLFC-HUIM model outperforms other existing methods, such as closed- and frequent closed-HUIM variants, in terms of execution time and memory consumption, making it suitable for different mined items and allied intelligence of business goals.

• Journal of Broadcast Engineering
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• v.17 no.1
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• pp.108-121
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• 2012

As Scalable Video Coding (SVC) is a video compression standard extended from H.264/AVC, it is a way to provide scalability in terms of temporal, spatial and quality. Although the compression efficiency of SVC is increased due to the scalability in many aspect, it is essential to reduce the complexity in order to efficiently use because the complexity is relatively increased. To reduce the complexity of SVC in the paper, we propose fast mode decision algorithm to reduce the complexity of encoding process using direction information of B-picture by efficiently performing inter-layer prediction. The proposed algorithm is a fast mode decision algorithm that makes different from detection mode number of forward and backward, bi-direction in the way using best mode of base-layer up-sampled after simply SKIP mode detection using the direction information of best mode of base-layer up-sampled. The experimental results show that the proposed algorithm approach can achieve the maximum computational time saving about 53% with almost no loss of rate distortion (RD) performance in the enhancement layer.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.6 no.2
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• pp.71-75
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• 2013

Recently proliferating heterogeneous multimedia service environments should be able to deal with many different transmission speeds, image sizes, or qualities of video. However, not many existing video compression standards satisfy those necessities. To satisfy the functional requirements, the standardization of the H.264/AVC Scalable Extension (SE) technique has been recently completed. It is an extension of the H.264/AVC which can encode several image sizes and qualities at the same time as a single bitstream. To perform optimum mode decision, motion estimation is performed for all MB modes, and the RD costs are compared to identify an MB mode with the smallest RD cost. This increases computational complexity of H.264/AVC SE encoding. In this paper, we propose an early skip mode detection scheme to reduce candidate modes and suggest an algorithm of fast mode decision utilizing reference modes according to the mode history.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.7A
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• pp.547-556
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• 2003

This paper proposes a novel arithmetic unit over GF(2$^{m}$ ) for low-area elliptic curve cryptographic processor. The proposed arithmetic unit, which is linear feed back shift register (LFSR) architecture, is designed by using hardware sharing between the binary GCD algorithm and the most significant bit (MSB)-first multiplication scheme, and it can perform both division and multiplication in GF(2$^{m}$ ). In other word, the proposed architecture produce division results at a rate of one per 2m-1 clock cycles in division mode and multiplication results at a rate of one per m clock cycles in multiplication mode. Analysis shows that the computational delay time of the proposed architecture, for division, is less than previously proposed dividers with reduced transistor counts. In addition, since the proposed arithmetic unit does not restrict the choice of irreducible polynomials and has regularity and modularity, it provides a high flexibility and scalability with respect to the field size m. Therefore, the proposed novel architecture can be used for both division and multiplication circuit of elliptic curve cryptographic processor. Specially, it is well suited to low-area applications such as smart cards and hand held devices.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.44 no.3 s.357
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• pp.18-25
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• 2007

In sensor networks, sensor nodes have limited computational capacity, power and memory. Thus energy efficiency is one of the most important requirements. How to extend the lifetime of wireless sensor networks has been widely discussed in recent years. However, one of the most effective approaches to cope with power conservation, network scalability, and load balancing is clustering technique. The function of a cluster head is to collect and route messages of all the nodes within its cluster. Cluster heads must be changed periodically for low energy consumption and load distribution. In this paper, we propose an energy-aware cluster head selection algorithm and Distance Estimation-based distributed Clustering Algorithm (DECA) in wireless sensor networks, which exchanges cluster heads for less energy consumption by distance estimation. Our simulation result shows that DECA can improve the system lifetime of sensor networks up to three times compared to the conventional scheme.

• The KIPS Transactions:PartA
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• v.11A no.2
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• pp.109-114
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• 2004

This paper presents a high-speed bit-parallel systolic divider for computing modular division A($\chi$)/B($\chi$) mod G($\chi$) in finite fields GF$(2^m)$. The presented divider is based on the binary GCD algorithm and verified through FPGA implementation. The proposed architecture produces division results at a rate of one every 1 clock cycles after an initial delay of 5m-2. Analysis shows that the proposed divider provides a significant reduction in both chip area and computational delay time compared to previously proposed systolic dividers with the same I/O format. In addition, since the proposed architecture does not restrict the choice of irreducible polynomials and has regularity and modularity, it provides a high flexibility and Scalability with respect to the field size m. Therefore, the proposed divider is well suited to VLSI implementation.

• Journal of KIISE:Computing Practices and Letters
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• v.6 no.6
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• pp.555-568
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• 2000

The World Wide Web has become the largest virtual system that is almost universal in scope. In recent research, it has become effective to utilize idle hosts existing in the World Wide Web for running applications that require a substantial amount of computation. This novel computing paradigm has been referred to as the advent of global computing. In this paper, we implement and propose a mobile object-based global computing framework called Tiger, whose primary goal is to present novel object-oriented programming libraries that support distribution, dispatching, migration of objects and concurrency among computational activities. The programming libraries provide programmers with access, location and migration transparency for distributed and mobile objects. Tiger's second goal is to provide a system supporting requisites for a global computing environment - scalability, resource and location management. The Tiger system and the programming libraries provided allow a programmer to easily develop an objectoriented parallel and distributed application using globally extended computing resources. We also present the improvement in performance gained by conducting the experiment with highly intensive computations such as parallel fractal image processing and genetic-neuro-fuzzy algorithms.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.6
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• pp.1010-1015
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• 2008

The choice of RFID system is recently progressing(being) rapidly at various field. For the sake of RFID system popularization, However, We should solve privacy invasion to gain the pirated information of RFID tag. There is the safest M Ohkubos's skill among preexistent studying to solve these problems. But, this skill has a problem that demands a immense calculation capability caused an increase in tag number when we discriminate tags. So, This paper proposes the way of transplant to Grid environment for keeping Privacy Protection up and reducing the Tag Identification Time. And, We propose the Tag Identification Process Model to apply Even Division Algorithm to separate SP with same site in each node. If the proposed model works in Grid environment at once, it would reduce the time to identify tags to 1/k.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.5
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• pp.143-150
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• 2019

Cloud computing has recently become an attractive solution for massively multiplayer online games(MMOGs), as it lifts operators from the burden of buying and maintaining hardware. Peer-to-peer(P2P) -based solutions present several advantages, including the inherent scalability, self-repairing, and natural load distribution capabilities. We propose a hybrid architecture for MMOGs that combines technological advantages of two different paradigms, P2P and cloud computing. An efficient and effective provisioning of resources and mapping of load are mandatory to realize an architecture that scales in economical cost and quality of service to large communities of users. As the number of simultaneous players keeps growing, the hybrid architecture relieves a lot of computational power and network traffic, the load on the servers in the cloud by exploiting the capacity of the peers. For MMOGs, besides server time, bandwidth costs represent a major expense when renting on-demand resources. Simulation results show that by controlling the amount of cloud and user-provided resource, the proposed hybrid architecture can reduce the bandwidth at the server while utilizing enough bandwidth of players.