• 산업경영시스템학회지
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• 제39권1호
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• pp.56-63
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• 2016

We consider a satellite mission scheduling problem, which is a promising problem in recent satellite industry. This problem has various considerations such as customer importance, due date, limited capacity of energy and memory, distance of the location of each mission, etc. Also we consider the objective of each satellite such as general purpose satellite, strategic mission and commercial satellite. And this problem can be modelled as a general knapsack problem, which is famous NP-hard problem, if the objective is defined as to maximize the total mission score performed. To solve this kind of problem, heuristic algorithm such as taboo and genetic algorithm are applied and their performance are acceptable in some extent. To propose more efficient algorithm than previous research, we applied a particle swarm optimization algorithm, which is the most promising method in optimization problem recently in this research. Owing to limitation of current study in obtaining real information and several assumptions, we generated 200 satellite missions with required information for each mission. Based on generated information, we compared the results by our approach algorithm with those of CPLEX. This comparison shows that our proposed approach give us almost accurate results as just less than 3% error rate, and computation time is just a little to be applied to real problem. Also this algorithm has enough scalability by innate characteristic of PSO. We also applied it to mission scheduling problem of various class of satellite. The results are quite reasonable enough to conclude that our proposed algorithm may work in satellite mission scheduling problem.

• Journal of Information Technology Applications and Management
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• 제20권3_spc호
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• pp.219-230
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• 2013

Real time accessiblity and agility in Ubiquitous-commerce is required under ubiquitous computing environment. The Research has been actively processed in e-commerce so as to improve the accuracy of recommendation. Existing Collaborative filtering (CF) can not reflect contents of the items and has the problem of the process of selection in the neighborhood user group and the problems of sparsity and scalability as well. Although a system has been practically used to improve these defects, it still does not reflect attributes of the item. In this paper, to solve this problem, We can use a implicit method which is used by customer's data and purchase history data. We propose a new clustering method of weighted preference for customer using k-means clustering and Bayesian network in order to improve the accuracy of recommendation. To verify improved performance of the proposed system, we make experiments with dataset collected in a cosmetic internet shopping mall.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 추계종합학술대회 논문집(1)
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• pp.9-12
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• 2000

Today, QoS is one of the most critical issues in the network research area and Differentiated Services (DiffServ) is considered as the most prominent solution to provide some kinds of service differentiation without introducing any scalability problem. Among DiffServ's approaches, Assured Service (AS) provides some minimal level of QoS guarantee by treating more preferably than traditional Best Effort (BE) traffic and by using different level of drop probabilities within the same AS classes. In this paper, we investigate the ECN's capability of improving overall goodput of the flows and the possibility of resolving the fairness problem among the flows belonging to same class in Differentiated Services architecture.

• 산업기술연구
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• 제17권
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• pp.255-260
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• 1997

The analysis of eigenvalue and eigenvector is a crucial procedure for many electromagnetic computation problems. Although it is always the case in practice that only selected eigenpairs are needed, computation of eigenpair still seems to be a time-consuming task. In order to compute the eigenpair more quickly, there are two resorts: one is to select a good algorithm with care and another is to use parallelization technique to improve the speed of the computing. In this paper, one of the best eigensolver, the Davidson method, is parallelized on a cluster of workstations. We apply this scheme to a ridged waveguide design problem and obtain promising linear speedup and scalability.

• Journal of information and communication convergence engineering
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• 제14권2호
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• pp.84-88
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• 2016

As good example of potential application-specific requirement, (m,k)-firm real-time streams have been recently introduced to deliver multimedia data efficiently in wireless sensor networks. In addition to stream model, communication protocols to meet specific (m,k)-firm real-time streams have been newly developed or extended from existing protocols. However, since the existing schemes for an (m,k)-firm stream have been proposed under typical flat architecture, the scalability problem remains unsolved when the number of real-time flows increases in the networks. To solve this problem, in this paper, we propose a new clustering scheme for an (m,k)-firm stream. The two different clustering algorithms are performed according to either the (m,k)-firm requirement or the deadline. Simulation results are presented to demonstrate the suitability of the proposed scheme under hierarchical architecture by showing that its performance is acceptable irrespective of the increase in the number of flows.

• 한국통신학회논문지
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• 제34권3B호
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• pp.225-234
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• 2009

Recently IPTV service is penetrating to the ordinary home users very swiftly. One of the first phase of IPTV service is considered to be VoD, and a nationwide availability of the VoD service imposes tremendous pressure to the network resource due to its requirements for the broad bandwidth, the inherent nature of unicast technology, and the large scalability, etc. This work suggests a novel and practical method to the design of network resource for the VoD service. Especially, we explore the distributed content storage problem that takes into account the popularity of the video contents and its corresponding link dimensioning problem that takes into account the grade of service for the flow level quality of service about the VoD service. By assuming a realistic topology for the nationwide IP backbone network of Korea, which is a typical tree topology, we suggest an analytic method for the design of VoD service.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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• pp.154-157
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• 1999

Photonic Slot Routing(PSR) is a promising approach to solve the fundamental scalability problem of all-optical packet switched WDM networks. In photonic slot routing, packets destined for the same subnetwork are aggregated to form a photonic slot which is jointly routed as a single unit of information through the network. The relative location of the nodes from bridge may cause to fairness problem in the unidirectional WDM ring network based on PSR. As photonic slots from different subnetworks can originate contentions at the bridge, packets may be dropped and retransmitted. Thus we evaluated the performance of PSR based WDM ring network in the point of fairness for each node and slot contentions at the bridge. Simulation results show that the PSR based WDM ring requires a slot access mechanism to guarantee the transmission fairness and efficient switch architecture to resolve slot contention at the bridge.

• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 2002년도 춘계공동학술대회
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• pp.320-325
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• 2002

Today many companies offer millions of products to customers. They are faced with a problem to choose particular products . In response to this problem a new marking strategy, recommendation has emerged. Among recommendation technologies collaborative filtering is most preferred. But the performance degrades with the number of customers and products. Namely, collaborative filtering has two major limitations, sparsity and scalability. To overcome these problems we introduced a new recommendation methodology using adjusted product hierarchy, grain. This methodology focuses on dimensionality reduction to improve recommendation quality and uses a marketer's specific knowledge or experience. In addition, it uses a new measure in the neighborhood formation step which is the most important one in recommendation process.

• Journal of information and communication convergence engineering
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• 제19권3호
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• pp.155-160
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• 2021

Differential evolution is an efficient algorithm for solving continuous optimization problems. However, its performance deteriorates rapidly, and the runtime increases exponentially when differential evolution is applied for solving large-scale optimization problems. Hence, a novel cooperative coevolution differential evolution based on Spark (known as SparkDECC) is proposed. The divide-and-conquer strategy is used in SparkDECC. First, the large-scale problem is decomposed into several low-dimensional subproblems using the random grouping strategy. Subsequently, each subproblem can be addressed in a parallel manner by exploiting the parallel computation capability of the resilient distributed datasets model in Spark. Finally, the optimal solution of the entire problem is obtained using the cooperation mechanism. The experimental results on 13 high-benchmark functions show that the new algorithm performs well in terms of speedup and scalability. The effectiveness and applicability of the proposed algorithm are verified.

• 대한임베디드공학회논문지
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• 제14권3호
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• pp.113-121
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• 2019

Algorithms for geographical routing and location update attract the researchers' interests in wireless ad hoc networks. Even though many various schemes have been proposed, most of them cause scalability problem in small groups of nodes. To defeat this problem, flooding algorithm is widely utilized due to low complexity. However, there is no previous research work to evaluate flooding algorithm through implementation instead of simulation. In this paper, we present implementation of flooding algorithm on Raspberry Pi and performance evaluation results.