• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 1998년도 The 12th Asia Quality Management Symposium* Total Quality Management for Restoring Competitiveness
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• pp.696-704
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• 1998

Artificial neural networks (ANN) have successfully applied into various areas. But, How to effectively established network is the one of the critical problem. This study will focus on this problem and try to extensively study. Firstly, four different learning algorithms ANNs were constructed. The learning algorithms include backpropagation, simulated annealing, genetic algorithm, and tabu search. The experimental results of the above four different learning algorithms were tested by statistical analysis. The training RMS, training time, and testing RMS were used as the comparison criteria.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2004년도 춘계학술대회 논문집
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• pp.287-292
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• 2004

In this study, we made a comparative study of backpropagation neural network and probabilistic neural network and bayesian classifier and perceptron as shape recognition algorithm of welding flaws. For this purpose, variables are applied the same to four algorithms. Here, feature variable is composed of time domain signal itself and frequency domain signal itself, Through this process, we confirmed advantages/disadvantages of four algorithms and identified application methods of few algorithms.

• 한국정보통신학회논문지
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• 제24권5호
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• pp.662-665
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• 2020

Energy Efficiency in any WSN (Wireless Sensor Network) is a critical issue to elongate the life of the batteries equipped in sensors. LEACH(Low Energy Adaptive Clustering Hierarchy) is one of the mostly used routing algorithms which reduce the amount of transmitted data and save the energy in the network. In this paper, a new technique to select channels in routing algorithms is suggested and compared with the LEACH, ALEACH and PEGASIS. This technique forms clusters depending upon the node density as the deployement of the nodes is random. As a result, the proposed algorithm presents the better performance of the energy efficiency than those of the current algorithms.

• Journal of Information Processing Systems
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• 제10권3호
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• pp.471-482
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• 2014

Influence maximization is an important problem of finding a small subset of nodes in a social network, such that by targeting this set, one will maximize the expected spread of influence in the network. To improve the efficiency of algorithm KK_Greedy proposed by Kempe et al., we propose two improved algorithms, Lv_NewGreedy and Lv_CELF. By combining all of advantages of these two algorithms, we propose a mixed algorithm Lv_MixedGreedy. We conducted experiments on two synthetically datasets and show that our improved algorithms have a matching influence with their benchmark algorithms, while being faster than them.

• International Journal of Computer Science & Network Security
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• 제21권9호
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• pp.41-50
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• 2021

Cloud computing is one of the most expanding technologies nowadays; it offers many benefits that make it more cost-effective and more reliable in the business. This paper highlights the various benefits of cloud computing and discusses different cryptography algorithms being used to secure communications in cloud computing environments. Moreover, this thesis aims to propose some improvements to enhance the security and safety of cloud computing technologies.

• 한국경영과학회지
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• 제29권3호
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• pp.145-155
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• 2004

The design of a communication network has long been a challenging optimization problem. Since the optimal design of a network topology is a well known as a NP-complete problem, many researches have been conducted to obtain near optimal solutions in polynomial time instead of exact optimal solutions. All of these researches suggested diverse heuristic algorithms that can be applied to network design problems. Among these algorithms, a simulated annealing algorithm has been proved to guarantee a good solution for many NP-complete problems. in applying the simulated annealing algorithms to network design problems, generating mechanisms for initial solutions and candidate solutions play an important role in terms of goodness of a solution and efficiency. This study aims at analyzing these mechanisms through experiments, and then suggesting reliable mechanisms.

• International Journal of Computer Science & Network Security
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• 제22권4호
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• pp.131-138
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• 2022

A Mobile Ad-hoc Network (MANET) is a collection of moving nodes that communicate and collaborate without relying on a pre-existing infrastructure. In this type of network, nodes can freely move in any direction. Routing in this sort of network has always been problematic because of the mobility of nodes. Most existing protocols use simple routing algorithms and criteria, while another important criterion is path selection. The existing protocols should be optimized to resolve these deficiencies. 'Particle Swarm Optimization (PSO)' is an influenced method as it resembles the social behavior of a flock of birds. Genetic algorithms (GA) are search algorithms that use natural selection and genetic principles. This paper applies these optimization models to the OLSR routing protocol and compares their performances across different metrics and varying node sizes. The experimental analysis shows that the Genetic Algorithm is better compared to PSO. The comparison was carried out with the help of the simulation tool NS2, NAM (Network Animator), and xgraph, which was used to create the graphs from the trace files.

• Journal of Communications and Networks
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• 제13권4호
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• pp.327-338
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• 2011

With the incitation to reduce power consumption and the aggressive reuse of spectral resources, there is an inevitable trend towards the deployment of small-cell networks by decomposing a traditional single-tier network into a multi-tier network with very high throughput per network area. However, this cell size reduction increases the complexity of network operation and the severity of cross-tier interference. In this paper, we consider a downlink two-tier network comprising of a multiple-antenna macrocell base station and a single femtocell access point, each serving multiples users with a single antenna. In this scenario, we treat the following beamforming optimization problems: i) Total transmit power minimization problem; ii) mean-square error balancing problem; and iii) interference power minimization problem. In the presence of perfect channel state information (CSI), we formulate the optimization algorithms in a centralized manner and determine the optimal beamformers using standard convex optimization techniques. In addition, we propose semi-decentralized algorithms to overcome the drawback of centralized design by introducing the signal-to-leakage plus noise ratio criteria. Taking into account imperfect CSI for both centralized and semi-decentralized approaches, we also propose robust algorithms tailored by the worst-case design to mitigate the effect of channel uncertainty. Finally, numerical results are presented to validate our proposed algorithms.

• 한국경영과학회지
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• 제32권2호
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• pp.89-97
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• 2007

We study the maximum integer multiflow problem and the minimum multicut problem in a ring network. Both problems in a general network are known to be NP-hard. In this paper, we develop polynomial time algorithms to solve the problems. We also prove that even In a ring network, maximum multiflow is not always integral, which implies that the amount of maximum integer flow does not always reach the minimum capacity of multicut.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2001년도 춘계종합학술대회
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• pp.144-147
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• 2001

ATM 망에서는 전송률 기반의 ABR 흐름제어를 위해 다수의 알고리즘들이 제안되고 있다. 이 알고리즘들의 주 목적은 셀 손실률을 회피하고 미사용중인 대역폭을 ABR 트래픽에 의해 사용되게 하는 것이다. 이리한 알고리즘들은 EFCI와 ER 스위치에서 동작하여 ABR 트래픽을 제어하는데 사용된다. 본 논문에서는 이러한 알고리즘들이 다양한 scale network에 적용하여 각 알고리즘들의 특성에 대해 분석하고, 각 알고리즘들의 셀 손실률을 도시하여 그 성능을 비교, 분석하고자 한다.