• Journal of Digital Convergence
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• v.13 no.11
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• pp.179-185
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• 2015

In this paper, we research the IPTV that is the convergence technique of TV and network technique and performed the performance evaluation of picture quality of IPTV in the situation of increasing the network traffic in the Internet environment. To do this, we constructed the mock Internet network similar to the real Internet environment and measured the quality of received video using V-Factor model according to the increase of network traffic, and analyzed the result of the experiment. Making use of the result of this paper for the threshold value of V-Factor, the measured factor of network performance, the measured factor of video performance in the watchable IPTV video quality.

• Proceedings of the IEEK Conference
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• 2003.07c
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• pp.2807-2810
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• 2003

In this paper, we propose a fuzzy control method for improving the control performance by automatically tuning the scaling factor. The proposed method is that automatically tune the input scaling factor and the output scaling factor of fuzzy logic system through neural network. Used neural network is ADALINE (ADAptive Linear NEron) neural network with delayed input. ADALINE neural network has simple construct, superior learning capacity and small computation time. In order to verify the effectiveness of the proposed control method, we performed simulation. The results showed that the proposed control method improves considerably on the environment of the disturbance.

• Journal of Korean Society for Quality Management
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• v.30 no.2
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• pp.86-98
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• 2002

Defining the relationship between the quality of injection molded parts and the process condition is very complicate because of lots of factor are involved and each factor has a non-linearity. With the development of CAE(Computer Aided Engineering) technology, the estimation of volumetric shrinkage of injection mold parts is possible by computer simulation even though restricted application. In this research, Neural Network applied for finding optimal processing condition. The percent of volumetric shrinkage compared on each case and show neural network can be successfully applied selecting optimum condition not only within factor level but also between factor level.

• ETRI Journal
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• v.39 no.5
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• pp.695-706
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• 2017

This paper presents a caching algorithm that offers better reconstructed data quality to the requesters than a probabilistic caching scheme while maintaining comparable network performance. It decides whether an incoming data packet must be cached based on the dynamic caching probability, which is adjusted according to the priorities of content carried by the data packet, the uncertainty of content popularities, and the records of cache events in the router. The adaptation of caching probability depends on the priorities of content, the multiplication factor adaptation, and the addition factor adaptation. The multiplication factor adaptation is computed from an instantaneous cache-hit ratio, whereas the addition factor adaptation relies on a multiplication factor, popularities of requested contents, a cache-hit ratio, and a cache-miss ratio. We evaluate the performance of the caching algorithm by comparing it with previous caching schemes in network simulation. The simulation results indicate that our proposed caching algorithm surpasses previous schemes in terms of data quality and is comparable in terms of network performance.

• ETRI Journal
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• v.40 no.5
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• pp.604-612
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• 2018

To solve the problem of unbalanced loads and the short network lifetime of heterogeneous wireless sensor networks, this paper proposes a node-selection algorithm based on energy balance and dynamic adjustment. The spacing and energy of the nodes are calculated according to the proximity to the network nodes and the characteristics of the link structure. The direction factor and the energy-adjustment factor are introduced to optimize the node-selection probability in order to realize the dynamic selection of network nodes. On this basis, the target path is selected by the relevance of the nodes, and nodes with insufficient energy values are excluded in real time by the establishment of the node-selection mechanism, which guarantees the normal operation of the network and a balanced energy consumption. Simulation results show that this algorithm can effectively extend the network lifetime, and it has better stability, higher accuracy, and an enhanced data-receiving rate in sufficient time.

• Current Optics and Photonics
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• v.4 no.4
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• pp.310-316
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• 2020

We propose and experimentally demonstrate an all-optical radio frequency (RF) spectrum broadening system based on time compression. By utilizing the procedure of dispersion compensation values, the frequency domain is broadened by compressing the linear chirp optical pulse which has been multiplexed by the radio frequency. A detailed mathematical description elucidates that the time compression is a very preferred scheme for spectrum broadening. We also report experimental results to prove this method, magnification factor at 2.7, 8 and 11 have been tested with different dispersion values of fiber, the experimental results agree well with the theoretical results. The proposed system is flexible and the magnification factor is determined by the dispersion values, the proposed scheme is a linear system. In addition, the influence of key parameters, for instance optical bandwidth and the sideband suppression ratio (SSR), are discussed. Magnification factor 11 of the proposed system is demonstrated.

• Journal of Korea Society of Industrial Information Systems
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• v.23 no.5
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• pp.33-41
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• 2018

Most important thing when designing and implementing a supply chain network is to consider various problems which may occur in real world situation. In this paper, we propose a supply chain network considering two problems (environmental factor and transportation types) under real world situation. CO2 emission amount as environmental factor is considered since it is usually generated from production and transportation processes. Normal delivery, direct delivery and direct shipment as transportation types are also considered since many customers ask various transportation types for delivery or shipment of their products under on-line or off-line purchase environment. The proposed supply chain network considering environmental factor and transportation types is represented in a mathematical formulation and implemented using hybrid genetic algorithm (HGA) approach. In numerical experiments, several scales of supply chain networks are presented and implemented using HGA approach. The performance of the HGA approach is compared with those of some conventional approaches under various measures of performance. Finally, it is proved that the performance of the HGA approach is superior to those of the others.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2005.10a
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• pp.327-332
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• 2005

This paper aims to analysis for evaluation factor and success prediction of port innovative cluster. This paper is divided three factors such ac policy, source and operation. In addition, three factors are divided into the twelve detail factors. the weight of each factor is calculated by Kohonen Network. At the result, this paper places the priority on the source factor.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.41 no.8
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• pp.914-921
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• 1992

In this paper, we introduce a Walsh network and an LMS algorithm, and show how these can be realized as an adaptive equalizer. The Walsh network is built from a set of Walsh and Block pulse functions. In the LMS algorithm, the convergence factor is an important design parameter because it governs stability and convergence speed, which depend on the proper choice of the convergence facotr. The conventional adaptation techniques use a fixed time constant convergence factor by the method of trial and error. In this paper, we propose an optimal method in the choice of the convergence factor. The proposed algorithm depends on the received signal and the output of the Walsh network in real time.

• International Journal of Computer Science & Network Security
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• v.22 no.4
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• pp.299-309
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• 2022

Human factor represents a very challenging issue to organizations. Human factor is responsible for many cybersecurity incidents by noncompliance with the organization security policies. In this paper we conduct a comprehensive review of the literature to identify strategies to address human factor. Security awareness, training and education program is the main strategy to address human factor. Scholars have consistently argued that importance of security awareness to prevent incidents from human behavior.