• Korea-Australia Rheology Journal
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• v.14 no.4
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• pp.189-201
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• 2002

The interaction between hydrophobically modified hydroxyethyl cellulose (hmHEC), containing approximately 1 wt% side-alkyl chains of $C_{16}$, and an anionic sodium dodecyl sulphate (SDS) surfactant was investigated. For a semi-dilute solution of 0.5 wt% hmHEC, the previously observed behaviour of a maximum in solution viscosity at intermediate SDS concentrations, followed by a drop at higher SDS concentrations, until above the cmc of surfactant when the solution resembles that of the unsubstituted polymer, was confirmed. Additionally, a two-phase region containing a hydrogel phase and a water-like supernatant was found at low SDS concentrations up to 0.2 wt%, a concentration which is akin to the critical association concentration, cac, of SDS in the presence of hmHEC. Above this concentration, SDS molecules bind strongly to form mixed micellar aggregates with the polymer alkyl side-chains, thus strengthening the network junctions, resulting in the observed increase in viscosity and elastic modulus of the solution. The shear behaviour of this polymer-surfactant complex during steady and step stress experiments was examined In great detail. Between SDS concentrations of 0.2 and 0.25 wt%, the shear viscosity of the hmHEC-polymer complex network undergoes shear-induced thickening, followed by a two-stage shear-induced fracture or break-up of the network. The thickening is thought to be due to structural rearrangement, causing the network of flexible polymers to expand, enabling some polymer hydrophobic groups to be converted from intra- to inter-chain associations. At higher applied stress, a partial local break-up of the network occurs, while at even higher stress, above the critical or network yield stress, a complete fracture of the network into small microgel-like units, Is believed to occur. This second network rupture is progressive with time of shear and no steady state in viscosity was observed even after 300 s. The structure which was reformed after the cessation of shear is found to be significantly different from the original state.

• IEMEK Journal of Embedded Systems and Applications
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• v.9 no.6
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• pp.361-367
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• 2014

This paper introduces balancing energy and memory consumption for lifetime increase of wireless sensor network. In cluster-based wireless sensor network, sensor nodes adjacent of cluster heads have a tendency to deplete their own battery energy and cluster heads occupy memory space significantly. If the nodes close to region where events occur frequently consume their energy and memory fully, network might be destroyed even though most of nodes are still alive. Therefore, it needs to balance network energy and memory with consideration of event occurrence probability so that network lifetime is increased. We show a method of balancing wireless sensor network energy and memory to organize cluster groups and elect cluster heads in terms of event occurrence probability.

• Journal of the Korea Society for Simulation
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• v.13 no.2
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• pp.65-73
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• 2004

The capability to provide the network service must survive even if a significant network system element is disrupted. To sustain the network service under the system failure, network survivability mechanisms minimizing the impact of failures are needed. Also, since the mobile network has its unique characteristic, the survivability scheme for the vulnerability of the mobile network is required. This paper proposes a survivability scheme to support the reliable service of the wireless access point level (BS-base station system). By the survivability scheme, the mobile network can use an overlap BS of the cellular network architecture after a BS system failure. We analyze the performance of the proposed scheme using Markov model. Also, a computer simulation is used for the scheme analysis. The proposed scheme shows that the service of the mobile network can be provided under the BS system failure.

• Journal of Computing Science and Engineering
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• v.2 no.4
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• pp.412-427
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• 2008

We propose ID-exchange protocol for Connectionless Location-Awareness Service (CLAS) to locate mobile nodes in indoor sensor network. When adapting location-awareness service to sensor network, the target system must be designed in accordance with various metrics which reflect the system requirement. We especially consider sustainability of the existing service which has been provided for its original purpose, such as environmental monitoring. The detailed meaning of sustainability here is that, even if location-awareness service is newly added to the existing service, the system must be assured to retain a stable network condition, and to deal with newly caused traffic properly. The CLAS ID-exchange protocol is especially designed for fixture and mobile nodes communication to achieve these properties. The protocol operates on 802.15.4 MAC layer to make mobile node work independently of the procedure to build routing table of fixture node, so a stable routing condition can be achieved even if there are many mobile nodes. Moreover, the dedicated frequency channel is assigned only for this protocol, so that traffic caused by location-awareness service can be distributed to another channel. A real system adapting the protocol was implemented to monitor fire and authorities' positions. We verified the overhead and elapsed time for location-awareness. The result shows the proposed protocol has a high performance in detecting speed, traffic distribution, and stability of overall network.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.5
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• pp.915-920
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• 2007

Using the existing algorithms that estimate the background noise, the detection probability for the week tonals is low and for the even week tonals, there is a limit not detected. Therefore it is required to algorithms which can improve the performance of the tonal extraction. Recently, many researches using artificial neural networks in sonar signal processing are performed. We propose a neural network with double feedback that can remove automatically the background noise and detect the even week tonals buried in background noise, therefore not detected by growing the week tonals lastingly for a certain time. For the real underwater target, experiments for the tonal extraction are performed by using the existing algorithms that estimate the background noise and the proposed neural network. As a result of the experiment, a method using the proposed neural network showed the better performance of the tonal extraction in comparison with the existing algorithms.

• Journal of Internet Computing and Services
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• v.23 no.4
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• pp.11-19
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• 2022

This paper is a study to evaluate the performance when classifying explosive components by capacity using a convolutional neural network (CNN). Among the existing explosive classification methods, the IMS steam detector method determines the presence or absence of an explosive only when the explosive concentration exceeds the threshold set by the user. The IMS steam detector has a problem of determining that even if an explosive exists, the explosive does not exist in an amount that does not exceed the threshold. Therefore, it is necessary to detect the explosive component even when the concentration of the explosive component does not exceed the threshold. Accordingly, in this paper, after imaging explosive time series data with the Gramian Angular Field (GAF) algorithm, it is possible to determine whether there are explosive components and the amount of explosive components even when the concentration of explosive components does not exceed a threshold.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.36 no.6
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• pp.603-608
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• 2023

Carbon black with high purity and excellent conductivity is used as a conductive filler in the semiconductive compound for EHV (Extra High Voltage) power cables of 345 kV or higher. When carbon black and CNT (carbon nanotube) are applied together as a conductive filler of a semiconductive compound, stable electrical properties of the semiconductive compound can be maintained even though the amount of conductive filler is significantly reduced. In EHV power cables, since the semi-conductive layer is close to the conductor, stable electrical characteristics are required even under high-temperature conditions caused by heat generated from the conductor. In this study, the theoretical principle that a semiconductive compound applied with carbon black and CNT can maintain excellent electrical properties even under high-temperature conditions was studied. Basically, the conductive fillers dispersed in the matrix form an electrical network. The base polymer and the matrix of the composite, expands by heat under high temperature conditions. Because of this, the electrical network connected by the conductive fillers is weakened. In particular, since the conductive filler has high thermal conductivity, the semiconductive compound causes more thermal expansion. Therefore, the effect of CNT as a conductive filler on the thermal conductivity, thermal expansion coefficient, and volume resistivity of the semiconductive compound was studied. From this result, thermal expansion and composition of the electrical network under high temperature conditions are explained.

• IE interfaces
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• v.15 no.3
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• pp.247-255
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• 2002

For the recent multimedia service, the network should be fast, stable, and reliable. In order to provide reliability of the network, certain survivability of the network, which guarantees it's functions even though there is some failure on the network, should be satisfied. Also, for a pair of nodes on the network, there must be paths of which numbers of hops are within a certain limit for realtime service between them. In this paper, we propose a longest shortcut method for solving the survivable network design problems with hop limit. Through the computational results, we compare the efficiency of the method with an existing shortest shortcut method and find that the proposed method is more efficient than the shortest shortcut method.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2002.04a
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• pp.463-468
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• 2002

In this paper, we proposed a recurrent time delayed neural network controller which compensate a output of neural network controller. Even if learn by neural network controller, it can occur an bad results from disturbance or load variations. So in order to adjust above case, we used the fuzzy compensator to get an expected results. And the weight of main neural network can be changed with the result of learning a inverse model neural network of plant, so a expected dynamic characteristics of plant can be got. As the results of simulation through the second order plant, we confirmed that the proposed recurrent time delayed neural network controller get a good response compare with a time delayed neural network controller.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.3
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• pp.35-42
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• 2007

We describe the problem of reducing the key material in the Even-Mansour cipher without security degradation. Even and Mansour proposed a block cipher based on XORing secret key material just prior to and after applying random oracle permutation P such that $C=k_2\bigoplus P(M\bigoplus k_1)$. Recently, Gentry and Ramzan showed that this scheme in the random permutation oracle can be replaced by the four-round Feistel network construction in the random function oracle and also proved that their scheme is super-pseudorandom. In this paper we reduce the key size from 2n to n, which is the optimal key size of Even-Mansour cipher in the random function oracle model and also give almost the same level of security.