• Journal of the Korea Convergence Society
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• v.3 no.2
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• pp.7-12
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• 2012

An advanced and proactive response mechanism against diverse attacks should be proposed for enhance its security and reliability on android based commercial smart work device. In this study, we propose a user-oriented vulnerability analysis and response system on commercial smart work device based on android when diverse attacks are activated. Proposed mechanism uses simplified and optimized memory for monitoring and detecting the abnormal behavior on commercial smart work device, with which we can find and determine the attacker's attempts. Additionally, proposed mechanism provides advanced vulnerability analysis and monitoring/control module.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.04a
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• pp.146-152
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• 1997

This paper deals with a study of striker type impact hammer drill for improving the drilling performance. The study was performed through a numerical simulation of the impact hammer mechanism, an experimental comparison of the numerical simulation results and an optimization of the impact mechanism. The numerical model of the impact hammer drill takes into account the striker motion and the effects of the pressure in the cylinder as well as the friction acting on the striker. The equation of motion is solved with the pressure equation in the cylinder and the friction force. At the moment of impact, an ideal impact model that uses restitutiion codfficient is used to calculate the sudden change of the striker motion. The impact force numerically simulated shows a good agreement with the experimental results and thus, the validity of the numerical model is proven. Based upon the proposed model, an optimization was performed to improve the impact force of the hammer drill. The objective function is to maximize the impact force and the design variables are striker mass, frequency of piston, bit guide mass, cylindrical diameter and dimensions of the mechanism components. Each design variable and some other conditions that are essential to maintain normal operation of the hammer drill are considered as constraints. The optimized result shows remarkable improvement in impact force and an experimental proof was investigated.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.579-579
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• 2012

Graphene has recently been a subject of much interest as a potential platform for future nanodevices such as flexible thin-film transistors, touch panels, and solar cells. And chemical vapor deposition (CVD) and related surface segregation techniques are a potentially scalable approach to synthesizing graphite films on a variety of metal substrates. The structural properties of such films have been studied by a number of methods, including Raman scattering, x-ray photoelectron spectroscopy (XPS), atomic force microscopy (AFM), and transmission electron microscopy (TEM). An understanding of the structural quality and thickness of the graphite films is of paramount importance both in improving growth procedures and understanding the resulting films' electronic properties. In this study, we synthesized the few-layered grapheneunder optimized condition to figure out the growth mechanism seen in CVD-grown graphenee by using various electron microscope. Especially, we observed directly film thickness, quality, nucleation site, and uniformity of grpahene by using AEM. The details will be discussed in my presentation.

• Nuclear Engineering and Technology
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• v.49 no.1
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• pp.43-53
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• 2017

Increasing the operation cycle length can be an important goal in the fuel reload design of a nuclear reactor core. In this research paper, a new optimization approach, electromagnetism mechanism (EM), is applied to the fuel arrangement design of the Bushehr WWER-1000 core. For this purpose, a neutronic solver has been developed for calculating the required parameters during the reload cycle of the reactor. In this package, two modules have been linked, including PARCS v2.7 and WIMS-5B codes, integrated in a solver for using in the fuel arrangement optimization operation. The first results of the prepared package, along with the cycle for the original pattern of Bushehr WWER-1000, are compared and verified according to the Final Safety Analysis Report and then the results of exploited EM linked with Purdue Advanced Reactor Core Simulator (PARCS) and Winfrith Improved Multigroup Scheme (WIMS) codes are reported for the loading pattern optimization. Totally, the numerical results of our loading pattern optimization indicate the power of the EM for this problem and also show the effective improvement of desired parameters for the gained semi-optimized core pattern in comparison to the designer scheme.

• Journal of information and communication convergence engineering
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• v.9 no.4
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• pp.452-456
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• 2011

Context-awareness system can provide an optimized services to users. Analyzing physical and complex circumstance elements which give direct or indirect influence to users can tell what users want. However, there are various situation informations around users and it requires high level technology to extract the service what users really want among those informations. The circumstance of the user can be changed from moment to moment, even the service what users want also can be changed in every minutes. Recently the researches to provide the service which a user demands has been progressed actively. Web based filtering method which reaches commercialization is a one of good examples. This method extracts necessary data according to users' demands from the documents on the Web or multimedia informations. However, there is a limit to use it to provide Context-awareness service because it extracts static data, not dynamic data. There is also other researches with a rule based filtering method in progress to filter situation information but this method doesn't have mechanism for dynamic data as well. We would like to solve these problems by providing a dynamic situation information filtering mechanism applying an weighted value about each property of objects and also applying Web based dynamic categories in this paper when unnecessary data should be filtered.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.8
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• pp.3474-3497
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• 2016

Network Function Virtualization (NFV) and Software Defined Networking (SDN) are recently considered as very promising drivers of the evolution of existing middlebox services, which play intrinsic and fundamental roles in today's networks. To address the virtual service deployment issues that caused by introducing NFV or SDN to networks, this paper proposes an optimal solution by combining quantum genetic algorithm with cooperative game theory. Specifically, we first state the concrete content of the service deployment problem and describe the system framework based on the architecture of SDN. Second, for the service location placement sub-problem, an integer linear programming model is built, which aims at minimizing the network transport delay by selecting suitable service locations, and then a heuristic solution is designed based on the improved quantum genetic algorithm. Third, for the service amount placement sub-problem, we apply the rigorous cooperative game-theoretic approach to build the mathematical model, and implement a distributed algorithm corresponding to Nash bargaining solution. Finally, experimental results show that our proposed method can calculate automatically the optimized placement locations, which reduces 30% of the average traffic delay compared to that of the random placement scheme. Meanwhile, the service amount placement approach can achieve the performance that the average metric values of satisfaction degree and fairness index reach above 90%. And evaluation results demonstrate that our proposed mechanism has a comprehensive advantage for network application.

• KIPS Transactions on Computer and Communication Systems
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• v.6 no.12
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• pp.479-486
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• 2017

Volunteer computing is a new computing paradigm that performs operations on idle resources of many nodes. The operation method of the client application for the execution of the volunteer computing is determined by the setting information of the user. Ideal operation requires optimized settings for system features and operating methods of other applications. In this paper, we analyze the usage ratio of CPU and GPU periodically, and develop a manager that dynamically applies optimized options. Through our proposed mechanism, the performance of the task computing is higher than that of the existing Volunteer Computing, and the performance interference is minimized. It is expected that volunteers will be able to provide higher computing resources for Volunteer Computing Project.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.4
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• pp.437-442
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• 2014

Recently, the needs for the development and application of the micro marine robot (MMR) which has the advantages in terms of size and cost are increasing. However, the basis is very short in the domestic. While the obstacle avoidance sonar (OAS) which was optimized in terms of size and performance and has the ability of 4-directional detection was developed for the obstacle avoidance of the micro surface robot (MSR) fortunately, the problem that the detection performance is degraded according to the shape of the obstacle because of using the fixed sonar-beam with the limited beam width and detection range exists. To solve this problem, the MSR mechanism that implements the rotating sonar-beam using the spur gear and the servo motor is proposed in this paper. To verify the performance of the proposed mechanism, the wall-tracking of the MSR is considered and the comparison and analysis in term of detection performance and actuation command is performed with conventional fixed sonar-beam. The test results show the validity of the proposed mechanism.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.2
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• pp.236-244
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• 2005

In this study, we introduce a new topology of Fuzzy Polynomial Neural Networks(FPNN) that is based on fuzzy relation and evolutionally optimized Multi-Layer Perceptron, discuss a comprehensive design methodology and carry out a series of numeric experiments. The construction of the evolutionally optimized FPNN(EFPNN) exploits fundamental technologies of Computational Intelligence. The architecture of the resulting EFPNN results from a synergistic usage of the genetic optimization-driven hybrid system generated by combining rule-based Fuzzy Neural Networks(FNN) with polynomial neural networks(PNN). FNN contributes to the formation of the premise part of the overall rule-based structure of the EFPNN. The consequence part of the EFPNN is designed using PNN. As the consequence part of the EFPNN, the development of the genetically optimized PNN(gPNN) dwells on two general optimization mechanism: the structural optimization is realized via GAs whereas in case of the parametric optimization we proceed with a standard least square method-based learning. To evaluate the performance of the EFPNN, the models are experimented with the use of several representative numerical examples. A comparative analysis shows that the proposed EFPNN are models with higher accuracy as well as more superb predictive capability than other intelligent models presented previously.

• Journal of Electrical Engineering and Technology
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• v.9 no.6
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• pp.2142-2153
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• 2014

Linearization of transducer characteristic plays a vital role in electronic instrumentation because all transducers have outputs nonlinearly related to the physical variables they sense. If the transducer output is nonlinear, it will produce a whole assortment of problems. Transducers rarely possess a perfectly linear transfer characteristic, but always have some degree of non-linearity over their range of operation. Attempts have been made by many researchers to increase the range of linearity of transducers. This paper presents a method to compensate nonlinearity of Linear Variable Displacement Transducer (LVDT) based on Extreme Learning Machine (ELM) method, Differential Evolution (DE) algorithm and Artificial Neural Network (ANN) trained by Genetic Algorithm (GA). Because of the mechanism structure, LVDT often exhibit inherent nonlinear input-output characteristics. The best approximation capability of optimized ANN technique is beneficial to this. The use of this proposed method is demonstrated through computer simulation with the experimental data of two different LVDTs. The results reveal that the proposed method compensated the presence of nonlinearity in the displacement transducer with very low training time, lowest Mean Square Error (MSE) value and better linearity. This research work involves less computational complexity and it behaves a good performance for nonlinearity compensation for LVDT and has good application prospect.