• Journal of the Korea Society of Computer and Information
• /
• v.15 no.8
• /
• pp.67-78
• /
• 2010

Various services such as IPTV, VoIP, multimedia over IP, on-line payment, on-line game, etc. were made possible due to the rapid advance of the network. In order to provide secure and seamless services over the network, the Internet service providers are performing continuous network monitoring using NMS. The main function of NMS is to perform a diagnosis to identify the potential causes of failure from event messages. In this paper, a simulation tool, named as NetDoctor, is presented which is capable of identifying and diagnosing the potential problems in the virtual network, before the network model is constructed. In NetDoctor, a series of various and artificial failure is imposed on the virtual network, and it was analyzed if NetDoctor could identify the problems. The experimental results on virtual network show that the developed tool is very effective in identifying and diagnosing the problems. The presented simulation tool can be used in the design of robust network.

• Journal of the Institute of Electronics Engineers of Korea TC
• /
• v.45 no.12
• /
• pp.74-82
• /
• 2008

In this paper, we propose a P2P based IPTV system using a multiple chain architecture. Proposed system is robust to the peer churn. As opposed to the internet the IPTV network managed by a single ISP has fewer bandwidth constraints and end-to-end connectivity. So, we emphasize preferentially robustness of a P2P network in IPTV environment. A single chain structure which was proposed previously emphasizes simplicity, however there exists considerable delay time at the end part of peers as the number of peers increasing. As a solution to the problem, we propose the scheme which seperates the chain into several levels and again divides each level into spans to diminish a delay time. Though the chain is separated into level and span, basic structure of proposed scheme is still a chain structure. So the scheme simplifies the recovery procedure caused by join or departure of peers. We will show the improved performance of proposed scheme rather than single chain structure with respect to the delay time and reliability.

• Survey Research
• /
• v.11 no.1
• /
• pp.19-41
• /
• 2010

Although it is possible to provide statistically reliable estimators of the entire population parameters based on each independent rolling sample, estimators of the small areas may not have the required statistical efficiency. Thus, in general, small area estimators are calculated based on the combined rolling sample after entire rolling sample survey is finished. In this study, we considered the construction of weights that is necessary in the analysis of the combined rolling sample. Unlike the past studies that provided the empirical results for the corresponding specific rolling sample survey, we considered linear models that depends only on design variables and rolling period and provided the corresponding Best Linear Unbiased Predictor(BLUP). Through a simulation study, we proposed the estimators for the population parameters that are robust to model failure and the BLUP under the assumed model. The results are applied to the 4th Korea National Health and Nutrition Examination Survey.

• Journal of Radiation Protection and Research
• /
• v.42 no.4
• /
• pp.212-221
• /
• 2017

Background: This study aims to calculate detector positions as a design of a radioactive source localizing radiation portal monitor (RPM) system using an improved genetic algorithm. Materials and Methods: To calculate of detector positions for a source localizing RPM system optimization problem is defined. To solve the problem, a modified iterative genetic algorithm (MIGA) is developed. In general, a genetic algorithm (GA) finds a globally optimal solution with a high probability, but it is not perfect at all times. To increase the probability to find globally optimal solution rather, a MIGA is designed by supplementing the iteration, competition, and verification with GA. For an optimization problem that is defined to find detector positions that maximizes differences of detector signals, a localization method is derived by modifying the inverse radiation transport model, and realistic parameter information is suggested. Results and Discussion: To compare the MIGA and GA, both algorithms are implemented in a MATLAB environment. The performance of the GA and MIGA and that of the procedures supplemented in the MIGA are analyzed by computer simulations. The results show that the iteration, competition, and verification procedures help to search for globally optimal solutions. Further, the MIGA is more robust against falling into local minima and finds a more reliably optimal result than the GA. Conclusion: The positions of the detectors on an RPM for radioactive source localization are optimized using the MIGA. To increase the contrast of the measurements from each detector, a relationship between the source and the detectors is derived by modifying the inverse transport model. Realistic parameters are utilized for accurate simulations. Furthermore, the MIGA is developed to achieve a reliable solution. By utilizing results of this study, an RPM for radioactive source localization has been designed and will be fabricated soon.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.2
• /
• pp.59-66
• /
• 2020

In this paper, we propose a pipe leak detection system through data collection using low-power wireless acoustic sensor modules and data analysis using deep auto-encoder. Based on the Fourier transform, we propose a low-power wireless acoustic sensor module that reduces data traffic by reducing the amount of acoustic sensor data to about 1/800, and we design the system that is robust to noise generated in the audible frequency band using only 20kHz~100kHz frequency signals. In addition, the proposed system is designed using a deep auto-encoder to accurately detect pipe leaks even with a reduced amount of data. Numerical experiments show that the proposed pipe leak detection system has a high accuracy of 99.94% and Type-II error of 0% even in the environment where high frequency band noise is mixed.

• Proceedings of the Korean Society of Propulsion Engineers Conference
• /
• 2004.03a
• /
• pp.605-610
• /
• 2004

Solid propellants allow thrusters to be light-weight, com-pact and robust because they require neither tank nor valve, Moreover, the solid propellant will not leak, spill or slosh. Consequently, the solid propellant thruster is one of the potential candidates for the microthruster. On the other hand, the control of the solid propellant combustion is difficult, since the conventional solid propellant continues to bum until all the stored propellant is consumed. Although particular devices like thrust reverser were designed to control the combustion, these devices were rarely used in the practical rocket motors. These devices rise thruster weight as well as complicate the thruster operation. In this study, a solid propellant microthruster using laser sustained combustion was designed in order to develop a high-efficiency microthruster overcoming the previously-mentioned difficulty. This designed thruster has semiconductor lasers and non-self-combustible solid propellants in addition to the conventional solid propellant thruster. In this designed thruster, the semiconductor laser controls the combustion of the non-self-combustible solid propellant. In order to demonstrate that the solid propellant combustion is controllable with laser, some non-self-combustible solid propellants were irradiated with the laser at a back-pressure of about 1㎪. A 40-W class Neodymium Yttrium Aluminum Garnet (ND:YAG) laser was used as a tentative alternate to the semiconductor laser. This experiment has shown that the solid propellant combustion was controllable with 10- W class laser irradiation.

• Smart Structures and Systems
• /
• v.9 no.2
• /
• pp.145-164
• /
• 2012

In this paper, solar-powered, multi-scale, vibration-impedance sensor node on Imote2 platform is presented for hybrid structural health monitoring (SHM) in cable-stayed bridge. In order to achieve the objective, the following approaches are proposed. Firstly, vibration- and impedance-based hybrid SHM methods are briefly described. Secondly, the multi-scale vibration and impedance sensor node on Imote2-platform is presented on the design of hardware components and embedded software for vibration- and impedance-based SHM. In this approach, a solar-powered energy harvesting is implemented for autonomous operation of the smart sensor nodes. Finally, the feasibility and practicality of the smart sensor-based SHM system is evaluated on a full-scale cable-stayed bridge, Hwamyung Bridge in Korea. Successful level of wireless communication and solar-power supply for smart sensor nodes are verified. Also, vibration and impedance responses measured from the target bridge which experiences various weather conditions are examined for the robust long-term monitoring capability of the smart sensor system.

• Structural Engineering and Mechanics
• /
• v.36 no.6
• /
• pp.759-783
• /
• 2010

In this paper, compressive strength of carbon fiber reinforced polymer (CFRP) confined concrete cylinders is formulated using a hybrid method coupling genetic programming (GP) and simulated annealing (SA), called GP/SA, and a robust variant of GP, namely multi expression programming (MEP). Straightforward GP/SA and MEP-based prediction equations are derived for the compressive strength of CFRP-wrapped concrete cylinders. The models are constructed using two sets of predictor variables. The first set comprises diameter of concrete cylinder, unconfined concrete strength, tensile strength of CFRP laminate, and total thickness of CFRP layer. The most widely used parameters of unconfined concrete strength and ultimate confinement pressure are included in the second set. The models are developed based on the experimental results obtained from the literature. To verify the applicability of the proposed models, they are employed to estimate the compressive strength of parts of test results that were not included in the modeling process. A sensitivity analysis is carried out to determine the contributions of the parameters affecting the compressive strength. For more verification, a parametric study is carried out and the trends of the results are confirmed via some previous studies. The GP/SA and MEP models are able to predict the ultimate compressive strength with an acceptable level of accuracy. The proposed models perform superior than several CFRP confinement models found in the literature. The derived models are particularly valuable for pre-design purposes.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.16 no.2
• /
• pp.138-143
• /
• 2006

This paper presents intelligent digital redesign method for hybrid state space fuzzy-model-based controllers. For effectiveness and stabilization of continuous-time uncertain nonlinear systems under discrete-time controller, Takagi-Sugeno(TS) fuzzy model is used to represent the complex system. And global approach design problems viewed as a convex optimization problem that we minimize the error of the norm bounds between nonlinearly interpolated linear operators to be matched. Also, by using the bilinear and inverse bilinear approximation method, we analyzed nonlinear system's uncertain parts more precisely. When a sampling period is sufficiently small, the conversion of a continuous-time structured uncertain nonlinear system to an equivalent discrete-time system have proper reason. Sufficiently conditions for the global state-matching of the digitally controlled system are formulated in terms of linear matrix inequalities (LMIs). Finally, a TS fuzzy model for the chaotic Lorentz system is used as an . example to guarantee the stability and effectiveness of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.22 no.3
• /
• pp.319-327
• /
• 2012

In this paper, we present a sign language recognition model which does not use any wearable devices for object tracking. The system design issues and implementation issues such as data representation, feature extraction and pattern classification methods are discussed. The proposed data representation method for sign language patterns is robust for spatio-temporal variances of feature points. We present a feature extraction technique which can improve the computation speed by reducing the amount of feature data. A neural network model which is capable of incremental learning is described and the behaviors and learning algorithm of the model are introduced. We have defined a measure which reflects the relevance between the feature values and the pattern classes. The measure makes it possible to select more effective features without any degradation of performance. Through the experiments using six types of sign language patterns, the proposed model is evaluated empirically.