• Convergence Security Journal
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• v.21 no.1
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• pp.129-135
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• 2021

Greedy protocols show good performance in Vehicular Ad-hoc Networks (VANETs) environment in general. But they make longer routes causing by surroundings or turn out routing failures in some cases when there are many traffic signals which generate empty streets temporary, or there is no merge roads after a road divide into two roads. When a node selects the next node simply using the distance to the destination node, the longer route is made by traditional greedy protocols in some cases and sometimes the route ends up routing failure. Most of traditional greedy protocols just take into account the distance to the destination to select a next node. Each node needs to consider not only the distance to the destination node but also the direction to the destination while routing a packet because of geographical environment. The proposed routing scheme considers both of the distance and the direction for forwarding packets to make a stable route. And the protocol can configure as the surrounding environment. We evaluate the performance of the protocol using two mobility models and network simulations. Most of network performances are improved rather than in compared with traditional greedy protocols.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.17 no.5
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• pp.73-86
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• 2007

Numerous types of models have been developed in recent years in response to the cyber threat posed by worms in order to analyze their propagation and predict their spread. Some of the most important ones involve mathematical modeling techniques such as Epidemic, AAWP (Analytical Active Worm Propagation Modeling) and LAAWP (Local AAWP). However, most models have several inherent limitations. For instance, they target worms that employ random scanning in the entire nv4 network and fail to consider the effects of countermeasures, making it difficult to analyze the extent of damage done by them and the effects of countermeasures in a specific network. This paper extends the equations and parameters of AAWP and LAAWP and suggests ALAAWP (Advanced LAAWP), a new worm simulation technique that rectifies the drawbacks of existing models.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.2
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• pp.53-58
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• 2021

In this paper, an alternative finite memory structure(FMS) smoothing filter is developed for discrete-time state-space model with a control input. To obtain the FMS smoothing filter, unbiasedness will be required beforehand in addition to a performance criteria of minimum variance. The FMS smoothing filter is obtained by directly solving an optimization problem with the unbiasedness constraint using only finite measurements and inputs on the most recent window. The proposed FMS smoothing filter is shown to have intrinsic good properties such as deadbeat and time-invariance. In addition, the proposed FMS smoothing filter is shown to be equivalent to existing FMS filters according to the delay length between the measurement and the availability of its estimate. Finally, to verify intrinsic robustness of the proposed FMS smoothing filter, computer simulations are performed for a temporary model uncertainty. Simulation results show that the proposed FMS smoothing filter can be better than the standard FMS filter and Kalman filter.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.4
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• pp.311-320
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• 2021

A study is performed for the real time fault diagnosis during operation and health estimation relating to performance deterioration in a turbojet engine used for an unmanned air vehicle. For this study the real time dynamic model is derived from the transient thermodynamic gas path analysis. For real fault conditions which are manipulated for the simulation, the detection techniques are applied such as Kalman filter and probabilistic decision-making approach based on statistical hypothesis test. Thereby the effectiveness is verified by showing good fault detection and isolation performances. For the health estimation with measurement parameters, it shows using an assumed performance degradation that the method by adaptive Kalman filter is feasible in practice for a condition based diagnosis and maintenance.

• Journal of Broadcast Engineering
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• v.26 no.6
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• pp.809-812
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• 2021

Air bubbles which may be generated during the PCB coating process can be a major cause of malfunction. so it is necessary to detect the bubbles in advance. In previous studies, candidates for bubbles were extracted using the brightness characteristics of bubbles, and the candidates were verified using CNN(Convolutional Neural Networks). In this paper, we propose a bubble detection method using a transfer learning-based CNN model. The VGGNet is adopted and sigmoid is used as a classification layer, and the last convolutional layer and classification layer are trained together when transfer learning is applied. The performance of the proposed method is F1-score 0.9044, which shows an improvement of about 0.17 compared to the previous study.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.7-13
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• 2022

Radio frequency fingerprinting refers to a methodology that extracts hardware-specific characteristics of a transmitter that are unintentionally embedded in a transmitted waveform. In this paper, we put forward a fingerprinting feature and deep learning structure that can identify the same type of Digital Mobile Radio(DMR) by inputting the in-phase(I) and quadrature(Q). We proposes using the magnitude in polar coordinates of I/Q as RF fingerprinting feature and a modified ResNet-1D structure that can identify them. Experimental results show that our proposed modified ResNet-1D structure can achieve recognition accuracy of 99.5% on 20 DMR.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.2
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• pp.133-146
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• 2023

Traffic states in urban areas are essential to implement effective traffic operation and traffic control. However, installing traffic sensors on numerous road sections is extremely expensive. Accordingly, estimating the traffic state using a vehicle-mounted camera, which shows a high penetration rate, is a more effective solution. However, the previously proposed methodology using object tracking or optical flow has a high computational cost and requires consecutive frames to obtain traffic states. Accordingly, we propose a method to detect vehicles and lanes by object detection networks and set the region between lanes as a region of interest to estimate the traffic density of the corresponding area. The proposed method only uses less computationally expensive object detection models and can estimate traffic states from sampled frames rather than consecutive frames. In addition, the traffic density estimation accuracy was over 90% on the black box videos collected from two buses having different characteristics.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.3
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• pp.287-295
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• 2023

The collapse of bridges due to earthquakes results in many casualties and property damages. Thus, accurate prediction and preparation are required for the behavior of bridges during earthquakes. In particular, columns play an important role in the seismic behavior of bridges. The risk of collapse due to an earthquake increases when there is a problem of the insufficient lap splice in the column. In this study, to analyze the characteristics of the lap splice in the column, a numerical model was defined for the insufficient lap-spliced columns and verified using experimental data. The developed column model was applied to a commonly used RC slab bridge. Nonlinear static analysis for the column was performed to evaluate the change in the performance of the column according to the lap-spliced length. In addition, this study assessed the effect of the lap-spliced length on the seismic fragility analysis.

• Journal of Convergence for Information Technology
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• v.12 no.3
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• pp.294-301
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• 2022

In this study, a multi-layer cascade (MLC) electrical array configuration method for thermoelectric generator consisting of plural number of thermoelectric modules (TEMs) was proposed to reduce mismatch loss caused by temperature maldistribution on the surfaces of the TEMs. To validate the effect of MLC on the mismatch loss reduction, a numerical model capable of reflecting multi-physics phenomena occuring in the TEMs was developed. MLC can be employed by placing a group of TEMs experiencing relatively low temperature differences in an electric layer with more electrical branches while locating a group of TEMs experiencing relatively high temperature differences in an electric layer with less electrical branches. The TEMs were classified using the temperature distribution obtained by the numerical model. A MLC with an optimal electrical branch ratio showed a 96.5% of electric power generation compared to an ideal case.

• The Journal of the Acoustical Society of Korea
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• v.28 no.6
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• pp.491-498
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• 2009

This paper presents the design method of an impedance matching network using an isolation transformer and the Chebyshev filter function for the high efficiency and the flat power driving of an underwater acoustic piezoelectric transducer. The proposed impedance matching network is designed for minimizing the reactance component of transducer and having the flat power response in the wide frequency range. We design a low pass filter with ladder-type circuit using the Chebyshev function as standard prototype filter function. In addition, we design the impedance matching network which is suitable for the equivalent circuit of transducer and the turn ratio of transformer through the bandpass frequency transformation. The proposed method is applied to the simulated dummy load of the tonpilz-type transducer operating in the middle frequency range. The simulation results are compared with the measured characteristics and the validity of the proposed method is verified.