• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.1A
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• pp.73-81
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• 2011

IEEE 802.11 PHY and MAC layer provide multiple channels and data rates. To improve the performance of IEEE 802.11 multi-radio ad hoc networks, it is required to utilize available channels and data rates efficiently. However, in IEEE 802.11 multi-rate networks, the rate anomaly (RA) problem occurs that the network performance is severely degraded as low-rate links affect high-rate links. Hence, in this paper, we propose a model-based rate separation (MRS) algorithm that uses multiple channels to separate different data rate links so that the RA problem is mitigated. MRS algorithm utilizes an existing throughput model that estimates the throughput of IEEE 802.11 single-hop networks to separate low-rate links and high-rate links. Through simulations, we demonstrate that the MRS algorithm shows improved network performance compared with existing algorithms in multi-radio ad hoc networks.

• Earthquakes and Structures
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• v.4 no.6
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• pp.607-627
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• 2013

The application of shape memory alloys (SMAs) to the seismic response reduction of civil engineering structures has attracted growing interest due to their self-centering feature and excellent fatigue performance. The loading rate dependence of SMAs raises a concern in the seismic analysis of SMA-based devices. However, the implementation of micromechanics-based strain-rate-dependent constitutive models in structural analysis software is rather complicated and computationally demanding. This paper investigates the feasibility of replacing complex rate-dependent models with rate-independent constitutive models for superelastic SMA elements in seismic time-history analysis. Three uniaxial constitutive models for superelastic SMAs, including one rate-dependent thermomechanical model and two rate-independent phenomenological models, are considered in this comparative study. The pros and cons of the three nonlinear constitutive models are also discussed. A parametric study of single-degree-of-freedom systems with different initial periods and strength reduction factors is conducted to examine the effect of the three constitutive models on seismic simulations. Additionally, nonlinear time-history analyses of a three-story prototype steel frame building with special SMA-based damping braces are performed. Two suites of seismic records that correspond to frequent and design basis earthquakes are used as base excitations in the seismic analyses of steel-braced frames. The results of this study show that the rate-independent constitutive models, with their parameters properly tuned to dynamic test data, are able to predict the seismic responses of structures with SMA-based seismic response modification devices.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.5
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• pp.735-743
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• 2012

In this paper, we present model predictive control (MPC) applied to lane keeping system (LKS) based on a vision module. Due to a slow sampling rate of the vision system, the conventional LKS using single rate control may result in uncomfortable steering control rate in a high vehicle speed. By applying MPC using multi-rate Kalman filter to active steering control, the proposed MPC-based active steering control system prevents undesirable saturated steering control command. The effectiveness of the MPC is validated by simulations for the LKS equipped with a camera module having a slow sampling rate on the curved lane with the minimum radius of 250[m] at a vehicle speed of 30[m/s].

• Convergence Security Journal
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• v.22 no.5
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• pp.145-154
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• 2022

Recently, the widespread proliferation and high sophistication of botnets are having serious consequences not only for enterprises and users, but also for cyber warfare between countries. Therefore, research to detect botnets is steadily progressing. However, the DGA-based botnet has a high detection rate with the existing signature and statistics-based technology, but also has a high limit in the false positive rate. Therefore, in this paper, we propose a detection model using text-based n-gram to detect DGA-based botnets. Through the proposed model, the detection rate, which is the limit of the existing detection technology, can be increased and the false positive rate can also be minimized. Through experiments on large-scale domain datasets and normal domains used in various DGA botnets, it was confirmed that the performance was superior to that of the existing model. It was confirmed that the false positive rate of the proposed model is less than 2 to 4%, and the overall detection accuracy and F1 score are both 97.5%. As such, it is expected that the detection and response capabilities of DGA-based botnets will be improved through the model proposed in this paper.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.141-144
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• 2003

This paper proposes an analytical model of off-line feed rate scheduling to obtain an optimum feed rate for high speed machining. Off-line feed rate scheduling is presented as an advanced technology to regulate cutting forces through change of feed per tooth, which directly affects variation of uncut chip thickness. In this paper, the feed rate scheduling model was developed using a mechanistic cutting force model using cutting-condition-independent coefficients. First, it was verified that cutting force coefficients are not changed with respect to cutting speed. Thus, the feed rate scheduling model using the cutting-condition-independent coefficients can be applied to set the proper feed rates for high speed machining as well as normal machining. Experimental results show that the developed fred rate scheduling model makes it possible to maintain the cutting force at a desired level during high speed machining.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.21 no.1
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• pp.1-10
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• 2015

Enzyme kinetics-based respiration model can be effectively used for estimating respiration rate in $O_2$ consumption and $CO_2$ production of fresh produce as a function of $O_2$ and $CO_2$ concentrations. Arrhenius equation can be applied to describe the temperature dependence of the respiration rate. Parameters of enzyme kinetics-based respiration model and activation energy of Arrhenius equation were compiled from analysis of literature data and closed system experiment. They enable to estimate the respiration rate for any modified atmosphere conditions at temperature of interest and thus can be used for design of modified atmosphere packaging of fresh produce.

• Transactions of Materials Processing
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• v.19 no.7
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• pp.393-398
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• 2010

This paper investigates the effect of material properties on the formability of sheet metals based on the Marciniak-Kuczynski model (M-K model). The hardening behavior of the material is modeled as the Hollomon model with the strain rate effect. The yield surfaces are constructed with Hosford79 yield function. The material properties considered in this study include the R-value, the strain hardening exponent, the strain rate hardening exponent, and the crystal structure of the material. The effect of the crystal structure on formability is roughly expressed as the change of the yield surface by varying the value of the exponent in Hosford79 yield function. Results show that the R-value affects neither the magnitude nor the shape of right hand side of forming limit diagrams (FLDs). Higher strain hardening exponent and higher strain rate hardening exponent improve the formability of sheet metals because they stabilize the forming processes.

• Journal of Korea Multimedia Society
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• v.21 no.12
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• pp.1467-1472
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• 2018

For the problem that the face image of surveillance video cannot be accurately identified due to the low resolution, this paper proposes a low resolution face recognition solution based on convolutional neural network model. Convolutional Neural Networks (CNN) model for multi-scale input The CNN model for multi-scale input is an improvement over the existing "two-step method" in which low-resolution images are up-sampled using a simple bi-cubic interpolation method. Then, the up sampled image and the high-resolution image are mixed as a model training sample. The CNN model learns the common feature space of the high- and low-resolution images, and then measures the feature similarity through the cosine distance. Finally, the recognition result is given. The experiments on the CMU PIE and Extended Yale B datasets show that the accuracy of the model is better than other comparison methods. Compared with the CMDA_BGE algorithm with the highest recognition rate, the accuracy rate is 2.5%~9.9%.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.4
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• pp.176-181
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• 2005

This paper presents an equal bit rate control algorithm utilizing the statistical change between the previous frame and the current frame. The previous studies on the model-based rate control have focused on the models of bit rate and distortion in types of coders, in terms of the quantization parameter. The proposed algorithm improves the typical model-based rate control by updating a model parameter instead of modeling a better model of the rate and distortion. The proposed algorithm updates this model parameter by recognizing the change in statistics between the previous frame and the current frame. We implement the proposed algorithm in MPEG-4 coders and verify its performance while comparing it to the TMN8's approach (up to 0.6dB of improvement).

• The Journal of the Acoustical Society of Korea
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• v.21 no.1E
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• pp.3-11
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• 2002

Broadcast news transcription is one of the hardest tasks in speech recognition because broadcast speech signals have much variability in speech quality, channel and background conditions. We developed a Korean broadcast news speech recognizer. We used a morpheme-based dictionary and a language model to reduce the out-of·vocabulary (OOV) rate. We concatenated the original morpheme pairs of short length or high frequency in order to reduce insertion and deletion errors due to short morphemes. We used a lexicon with multiple pronunciations to reflect inter-morpheme pronunciation variations without severe modification of the search tree. By using the merged morpheme as recognition units, we achieved the OOV rate of 1.7% comparable to European languages with 64k vocabulary. We implemented a hidden Markov model-based recognizer with vocal tract length normalization and online speaker adaptation by maximum likelihood linear regression. Experimental results showed that the recognizer yielded 21.8% morpheme error rate for anchor speech and 31.6% for mostly noisy reporter speech.