• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.4
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• pp.337-344
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• 2014

While implicit integration methods such as Newton's method have excellent stability for the analysis of stiff and constrained mechanical systems, they have the drawback that the evaluation and LU-factorization of the system Jacobian matrix required at every time step are time-consuming. This paper proposes a Jacobian update-free Newton's method in order to overcome these defects. Because the motions of all bodies in a vehicle model are limited with respect to the chassis body, the equations are formulated with respect to the moving chassis-body reference frame instead of the fixed inertial reference frame. This makes the system Jacobian remain nearly constant, and thus allows the Newton's method to be free from the Jacobian update. Consequently, the proposed method significantly decreases the computational cost of the vehicle dynamic simulation. This paper provides detailed generalized formulation procedures for the equations of motion, constraint equations, and generalized forces of the proposed method.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.5
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• pp.225-234
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• 2018

Control flow errors are caused by the vulnerability of memory and result in system failure. Signature-based control flow monitoring is a representative method for alleviating the problem. The method commonly consists of two routines; one routine is signature update and the other is signature verification. However, in the existing signature-based control flow monitoring, monitoring target application is tightly combined with the monitoring code, and the operation of monitoring in a single thread is the basic model. This makes the signature-based monitoring method difficult to expect performance improvement that can be taken in multi-thread and multi-core environments. In this paper, we propose a new signature-based control flow monitoring model that separates signature update and signature verification in thread level. The signature update is combined with application thread and signature verification runs on a separate monitor thread. In the proposed model, the application thread and the monitor thread are separated from each other, so that we can expect a performance improvement that can be taken in a multi-core and multi-thread environment.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.159-161
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• 2004

Many motion object detection algorithms rely on the process of background subtraction, an important technique that is used for detecting changes from a model of the background scene. This paper propose a novel method to update the background model image of a visual surveillance system which is not stationary. In order to do this, we use a background model based on statistical qualities of monitored images and another background model that excluded motions. By comparing each changed area computed from the two background model images and current monitored image, the areas that will be updated are decided.

• International journal of advanced smart convergence
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• v.9 no.2
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• pp.20-27
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• 2020

Sound event detection in real-world environments suffers from the interference of non-stationary and time-varying noise. This paper presents an adaptive noise reduction method for sound event detection based on non-negative matrix factorization (NMF). In this paper, we proposed a deep learning model that integrates Convolution Neural Network (CNN) with Non-Negative Matrix Factorization (NMF). To improve the separation quality of the NMF, it includes noise update technique that learns and adapts the characteristics of the current noise in real time. The noise update technique analyzes the sparsity and activity of the noise bias at the present time and decides the update training based on the noise candidate group obtained every frame in the previous noise reduction stage. Noise bias ranks selected as candidates for update training are updated in real time with discrimination NMF training. This NMF was applied to CNN and Hidden Markov Model(HMM) to achieve improvement for performance of sound event detection. Since CNN has a more obvious performance improvement effect, it can be widely used in sound source based CNN algorithm.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1996.04a
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• pp.172-178
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• 1996

Databases are critical to business information systems, and RDBMS is most widely usded for the database system. Normalization has been designed to control various anomalies(insert, update, and delete anomalies). However, normalized databese design does not account for the tradeoffs necessary for the performance. In this research, we develop a model for database desin by denormalization of duplicating attributes in order to reduce frequent join processes. In this model, we consider insert, update, and delete costs. The anomalies are treated by additional disk I/O which is necessary for each insert and update transaction. We propose a branch and bound method for this model, and show considerable cost reduction.

• The Journal of Information Systems
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• v.17 no.4
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• pp.281-299
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• 2008

An online game is popular topic due to the increased total online game market volume nowadays. Even though many studies on an online game are released, most studies have used survey method that reveal only section of the situation like a snapshot. For this reason, previous studies have a little limitation that does not show dynamically changing issues like a product life cycle and change in customer's satisfaction. Because of this, we researched on an online game with the system dynamic model which can show dynamic simulation to analysis time series data. We chose MMORPG (Massively Multi-play Online Role Playing Game) in sort of an online game because it has many absorbing factors and enthusiastic users. We assumed that the game developer is ready for updated version game and release that periodically and focused on dormant users who used to be enthusiastic about MMORPG and designed simulation model which analyze how to influence of update and CRM strategy on users. The simulation results showed that the update has positive influences to gather new users and hold established users and CRM strategies help to prevent dormant users from transferring to rivals to offer them re-absorbing factors. Through this study, we confirmed importance of update on a online game and suggested the necessity to introduce CRM strategy in an online game market.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.7-13
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• 2017

Many systems rely on reliable timestamps to determine the time of a particular action or event. This is especially true in digital investigations where investigators are attempting to determine when a suspect actually committed an action. The challenge, however, is that objects are not updated at the exact moment that an event occurs, but within some time-span after the actual event. In this work we define a simple model of digital systems with objects that have associated timestamps. The model is used to predict object update patterns for objects with associated timestamps, and make predictions about these update time-spans. Through empirical studies of digital systems, we show that timestamp update patterns are not instantaneous. We then provide a method for calculating the distribution of timestamp updates on a particular system to determine more accurate action instance times.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06b
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• pp.23-28
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• 1996

Model-based coding is one of several approaches to very low bit rate image coding and it can be used in many applications such as image creation and virtual reality. However, its analysis and synthesis processes remain difficult, especially in the sense that the resulting synthesized image reveals some degradation in detailed facial components such as furrows around eyes and mouth. To solve the problem, a large number of methods have been proposed and the texture update method is one of them. In this paper, we investigate texture synthesis for model-based coding. In the update process of the proposed texture synthesis algorithm, texture information is stored in a memory and the decoder reuses it. With this method, the transmission bit rate for texture data can be reduced compared with the conventional method updating texture periodically.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.34 no.1
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• pp.35-42
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• 2021

This paper presents an on-line finite element model updating method for in-service structures using measured data. Conventional updating methods, which are based on numerical optimization, are not efficient for on-line updating because they generally require repeated eigenvalue analyses until convergence criteria are met. The proposed method enables fully automated on-line finite element model updating, almost simultaneously with vibration measurement, without any user intervention or off-line procedures. The automated covariance-driven stochastic subspace identification (Cov-SSI) method is utilized to identify modal frequencies and vectors, and the identified modal data is fed to the neural network of the inverse eigenvalue function to produce the updated finite element model parameters. Numerical examples for a wind excited 20-story building structure shows that the proposed method can update the series of finite element model parameters automatically. It is also shown that sudden changes in the structural parameters can be detected and traced successfully.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.11C
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• pp.1161-1168
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• 2003

In this paper, we propose an improved statistical model-based voice activity detection algorithm and threshold update method. We first improve signal-to-noise ratio by using speech enhancement preprocessing algorithm combined power subtraction method and matched filter, then apply it to LLR test optimum decision rule for improving the performance even in low SNR conditions. And we propose an adaptive threshold update method that was not concerned in any papers. We also perform extensive computer simulations to demonstrate the performance improvement of the proposed VAD algorithm employing the proposed speech enhancement preprocessing algorithm and adaptive threshold update method under various background noise environments. Finally we verify our results by comparing ITU-T G.729 Annex B.