• Proceedings of the KOSOMBE Conference
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• v.1997 no.05
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• pp.184-187
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• 1997

In terms of a system identification, we present a method for autoregressive(AR) modelling of variious biomedical signal. Model order is estimated fly low rank approximation and coefficients are determined by innovation processes of Kalman filter derivation. An application of the method is given for visual evoked potentials.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.36 no.11
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• pp.813-818
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• 1987

In this paper, high resolution spectral estimation by AR modelling and principal comonent analysis is proposed. The given data can be expanded by the eigenvectors of the estimated covariance matrix. The eigenspectrum is obtained for each eigenvector using the Autoressive(AR) spectral estimation technique. The final spectrum estimate is obtained by weighting each eigenspectrum with the corresponding eigenvalue and summing them. Although the proposed method increases in computational complexity, it shows good frequency resolution especially for short data records and narrow-band data whose signal-to-noise ratio is low.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.419-430
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• 2014

An accurate prediction of electricity supply and demand is important for daily life, industrial activities, and national management. In this paper electricity sales is predicted by time series modelling. Real data analysis shows the transfer function model with cooling and heating days as an input time series and a pulse function as an intervention variable outperforms other time series models for the root mean square error and the mean absolute percentage error.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.6
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• pp.168-176
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• 1996

A diagnosis system which can monitor tool breakage and chipping in real time was developed using a DSP(Digital Signal Processor) board in face milling operation. AR modelling and band energy method were used to extract the feature of tool states from cutting force signals. Artificial neural network embedded on DSP board discriminates different patterns from features got after signal processing. The features extracted from AR modelling are more accurate for the malfunction of a process than those from band energy method, even though the computing speed of the former is slow. From the processed features, we can construct the real time diagnosis system which monitors malfunction by using a DSP board having a parallel processing capability.

• Architectural research
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• v.19 no.1
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• pp.1-6
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• 2017

Over the past decade, building information modeling (BIM) has gained a foothold in the construction sector. However, as digital data generated in the virtual space of a computer environment, BIM-based data have an inherent limitation in their application efficacy under field conditions. To overcome this, the present study employs augmented reality (AR) to reduce the discrepancy between the digital data generated in virtual spaces and real-world conditions. We assessed the potential applicability of an AR-based interface by analyzing existing examples of Apple, Google, and Facebook, which reflect the recent developments of technologies focusing on user experience. We then proceeded with an AR study, restricting the scope of application to a mobile environment in which an efficient information transmission between a digital model and real life can take place. Object-oriented software engineering was employed to ensure an efficient implementation of a BIM-based AR system for campus space management (CSM) in a mobile environment. Finally, we conducted a module test to check the reliability of the CSM method by using an AR-based mobile system with a prototype of the model used in university campuses, and extracted and itemized the supplementary requirements for CSM by using BIM tools for running AR applications.

• Proceedings of the KOSOMBE Conference
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• v.1995 no.11
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• pp.109-112
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• 1995

This paper is a study on the detection of the significant point in ECG signal. ECG signal consists of two components; one is high frequency component to be detected and the other is low frequency component to be removed. AR model is appropriate for modelling and removing the low frequency component. AR model coefficients are updated by artificial neural network algorithm. We can remove the background noise(low frequency) by passing through the AR filter. The remaining signals which include high frequency noise are sent to the matched filter to pass only the signal which we want to extract. The template used in matched filter is updated adaptively.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.1
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• pp.185-193
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• 1997

This paper presents the on-line monitoring of the surface roughness in a face milling operation. The cut- ting force was used to monitor the surface roughness, since the insert run-outs not only deteriorate surface roughness but also change cutting force. AR model and band energy method were taken to extract the fea- tures from the cutting force. The features extracted from AR modelling are more accurate about the moni- toring than those from band energy method, whereas, the computing speed of the former is slow. An artifi- cal neural network discriminated the level of the surface roughness by using the features extracted via signal processing.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.171-178
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• 2014

This paper presents dynamic modelling of a virtual object in augmented reality environments when external forces are applied to the object in real-time fashion. In order to simulate a natural behavior of the object we employ the theory of Newtonian physics to construct motion equation of the object according to the varying external forces applied to the AR object. In dynamic modelling process, the physical interaction is taken placed between the augmented object and the physical object such as a haptic input device and the external forces are transferred to the object. The intrinsic properties of the augmented object are either rigid or elastically deformable (non-rigid) model. In case of the rigid object, the dynamic motion of the object is simulated when the augmented object is collided with by the haptic stick by considering linear momentum or angular momentum. In the case of the non-rigid object, the physics-based simulation approach is adopted since the elastically deformable models respond in a natural way to the external or internal forces and constraints. Depending on the characteristics of force caused by a user through a haptic interface and model's intrinsic properties, the virtual elastic object in AR is deformed naturally. In the simulation, we exploit standard mass-spring damper differential equation so called Newton's second law of motion to model deformable objects. From the experiments, we can successfully visualize the behavior of a virtual objects in AR based on the theorem of physics when the haptic device interact with the rigid or non-rigid virtual object.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.2
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• pp.304-310
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• 2020

The technology in 3D modelling have advanced not only maps, heritages, constructions but also trees modelling. By laser scanning(Faro s350) and photogrammetry software(Pix4d) for 3D modelling, this study compared with real coniferous tree and both technology's results about characteristics of shape, texture, and dimensions. As a result, both technologies all showed high reproducibility. The scanning technique showed very good results in the reproduction about bark and leaves. Comparing the detailed dimensions on it, the error between the actual tree and modelling with scanning was 1.7~2.2%, and the scanning result was larger than the actual tree. The error between the actual tree and photogrammetry was only 0.2~0.5%, which was larger than the actual tree. On the other hand, the dark areas's modelling was not fully processed. This study is meaningful as a basic research that can be used for tree DB on BIM for the landscape architecture, landscape design and analysis with AR technology, historical tree and heritage also.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.4
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• pp.24-31
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• 2005

A plused laser ablation deposition(PLAD) technique has been used for producing fine particle as well as thin film at relatively low substrate temperatures. However, in order to manufacture and evaluate such materials in detail, motions of plume particles generated by laser ablation have to be understood and interactions between the particles by ablation and gas plasma have to be clarified. Therefore this paper was focused on the understanding of plume motion in laser ablation assisted by hi plasmas at 100[mTorr]. One-dimensional hybrid model consisting of fluid and particle models was developed and three kinds of plume particles which are carbon atom(C), $ion(C^+)$ and electron were considered in the calculation of particle method. It was obtained that ablated $C^+$ was electrically captured in Ar plasmas by strong electric field(E). The difference between motions of the ablated electrons and $C^+$ made E strong and the collisional processes active. The energies of plume particles were investigated on a substrate surface. In addition the plume motion in Ar gas was also calculated and discussed.