• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.10
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• pp.2409-2416
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• 2015

This paper presents an orientation-based adaptive prediction method for effective lossless image compression. For a robust prediction, the proposed method estimates the directional information and the property near the current pixel in a support region-based fashion, not a pixel-based one which is sensitive to a small variation. We improve the prediction performance effectively by selection of the prediction pixel adaptively according to the similarity between support regions of the current pixel and the neighboring pixels. Comprehensive experiments demonstrate that the proposed scheme achieves excellent prediction performance measured in entropy of the prediction error compared to a number of conventional prediction methods such as MED, GAP, and EDP. Moreover the complexity of the proposed algorithm measured by average execution time is low compared to MED which is the simplest prediction method.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.208-208
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• 2022

Recently, the frequency of abnormal weather due to complex factors such as global warming is increasing frequently. From the past rainfall patterns, it is evident that climate change is causing irregular rainfall patterns. This phenomenon causes difficulty in predicting rainfall and makes it difficult to prevent and cope with natural disasters, casuing human and property damages. Therefore, accurate rainfall estimation and rainfall occurrence time prediction could be one of the ways to prevent and mitigate damage caused by flood and drought disasters. However, rainfall prediction has a lot of uncertainty, so it is necessary to understand and reduce this uncertainty. In addition, when accurate rainfall prediction is applied to the rainfall-runoff model, the accuracy of the runoff prediction can be improved. In this regard, this study aims to increase the reliability of rainfall prediction by analyzing the uncertainty of the Korean rainfall ensemble prediction data and the outflow analysis model using the Limited Area ENsemble (LENS) and the Grid based Rainfall-runoff Model (GRM) models. First, the possibility of improving rainfall prediction ability is reviewed using the QM (Quantile Mapping) technique among the bias correction techniques. Then, the GRM parameter calibration was performed twice, and the likelihood-parameter applicability evaluation and uncertainty analysis were performed using R², NSE, PBIAS, and Log-normal. The rainfall prediction data were applied to the rainfall-runoff model and evaluated before and after calibration. It is expected that more reliable flood prediction will be possible by reducing uncertainty in rainfall ensemble data when applying to the runoff model in selecting behavioral models for user uncertainty analysis. Also, it can be used as a basis of flood prediction research by integrating other parameters such as geological characteristics and rainfall events.

• Magazine of the Korea Concrete Institute
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• v.3 no.1
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• pp.71-78
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• 1991

Moleclar size distribution of three AC-20 asphalt cements were observed using high pressure - gel permeation chromatograph (HP-GPC). Bituminous concrete specimens were made using the asphalt cements and one aggre¬gate in laboratory to measure mechanical properties, tensile strength CIS) and resilient modulusCM,J. in dry and wet conditons. Results of mechanical property tests and profile of molecular size distribution of asphalt cements were analyzed to evaluate the relatonship of mechanical property with chromatogram. Regression analy¬sis showed a strong correlation between a mechanical property and sliced percent areas of chromatogram. Mathematical prediction models were developed based on the regression analysis. It was shown that characteris¬tics of asphalt cement chromatogram could be successfully used for estimation of selected mechanical property of asphalt concrete .

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2003.10b
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• pp.51-54
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• 2003

Internal defects such as chevron crack occasionally occur in the process of cold extrusion or cold drawing. It is known that the existence and property of inclusion greatly influences the generation of the internal crack. However, in the plastic working field, research about the effect of the inclusion on the fracture is not theoretically analyzed. This paper describes effects of the physical property of inclusion on the internal fracture generation in the process. Prediction of fracture was evaluated by critical damage value calculated by the equation of Cockcroft & Latham and its change by the inclusion physical property such as size and stiffness was investigated.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.118-125
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• 2004

The assessment of fatigue property is one of the most indispensable factors to design mechanical structures or parts. For accurately assessing fatigue property, it is necessary to precisely identify the loading condition and material property of the objective structure. However, there are many kind of problems in conducting predictive activity for a design concerned with variable factor such as fatigue phenomenons and environments. Therefore, most of the fatigue problems have been assessed from exiting experiment data and prediction method. In this study, expert system is developed for simply conducting performance assessment of weldments based on Finite element Analysis carrying out performance improvement and safety assessment of welded structures.

• Tunnel and Underground Space
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• v.5 no.3
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• pp.214-222
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• 1995

Geological events which are undetected by the surface geophysical or geological survey phase can cause many problems, especially when the tunnel is excavated by TBM. To detect the geological events ahead of tunnel face, a seismic method applied from VSP method is used. Generally uniaxial geophone has been used in surface seismic survey. But this time, triaxial geophone is used to reduce the noise of tunnel wave. DME(Dip moveout Enhancement) filter and diffraction stack method are used. Applying these techniques to the road tunnel in construction, it is proved that the geological events ahead of tunnel face is fairly well predicted. From the seismic trace, Vp and Vs which are related to the rock property can be also obtained. Rock property and proper support design can be dedced from these parameters.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2003.05a
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• pp.383-386
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• 2003

This paper deals with transmission loss of 3-dimensional rectangular plenum lined chamber. There are three kinds of rectangular plenum lined chamber: throughflow type, flow-reversal type, and end-in/side-out type. The combination of above three types of rectangular plenum lined chamber is used for the commercial HVAC system and automobile exhaust system. However, the ambiguity and complexity of sound absorbing material property and 3-dimensional property have impeded research. In this paper, the transmission loss of three kinds of rectangular plenum lined chamber is derived and calculated. The effect of increase of sound absorbing material is also considered. Analytical solution is calculated by using the locally-reacting property of sound absorbing material.

• Environmental Engineering Research
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• v.15 no.3
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• pp.135-140
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• 2010

With the various urban characteristics of each city, the existing water demand prediction, which uses average liter per capita day, cannot be used to achieve an accurate prediction as it fails to consider several variables. Thus, this study considered social and industrial factors of 164 local cities, in addition to population and other directly influential factors, and used main substance and cluster analyses to develop a more efficient water demand prediction model that considers unique localities of each city. After clustering, a multiple regression model was developed that proved that the $R^2$ value of the inclusive multiple regression model was 0.59; whereas, those of Clusters A and B were 0.62 and 0.74, respectively. Thus, the multiple regression model was considered more reasonable and valid than the inclusive multiple regression model. In summary, the water demand prediction model using principal component and cluster analyses as the standards to classify localities has a better modification coefficient than that of the inclusive multiple regression model, which does not consider localities.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.213-216
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• 2001

The H.263 Annex I method for the intraframe coding is based on the prediction in DCT domain, unlike JPEG, MPEG-1, and MPEG-2 where the intraframe coding uses block DCT, independent of the neighboring blocks. In this paper, we show the ineffectiveness of H.263 Annex I prediction method by mathematically deriving the spatial domain meaning of H.263 Annex I prediction method. Based on the derivation, we propose a prediction method which is based on the spatial correlation property of image signals. From the experiment and derivation, we verified the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.1975-1988
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• 2019

Short-term traffic flow prediction plays an important role in intelligent transportation systems (ITS) in areas such as transportation management, traffic control and guidance. For short-term traffic flow regression predictions, the main challenge stems from the non-stationary property of traffic flow data. In this paper, we design an ensemble cascading prediction framework based on extremely randomized trees (extra-trees) using a boosting technique called EET to predict the short-term traffic flow under non-stationary environments. Extra-trees is a tree-based ensemble method. It essentially consists of strongly randomizing both the attribute and cut-point choices while splitting a tree node. This mechanism reduces the variance of the model and is, therefore, more suitable for traffic flow regression prediction in non-stationary environments. Moreover, the extra-trees algorithm uses boosting ensemble technique averaging to improve the predictive accuracy and control overfitting. To the best of our knowledge, this is the first time that extra-trees have been used as fundamental building blocks in boosting committee machines. The proposed approach involves predicting 5 min in advance using real-time traffic flow data in the context of inherently considering temporal and spatial correlations. Experiments demonstrate that the proposed method achieves higher accuracy and lower variance and computational complexity when compared to the existing methods.