• Geophysics and Geophysical Exploration
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• v.9 no.1
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• pp.86-92
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• 2006

The full-waveform inversion algorithm using normalised seismic wavefields can avoid potential inversion errors due to source estimation required in conventional full-waveform inversion methods. In this paper, we have modified the inversion scheme to install a weighted smoothness constraint for better resolution, and to implement a staged approach using normalised wavefields in order of increasing frequency instead of inverting all frequency components simultaneously. The newly developed scheme is verified by using a simple two-dimensional fault model. One of the most significant improvements is based on introducing weights in model parameters, which can be derived from integrated sensitivities. The model-parameter weighting matrix is effective in selectively relaxing the smoothness constraint and in reducing artefacts in the reconstructed image. Simultaneous multiple-frequency inversion can almost be replicated by multiple single-frequency inversions. In particular, consecutively ordered single-frequency inversion, in which lower frequencies are used first, is useful for computation efficiency.

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.4
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• pp.3-12
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• 2011

Understanding of water sediment trends is an important part of water quality monitoring. Water quality variables change over time and space, and cannot be modeled or explained clearly by either temporal or spatial analysis alone. This research analysed the trends of temperature, pH levels and dissolved oxygen levels based on the sediment records and spatial data obtained in Lower Mekong Basin (LMB) during 1985-2005. Our aim is to evaluate spatio-temporal trends and graphical analyses using an Inverse Distance Weighting (IDW) interpolation method. The main results from this research can be summarized as follows. The maximum temperature and pH have been stable during the study period and the maximum dissolved oxygen has been increasing gradually until 2002. The minimum pH and dissolved oxygen have been changing in an unsteady trend during the period. A spatial analysis shows that the water temperature in this region has been increasing over time. The pH trend shows that it is decreasing during 1993-2005. Dissolved oxygen concentration has been increasing from 1989 onwards and stays in that track.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.5
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• pp.730-736
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• 2009

It is more important to analysis of huge gemonics data in Bioinformatics. Here we present a novel datamining approach to predict structure and function using protein's primnary structure only. We propose not also to develope n-Block substring search algorithm in reducing enormous search space effectively in relation to feature selection, but to formulate weighted linear algorithm in a prediction of structure and function of a protein using primary structure. And we show efficient in protein domain characterization and classification by calculation weight value in determining domain association in each selected substring, and also reveal that more efficient results are acquired through claculated model score result in an inference about degree of association with each CDS(coding sequence) in domain.

• Journal of Korea Water Resources Association
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• v.32 no.4
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• pp.437-445
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• 1999

The present paper describes the problem of hydrologic response estimation using non-parametric ridge regression method. The method adapted in this work is based on the minimization of the $C_L$ statistics, which is an estimate of the mean square prediction error. For this method, effects of using both the identity matrix and the Laplacian matrix were considered. In addition, we evaluated methods for estimating the error variance of the impulse response. As a result of analyzing synthetic and real data, a good estimation was made when the Laplacian matrix for the weighting matrix and the bias corrected estimate for the error variance were used. The method and procedure presented in present paper will play a robust and effective role on separating hydrologic response.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.7
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• pp.2913-2918
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• 2011

This paper proposed the friction model using Preisach algorithm with neural network based on experimental results. In order to apply the neural network algorithm, the back propagation update rule was used and the updated weighting factor of neural network was applied to distribute function of Preisach model. In order to implement the proposed algorithm, the LabView software was used to apply to the precision control of mechanical system. The evaluation of the proposed friction model was executed through experiments.

• Journal of the Korea Institute of Military Science and Technology
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• v.2 no.1
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• pp.101-109
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• 1999

The objective of this research is to study effects of the residual stresses on the crack growth and the life of the structure, caused by cold working around the hole of the aircraft structure which will be jointed by rivets and bolts, etc. The compensated Morrow's equation, by experimental data from the materials AL7075-T6 and AL2024-T3, is suggested to calculate the values of the fatigue life prediction of the structure. Also, the compensated Forman's equation, by experimental data from a material AL7075-T6, is suggested to calculate the values of the crack growth prediction of the structure. It is founded that the calculated values from the suggested equations are almost close to the known values of the fatigue life prediction and the crack growth prediction. It is shown that this paper, associated with an initial research on the effects of residual stresses around hole, gives a direction to study the problem at the aircraft maintenance field.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37 no.2A
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• pp.113-118
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• 2012

In this paper, we propose the removal of search point using motion vector correlation and distance between reference frames in H.264/AVC. We remove the search points in full search method and predictive motion vectors in enhanced predictive zonal search method. Since the probability that the reference frame far from the current frame is selected as the best reference frame is decreased, we apply the weighted average based on distance between the current and reference frame to determine the fianl search range. In general, the size of search range is smaller than initial search range. We reduce motion estimation time using the final search range in full search method. Also, the refinement process is adaptively applied to each reference frame. The proposed methods reduce the computational throughput of full search method by 57.13% and of enhanced predictive zonal search by 14.71% without visible performance degradation.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.241-241
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• 2017

기후변화로 인하여 강우의 불확실성이 가중되고 홍수, 가뭄 등 물 관련 재해의 발생빈도 및 강도가 증가함에 따라 안정적인 용수공급 등 수자원 관리 및 운영에 어려움을 겪고 있어 예측기반의 수자원 계획 및 운영이 요구되고 있는 실정이다. 우리나라 기상청에서는 2010년 6월 영국기상청과 장기 계절예측시스템의 구축 및 운영에 관한 협정을 체결하였으며 2014년부터 전지구 계절예측시스템 GloSea5(Global seasonal forecasting system version 5)을 현업에 활용하고 있다. GloSea5 모델은 대기(UM), 지면(JULES), 해양(NEMO), 해빙(CICE) 모델이 커플러(OASIS)에 의해 결합된 통합 시스템으로 일단위 자료로 제공된다. 현재 수자원 분야에서는 장기예보자료가 제공되고 있음에도 불구하고 장기예보자료의 불확실성 및 수문 모형 입력자료로의 활용 어려움, 예측자료의 검증 미흡 등으로 기상청에서 제공하는 장기예보를 참고할 뿐 실제로는 과거 관측자료를 기반한 빈도해석 결과를 활용하여 댐 운영 계획을 수립하고 있는 실정이다. 따라서, 본 연구에서는 GloSea5모델에서 제공되는 일 단위 예측 강수량을 수자원 장기이수계획 및 관리에 활용하고자 GloSea5모델의 예측력을 평가하고 수치모델이 가지는 시스템 에러에 대하여 편의보정 및 지점 상세화를 수행하였다. 본 연구의 분석결과는 향후, 저수지 운영계획 및 증가하는 물수요와 불확실한 공급에 대한 의사결정 지원, 가뭄 대비를 위한 물 공급 제한 등에 활용 가능할 것으로 판단된다.

• Convergence Security Journal
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• v.24 no.2
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• pp.151-160
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• 2024

In recent years with high interest rates and inflations, which worsen people's lives, voice phishing crimes also increase along with damage. Voice phishing that becomes more evolved by technology developments causes serious financial and mental damage to victims. This work aims to study time series models for its accurate prediction. ARIMA, SARIMA and SARIMAX models are compared. As exogenous variables, the amount of damages and the numbers of arrests and criminals are adopted. Forecasting performances are evaluated. Prediction intervals are constructed along with empirical coverages, which justify the superiority of the model. Finally, the numbers of voice phishing up to December 2024 are predicted, through which we expect the establishment of future prevention strategies for voice phishing.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.9
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• pp.351-360
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• 2018

The LWR (Locally Weighted Regression) model, which is traditionally a lazy learning model, is designed to obtain the solution of the prediction according to the input variable, the query point, and it is a kind of the regression equation in the short interval obtained as a result of the learning that gives a higher weight value closer to the query point. We study on an incremental ensemble learning approach for LWR, a form of lazy learning and memory-based learning. The proposed incremental ensemble learning method of LWR is to sequentially generate and integrate LWR models over time using a genetic algorithm to obtain a solution of a specific query point. The weaknesses of existing LWR models are that multiple LWR models can be generated based on the indicator function and data sample selection, and the quality of the predictions can also vary depending on this model. However, no research has been conducted to solve the problem of selection or combination of multiple LWR models. In this study, after generating the initial LWR model according to the indicator function and the sample data set, we iterate evolution learning process to obtain the proper indicator function and assess the LWR models applied to the other sample data sets to overcome the data set bias. We adopt Eager learning method to generate and store LWR model gradually when data is generated for all sections. In order to obtain a prediction solution at a specific point in time, an LWR model is generated based on newly generated data within a predetermined interval and then combined with existing LWR models in a section using a genetic algorithm. The proposed method shows better results than the method of selecting multiple LWR models using the simple average method. The results of this study are compared with the predicted results using multiple regression analysis by applying the real data such as the amount of traffic per hour in a specific area and hourly sales of a resting place of the highway, etc.