• Economic and Environmental Geology
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• v.26 no.2
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• pp.207-215
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• 1993

In modem petroleum reservoir engineering, the characterization of reservoir heterogeneities is very important to accurately understand and predict reservoir production performance. Formation evaluation for the description of reservoir is generally conducted by performing the analysis of well logging, core testing, and well testing. However, the measured data points by well logging or core testing are in general very sparse and hence reservoir properties should be interpolated and extrapolated from measured points to uncharacterized areas. In assigning the data for the unknown points, simple averaging technique is not feasible as optimum estimation method since this method does not account the spatial relationship between the data points. The main goal of this work is to develop PC-version of multi-purpose geostatistical model in which several stages are systematically proceeded. In the development of model, the simulator employs a automatic selection of semivariogram function such as exponential or spherical model with the best values of $R^2$. The simulator also implements a special algorithm for the fitting of semivariogram function to experimental sernivariogram. The special algorithm such as trial and error scheme is devised since this method is much more reliable and stable than Gauss-Newton method. The simulator has been tested under stringent conditions and found to be stable. Finally, the validity and the applicability of the developed model have been studied against some existing actual field data.

• Korean Journal of Construction Engineering and Management
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• v.10 no.2
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• pp.145-154
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• 2009

For developing an Automation equipment in construction, it is a key issue to develop 3D modeling technology which can be used for automatically recognizing environmental objects. Recently, for the development of "Intelligent Excavating System(IES), a research developing the real-time 3D terrain modeling technology has been implemented from 2006 in Korea and a stereo vision system is selected as the optimum technology. However, as a result of performance tests implemented in various earth moving environment, the 3D images obtained by stereo vision included considerable noise. Therefore, in this study, for getting rid of the noise which is necessarily generated in stereo image matching, the noise elimination algorithm of stereo-vision images for 3D terrain modeling was developed. The consequence of this study is expected to be applicable in developing an automation equipments which are used in field environment.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.13 no.3
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• pp.288-300
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• 2002

In this paper, a novel method of equalization of RF transceivers is suggested for MIMO(Multiple Input Multiple Output) antenna actively studied for high speed data transmission in the recent IMT-2000 system. The core of suggestion is in equalizing the transfer characteristics of multiple transceivers using feedback and memory during the predefined calibration time. This makes it possible to weight the signals in the intermediate frequency, which is easier in the application of recently developed DoA(Direction of Arrival) algorithms. In addition, the time varying optimum cell formation according to traffic is feasible by antenna beam-forming based on the DoA information. The suggested method of equalizing multiple transceivers are successfully verified using envelope simulation. two outputs. This paper is concerned with the diagnosis of multiple crosstalk-faults in OSM. As the network size becomes larger in these days, the convent.
nal diagnosis methods based on tests and simulation be.
me inefficient, or even more impractical. We propose a simple and easily implementable alg？ithm for detection and isolation of the multiple crosstalk-faults in OSM. Specifically, we develop an algorithm for isolation of the source fault in switc.
ng elements whenever the multiple crosstalk-faults are.
etected in OSM. The proposed algorithm is illustrated by an example of 16$\times$16 OSM.

• Korean Journal of Optics and Photonics
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• v.13 no.6
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• pp.493-500
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• 2002

Fingerprint recognition is concerned with fingerprint acquisition and matching. Our research was focused on a fingerprint matching method using an inkless fingerprint input sensor at the fingerprint acquisition step. Since an inkless fingerprint sensor produces a digital-image-processed fingerprint image, we did not consider noise that can happen while acquiring the fingerprint. And making the user attempt fingerprint input as random, we considered image distortion that translation and rotation are included as complex. NJTC algorithm is used for fingerprint identification and verification. The method to find the center of the fingerprint is added in the NJTC algorithm to supplement discrimination of fingerprint recognition. From this center point, we decided the optimum cropping size for effective matching with pixels and demonstrated that the proposed method has high discrimination and high efficiency.

• Journal of Information Processing Systems
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• v.15 no.6
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• pp.1306-1325
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• 2019

As the world is moving towards digitization, data is generated from various sources at a faster rate. It is getting humungous and is termed as big data. The financial sector is one domain which needs to leverage the big data being generated to identify financial risks, fraudulent activities, and so on. The design of predictive models for such financial big data is imperative for maintaining the health of the country's economics. Financial data has many features such as transaction history, repayment data, purchase data, investment data, and so on. The main problem in predictive algorithm is finding the right subset of representative features from which the predictive model can be constructed for a particular task. This paper proposes a correlation-based method using submodular optimization for selecting the optimum number of features and thereby, reducing the dimensions of the data for faster and better prediction. The important proposition is that the optimal feature subset should contain features having high correlation with the class label, but should not correlate with each other in the subset. Experiments are conducted to understand the effect of the various subsets on different classification algorithms for loan data. The IBM Bluemix BigData platform is used for experimentation along with the Spark notebook. The results indicate that the proposed approach achieves considerable accuracy with optimal subsets in significantly less execution time. The algorithm is also compared with the existing feature selection and extraction algorithms.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.5
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• pp.522-534
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• 2002

In this paper, we propose a new object tracking system using stereo images to improve the performance of the automatic object tracking system. The existing object tracking system has optimum characteristics, but it requires a lot of computation. In the case of the image with a single eye, the system is difficult to estimate and track for the various transformation of the object. Because the stereo image by both eyes is difficult to estimate the translation and the rotation, this paper deals with the tracking method, which has the ability to track the image for translation for real time, with block matching algorithm in order to decrease the calculation. The experimental results demonstrate the usefulness of proposed system with the recognition rate of 88% in the rotation, 89% in the translation, 88% in various image, and with the mean rate of 88.3%.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.203-210
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• 2017

Data clustering is one of the most difficult and challenging problems and can be formally considered as a particular kind of NP-hard grouping problems. The K-means algorithm is one of the most popular and widely used clustering method because it is easy to implement and very efficient. However, it has high possibility to trap in local optimum and high variation of solutions with different initials for the large data set. Therefore, we need study efficient computational intelligence method to find the global optimal solution in data clustering problem within limited computational time. The objective of this paper is to propose a combined artificial bee colony (CABC) with K-means for initialization and finalization to find optimal solution that is effective on data clustering optimization problem. The artificial bee colony (ABC) is an algorithm motivated by the intelligent behavior exhibited by honeybees when searching for food. The performance of ABC is better than or similar to other population-based algorithms with the added advantage of employing fewer control parameters. Our proposed CABC method is able to provide near optimal solution within reasonable time to balance the converged and diversified searches. In this paper, the experiment and analysis of clustering problems demonstrate that CABC is a competitive approach comparing to previous partitioning approaches in satisfactory results with respect to solution quality. We validate the performance of CABC using Iris, Wine, Glass, Vowel, and Cloud UCI machine learning repository datasets comparing to previous studies by experiment and analysis. Our proposed KABCK (K-means+ABC+K-means) is better than ABCK (ABC+K-means), KABC (K-means+ABC), ABC, and K-means in our simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.1A
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• pp.10-27
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• 2005

In this paper, we propose a high level design architecture of WCDMA(UMTS) base station modem and synchronization algorithms applied to the proposed architecture. Also analysis of each synchronization algorithm and performance evaluation of fixed point designed modem are shown. Since the target system is base station modem, each synchronization algorithm is designed for its stable operation. To minimize implementation complexity, optimum fixed point design for best operation of synchronization algorithms is performed. We performed symbol level link simulation with fixed point designed modem simulator for data rate of 12.2kbps, 64kbps, 144kbps, and 384kbps. We compared performance results to the minimum requirements specified in 3GPP TS 25.104(Release 5). Extensive computer simulation shows that the proposed modem architecture has stable operation and outperform the minimum requirement by 2 dB. The proposed modem architecture has been applied in the implementation of WCDMA reverse link receiver modem chip successfully.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.3B
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• pp.135-143
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• 2008

In this paper, we propose a QoS guaranteed and energy-efficient transmission scheme for Wireless Personal Area Networks (WPANs), which operate in conjunction with contention-based access protocols such as CSMA/CA. Energy consumption is one of the most important issues in WPAN systems, because WPAN devices are often required to operate under limited battery capacity. Furthermore, if the WPAN adopts a contention-based medium access protocol, the energy consumption problem becomes even more critical due to the collisions caused by independent channel access trials. Therefore, in this paper, we propose an algorithm that selects the optimum fragment size, modulation level, and transmission power, in order to minimize the energy consumption and guaranteethe QoS (Quality of Service) requirements, simultaneously. Our simulation results show that the proposed algorithm has better performance than the previous ones.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.360-365
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• 2003

In this paper, GMDH(Croup Method of Data Handling) algorithm which is proved to be more excellent in efficiency and accuracy of practical use of data is applied to electric power demand forecasting. As a result, it became much easier to make a choice of input data and make an exact prediction based on a lot of data. Also, we considered both economy factors(GDP, export, import, number of employee, number of economically active population and consumption of oil) and climate factors(average temperature) when forecasting. We assumed target forecast period from first quarter 1999 to first quarter 2001, and suggested more accurate forecasting method of electric power demand by using 3-step computer simulation processes(first process for selecting optimum input period, second for analyzing time relation of input data and forecast value, and third for optimizing input data) for improvement of forecast precision. The proposed method can get 0.96 percent of mean error rate at target forecast period.