• Geophysics and Geophysical Exploration
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• v.14 no.4
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• pp.335-341
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• 2011

Most sensing and instrumentation systems should have very higher sampling rate than required data rate not to miss important information. This means that the system can be inefficient in some cases. This paper introduces two new research areas about information acquisition with high accuracy from less number of sampled data. One is Compressed Sensing technology (which obtains original information with as little samples as possible) and the other is Super-Resolution technology (which gains very high-resolution information from restrictively sampled data). This paper explains fundamental theories and reconstruction algorithms of compressed sensing technology and describes several applications to geophysical exploration. In addition, this paper explains the fundamentals of super-resolution technology and introduces recent research results and its applications, e.g. FRI (Finite Rate of Innovation) and LIMS (Least-squares based Iterative Multipath Super-resolution). In conclusion, this paper discusses how these technologies can be used in geophysical exploration systems.

• Journal of Environmental Science International
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• v.6 no.4
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• pp.323-333
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• 1997

An objective method for the generation of velocity streamfunction is presented for dealing with discretely sampled oceauc data. The method treats a Poisson equation (forced by vorticity) derived from Helmholtz theorem In which streamfunction is obtained by isolating the non-divergent part of the two-dimensional flow field. With a mixed boundary condition and vorticity field estimated from observed field, the method Is Implemented over the Texas-Louisiana show based on the current meter data of the Texas-Louisiana Shelf Circulation and Transport Processes Study (LATEX) measured at 31 moorings for 32 months (April 1992 - November 1994). The resulting streamfunction pattern is quote consistent with observations. The streamfunction field by this method presents an opportunity to initiauze and to verier computer models for local forecasts of enoronmental flow conditions for ell spill, nutrient and plankton transports as well as opportuuty to understand shelf-wlde low-frequency currents.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.1
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• pp.28-32
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• 2014

For a signal such as speech showing piece-wise linear shape in a very short time period, a nonuniform sampling method based on the inflection point detection (IPD) is proposed to reduce data rate. The method exploits the geometrical characteristics of signal further than the existing local maxima/minima detection (MMD) based sampling method. As results, the reconstructed signal by the interpolation of the IPD based sampled data resembles the original speech more. Computer simulation shows that the proposed IPD based method produces about 9~23 dB improvement over the existing MMD method. To show the usefulness of the IPD technique, it is applied to speech coding, and compared to the continuously variable slope delta modulation (CVSD). The nonuniformly sampled data is binary coded with one bit flag set "1". Noninflection samples are not sent, but only flag bits set 0 are sent. The method shows 0.3 ~ 9 dB SNR and 0.5 ~ 1.3 mean opinion score (MOS) improvements over the CVSD.

• Journal of the Korea Computer Graphics Society
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• v.26 no.5
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• pp.15-24
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• 2020

We present a supervised learning method that estimates the simulation parameters required to simulate the fabric from the static drape shape of a given fabric sample. The static drape shape was inspired by Cusick's drape, which is used in the apparel industry to classify fabrics according to their mechanical properties. The input vector of the training model consists of the feature vector extracted from the static drape and the density value of a fabric specimen. The output vector consists of six simulation parameters that have a significant influence on deriving the corresponding drape result. To generate a plausible and unbiased training data set, we first collect simulation parameters for 400 knit fabrics and generate a Gaussian Mixed Model (GMM) generation model from them. Next, a large number of simulation parameters are randomly sampled from the GMM model, and cloth simulation is performed for each sampled simulation parameter to create a virtual static drape. The generated training data is fitted with a log-linear regression model. To evaluate our method, we check the accuracy of the training results with a test data set and compare the visual similarity of the simulated drapes.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.34 no.3
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• pp.259-273
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• 1998

The hydroacoustic surveys to provide the essential information for the assessment, management and utilization of fishery resources in the southern waters of Korea were carried out during five research cruises between October 1996 and October 1997 by the training ship KAYA of Pukyong National University. These hydroacoustic investigations were designed to obtain more precise estimates of the geographic distribution, absolute abundance and biological characteristics of the fishery resources, and the vertically integrated densities of fish in terms of volume backscattering strength(SV) by survey region and depth bins, such as the entire water column and the 0~ 10 m from bottom fraction, were measured separately. Hydroacoustic data were collected by using a Simrad EK 500 Scientific echo sounder operating at two frequencies of 38kHz and 120kHz and the data stored in field were later processed on a HP PC using a Simrad EP 500 echo integration and target strength analysis system. The biological compositions of echo signal were identified and sampled using a demersal trawl during daylight hours. The mean target strength to scale the echo integration data for hydroacoustic surveys was derived from the relationship between the SV and the weight of trawl catch per unit volume of the water column sampled by demersal trawls. The results obtained can be summarized as follow : 1. The mean volume backscattering strength for the entire water column in the southern waters of Korea between 1996 and 1997 were -67.2 dB and -70.9 dB at two frequencies of 38 kHz and 120 kHz , respectively, and for the bottom layer of the 0-10 m from bottom friction were -68.8 dB, -70.2 dB, respectively. That is, the volume backscattering strength for the entire water column at low frequency was higher than that at high frequency. 2. The relationship between the mean backscattering strength (〈SV〉, dB) for the depth strata of trawl hauls and the weight (C, kg/m3) per cubic meter of the catch sampled by bottom trawling in the southern waters of Korea in January and July 1997 were expressed by the following equations: 38 kHz : 〈SV〉= -28.2 + 10 log(C), 120 kHz : 〈SV〉= -32.4 + 10 log(C). The mean weight -normalized target strengths derived from these equitions were -28.2 dB/ kg, -32.4 dB/ kg at 38 kHz and 120 kHz , respectively. That is, the mean weight -normalized target strength at 38 kHz was 4.2 dB higher than that at 120 kHz. 3. The distribution density of fish in terms of biomass per unit volume in the southern waters of Korea were estimated to be 125.9 $\times$ 10-6 kg/m3 and 141.3 $\times$ 10-6 kg/m3 at 38 kHz and 120 kHz , respectively.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.5 no.1
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• pp.7-12
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• 2006

Recently, the fractal interpolation methods have been widely introduced and used to estimate and analyze various theoretical and experimental data. Because of the chaotic behaviors of dynamic cutting force data, some method for end-milling force analysis must be used. The fractal analysis used in this paper is fractal linear interpolation and fractal dimension. Also, several methods for computing fractal dimensions have been used in which the fractal dimension of the typical dynamic end-milling force was calculated according to number of data points that are generally lower than 200 data points sampled. This fractal analysis shows a possible prediction of end-milling force that has some dynamic chatter property or stationary property in endmilling operation.

• Journal of Energy Engineering
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• v.23 no.3
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• pp.66-71
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• 2014

Oil is obviously vital for economic growth and industry development. This paper attempts to explore whether or not there is a inverted-U relationship between oil consumption and economic growth. To this end, we employ a panel data analysis with fixed effect or random effect models using the set of data from 61 countries for the year 1990-2008. In conclusion, a statistically significant inverted-U relationship between per capita consumption of oil and per capita GDP is found. However, the level of per capita GDP at the peak point of per capita oil consumption is estimated to be 65,072 in 2005 international constant dollars, which is much larger than economic scales of sampled countries. Thus, as per capita GDP grows, per capita oil consumption is predicted to increase until eventually reaching the peak.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.4 s.97
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• pp.102-109
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• 1999

Reverse engineering is a technique that helps designers to quickly generate computer interpretable data from existing physical objects. It can be used for generating CAD data from a mechanical part of high precision, or generating computer animation characters from physical mock-ups. We developed a low precision reverse engineering system that is composed of surface/solid generation software and a contact type commercial 3D digitizer. A unique point sampling procedure has been devised to easily form solid topology from the sampled data. It was also shown that STL data for rapid prototyping was successfully generated from the solid.

• Journal of the Korean Data and Information Science Society
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• v.25 no.3
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• pp.677-684
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• 2014

Support vector quantile regression (SVQR) is capable of providing more complete description of the linear and nonlinear relationships among random variables. To improve the estimation performance of SVQR we propose to use SVQR ensemble with bagging (bootstrap aggregating), in which SVQRs are trained independently using the training data sets sampled randomly via a bootstrap method. Then, they are aggregated to obtain the estimator of the quantile regression function using the penalized objective function composed of check functions. Experimental results are then presented, which illustrate the performance of SVQR ensemble with bagging.

• Proceedings of the KSEEG Conference
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• 2000.04b
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• pp.308-310
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• 2000

Sampling rates become inconsistent when spatial data in spherical coordinate are re-sampled with respect latitudinal or longitudinal degree for mathematical processes such as Fourier Transfrom, and this results in the distrtions of the processed data in the wavenmber domain. This distortions are more evident in the polar regions. An example is presented to show such distortions during the recovery process of free-air gravity anomalies from ERSI radar atimeter data in Russian Arctic Barents Sea, and a method is present to minimize the distortion using Lambect Conformal Conic map projection.