• Journal of the Korean Data and Information Science Society
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• v.28 no.4
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• pp.937-945
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• 2017

The purpose of using a control chart is to detect any change that occurs in the process. When control charts are used to monitor processes, we want to identify this changes as quickly as possible. Many problems in quality control involve a vector of observations of several characteristics rather than a single characteristic. Multivariate CUSUM or EWMA charts have been developed to address the problem of monitoring covariance matrix or the joint monitoring of mean vector and covariance matrix. However, control charts tend to work poorly when we use the highly correlatted variables. In order to overcome it, Hawkins (1991) proposed the use of regression adjustment variables. In this paper, to monitor covariance matrix, we investigate the performance of MEWMA-type control charts with and without the use of regression adjusted variables.

• Bulletin of the Korean Mathematical Society
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• v.60 no.5
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• pp.1299-1320
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• 2023

In the present paper, firstly we obtain the general expression of the canal hypersurfaces that are formed as the envelope of a family of pseudo hyperspheres, pseudo hyperbolic hyperspheres and null hyper-cones whose centers lie on a non-null curve with non-null Frenet vector fields in E⁴₁ and give their some geometric invariants such as unit normal vector fields, Gaussian curvatures, mean curvatures and principal curvatures. Also, we give some results about their flatness and minimality conditions and Weingarten canal hypersurfaces. Also, we obtain these characterizations for tubular hypersurfaces in E⁴₁ by taking constant radius function and finally, we construct some examples and visualize them with the aid of Mathematica.

• ETRI Journal
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• v.46 no.2
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• pp.307-322
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• 2024

Most object detection methods use a horizontal bounding box that causes problems between adjacent objects with arbitrary directions, resulting in misaligned detection. Hence, the horizontal anchor should be replaced by a rotating anchor to determine oriented bounding boxes. A two-stage process of delineating a horizontal bounding box and then converting it into an oriented bounding box is inefficient. To improve detection, a box-boundary-aware vector can be estimated based on a convolutional neural network. Specifically, we propose a ResNeXt101 encoder to overcome the weaknesses of the conventional ResNet, which is less effective as the network depth and complexity increase. Owing to the cardinality of using a homogeneous design and multi-branch architecture with few hyperparameters, ResNeXt captures better information than ResNet. Experimental results demonstrate more accurate and faster oriented object detection of our proposal compared with a baseline, achieving a mean average precision of 89.41% and inference rate of 23.67 fps.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.1
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• pp.55-64
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• 2013

Due to the popularization of digital high-performance capturing equipments and the emergence of powerful image-editing softwares, it is easy for anyone to make a high-quality counterfeit money. However, the probability of detecting a counterfeit money to the general public is extremely low. In this paper, we propose a counterfeit money detection algorithm using a general purpose scanner. This algorithm determines counterfeit money based on the different features in the printing process. After the non-local mean value is used to analyze the noises from each money, we extract statistical features from these noises by calculating a gray level co-occurrence matrix. Then, these features are applied to train and test the support vector machine classifier for identifying either original or counterfeit money. In the experiment, we use total 324 images of original money and counterfeit money. Also, we compare with noise features from previous researches using wiener filter and discrete wavelet transform. The accuracy of the algorithm for identifying counterfeit money was over 94%. Also, the accuracy for identifying the printing source was over 93%. The presented algorithm performs better than previous researches.

• Journal of Korea Multimedia Society
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• v.2 no.3
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• pp.289-296
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• 1999

In this paper, an improved fractal color image decoding method using the data dependence parts and the vector distortion measure is proposed. The vector distortion measure exploits the correlation between different color components. The pixel in RGB color space can be considered as a 30dimensional vector with elements of RGB components. The root mean square error(rms) in RGB color for similarity measure of two blocks R and R' was used. We assume that various parameter necessary in image decoding are stored in the transform table. If the parameter is referenced in decoding image, then decoding is performed by the recursive decoding method. If the parameter is not referenced in decoding image, then the parameters recognize as the data dependence parts and store its in the memory. Non-referenced parts can be decoded only one time, because its domain informations exist in the decoded parts by the recursive decoding method. Non-referenced parts are defined the data dependence parts. Image decoding method using data dependence classifies referenced parts and non-referenced parts using information of transform table. And the proposed method can be decoded only one time for R region decoding speed than Zhang & Po's method, since it is decreased the computational numbers by execution iterated contractive transformations for the referenced range only.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.3
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• pp.213-224
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• 1992

An encoding technique based on region splitting and vector quantization is proposed for the lower level Laplacian pyramid images. The lower level Laplacian pyramid images have lower variance than higher levels but a great influence on compression ration due to large spatial area. And so from data compression viewpoint, we subdivide them with variance thresholding into two regions such as one called : flat region” and the other “edge region”, and encode the flat region with its mean value and the edge region as vector quantization method. The edge region can be reproduced faithfully and significant improvement on compression ratio can be accomplished with a little degradation of PSNR in spite of the effect of large flat region since the codebook used is generated from the edge region only on from the entire image including the flat region. It can be verified by computer simulation results that proposed method is more efficient in compression ratio and processing time than the conventional encoding technique of vector quantization.

• Journal of the Korean Institute of Landscape Architecture
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• v.29 no.1
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• pp.22-31
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• 2001

The purpose of this study is to compare calculated pollutant loadings using pollutant load unit factors and vector type coverage, and expected mean concentration(EMC) and raster type of digital elevation model(DEM). This study is also focusing on comparison of the advantages and the disadvantages of the two methods, and seeking for a method of calculation of pollutant loadings using DEM. Estimation of pollutant inputs using pollutant load unit factors has limitations in identifying seasonal variations of pollutant loadings. Seasonal changes of runoffs should be considered in the calculation of pollutant loadings from catchments into reservoirs. Evaluation of pollutant inputs using runoff-coefficient and EMC can overcome these drawbacks. Proper EMC and runoff-coefficient values for the Koeup stream catchments of the Koheung estuarine lake were drawn from review of related papers. Arc/Info was employed to establish database of spatial and attribute data of point and non-point pollutant sources and characteristics of the catchments. ArcView was used to calculate point and non-point pollutant loadings. Pollutant loads estimated with either unit factors-coverages, i.e., pollutant load unit factors and vector coverages f point sources and land use, or EMC and digital elevation mode(DEM) were compared with stream monitoring loads. We have found that some differences were shown between monitoring results and estimated loads by Unit Factors-Coverage and EMC-DEM. Monthly variations of pollutant loads evaluated with EMC-DEM were similar to those with monitoring result. The method using EMC-DEM can calculate accumulated flows and pollutant loads and can be utilized to identify stream networks. A future research on correcting the difference between vector type stream using flow direction grid and digitalizing vector type should be conducted in order to obtain more exact calculation of pollutant loadings.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.25 no.4
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• pp.476-482
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• 2014

In this study, we analyzed the effect of corn growth on the radar backscattering coefficient. At first, we measured the backscattering coefficients of various corn fields using a polarimetric scatterometer system. The backscattering coefficients of the corn fields were also computed using the 1st-order VRT(Vector Radiative Transfer) model with field-measured input parameters. Then, we analyzed the experimental and numerical backscattering coefficients of corn fields. As a result, we found that the backscatter from an underlying soil layer is dominant for early growing stage. On the other hand, for vegetative stage with a higher LAI(Leaf-Area-Index), the backscatter from vegetation canopy becomes dominant, and its backscattering coefficients increase as incidence angle increases because of the effect of leaf angle distribution. It was also found that the estimated backscattering coefficients agree quite well with the field-measured radar backscattering coefficients with an RMSE(Root Mean Square Error) of 1.32 dB for VV-polarization and 0.99 dB for HH-polarization. Finally, we compared the backscattering characteristics of vegetation and soil layers with various LAI values.

• The Journal of the Acoustical Society of Korea
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• v.19 no.1
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• pp.97-102
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• 2000

Subband coding is to divide the signal frequency band into a set of uncorrelated frequency bands by filtering and then to encode each of these subbands using a bit allocation rationale matched to the signal energy in that subband. The actual coding of the subband signal can be done using waveform encoding techniques such as PCM, DPCM and vector quantizer(VQ) in order to obtain higher data compression. Most researchers have focused on the error in the quantizer, but not on the overall reconstruction error and its dependence on the filter bank. This paper provides a thorough analysis of subband codecs and further development of optimum filter bank design using vector quantizer. We compute the mean squared reconstruction error(MSE) which depends on N the number of entries in each code book, k the length of each code word, and on the filter bank coefficients. We form this MSE measure in terms of the equivalent quantization model and find the optimum FIR filter coefficients for each channel in the M-band structure for a given bit rate, given filter length, and given input signal correlation model. Specific design examples are worked out for 4-tap filter in 2-band paraunitary filter bank structure. These optimum paraunitary filter coefficients are obtained by using Monte Carlo simulation. We expect that the results of this work could be contributed to study on the optimum design of subband codecs using vector quantizer.

• Journal of Korea Port Economic Association
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• v.27 no.2
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• pp.217-240
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• 2011

In this study, vector autoregressive and vector error correction models in the short-run dynamics are considered to analyze the effect of the changes in international crude oil prices on Baltic dry index, Baltic Capesize index and Baltic Panamax index, and the intercorrelations between Capesize and Panamax prices, respectively. First, using the vector autoregressive model, the changes in international crude oil price have a statistically significant positive effect for Capesize at lag 1, for Panamax a significant negative effect at lag 3 and a significant positive effect for Baltic dry index at lag 1. From the impulse response analysis, the international crude oil price causes Baltic dry index to increase in the sort-run and the effect converges on the mean after 3 months. Second, using the vector error correction model, the empirical results for the spillover effects between Capesize and Panamax markets provide that in the case of the deviation from a long-run equilibrium the Panamax price is adjusted toward decreasing. The increases in freight rates of the Capesize market at lag 1 lead to increase the freight rates in Panamax market at present. The Panamax responses from the Capesize shocks increase rapidly for 3 months and the effect converges on the mean after 5 months. The Capesize responses from the Panamax shocks are relatively small, and increase weakly for 3 months and the effect disappears thereafter.