• The Korean Journal of Applied Statistics
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• v.36 no.6
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• pp.529-545
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• 2023

This paper introduces the Banded-VHAR model suitable for high-dimensional long-memory time series with band structure. The Banded-VHAR model has nonignorable correlations only with adjacent dimensions due to data features, for example, geographical information. Row-wise estimation method is adapted for fast computation. Also, two estimation methods, namely BIC and ratio methods, are proposed to estimate the width of band. We demonstrate asymptotic consistency of our proposed estimation methods through simulation study. Real data applications to pm2.5 and apartment trading volume substantiate that our Banded-VHAR model outperforms traditional sparse VHAR model in forecasting and easy to interpret model coefficients.

• Journal of Wind Energy
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• v.14 no.1
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• pp.37-43
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• 2023

In this study, synthetic time series wind data was generated numerically using a second-order Markov chain. One year of wind data in 2020 measured by the AWS on Wido Island was used to investigate the statistics for measured wind data. Both the transition probability matrix and the cumulative transition probability matrix for annual hourly mean wind speed were obtained through statistical analysis. Probability density distribution along the wind speed and autocorrelation according to time were compared with the first- and the second-order Markov chains with various lengths of time series wind data. Probability density distributions for measured wind data and synthetic wind data using the first- and the second-order Markov chains were also compared to each other. For the case of the second-order Markov chain, some improvement of the autocorrelation was verified. It turns out that the autocorrelation converges to zero according to increasing the wind speed when the data size is sufficiently large. The generation of artificial wind data is expected to be useful as input data for virtual digital twin wind turbines.

• Korean journal of communication and information
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• v.56
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• pp.48-70
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• 2011

Although many researchers propose that market-driven journalism is incurred by the worsening of financial situation as a result of intensifying competition in mass media industry, few studies investigated this claim with actual news data. This study analyzed the headline news of eight major newspapers and two terrestrial TV companies to find the weakening of 'orientating-journalism' function of Korean news media. The results revealed that the duplication rate of news items among ten news companies were decreasing, and the range of news subjects were broadened into diverse topics during last ten years. Therefore it seemed that the tendency of monopolization of a certain events or issues was weakening in news reporting. The financial situation of news companies is an important factor in explaining the change of news reporting. The companies with more worse financial situation have higher duplication rate of news topics along as the more amount of soft news items, leading to the gradual deterioration of their own voices in reporting. The rate of 'independent issue report' was also less than seven precent, thus their reporting is evaluated as having many limitations. In sum, the major newspapers and network broadcasting companies are still exerting strong influences in agenda-setting, but they(mostly newspapers) are suffering from the financial problems, resulting the deterioration of performing orientation journalism function. This study concluded with remarks about the role of major news media in current changing situation.

• Journal of KIISE:Software and Applications
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• v.37 no.2
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• pp.104-109
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• 2010

The lighting reflection is a common problem in image analysis and causes the many difficulties to extract distinct features in related fields. Furthermore, the problem grows in the rainy night. In this paper, we aim to remove light reflection effects and reconstruct a road surface without lighting reflections in order to extract distinct features. The proposed method utilizes a 3D analysis based on a multiple geometry using captured images, with which we can combine each reflected areas; that is, we can remove lighting reflection effects and reconstruct the surface. At first, the regions of lighting sources and reflected surfaces are extracted by local maxima based on vertically projected intensity-histograms. After that, a fundamental matrix and homography matrix among multiple images are calculated by corresponding points in each image. Finally, we combine each surface by selecting minimum value among multiple images and replace it on a target image. The proposed method can reduces lighting reflection effects and the property on the surface is not lost. While the experimental results with collected data shows plausible performance comparing to the speed, reflection-overlapping areas which can not be reconstructed remain in the result. In order to solve this problem, a new reflection model needs to be constructed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.1
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• pp.59-69
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• 2018

In this paper, we present a robust beamforming design to tackle the weighted sum-rate maximization (WSRM) problem in a multicell multiple-input multiple-output (MIMO) - non-orthogonal multipleaccess (NOMA) downlink system for 5G wireless communications. This work consider the imperfectchannel state information (CSI) at the base station (BS) by adding uncertainties to channel estimation matrices as the worst-case model i.e., singular value uncertainty model (SVUM). With this observation, the WSRM problem is formulated subject to the transmit power constraints at the BS. The objective problem is known as on-deterministic polynomial (NP) problem which is difficult to solve. We propose an robust beam forming design which establishes on majorization minimization (MM) technique to find the optimal transmit beam forming matrix, as well as efficiently solve the objective problem. In addition, we also propose a joint user clustering and power allocation (JUCPA) algorithm in which the best user pair is selected as a cluster to attain a higher sum-rate. Extensive numerical results are provided to show that the proposed robust beamforming design together with the proposed JUCPA algorithm significantly increases the performance in term of sum-rate as compared with the existing NOMA schemes and the conventional orthogonal multiple access (OMA) scheme.

• Journal of the Earthquake Engineering Society of Korea
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• v.3 no.2
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• pp.87-96
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• 1999

To analyze the dynamic behavior of structure, direct integration and mode superposition may be utilized in time domain analysis. As finite number of frequencies can give relatively exact solutions, mode superposition is preferable in analyzing structural behavior. In non-linear analysis, however, mode superposition is seldom used since time-varying element stiffness changes stiffness matrix, and the change of stiffness matrix leads to the change of essential constants - natural frequencies and mode shapes. In spite of these difficulties, there are some attempts to adopt mode superposition because of low cost compared to direct integration, but the result is not satisfactory. In this paper, a method using mode superposition in non-linear analysis is presented by separating local element stiffness from global stiffness matrix with the difference between linear and non-linear restoring forces to the external force vectors included. Moreover, the hysteresis model changing with the relative deformation in each floor makes it possible to analyze non-linear behavior of structure. The proposed algorithm is applied to shear beam model and the maximum displacement is compared with the result using direct integration method.

• Journal of Korea Foresty Energy
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• v.22 no.3
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• pp.1-10
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• 2003

The successional status and potential natural vegetation were examined in the natural deciduous forest in Mt. Chombong area. The examination was based on the subsequent process of generation replacement by understory saplings for the dominant canopy trees within 106 20mx20m square sample plots. The transition matrix model, which was modified from mathematical theory of Markov chain, was employed to analyze the successional status of the study forest. The model suggests that study forest is still seral, and it is considered to be more than 500 years away from the steady state or climax in terms of species composition. The simulations predict a remarkable decrease in the proportion of species composition of the present dominant Quercus mongolica and Kalopanax pictus from current 42.6% and 8.1% to less than 13.3% and 0.5%, respectively, at the steady state. On the contrary, the proportions of Abies holophylla, Acer mono, Fraxinus mandshurica, Tilia amurensis, and Acer pseudo-sieboldianum will increase at the steady state. The change of predicted composition ratio was generally coincide with the result of tolerance index to be compared with the study model. The hypothesis and sensitivity of the model were also discussed to evaluate the applicability to the real situation. The overall results indicated that the present dynamics of the forest must reflect the seral state due to previous disturbance mainly by human related interference.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.5
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• pp.1054-1065
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• 1993

A computer simulation is performed on the effectiveness of the active minimization of harmonically excited enclosed sound fields for producing global reduction in the amplitude of the pressure fluctuations. In this study for the appreciable reductions in total time averaged acoustic potential energy, $E_{pp}$, the transducer location strategies for three dimensional active noise control is presented based on a state space modal which approximates the closed acoustic field.In this study, the above theoretical basis is used to investigate the application of active control to sound fields of low modal density. By the used of room-like 3-dimensional rectangular enclosure it is demonstrated that the reductions in $E_{pp}$ can be achieved by using a single secondary source, provided that the source is placed within the half a wavelength from the primary source and placed away from nodal line of the sound field. Concerning the reductions in $E_{pp}$ by minimzing the pressure in sound fields by the use of 3-dimensional rectangular enclosure, the effects of the number of sensors and the locations of these sensors are investigated. When a few modes dominate the response it is found that if only a limited number of sensors are located away from nodal line and located at the pressure maxima of the sound field such as at each corner of a rectangular enclosure.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.3
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• pp.183-191
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• 2021

Non-intrusive load monitoring is a technology that can be used for predicting and classifying the type of appliances through real-time monitoring of user power consumption, and it has recently got interested as a means of energy-saving. In this paper, we propose a system for classifying appliances from user consumption data by combining GAF(Gramian angular field) technique that can be used for converting one-dimensional data to the two-dimensional matrix with convolutional neural networks. We use REDD(residential energy disaggregation dataset) that is the public appliances power data and confirm the classification accuracy of the GASF(Gramian angular summation field) and GADF(Gramian angular difference field). Simulation results show that both models showed 94% accuracy on appliances with binary-state(on/off) and that GASF showed 93.5% accuracy that is 3% higher than GADF on appliances with multi-state. In later studies, we plan to increase the dataset and optimize the model to improve accuracy and speed.

• Journal of the Korea Society for Simulation
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• v.19 no.1
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• pp.143-151
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• 2010

Fingerprint classification is a step to increase the efficiency of an 1:N fingerprint recognition system and plays a role to reduce the matching time of fingerprint and to increase accuracy of recognition. It is difficult to classify fingerprints, because the ridge pattern of each fingerprint class has an overlapping characteristic with more than one class, fingerprint images may include a lot of noise and an input condition is an exceptional case. In this paper, we propose a novel approach to design a stochastic model and to accomplish fingerprint classification using a directional characteristic of fingerprints for an effective classification of various qualities. We compute the directional value by searching a fingerprint ridge pixel by pixel and extract a directional characteristic by merging a computed directional value by fixed pixels unit. The modified Markov model of each fingerprint class is generated using Markov model which is a stochastic information extraction and a recognition method by extracted directional characteristic. The weight list of classification model of each class is decided by analyzing the state transition matrixes of the generated Markov model of each class and the optimized value which improves the performance of fingerprint classification using GA (Genetic Algorithm) is estimated. The performance of the optimized classification model by GA is superior to the model before the optimization by the experiment result of applying the fingerprint database of various qualities to the optimized model by GA. And the proposed method effectively achieved fingerprint classification to exceptional input conditions because this approach is independent of the existence and nonexistence of singular points by the result of analyzing the fingerprint database which is used to the experiments.