• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.8A
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• pp.879-888
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• 2004

In this paper, we propose a real time QoS(Quality of Service) guaranteed transmission mechanism for MPEG video traffic at the congested node in IP based networks. Recent spread of the Internet has increased the demands of a real time multimedia service of the quality, Because the type of Internet services can, however, offer the best effort delivery strategies, it is difficult to treat all the types of traffic with differential COS (Class of Service). Most of all, the hierarchical coding method of MPEG data utilizes the reference frame for the motion prediction. The loss of the reference frames makes QoS of the video traffic degraded because the reference frame bit error causes the consecutive packet loss. Therefore we have studied the real time QoS guaranteed mechanism for video traffic by analyzing the previous methods. Computer simulation results show that the proposed scheme has better performance than the previous one.

• Tunnel and Underground Space
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• v.19 no.6
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• pp.558-566
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• 2009

Time-dependent behavior is a basic mechanical property of rocks. Predicting the failure time of rock structures by analyzing the time-dependent characteristic is important and problematic. It is tried to predict the failure time of tunnel, slope & laboratory creep test specimen from measured displacement(or strain) and rate with relationship suggested by Voight($\ddot{\Omega}=A\dot{\Omega}^\alpha$, where $\Omega$ is a measurable quantity such as strain & displacement and A & $\alpha$ are constants). A & $\alpha$ are estimated through applying the nonlinear least square method to the single and double integrated Voight's equations and utilized to predict the failure time. Predicted failure time is in accordance with real one except minor error. Linear inverse rate method applied to creep strain and rate yields a poor linear correlation of data and precision of predicted failure time is not better than methods using strain and rate.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.20 no.5
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• pp.471-479
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• 2009

In this paper, we proposed an improved ray tracing method with an amelioration of visible tree structure, a visible face determination method, and non-uniform random test point method. In a proposed visible tree structure, it reduces tree nodes by means of merging similar nodes. In a visible face determination method, it shows that a ray hit test with a packet ray method can reduce a test time. A ray tracing method involving with a packet ray hit test method can improve a tree construction time up to 3.3 times than a ray tracing method with a single ray hit test method. Furthermore, by seeding a non-uniform and random test point on a face, tree construction time is improved up to 1.11 times. Received powers from the proposed ray tracing results and measured results have good agreement with 1.9 dB RMS error.

• Journal of Biosystems Engineering
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• v.37 no.4
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• pp.252-257
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• 2012

Purpose: The net rind pattern and color of melon surface are important for a high market value of melon fruits. The development of the net and color are closely related to the changes in shape, size, and maturing. Therefore, the net and color characteristics can be used indicators for assessment of melon quality. The goal of this study was to investigate the possibility of estimating melon soluble solids content (SSC) and firmness by analyzing the net and color characteristics of fruit surface. Methods: The true color images of melon surface obtained at fruit equator were analyzed with 18 color features and 9 texture features. The partial least squares (PLS) method was used to estimate SSC and firmness in melons using their color and texture features. Results: In sensing melon SSC, the coefficients of determination of validation (${R_v}^2$) of the prediction models using the color and texture features were 0.84 (root mean square error of validation, RMSEV: 1.92 $^{\circ}Brix$) and 0.96 (RMSEV: 0.60 $^{\circ}Brix$), respectively. The ${R_v}^2$ values of the models for predicting melon firmness using the color and texture features were 0.64 (RMSEV: 4.62 N) and 0.79 (RMSEV: 2.99 N), respectively. Conclusions: In general, the texture features were more useful for estimating melon internal quality than the color features. However, to strengthen the usefulness of the color and texture features of melon surface for estimation of melon quality, additional experiments with more fruit samples need to be conducted.

• Korean Journal of Agricultural Science
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• v.39 no.3
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• pp.413-420
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• 2012

Spectroscopic measurement method based on visible and near-infrared wavelengths was prominent technology for rapid and non-destructive evaluation of internal quality of fruits. Reflectance measurement was performed to evaluate firmness, soluble solid content, and acid content of truss tomatoes by hyperspectral reflectance imaging system. The Vis/NIR reflectance spectra was acquired from truss tomatoes sorted by 6 ripening stages. The multivariable analysis based on partial least square (PLS) was used to develop regression models with several preporcessing methods, such as smoothing, normalization, multiplicative scatter correction (MSC), and standard normal variate (SNV). The best model was selected in terms of coefficient of determination of calibration ($R_c^2$) and full cross validation ($R_{cv}^2$), and root mean standard error of calibration (RMSEC) and full cross validation (RMSECV). The results of selected models were 0.8976 ($R_p^2$), 6.0207 kgf (RMSEP) with gaussian filter of smoothing, 0.8379 ($R_p^2$), $0.2674^{\circ}Bx$ (RMSEP) with the mean of normalization, and 0.7779 ($R_p^2$), 0.1033% (RMSEP) with median filter of smoothing for firmness, soluble solid content (SSC), and acid content, respectively. Results show that Vis / NIR hyperspectral reflectance imaging technique has good potential for the measurement of internal quality of truss tomato.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.6
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• pp.1398-1417
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• 2013

A method is proposed to reduce excess resources from a virtual machine(VM) while avoiding subsequent migrations for a computer cluster that provides cloud service. The proposed scheme cuts down on the resources of a VM based on the probability that migration may occur after a reduction. First, it finds a VM that can be scaled down by analyzing the history of the resource usage. Then, the migration probability is calculated as a function of the VM resource usage trend and the trend error. Finally, the amount of resources needed to eliminate from an underutilized VM is determined such that the migration probability after the resource reduction is less than or equal to an acceptable migration probability. The acceptable migration probability, to be set by the cloud service provider, is a criterion to assign a weight to the resource reduction either to prevent VM migrations or to enhance VM utilization. The results of simulation show that the proposed scheme lowers migration frequency by 31.6~60.8% depending on the consistency of resource demand while losing VM utilization by 9.1~21.5% compared to other known approaches, such as the static and the prediction-based methods. It is also verified that the proposed scheme extends the elapsed time before the first occurrence of migration after resource reduction 1.1~2.3-fold. In addition, changes in migration frequency and VM utilization are analyzed with varying acceptable migration probabilities and the consistency of resource demand patterns. It is expected that the analysis results can help service providers choose a right value of the acceptable migration probability under various environments having different migration costs and operational costs.

• Korean Institute of Interior Design Journal
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• v.26 no.3
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• pp.45-54
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• 2017

A social phenomenon that occurs in a physical space is said to be a complex system. However, space syntax, which is commonly employed by researchers to identify such social phenomena, has various limitations in interpreting their complexity. On the other hand, agent-based modeling considers a variety of factors including the personality of the agent, objective-oriented work flows, estimation according to time flows and better prediction of space use through diverse parameters depending the situation, as well as the characteristics of the space. The agent-based method thus has the potentials to be developed as an alternative to space syntax techniques. In particular, discrete event driven simulation(DEVS), which is part of the agent-based modeling method, embraces the concept of networks just like space syntax, which allows a possible theoretical linkage in the future. This study suggests a procedural model of agent-based DEVS reflecting two different connection methods, i.e. connections between adjacent areas and those of the entire space, and attempts to identify the relationship between the local and regional indices of space syntax. A number of spaces were selected as examples-one for a preliminary experiment and eight modified for the main experiment-and space syntax and DEVS were applied to each of them. The comparative analysis of the results led to the conclusions as follows: 1) Adjacent connections were closely related to local indices, while the whole-space approach to regional indices. Local integration shows both characteristics. 2) Observation of the time flow model indicated a faster convergence with the range of 1 to 3-fold of the total time of one lap, with the error of less than 10%. 3) The heat map analysis showed more obvious characteristics of using the space for the entire space rather than adjacent connections. 4) Space syntax shows higher eligibility than ABM.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 2017.04a
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• pp.44-44
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• 2017

The objective of this study was to evaluate firmness, and sweetness index (SI) of tomatoes (Lycopersicum esculentum) by using hyperspectral imaging (HSI) in the range of 1000-1400 nm. The mean spectra of the 95 matured tomato samples were extracted from the hyperspectral images, and the reference firmness and sweetness index of the same sample were measured and calibrated with their corresponding spectral data by partial least squares (PLS) regression with different preprocessing method. The results showed that the regression model developed by PLS regression based on Savitzky-Golay (S-G) second-derivative preprocessed spectra resulted in better performance for firmness, and SI of tomatoes compared to models developed by other preprocessing methods, with correlation coefficients (rpred) of 0.82, and 0.74 with standard error of prediction (SEP) of 0.86 N, and 0.63 respectively. Then, the feature wavelengths were identified using model-based variable selection method, i.e., variable important in projection (VIP), resulting from the PLS regression analyses and finally chemical images were derived by applying the respective regression coefficient on the spectral image in a pixel-wise manner. The resulting chemical images provided detailed information on firmness, and sweetness index (SI) of tomatoes. Therefore, these research demonstrated that HIS technique has a potential for rapid and non-destructive evaluation of the firmness and sweetness index of tomatoes.

• Journal of the Korean Data and Information Science Society
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• v.27 no.2
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• pp.327-335
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• 2016

The People's Republic of China has vigorously been pursuing the internationalization of the Chinese Yuan or Renminbi after the financial crisis of 2008. In this view, an abrupt increase of use of the Chinese Yuan in the onshore and offshore markets are important milestones to be one of important currencies. One of the most frequently used methods to forecast volatility is GARCH model. Since a prediction error of the GARCH model has been reported quite high, a lot of efforts have been made to improve forecasting capability of the GARCH model. In this paper, we have proposed MLP-GARCH and a DL-GARCH by employing Artificial Neural Network to the GARCH. In an application to forecasting Chinese Yuan volatility, we have successfully shown their overall outperformance in forecasting over the GARCH.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.39 no.1
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• pp.7-14
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• 1994

This study was conducted to establish the rapid evaluation method of chemical components of rice grain on the basis of non-destructive method. A near-infrared reflectance spectroscopic(NIRS) method was utilized, for the determination of amylose, protein, magnesium, and potassium content of rice. A multiple linear regression analysis for the data obtained by standard laboratory methods and NIRS method was carried out to make a calibration. The standard error of prediction for amylose, protein, magneisum and potassium content were 0.88%, 0.28%, 12.62mg and 10.79mg, respectively. It was concluded that the NlRS method can be useful the rapid determination of amylose, protein, magnesium and potassium content instead of the existing laboratory method.