• Journal of Institute of Control, Robotics and Systems
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• v.21 no.9
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• pp.836-842
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• 2015

In this paper, the target size and model based target size estimator (TMBE) algorithm is presented for iimaging infrared (IIR) seeker. At the imaging seeker, target size information is important factor for accurate tracking. The model based target size estimator filter (MBEF) algorithm was proposed to estimate target size at imaging infrared seeker. But, the model based target size estimator filter algorithm need to know relative distance from the target. In order to overcome the problem, we propose target size and model based target size estimator filter (TMBEF) algorithm which based on the target size. The performance of proposed algorithm is tested at target intercept scenario. The experiment results show that the proposed algorithm has the accurate target size estimating performance.

• Fashion & Textile Research Journal
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• v.17 no.2
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• pp.278-286
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• 2015

Fashion industry has tried to adopt the virtual garment technology to reduce the time and effort spent on sample creation. For garment manufacturers to adopt the virtual garment technology as an alternative to sample creation, 3D avatars that meet the needs of each brand should be developed. Virtual garment softwares that are available in the market provide avatars with standardized body models and allow to modify the size by manually entering size specifications. This study proposed a methodology to develop size specifications for 3D avatars as well as brand-customized production sizes. For this, a man's fashion brand which is using virtual garment technology is selected. And the Size Korea database is used to develop size specification based on the customers' body shape. This study developed regression equations on body size specifications, which in turn proposed a regression model to proportionately change size specifications of 3D fitting-models. Based on the each body size calculated by the regression model, a standard model is created, and the skeleton-skin algorithm is applied to the regression model to obtain the results of size changes. Then, the 3D model sizes are tested for size changes as well as measured, which verifies that the regression model reflects body size changes.

• Journal of Distribution Science
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• v.20 no.12
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• pp.117-123
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• 2022

Purpose: This study investigates the relationship between earnings forecasts estimated from a cross-sectional earnings forecast model and firm characteristics such as firm size, sales volatility, and earnings volatility. Research design, data and methodology: The association between earnings forecasts and the aforementioned firm characteristics is examined using 214 firm-year observations with analyst following and 848 firm-year observations without analyst following for the period of 2011-2019. I estimate future earnings using a cross-sectional earnings forecast model, and then compare these model-based earnings forecasts with analysts' earnings forecasts in terms of forecast bias and forecast accuracy. The earnings forecast bias and accuracy are regressed on firm size, sales volatility, and earnings volatility. Results: For a sample with analyst following, I find that the model-based earnings forecasts are more accurate as the firm size is larger, whereas the analysts' earnings forecasts are less biased and more accurate as the firm size is larger. However, for a sample without analyst following, I find that the model-based earnings forecasts are more pessimistic and less accurate as firms' past earnings are more volatile. Conclusions: Although model-based earnings forecasts are useful for evaluating firms without analyst following, their accuracy depends on the firms' earnings volatility.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.59 no.2
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• pp.99-109
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• 2023

In this study, a comparative test operation was conducted through the alternate haul method to examine the selectivity of the four mesh sizes (60 mm, 90 mm, 110 mm, and 130 mm) of the trawl codend. The selectivity was analyzed using the SELECT model considering the fishing efficiency (split parameter) of each fishing gear in the comparative test fishing operation in the trawl and the maximum likelihood method for parameter estimation. A selectivity master curve was estimated for several mesh sizes using the extended-SELECT model. As a result of analyzing the selectivity for silver croaker based on the results of three times hauls for each experimental gear, it was found that the size of the fish caught increased as the size of the mesh size increased. When the selectivity for each mesh size analyzed by the SELECT model considering the split ratio was evaluated based on the size of the AIC value, the estimated split model was superior to the equal split model. Based on the master curve, the 50% selection length value was 2.893, which was estimated to be 136 mm based on the mesh size of 60 mm. In some selectivity models, there was a large deviance between observed and theoretical values due to the non-uniformity of the distribution of fished length classes. As a result, it is considered that appropriate sea trials and selectivity evaluation methods with high reliability should be applied to present trawl fishery resource management methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.3043-3067
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• 2022

With the mobile traffic in the network increases exponentially, multi-access edge computing (MEC) develops rapidly. MEC servers are deployed geo-distribution, which serve many mobile terminals locally to improve users' QoE (Quality of Experience). When the cache space of a MEC server is full, how to replace the cached videos is an important problem. The problem is also called the cache replacement problem, which becomes more complex due to the dynamic video popularity and the varied video sizes. Therefore, we proposed a new cache replacement scheme based on local video popularity and video size to solve the cache replacement problem of MEC servers. First, we built a local video popularity model, which is composed of a popularity rise model and a popularity attenuation model. Furthermore, the popularity attenuation model incorporates a frequency-dependent attenuation model and a frequency-independent attenuation model. Second, we formulated a utility based on local video popularity and video size. Moreover, the weights of local video popularity and video size were quantitatively analyzed by using the information entropy. Finally, we conducted extensive simulation experiments based on the proposed scheme and some compared schemes. The simulation results showed that our proposed scheme performs better than the compared schemes in terms of hit rate, average delay, and server load under different network configurations.

• Food Science of Animal Resources
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• v.35 no.5
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• pp.630-637
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• 2015

In the dairy industry, natural plant-based powders are widely used to develop flavor and functionality. However, most of these ingredients are water-insoluble; therefore, emulsification is essential. In this study, the efficacy of high pressure homogenization (HPH) on natural plant (chocolate or vanilla)-based model emulsions was investigated. The particle size, electrical conductivity, Brix, pH, and color were analyzed after HPH. HPH significantly decreased the particle size of chocolate-based emulsions as a function of elevated pressures (20-100 MPa). HPH decreased the mean particle size of chocolate-based emulsions from 29.01 μm to 5.12 μm, and that of vanilla-based emulsions from 4.18 μm to 2.44 μm. Electrical conductivity increased as a function of the elevated pressures after HPH, for both chocolate- and vanilla-based model emulsions. HPH at 100 MPa increased the electrical conductivity of chocolate-based model emulsions from 0.570 S/m to 0.680 S/m, and that of vanilla-based model emulsions from 0.573 S/m to 0.601 S/m. Increased electrical conductivity would be attributed to colloidal phase modification and dispersion of oil globules. Brix of both chocolate- and vanilla-based model emulsions gradually increased as a function of the HPH pressure. Thus, HPH increased the solubility of plant-based powders by decreasing the particle size. This study demonstrated the potential use of HPH for enhancing the emulsification process and stability of the natural plant powders for applications with dairy products.

• Steel and Composite Structures
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• v.45 no.2
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• pp.263-279
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• 2022

With the span and arch rib size of concrete-filled steel tube (CFST) arch bridges increase, the hydration heat of pumped mass concrete inside large-size steel tube causes a significant temperature variation, leading to a risk of thermal stress-induced cracking during construction. In order to tackle this phenomenon, a hydration heat conduction model based on hydration degree was established through a nonlinear temperature analysis incorporating an exothermic hydration process to obtain the temperature field of large-size CFST. Subsequently, based on the evolution of elastic modulus based on hydration degree and early-age creep rectification, the finite element model (FEM) model and analytical study were respectively adopted to investigate the variation of the thermal stress of CFST during hydration heat release, and reasonable agreement between the results of two methods is found. Finally, a comparative study of the thermal stress with and without considering early-age creep was conducted.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.52 no.6
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• pp.719-724
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• 2019

This study is an extension of our previous model for a size-based fish stock assessment. In the previous model, we applied an allometric length-weight relationship (W=α·L^β) to convert lengths of fish to weights, and estimated those parameters α and β, using data about lengths and weights aggregated over years. In this study, we focused on whether consideration of temporal (e.g., year-to-year) variability in those estimates (i.e., ${\hat{\alpha}}$ and ${\hat{\beta}}$) would contributive. After calculating year-specific estimates (i.e., year-specific pairs of ${\hat{\alpha}}$ and ${\hat{\beta}}$) by applying data about lengths and weights separated by year, we evaluated the contribution of those year-specific pairs of ${\hat{\alpha}}$ and ${\hat{\beta}}$ to the performance of the size-based stock assessment model. The model with such year-to-year variability being considered (lower AIC) outperformed that with the variability being ignored (higher AIC). We illustrated this study using data on Korean chub mackerel Scomber japonicus from 2005-2017.

• The KIPS Transactions:PartD
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• v.11D no.3
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• pp.597-604
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• 2004

Accurate software cost estimation is essential to both developers and customers. Most of the cost estimating models based on the size measure methods, such as LOC and FP, are obtained through size estimation. The accuracy of size estimation directly influences the accuracy of cost estimation. As a result, the overall structure of regression-based cost models applies the power function based on software size. Many growth phenomenon in nature such as the growth in living organism, performance of technology, and learning capability of human show an S-shaped curve. This paper proposes a model which estimates the developing effort by using the growth curve. The presented model assumes that the relation cost and size follows the growth curve. The appropriateness of the growth curve model based on Function Point, Full-Function Point and Use-Case Point, which are the general methods in estimating the software size have been confirmed. The proposed growth curve model shows similar performance with power function model. In conclusion, the growth curve model can be applied in the estimation of the software cost.

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.55-64
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• 2024

In this study, we consider the sample size determination problem for clustered count data with many zeros. In general, zero-inflated Poisson and binomial models are commonly used for zero-inflated data; however, in real data the assumptions that should be satisfied when using each model might be violated. We calculate the required sample size based on a discrete Weibull regression model that can handle both underdispersed and overdispersed data types. We use the Monte Carlo simulation to compute the required sample size. With our proposed method, a unified model with a low failure risk can be used to cope with the dispersed data type and handle data with many zeros, which appear in groups or clusters sharing a common variation source. A simulation study shows that our proposed method provides accurate results, revealing that the sample size is affected by the distribution skewness, covariance structure of covariates, and amount of zeros. We apply our method to the pancreas disorder length of the stay data collected from Western Australia.