• Science of Emotion and Sensibility
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• v.14 no.3
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• pp.385-394
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• 2011

The purpose of this research is to compare and analyze visual images between the Real garment and the 3D garment simulation with the various fabrics of flare skirts and to analyze the correlation between mechanical properties and visual images. The picture images (printed on paper) of the Real garment and the 3D garment simulation of experimental flare skirts were shown to the evaluation group of women in their 20s majoring in clothing and textiles, and were evaluated by questionnaires with 32 adjectives. SPSS Version 12.0 statistics program was utilized to analyze data. Factor analysis, One Way ANOVA, T-test and Duncan test were used to investigate visual effect of the Real garment and the 3D garment simulation. As the result of conducting factor analysis on the visual appearance, the images were driven with five factors: 'drapeability', 'attractive', 'body compensation', 'bulkiness', 'activeness'. Visual images were significantly related with mechanical properties of various fabrics, and the visual images between 3D garment simulations and real garment differed with various fabrics and their mechanical properties. Visual images of silk and polyester group, cotton, linen and wool group were significantly related with weight and thickness of kinds of fabrics.

• Economic and Environmental Geology
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• v.53 no.3
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• pp.245-258
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• 2020

In this study, a data-driven response surface method using the results acquired from the numerical simulation is developed to evaluate the potential storage capacity of groundwater due to the construction of a groundwater dam. The hydraulic conductivities of alluvium and basement rock, depth and slope of the channel are considered as the natural conditions of the location for groundwater dam construction. In particular, the probability models of the hydraulic conductivities and the various types of geometry of the channel are considered to ensure the reliability of the numerical simulation and the generality of the developed estimation model. As the results of multiple simulations, it can be seen that the hydraulic conductivity of basement rock and the depth of the channel greatly influence to the groundwater storage capacity. In contrast, the slope of the channel along the groundwater flow direction shows a relatively lower impact on the storage capacity. Based on the considered natural conditions and the corresponding numerical simulation results, the storage capacity estimation model is developed applying an artificial neural network as the nonlinear regression model for training. The developed estimation model shows a high correlation coefficient (>0.9) between the simulated and the estimated storage amount. This result indicates the superiority of the developed model in evaluating the storage capacity of the potential location for groundwater dam construction without the numerical simulation. Therefore, a more objective and efficient comparison for the storage capacity between the different potential locations can be possibly made based on the developed estimation model. In line with this, the proposed method can be an effective tool to assess the optimal location of groundwater dam construction across Korea.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.183-200
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• 2022

A variety of simulation approaches based on automated driving technologies have been proposed to develop traffic operations strategies to prevent traffic crashes and alleviate congestion. The maneuver of simulated autonomous vehicles (AVs) needs to be realistic and be effectively differentiated from the behavior of manually driven vehicles (MVs). However, the verification of simulated AV maneuvers is limited due to the difficulty in collecting actual AVs trajectory and interaction data with MVs. The purpose of this study is to develop a methodology to evaluate the suitability of AV maneuvers based on both driving and traffic simulation experiments. The proposed evaluation framework includes the requirements for the behavior of individual AVs and the traffic stream performance resulting from the interactions with surrounding vehicles. A driving simulation approach is adopted to evaluate the feasibility of maneuvering of individual AVs. Meanwhile, traffic simulations are used to evaluate whether the impact of AVs on the performance of traffic stream is reasonable. The outcome of this study is expected to be used as a fundamental for the design and evaluation of transportation systems using automated driving technologies.

• Journal of Korea Water Resources Association
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• v.55 no.10
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• pp.707-721
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• 2022

In this study, a state-of-the-art review on urban inundation simulation technology was presented summarizing major achievements and limitations, and future research recommendations and challenges. More than 160 papers published in major domestic academic journals since the 2000s were analyzed. After analyzing the core themes and contents of the papers, the status of technological development was reviewed according to simulation methodologies such as physically-based and data-driven approaches. In addition, research trends for application purposes and advances in overseas and related fields were analyzed. Since more than 60% of urban inundation research used Storm Water Management Model (SWMM), developing new modeling techniques for detailed physical processes of dual drainage was encouraged. Data-based approaches have become a new status quo in urban inundation modeling. However, given that hydrological extreme data is rare, balanced research development of data and physically-based approaches was recommended. Urban inundation analysis technology, actively combined with new technologies in other fields such as artificial intelligence, IoT, and metaverse, would require continuous support from society and holistic approaches to solve challenges from climate risk and reduce disaster damage.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.7
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• pp.665-674
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• 2000

In data parallel programs incurring high cache locality, the choice of grain sizes affects cache performance. Though the grain sizes chosen provide fair load balance among processors, the grain sizes that ignore underlying caching effect result in address interferences between grains allocated to a processor. These address interferences appear to have a negative impact on the cache locality, since they result in cache conflict misses. To address this problem, we propose a best grain size driven from a cache size and the number of processors based on direct mapped cache's characteristic. Since the proposed method does not map the grains to the same location in the cache, cache conflict misses are reduced. Simulation results show that the proposed best grain size substantially improves the performance of tested data parallel programs through the reduction of cache misses on direct-mapped caches.

• Biotechnology and Bioprocess Engineering:BBE
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• v.10 no.5
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• pp.425-431
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• 2005

The systems-level analysis of microbes with myriad of heterologous data generated by omics technologies has been applied to improve our understanding of cellular function and physiology and consequently to enhance production of various bioproducts. At the heart of this revolution resides in silico genome-scale metabolic model, In order to fully exploit the power of genome-scale model, a systematic approach employing user-friendly software is required. Metabolic flux analysis of genome-scale metabolic network is becoming widely employed to quantify the flux distribution and validate model-driven hypotheses. Here we describe the development of an upgraded MetaFluxNet which allows (1) construction of metabolic models connected to metabolic databases, (2) calculation of fluxes by metabolic flux analysis, (3) comparative flux analysis with flux-profile visualization, (4) the use of metabolic flux analysis markup language to enable models to be exchanged efficiently, and (5) the exporting of data from constraints-based flux analysis into various formats. MetaFluxNet also allows cellular physiology to be predicted and strategies for strain improvement to be developed from genome-based information on flux distributions. This integrated software environment promises to enhance our understanding on metabolic network at a whole organism level and to establish novel strategies for improving the properties of organisms for various biotechnological applications.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.16 no.2
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• pp.88-93
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• 2017

Due to the requirement of the development of the precision manufacturing industry, the accuracy of machine tools has become a key issue in this field. A critical factor that affects the accuracy of machine tools is the feed system, which is generally driven by a ball screw. Basically, to improve the performance of the feed drive system, which will be thermally extended lengthwise by continuous usage, a thermal error compensation system that is highly dependent on the feedback temperature or positioning data is employed in the machine tool system. Due to the overdependence on measuring technology, the cost of the compensation system and low productivity level are inevitable problems in the machine tool industry. This paper presents a novel feed drive thermal error compensation system method that could compensate for thermal error without positioning or temperature feedback. Regarding this thermal error compensation system, the heat generation of components, principal of compensation, thermal model, mathematic model, and calculation method are discussed. As a result, the test data confirm the correctness of the developed feed drive thermal error compensation system very well.

• Journal of Internet Computing and Services
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• v.13 no.5
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• pp.1-8
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• 2012

In this paper, we propose a new clustering combination based on numerical data driven for rule generation mechanism. In large and complicated space, a clustering method can obtain limited performance results. To overcome the single clustering method problem, hybrid combined methods can solve problem to divided simple cluster estimation. Fundamental structure of the proposed method is combined by mountain clustering and modified Chen clustering to extract detail cluster information in complicated data distribution of non-parametric space. It has automatic rule generation ability with advanced density based operation when intelligent systems including neural networks and fuzzy inference systems can be generated by clustering results. Also, results of the mechanism will be served to information of decision support system to infer the useful knowledge. It can extend to healthcare and medical decision support system to help experts or specialists. We show and explain the usefulness of the proposed method using simulation and results.

• Journal of Korean Society on Water Environment
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• v.24 no.5
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• pp.603-610
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• 2008

A mathematical model was developed to understand how the presence of plants affects vertical profiles of electron acceptors, their reduced species, and trace metals in the wetland sediments. The model accounted for biodegradation of organic matter utilizing sequential electron acceptors and subsequent chemical reactions using stoichiometric relationship. These biogeochemical reactions were affected by the combined effects of oxygen release and evapotranspiration driven by wetland plants. The measured data showed that $SO_4{^{2-}}$ concentrations increased at the beginning of the growing season and then gradually decreased. Based on the measured data, it was hypothesized that the limitation of the solid phase sulfide in direct contact with the roots may result in the gradual decrease of $SO_4{^{2-}}$ concentrations. With the dynamic formulation for the limitation of the solid phase sulfide, model simulated time variable sulfate profiles using published model parameters. Oxygen release from roots produced divalent metal species (i.e. $Cd^{2+}$) as well as oxidized sulfur species (i.e. $SO_4{^{2-}}$) in the sediment pore water. Evapotranspiration-induced advection increased flux of divalent metal species from the overlying water column into the rhizosphere. The increased divalent metal species were converted to the metal sulfide with sufficient FeS around the rhizosphere, which contributed to the decrease of bioavailability and toxicity of divalent metal activity in the pore water. Since the divalent metal activity is a good predictor of the metal bioavailability, this model with a proper simulation of solid phase sulfide plays an essential role to predict the dynamics of trace metals in the wetland sediments.

• Journal of KIISE:Computer Systems and Theory
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• v.37 no.5
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• pp.285-291
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• 2010

Flash memory has many good features such as small size, shock-resistance, and low power consumption, but the cost of flash memory is still high to substitute for hard disk entirely. Recently, some mobile devices, such as laptops, attempt to use both flash memory and hard disk together for taking advantages of merits of them. However, existing OSs (Operating Systems) are not optimized to use the heterogeneous storage media. This paper presents a new buffer cache management scheme. First, we allocate buffer cache space according to access patterns of block references and the characteristics of storage media. Second, we prefetch data blocks selectively according to the location of them and access patterns of them. Third, we moves destaged data from buffer cache to hard disk or flash memory considering the access patterns of block references. Trace-driven simulation shows that the proposed schemes enhance the buffer cache hit ratio by up to 29.9% and reduce the total I/O elapsed time by up to 49.5%.