• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2003.04a
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• pp.434-440
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• 2003

The exchange of model design date among heterogeneous CAD systems is a difficult task because each system has different data structures suitable for its own functions. STEP has been able to represent product information as a common computer-interpretable form that is required to remain complete and consistent when the product informant is needed to be exchanged among different computer system. However, STEP has difficult architecture in is representing point, line, curve and vectors of element, more over it can't represent geometry data of feature based models. In this study, a structure of XML document that represents geometry data of feature based models as neutral format has been developed. To use the developed XML document, a Converter has also been developed to exchange modules so that it can exchange feature based data models among heterogeneous CAD systems. Aa for evaluation of the developed XML document and Converter, Solidworks and SolidEdge are selected.

• East Asian Economic Review
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• v.25 no.4
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• pp.403-424
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• 2021

AdaBoost tweaks the sample weight for each training set used in the iterative process, however, it is demonstrated that it provides more correlated errors as the boosting iteration proceeds if models' accuracy is high enough. Therefore, in this study, we propose a novel way to improve the performance of the existing AdaBoost algorithm by employing heterogeneous models and a stochastic twist. By employing the heterogeneous ensemble, it ensures different models that have a different initial assumption about the data are used to improve on diversity. Also, by using a stochastic algorithm with a decaying convergence rate, the model is designed to balance out the trade-off between model prediction performance and model convergence. The result showed that the stochastic algorithm with decaying convergence rate's did have a improving effect and outperformed other existing boosting techniques.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.12
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• pp.4492-4507
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• 2021

In camera sensor networks (CSNs), in order to better identify the point, full-view problem requires capture any facing direction of target (point or intruder), and its coverage prediction and sensor density issues are more complicated. At present, a lot of research supposes that a large number of homogeneous camera sensors are randomly distributed in a bounded square monitoring region to obtain full-view rate which is close to 1. In this paper, we deduce the sensor density prediction model in heterogeneous deployed CSNs with arbitrary full-view rate. Aiming to reduce the influence of boundary effect, we introduce the concepts of expanded monitoring region and maximum detection area. Besides, in order to verify the performance of the proposed sensor density model, we carried out different scenarios in simulation experiments to verify the theoretical results. The simulation results indicate that the proposed model can effectively predict the sensor density with arbitrary full-view rate.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.10a
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• pp.984-987
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• 2018

In an Internet of Thing (IoT) environment, entities with different attributes and capacities are going to be connected in a highly connected fashion. Specifically, not only the mechanical and electronic devices but also other entities such as people, locations and applications are connected to each other. Understanding and managing these connections play an important role for businesses, which identify opportunities for new IoT services. Traditional approach for storing and querying IoT data is used of a relational database management system (RDMS) such as MySQL or MSSQL. However, using RDMS is not flexible and sufficient for handling heterogeneous IoT data because these data have deeply complex relationships which require nested queries and complex joins on multiple tables. In this paper, we propose a graph model for constructing a graph database of heterogeneous IoT data. Graph databases are purposely-built to store highly connected data with nodes representing entities and edges representing the relationships between these entities. Our model fuses social graph, spatial graph, and things graph, and incorporates the relationships among them. We then present a case study which applies our model for representing data from a Smart Campus using Neo4J platform. Through the results of querying to answer real questions in Smart Campus management, we show the viability of our model.

• Food Science of Animal Resources
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• v.39 no.2
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• pp.222-228
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• 2019

This research was motivated by our encounter with the situation where an optimization was done based on statistically non-significant models having poor fits. Such a situation took place in a research to optimize manufacturing conditions for improving storage stability of coffee-supplemented milk beverage by using response surface methodology, where two responses are $Y_1$=particle size and $Y_2$=zeta-potential, two factors are $F_1$=speed of primary homogenization (rpm) and $F_2$=concentration of emulsifier (%), and the optimization objective is to simultaneously minimize $Y_1$ and maximize $Y_2$. For response surface analysis, practically, the second-order polynomial model is almost solely used. But, there exists the cases in which the second-order model fails to provide a good fit, to which remedies are seldom known to researchers. Thus, as an alternative to a failed second-order model, we present the heterogeneous third-order model, which can be used when the experimental plan is a two-factor central composite design having -1, 0, and 1 as the coded levels of factors. And, for multi-response optimization, we suggest a modified desirability function technique. Using these two methods, we have obtained statistical models with improved fits and multi-response optimization results with the predictions better than those in the previous research. Our predicted optimum combination of conditions is ($F_1$, $F_2$)=(5,000, 0.295), which is different from the previous combination. This research is expected to help improve the quality of response surface analysis in experimental sciences including food science of animal resources.

• Computers and Concrete
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• v.9 no.1
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• pp.35-50
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• 2012

The 2D representative volume element (RVE) for softening quasi-brittle materials like concrete is determined. Two alternative methods are presented to determine a size of RVE in concrete subjected to uniaxial tension by taking into account strain localization. Concrete is described as a heterogeneous three-phase material composed of aggregate, cement matrix and bond. The plane strain FE calculations of strain localization at meso-scale are carried out with an isotropic damage model with non-local softening.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.350-351
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• 2011

In this paper we study the impact of heterogeneous round trip times on multipath TCP (MPTCP) performance via analysis the fluid model and simulation. Using parameter 'a' in MPTCP can alleviate poor performance due to divergent RTTs between paths. Moreover, divergent RTIs in MPTCP can affect response to changes in the network conditions.

• Proceedings of the CALSEC Conference
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• 1999.07b
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• pp.563-574
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• 1999

In CALS/EC environment, there are geographically dispersed heterogeneous databases and various applications. Integrated database environment provides transparent access mechanism for heterogeneous and distributed databases and interoperability between applications in various platforms. Because elements exist geographically in integrated database environment, directory service is necessary for providing unique access mechanism for elements. In this paper, we design a directory service using CORBA based access interface and object-oriented DIB model for accessing transparently to elements and interoperability with other information system.

• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.551-562
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• 1995

We consider the iterated bootstrap method in regression model with heterogeneous error variances. The iterated wild bootstrap confidence intervla of the mean response is considered. It is shown that the iterated wild bootstrap confidence interval has coverage error of order $n^{-1}$ wheresa percentile method interval has an error of order $n^{-1/2}$. The simulation results reveal that the iterated bootstrap method calibrates the coverage error of percentile method interval successfully even for the small sample size.

• Nuclear Engineering and Technology
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• v.49 no.7
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• pp.1379-1387
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• 2017

This paper presents a comparison of homogenization techniques implemented in the APOLLO3 platform for transport core calculations: standard scalar flux weighting and new flux-moment homogenization, in different combinations with (or without) leakage models. Besides the historical B1-homogeneous model, a new B-heterogeneous one has indeed been implemented recently in the two/three-dimensional-transport solver using the method of characteristics. First analyses have been performed on a very simple Sodium Fast Reactor core with a regular hexagonal lattice. They show that using the heterogeneous leakage model in association with flux-moment homogenization strongly improves the prediction of $k_{eff}$ and void reactivity effects. These good results are confirmed when the application is done to the fissile assemblies of the more complex CFV (Low Void Effect) core of the ASTRID (Advanced Sodium Technological Reactor for Industrial Demonstration) project of sodium-cooled fast breeder reactor (Generation IV).