• International Journal of Control, Automation, and Systems
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• v.3 no.4
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• pp.509-523
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• 2005

We are developing a novel framework, PRIDE (PRediction In Dynamic Environments), to perform moving object prediction (MOP) for autonomous ground vehicles. The underlying concept is based upon a multi-resolutional, hierarchical approach which incorporates multiple prediction algorithms into a single, unifying framework. The lower levels of the framework utilize estimation-theoretic short-term predictions while the upper levels utilize a probabilistic prediction approach based on situation recognition with an underlying cost model. The estimation-theoretic short-term prediction is via an extended Kalman filter-based algorithm using sensor data to predict the future location of moving objects with an associated confidence measure. The proposed estimation-theoretic approach does not incorporate a priori knowledge such as road networks and traffic signage and assumes uninfluenced constant trajectory and is thus suited for short-term prediction in both on-road and off-road driving. In this article, we analyze the complementary role played by vehicle kinematic models in such short-term prediction of moving objects. In particular, the importance of vehicle process models and their effect on predicting the positions and orientations of moving objects for autonomous ground vehicle navigation are examined. We present results using field data obtained from different autonomous ground vehicles operating in outdoor environments.

• Journal of Digital Convergence
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• v.11 no.4
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• pp.391-396
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• 2013

Character industry is fundamentally based on a technical environment, a media, like any other cultural content industry. In order to extend a life of a character and increase the brand value, a choice and utilization of a more efficient way is necessary. Analyzing why game characters are less worth as a value of commodities than other media contents is presented and suggests complementary methods for the matter. In this study, an approach to increase a brand value of a game character, as well as, linking to develop profitable models afterward is suggested presenting a case of game development.

• Structural Engineering and Mechanics
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• v.58 no.5
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• pp.905-929
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• 2016

This paper assesses efficiency of the continuum method as the idealized system of building structures. A modified Coupled Two-Beam (CTB) model equipped with classical and non-classical damping has been proposed and solved analytically. In this system, complementary (non-classical) damping models composed of bending and shear mechanisms have been defined. A spatial shear damping model which is non-homogeneously distributed has been adopted in the CTB formulation and used to equivalently model passive dampers, viscous and viscoelastic devices, embedded in building systems. The application of continuum-based models for the dynamic analysis of shear wall systems has been further discussed. A reference example has been numerically analyzed to evaluate the efficiency of the presented CTB, and the optimization problems of the shear damping have been finally ascertained using local and global performance indices. The results reveal the superior performance of non-classical damping models against the classical damping. They show that the critical position of the first modal rotation in the CTB is reliable as the optimum placement of the shear damping. The results also prove the good efficiency of such a continuum model, in addition to its simplicity, for the fast estimation of dynamic responses and damping optimization issues in building systems.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.6
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• pp.11-21
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• 1997

The delay models for CMOS invertr presented so far predicted the delay time quite accurately whens input transition-time is very small. But the problem that the accuracy is inclined to decrease becomes apparent as input transition tiem increases. In this paper, a delay model for CMOS inverter is presented, which accuractely predicts the delay time even though input transition-time increases. To inverter must be included in modeling process because the main reason of inaccuracy as input transition tiem is the leakage current through the complementary MOS. For efficient modeling, this paper first models the MOSes with simple I-V charcteristic, with which both the pMOS and the nMOS are considered easily in calculating the inverter delay times. This resulting model needs few parameters and re-models each MOS effectively and simply evaluates output voltage to predict delay time, delay values obtained from this effectively and simply evaluates output voltage to predict delay time, delay values obtained from this model have been found to be within about 5% error rate of the SPICE results. The calculation time to predict the delay time with the model from this paper has the speed of more than 70times as fast as to the SPICE.

• Journal of Elementary Mathematics Education in Korea
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• v.17 no.3
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• pp.431-455
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• 2013

In this thesis, I classified various meanings of fraction into two categories, i.e concept(rate, operator, division) and model(whole-part, measurement, allotment), and surveyed appearances which is shown in Korea elementary mathematics textbook. Based on this results, I derived several implications on learning-teaching of fraction in elementary education. Firstly, we have to pursuit a unified formation of fraction concept through a complementary advantage of various concepts and models Secondly, by clarifying the time which concepts and models of fraction are imported, we have to overcome a ambiguity or tacit usage of that. Thirdly, the present Korea's textbook need to be improved in usage of measurement model. It must be defined more explicitly and must be used in explanation of multiplication and division algorithm of fraction.

• International Journal of Ocean System Engineering
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• v.3 no.3
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• pp.116-130
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• 2013

The prediction of ocean currents in real time over the warning times of a few hours or days is required in planning many operation-related activities in the ocean. Traditionally this is done through numerical models which are targeted toward producing spatially distributed information. This paper discusses a complementary method to do so when site-specific predictions are desired. It is based on the use of a recurrent type of neural network as well as the statistical tool of model tree. The measurements made at a site in Indian Ocean over a period of 4 years were used. The predictions were made over 72 time steps in advance. The models developed were found to be fairly accurate in terms of the selected error statistics. Among the two modeling techniques the model tree performed better showing the necessity of using distributed models for different sub-domains of data rather than a unique one over the entire input domain. Typically such predictions were associated with average errors of less than 2.0 cm/s. Although the prediction accuracy declined over longer intervals, it was still very satisfactory in terms of theselected error criteria. Similarly prediction of extreme values matched with that of the rest of predictions. Unlike past studies both east-west and north-south current components were predicted fairly well.

• Computers and Concrete
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• v.29 no.6
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• pp.433-444
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• 2022

Concrete's compressive strength is widely studied in order to understand many qualities and the grade of the concrete mixture. Conventional civil engineering tests involve time and resources consuming laboratory operations which results in the deterioration of concrete samples. Proposing efficient non-destructive models for the prediction of concrete compressive strength will certainly yield advancements in concrete studies. In this study, the efficiency of using radial basis function neural network (RBFNN) which is not common in this field, is studied for the concrete compressive strength prediction. Complementary studies with back propagation neural network (BPNN), which is commonly used in this field, have also been carried out in order to verify the efficiency of RBFNN for compressive strength prediction. A total of 13 input parameters, including novel ones such as cement's and fly ash's compositional information, have been employed in the prediction models with RBFNN and BPNN since all these parameters are known to influence concrete strength. Three different train: test ratios were tested with both models, while different hidden neurons, epochs, and spread values were introduced to determine the optimum parameters for yielding the best prediction results. Prediction results obtained by RBFNN are observed to yield satisfactory high correlation coefficients and satisfactory low mean square error values when compared to the results in the previous studies, indicating the efficiency of the proposed model.

• Nuclear Engineering and Technology
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• v.42 no.2
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• pp.145-150
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• 2010

The paper is describing work being developed in the frame of a 5-year IAEA Coordinated Research Programme (CRP) started in late 2005. Participants gained knowledge of modelling methodologies and experience in the development and use of rather sophisticated simulation tools in support of site characterization and performance assessment calculations. These goals were achieved by a coordinated effort, in which the advantages and limitations of numerical models are examined and demonstrated through a comparative analysis of simplified, illustrative test cases. This knowledge and experience should help them address these issues in their own country's nuclear waste program. Coordination efforts during the first three years of the project aimed at enabling this transfer of expertise and maximizing the learning experience of the participants as a group. This was accomplished by identifying common interests of the participants (i.e., Process Modelling and Total System Performance Assessment methodology), and by defining complementary tasks that are solved by the members. Synthesis of all available results by comparative assessments is planned in the coming months. The project will be completed end of 2010. This paper is summarizing activities up to November 2009.

• Molecules and Cells
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• v.37 no.7
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• pp.503-510
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• 2014

Lymphatic vessels provide essential roles in maintaining fluid homeostasis and lipid absorption. Dysfunctions of the lymphatic vessels lead to debilitating pathological conditions, collectively known as lymphedema. In addition, lymphatic vessels are a critical moderator for the onset and progression of diverse human diseases including metastatic cancer and obesity. Despite their clinical importance, there is no currently effective pharmacological therapy to regulate functions of lymphatic vessels. Recent efforts to manipulate the Vascular Endothelial Growth Factor-C (VEGFC) pathway, which is arguably the most important signaling pathway regulating lymphatic endothelial cells, to alleviate lymphedema yielded largely mixed results, necessitating identification of new targetable signaling pathways for therapeutic intervention for lymphedema. Zebrafish, a relatively new model system to investigate lymphatic biology, appears to be an ideal model to identify novel therapeutic targets for lymphatic biology. In this review, we will provide an overview of our current understanding of the lymphatic vessels in vertebrates, and discuss zebrafish as a promising in vivo model to study lymphatic vessels.

• Journal of Mechanical Science and Technology
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• v.20 no.5
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• pp.658-667
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• 2006

Fractional derivative models, which are used to describe the viscoelastic behavior of material, have received considerable attention. Thus it is necessary to put forward the analysis solutions of dynamic systems containing a fractional derivative. Although previously reported such kind of fractional calculus-based constitutive models, it only handles the particularity of rational number in part, has great limitation by reason of only handling with particular rational number field. Simultaneously, the former study has great unreliability by reason of using the complementary error function which can't ensure uniform real number. In this paper, a new approach is proposed for an analytical scheme for dynamic system of a spring-mass-damper system of single-degree of freedom under general forcing conditions, whose damping is described by a fractional derivative of the order $0<{\alpha}<1$ which can be both irrational number and rational number. The new approach combines the fractional Green's function and Laplace transform of fractional derivative. Analytical examples of dynamic system under general forcing conditions obtained by means of this approach verify the feasibility very well with much higher reliability and universality.