• Journal of Environmental Impact Assessment
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• v.20 no.4
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• pp.509-521
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• 2011

The purpose of this study is to estimate overall reliability and applicability of the watershed modeling for systematic management of point and non-point sources via water quality analysis and prediction of runoff discharge within watershed. Recently, runoff characteristics and pollutant characteristics have been changing in watershed by anomaly climate and urbanization. In this study, the effects of watershed scale were analyzed in runoff and water quality modeling using HSPF. In case of correlation coefficient, its range was from 0.936 to 0.984 in case A(divided - 2 small watersheds). On the other hand, its range was form 0.840 to 0.899 in case B(united - 1 watershed). In case of Nash-Sutcliffe coefficient, its range was from 0.718 to 0.966 in case A. On the other hand, its range was from 0.441 to 0.683 in case B. As a result, it was judged that case A was more accurate than case B. Therefore, runoff and water quality modeling in minimum watershed scale that was provided data for calibration and verification was judged to be favorable in accuracy. If optimal watershed dividing and parameter optimization using PEST in HSPF with more reliable measured data are carried out, more accurate runoff and water quality modeling will be performed.

• Biotechnology and Bioprocess Engineering:BBE
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• v.11 no.1
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• pp.67-71
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• 2006

This paper compares regression and neural network modeling approaches to predict competitive biosorption equilibrium data. The regression approach is based on the fitting of modified Langmuir-type isotherm models to experimental data. Neural networks, on the other hand, are non-parametric statistical estimators capable of identifying patterns in data and correlations between input and output. Our results show that the neural network approach outperforms traditional regression-based modeling in correlating and predicting the simultaneous uptake of copper and cadmium by a microbial biosorbent. The neural network is capable of accurately predicting unseen data when provided with limited amounts of data for training. Because neural networks are purely data-driven models, they are more suitable for obtaining accurate predictions than for probing the physical nature of the biosorption process.

• Proceedings of the Korea Society for Simulation Conference
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• 2002.05a
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• pp.253-258
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• 2002

This paper proposes a methodology for development of protocol models. The methodology attempts to employ two modeling environments in models development, NS2 and DEVSim++, which will interoperate during simulation. NS2 is a widely used network simulator in protocol research, which employs an informal modeling approach. Within the approach time and state information of protocol models are not explicitly described, thus being hard to validate model. On the other hand the DEVS formalism is a mathematical framework for modeling a discrete event system in a hierarchical, modular manner. In DEVS, model's time and state information is described explicitly, By using DEVS formalism, models can easily be validated and errors in the modeling stage can be reduced. However, the DEVS simulator, DEVSim++, supports a small amount of models library which are required to build simulation models of general communication network. Although NS2 employs an informal modeling approach and models validation is difficult, it supports abundant models library validated by experimental users. Thus, combination of DEVS models and NS2 models may be an effective solution for network modeling. Such combination requires interoperation between DEVSim++ simulator and NS2 simulator. This paper develops an environment for such interoperation. Correctness and effectiveness of the implemented interoperation environment have been validated by simulation of UDP and TCP models.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.830-833
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• 2005

The diversification of the regulating system was promoted with the development of the computer technology. On the other hand, environmental problems and the energy conservation problem are being valued as for needs of the society. Our research was able to be achieved in such a situation.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.01a
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• pp.37-44
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• 2001

This paper describes the modeling of work environment for the extraction of abstract operation rules for cooperative work with multiple agent. We propose the modeling method using a potential field. In the method, it is applied to a box pushing problem, which is to move a box from a start to a goal b multiple agent. The agents follow the potential value when they move and work in the work environment. The work environment is represented as the grid space. The potential field is generated by Genetic Algorithm(GA) for each agent. GA explores the positions of a potential peak value in the grid space, and then the potential value stretching in the grid space is spread by a potential diffusion function in each grid. However it is difficult to explore suitable setting using hand coding of the position of peak potential value. Thus, we use an evlolutionary computation way because it is possible to explore the large search space. So we make experiments the environment modeling using the proposed method and verify the performance of the exploration by GA. And we classify some types from acquired the environment model and extract the abstract operation rule, As results, we find out some types of the environment models and operation rules by the observation, and the performance of GA exploration is almost same as the hand coding set because these are nearly same performance on the evaluation of the consumption of agent's energy and the work step from point to the goal point.

• Physical Therapy Korea
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• v.14 no.2
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• pp.1-10
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• 2007

The purpose of this experiment was to investigate the applicability of audio-visual modeling for improving the efficiency of rehabilitative programs by analyzing the effects of observing these various models on the capacity of stroke patients to perform upper limb activities. Twenty-one stroke patients participated in the experiment and were randomly assigned to either task modeling, sport modeling, or control group. During 2 weeks of intervention, subjects in all groups participated in the physical practice of experimental tasks. These tasks comprised of a Nine Hole Peg Test, the Jebsen-Taylor Hand Function tests, and locomotion. These tasks were performed 5 days a week, 30 min per day. In addition to the physical practice, the task modeling group observed a model performing experimental tasks and locomotive activities for 20 min, while the sport modeling group observed a model performing various sport activities for 20 min. Subjects' ability to perform the experimental tasks was measured 3 times, before, immediately after, and 1 week after the intervention. Analyses of the capacity to perform upper extremity activities displayed significant improvement from the pre-test to immediate and delayed post-tests in all groups. However, the amount of improvement was the highest in the task modeling group. The task modeling group was superior to the control group in the post-test of all experimental tasks, whereas the sport modeling group did not display significant differences from the control group. These results suggest that audio-visual modeling can be used as an effective cognitive intervention for facilitating the rehabilitation of stroke patients, and its rehabilitative effect can be maximized when the program is comprised of performance scenes directly related to the target task.

• Computers and Concrete
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• v.19 no.2
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• pp.171-177
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• 2017

Water pressure test operation is used before the grouting to determine the rate of penetrability, the necessity and estimations related to grouting, by the penetration of water into the borehole. One of the parameters which have the highest effect is pressure of water penetration since the application of excessive pressure causes the hydraulic fracture to occur in the rock mass, and on the other hand, it must not be so small that prevents from seeing mechanical weaknesses and the rate of permeability. Mathematical modeling is used for the first time in this study to determine the optimum pressure. Thus, the joints that exist in the rock mass are simulated using cylindrical shell model. The joint surroundings are also modeled through Pasternak environment. To obtain equations governing the joints and the surroundings, energy method is used accompanied by Hamilton principle and an analytical solution method is used to obtain the maximum pressure. In order to validate the modeling, the pressure values obtained by the model were used in the sites of Seymareh and Aghbolagh dams and the relative error rates were measured considering the differences between calculated and actual pressures. Modeling in the sections of Seymareh dam showed 4.75, 3.93, 4.8 percent error rates and in the sections of Aghbolagh dam it rendered the values of 22.43, 5.22, 2.6 percent. The results indicate that this modeling can be used to estimate the amount of pressure for hydraulic fracture in water pressure test, to predict it and to prevent it.

• Journal of Environmental Impact Assessment
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• v.6 no.2
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• pp.81-92
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• 1997

This paper presents the results from the comparison analysis and evaluation between the air pollutant dispersion modeling results and the observation data in the area within a 10 km radius from the Boryong thermal power plants. The observation data used in this study were the air pollutant concentrations which had been continuously measured from 8 locations around the Boryong power plants by TMS(tele-monitoring system) for 3 months from September to November, 1996. The short-term and long-term predictions were carried out using ISC3 model and LPDM(Lagrangian Panicle Dispersion Model). The results of ISC3 modeling in a short-term showed highly as 0.7 in a correlation coefficient, but in a long-term showed just 0.54. On the other hand, LPDM showed 0.78 in a correlation coefficient for a long-term, but in a short-term showed highly value than the observation concentrations.

• Journal of Computational Design and Engineering
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• v.1 no.1
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• pp.1-12
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• 2014

In this paper, we propose a new method of reconstructing the hand models for individuals, which include the link structure models, the homologous skin surface models and the homologous tetrahedral mesh models in a reference posture. As for the link structure model, the local coordinate system related to each link consists of the joint rotation center and the axes of joint rotation, which can be estimated based on the trajectories of optimal markers on the relative skin surface region of the subject obtained from the motion capture system. The skin surface model is defined as a three-dimensional triangular mesh, obtained by deforming a template mesh so as to fit the landmark vertices to the relative marker positions obtained motion capture system. In this process, anatomical dimensions for the subject, manually measured by a caliper, are also used as the deformation constraints.

• Journal of the HCI Society of Korea
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• v.2 no.2
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• pp.19-26
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• 2007

This paper presents an augmented reality based modeling system that can provide pottery design experiences to the user. Augmented reality offers natural 3D interaction, a tangible interface, and integration into the real environment. In addition, six modeling techniques that mimics the hand movements in real world deformation process and an occlusion based interaction technique is provided for pottery modeling. The developed interface facilitates fast and intuitive pottery design. The AR pottery system can be used for pottery prototyping/design and educational purposes.