• Asia pacific journal of information systems
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• v.28 no.2
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• pp.75-92
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• 2018

Conceptual modeling is well suited as a subject that constitutes the "core" of the Information Systems (IS) discipline and has grown in response to IS development. Several modeling grammars and methods have been studied extensively in the IS discipline. Previous studies, however, present deficiencies in research methods and even put forward contradictory results about the ternary relationship in conceptual modeling. For instance, some studies contend that the semantics of a binary relationship are better for novices, but others argue that a ternary relationship is better than three binary relationships when the association among three entity types clearly exists. The objective of this research is to acquire complete and accurate understanding of the ternary relationship, specifically to understand practitioners' modeling performance when utilizing either a ternary or binary relationship. To the best of our knowledge, no previous work clearly compares real-world modeler performance differences between binary and ternary representations. By investigating practitioners' understanding of ternary relationship and identifying practitioners' cognition, this research can broaden the perspective on conceptual modeling.

• Journal of the Geological Society of Korea
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• v.54 no.6
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• pp.641-656
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• 2018

Although an amount of hydrocarbon has been discovered in the West Korea Bay Basin (WKBB), located in the North Korean offshore area, geophysical investigations associated with these hydrocarbon reservoirs are not permitted because of the current geopolitical situation. Interpretation of satellite derived potential field data can be alternatively used to image three-dimensional (3D) density distribution in the sedimentary basin associated with hydrocarbon deposits. We interpreted the TRIDENT satellite-derived gravity field data to provide detailed insights into the spatial distribution of sedimentary density structures in the WKBB. We used 3D forward density modeling for the interpretation that incorporated constraints from existing geological and geophysical information. The gravity data interpretation and 3D forward modeling showed that there are two modeled areas in the central subbasin that are characterized by very low density structures, with a maximum density of about $2,000kg/m^3$, indicating some type of hydrocarbon reservoir. One of the anticipated hydrocarbon reservoirs is located in the southern part of the central subbasin with a volume of about $250km^3$ at a depth of about 3,000 m in the Cretaceous/Jurassic layer. The other hydrocarbon reservoir should exist in the northern part of the central subbasin, with an average volume of about $300km^3$ at a depth of about 2,500 m. A comparison between the TRIDENT derived gravity field and the ship-based gravity field measured in 1980s shows us that our results are highly reliable and there is a very high probability to detect another low-density layer existings in the northwestern part of the central subbasin.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.12
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• pp.19-29
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• 1997

This paper presents stable kinematic modeling and path planning and path tracking algorithms for the poisition control of 4-wheeled 2-d.o.f(degree of freedom) mobile robot. We drived the actuated inverse and sensed forward solution for the calculation of actuator velocity and robot velocities. the deal-reckoning algorithm is introduced to calculate the position of WMR in real time. The gaussian functions are applied to control and to design the smooth orientation angle of WMR and the path planning algorithm for obstacle avoidance is prosed. We composed feedback control system to compensate for error because of uncertainty kinematic modeling and measurement noise. The simulation resutls show that the proposed kinematkc modeling and path planning and feedback control algorithms are useful.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.883-889
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• 2005

Micro robots have been developed for many applications: medical, industrial, military, and so on. A small mobile robot was built and it has three legs made of bimorph piezoelectric actuators. It proceeds by vibrating the rear leg and it rotates by vibrating one of the front legs. The locomotion of the robot is described by relative position of mass center and the friction between the legs and the floor. This paper describes the principles of locomotion and modeling of the robot Modeling was simulated to investigate the dynamics of its mobility. The simulation results verified the modeling by showing similar movement of the robot as measured. It remained, however, several problems through experiments such as crooked direction of forward movement and proceeding speed.

• Smart Structures and Systems
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• v.15 no.4
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• pp.1103-1120
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• 2015

A self-sensing magnetorheological (MR) damper with embedded piezoelectric force sensor has recently been devised to facilitate real-time close-looped control of structural vibration in a simple and reliable manner. The development and characterization of the self-sensing MR damper are presented based on experimental work, which demonstrates its reliable force sensing and controllable damping capabilities. With the use of experimental data acquired under harmonic loading, a nonparametric dynamic model is formulated to portray the nonlinear behaviors of the self-sensing MR damper based on NARX modeling and neural network techniques. The Bayesian regularization is adopted in the network training procedure to eschew overfitting problem and enhance generalization. Verification results indicate that the developed NARX network model accurately describes the forward dynamics of the self-sensing MR damper and has superior prediction performance and generalization capability over a Bouc-Wen parametric model.

• Geomechanics and Engineering
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• v.1 no.4
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• pp.307-321
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• 2009

The paper employs a feed forward neural network with back-propagation algorithm for modeling time dependent swell in clays containing carbonate in the presence of sulfuric acid. The oedometer swell percent is estimated at a nominal surcharge pressure of 6.25 kPa to develop 612 data sets for modeling. The input parameters used in the network include time, sulfuric acid concentration, carbonate percentage, and liquid limit. Among the total data sets, 280 (46%) were assigned to training, 175 (29%) for testing and the remaining 157 data sets (25%) were relegated to cross validation. The network was programmed to process this information and predict the percent swell at any time, knowing the variable involved. The study demonstrates that it is possible to develop a general BPNN model that can predict time dependent swell with relatively high accuracy with observed data ($R^2$=0.9986). The obtained results are also compared with generated non-linear regression model.

• Journal of the Korea Society for Simulation
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• v.11 no.1
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• pp.71-82
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• 2002

One of the most important things in the research for MIN-based switch operation the management scheme of network cycle. In the traditional MIN, when the receving buffer module is empty, the sell has to move forward the front-most buffer position by the characteristic of the conventional FIFO queue. However, most of buffer modules are almost always full for practical amount of input loads. The long network cycle of the traditional scheme is thus a substantial waste of bandwidth. In this paper, we propose the modeling method for the input and multi-buffered MIN with unit step buffering scheme, In spite of simplicity, simulation results show that the proposed model is very accurate comparing to previous modeling approaches in terms of throughput and the trend of delay.

• The Journal of Korea Robotics Society
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• v.15 no.4
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• pp.301-308
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• 2020

In this paper, we deal with the static modeling of a continuum robot that can perform surgical interventions. The proposed continuum robot is made of stainless steel wires and a multi lumen flexible tube using a thermoplastic elastomer. This continuum robot could be most severely deformed in physical contact with narrow external environments, when a lateral external force acts at the distal tip of the continuum robot. In order to predict the shape and displacement under the lateral external force loading, the forward kinematics, the statics modeling, the force-moment equilibrium equation, and the virtual work-energy method of the continuum robot are described. The deflection displacements were calculated using the virtual work-energy method, and the results were compared with the displacement obtained by the conventional cantilever beam theories. In conclusion, the proposed static modeling and the virtual work-energy method can be used in arrhythmia procedure simulations.

• Geomechanics and Engineering
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• v.33 no.6
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• pp.567-581
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• 2023

The prediction and achievement of a proper rock fragmentation size is the main challenge of blasting operations in surface mines. This is because an optimum size distribution can optimize the overall mine/plant economics. To this end, this study attempts to develop four improved artificial intelligence models to predict rock fragmentation through cascaded forward neural network (CFNN) and radial basis function neural network (RBFNN) models. In this regards, the CFNN was trained by the Levenberg-Marquardt algorithm (LMA) and Conjugate gradient backpropagation (CGP). Further, the RBFNN was optimized by the Dragonfly Algorithm (DA) and teaching-learning-based optimization (TLBO). For developing the models, the database required was collected from the Midouk copper mine, Iran. After modeling, the statistical functions were computed to check the accuracy of the models, and the root mean square errors (RMSEs) of CFNN-LMA, CFNN-CGP, RBFNN-DA, and RBFNN-TLBO were obtained as 1.0656, 1.9698, 2.2235, and 1.6216, respectively. Accordingly, CFNN-LMA, with the lowest RMSE, was determined as the model with the best prediction results among the four examined in this study.

• Journal of Broadcast Engineering
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• v.19 no.2
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• pp.268-271
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• 2014

Conventional forward error correction (FEC) code rate decision schemes using analytical source coding distortion model and channel-induced distortion model are usually complex, and require the typical process of model parameter training which involves potentially high computational complexity and implementation cost. To avoid the complex modeling procedure, we propose a simple but accurate joint source-channel distortion model to estimate channel loss threshold set for optimal FEC code rate decision.