• International Journal of Control, Automation, and Systems
• /
• v.1 no.1
• /
• pp.134-141
• /
• 2003

A major research issue associated with service robots is the creation of an environment recognition system for mobile robot navigation that is robust and efficient on various environment situations. In recent years, intelligent autonomous mobile robots have received much attention as the types of service robots for serving people and industrial robots for replacing human. To help people, robots must be able to sense and recognize three dimensional space where they live or work. In this paper, we propose a three dimensional environmental modeling method based on an edge enhancement technique using a planar fitting method and a neural network technique called "Growing Neural Gas Network." Input data pre-processing provides probabilistic density to the input data of the neural network, and the neural network generates a graphical structure that reflects the topology of the input space. Using these methods, robot's surroundings are autonomously clustered into isolated objects and modeled as polygon patches with the user-selected resolution. Through a series of simulations and experiments, the proposed method is tested to recognize the environments surrounding the robot. From the experimental results, the usefulness and robustness of the proposed method are investigated and discussed in detail.in detail.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
• /
• v.12 no.5
• /
• pp.777-786
• /
• 2001

In this paper, as one of countermeasure techniques for a frequency selective fading, a digital slope equalizer(DSE) for 64-QAM digital radio relay system is analyzed in terms of principle, channel modeling, and digital implementation. Also computer simulations have been performed for DSE with a complex 13-tap adaptive time domain equalizer chip. It is shown that about 4.5 dB improvement in system signature can be obtained at the channel edge, and a variety of simulated results are reviewed in view of DSE modeling limit, operating frequency, control coefficient, signal constellation, and system signature. Finally, the functions of DSE chip confirmed up to 61 MHz clock operation are illustrated.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
• /
• 2004.10a
• /
• pp.382-387
• /
• 2004

As the increasing needs in the industrial filed, many studies for the 3D CAD system are carried out. There are two types of 3D CAD system. One is manifold modeler, the other is non-manifold modeler. In the manifold modeler only 3D objects can be modeled. In the non-manifold modeler 3D, 2D, 1D, and 0D objects can be modeled in a unified data structure. Recently there are many studies on the non-manifold modeler. Most of them are focused on finding unknown topological entities and representing all kinds of topological entities found. In this paper, efficient data structure is selected. The boundary information on a face and an edge is included in this data structure. The boundary information on a vertex is excluded considering the frequency of usage. Because the disk cycle information is not required in most case of modeling. It is compact. It stores essential non-manifold information such as loop cycle and radial cycle. A suitable Euler-Poincare equation is studied and selected. Using the efficient data structure and the selected Euler-Poincare equation, 18 basic Euler operators are implemented. Several 3D models are created using the implemented modeler. A non-manifold modeling can be carried out using the implemented 3D CAD system. The results of this paper could be used in the further studies such as an implementation of Boolean operators, and a translation of 2D CAD drawings to 3D models.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.18 no.4
• /
• pp.530-536
• /
• 2008

Localization is one of the fundamental problems in wireless sensor networks (WSNs) that forms the basis for many location-aware applications. Localization in WSNs is to determine the position of node based on the known positions of several nodes. Most of previous localization method use triangulation or multilateration based on the angle of arrival (AOA) or distance measurements. In this paper, we propose an enhanced centroid localization method based on edge weights of adjacent nodes using fuzzy modeling and genetic algorithm when node connectivities are known. The simulation results shows that our proposed centroid method is more accurate than the simple centroid method using connectivity only.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
• /
• v.21 no.4
• /
• pp.427-438
• /
• 2023

Thermodynamic sorption modeling can enhance confidence in assessing and demonstrating the radionuclide sorption phenomena onto various mineral adsorbents. In this work, Ca-montmorillonite was successfully purified from Bentonil-WRK bentonite by performing the sequential physical and chemical treatments, and its geochemical properties were characterized using X-ray diffraction, Brunauer-Emmett-Teller analysis, cesium-saturation method, and controlled continuous acid-base titration. Further, batch experiments were conducted to evaluate the adsorption properties of Cs(I) and Sr(II) onto the homoionic Ca-montmorillonite under ambient conditions, and the diffuse double layer model-based inverse analysis of sorption data was performed to establish the relevant surface reaction models and obtain corresponding thermodynamic constants. Two types of surface reactions were identified as responsible for the sorption of Cs(I) and Sr(II) onto Ca-montmorillonite: cation exchange at interlayer site and complexation with edge silanol functionality. The thermodynamic sorption modeling provides acceptable representations of the experimental data, and the species distributions calculated using the resulting reaction constants accounts for the predominance of cation exchange mechanism of Cs(I) and Sr(II) under the ambient aqueous conditions. The surface complexation of cationic fission products with silanol group slightly facilitates their sorption at pH > 8.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.41 no.5
• /
• pp.353-359
• /
• 2017

The classical computer numerical control (CNC) machine is widely used for mold making in various industries. However, while improving the process, it has a negative effect on production quality and worker safety. As a result, the complaints of workers have increased and production quality has decreased. Therefore, we found optimizing cutting conditions to mold industrials for cutting conditions commonly used. However, the problem is the insert tool geometric modeling. In this study, the modeling of an insert tool was performed using the Solidworks program. The insert tool model was imported into the analysis application AdvantEdge, which predicted cutting forces, tool stress, and temperature.

• Geophysics and Geophysical Exploration
• /
• v.10 no.4
• /
• pp.275-284
• /
• 2007

For precise interpretation of magnetotelluric (MT) data distorted by irregular surface terrain, topography effects are investigated by computing apparent resistivities, phases, tippers and induction vectors for a three-dimensional (3D) hill-and-valley model. To compute MT responses for the 3D surface topography model, we use a 3D MT modeling algorithm based on an edge finite-element method which is free from vector parasites. Distortions on the apparent resistivity and phase are mainly caused by distorted currents that flow along surface topography. The distribution of tipper amplitudes over both hill and valley are the same, while the tipper points toward the center of hill and the base of the valley. The real part of induction vector also points in the same direction as that of tipper, while the imaginary part in the opposite direction.

• Journal of Intelligence and Information Systems
• /
• v.15 no.2
• /
• pp.1-13
• /
• 2009

Scene classification and concept-based procedures have been the great interest for image categorization applications for large database. Knowing the category to which scene belongs, we can filter out uninterested images when we try to search a specific scene category such as beach, mountain, forest and field from database. In this paper, we propose an adaptive segmentation method for real-world natural scene classification based on a semantic modeling. Semantic modeling stands for the classification of sub-regions into semantic concepts such as grass, water and sky. Our adaptive segmentation method utilizes the edge detection to split an image into sub-regions. Frequency of occurrences of these semantic concepts represents the information of the image and classifies it to the scene categories. K-Nearest Neighbor (k-NN) algorithm is also applied as a classifier. The empirical results demonstrate that the proposed adaptive segmentation method outperforms the Vogel and Schiele's method in terms of accuracy.

• Geophysics and Geophysical Exploration
• /
• v.14 no.2
• /
• pp.164-175
• /
• 2011

Using natural electromagnetic (EM) fields at low frequencies, magnetotelluric (MT) surveys can investigate conductivity structures of the deep subsurface and thus are used to explore geothermal energy resources and investigate proper sites for not only geological $CO_2$ sequestration but also enhanced geothermal system (EGS). Moreover, marine MT data can be used for better interpretation of marine controlled-source EM data. In the interpretation of MT data, MT modeling schemes are important. This study improves a three dimensional (3D) MT modeling algorithm which uses edge finite elements. The algorithm computes magnetic fields by solving an integral form of Faraday's law of induction based on a finite difference (FD) strategy. However, the FD strategy limits the algorithm in computing vertical magnetic fields for a topographic model. The improved algorithm solves the differential form of Faraday's law of induction by making derivatives of electric fields, which are represented as a sum of basis functions multiplied by corresponding weightings. In numerical tests, vertical magnetic fields for topographic models using the improved algorithm overcome the limitation of the old algorithm. This study recomputes induction vectors and tippers for a 3D hill and valley model which were used for computation of the responses using the old algorithm.

• Journal of KIISE:Computer Systems and Theory
• /
• v.32 no.10
• /
• pp.520-529
• /
• 2005

A feature-based 3D modeling algorithm is presented in this paper. Since conventional methods use depth-based techniques, they need much time for the image matching to extract depth information. Even feature-based methods have less computation load than that of depth-based ones, the calculation of modeling error about whole pixels within a triangle is needed in feature-based algorithms. It also increase the computation time. Therefore, the proposed algorithm consists of three phases, which are an initial 3D model generation, model evaluation, and model refinement phases, in order to acquire an efficient 3D model. Intensity gradients and incremental Delaunay triangulation are used in the Initial model generation. In this phase, a morphological edge operator is adopted for a fast edge filtering, and the incremental Delaunay triangulation is modified to decrease the computation time by avoiding the calculation errors of whole pixels and selecting a vertex at the near of the centroid within the previous triangle. After the model generation, sparse vertices are matched, then the faces are evaluated with the size, approximation error, and disparity fluctuation of the face in evaluation stage. Thereafter, the faces which have a large error are selectively refined into smaller faces. Experimental results showed that the proposed algorithm could acquire an adaptive model with less modeling errors for both smooth and abrupt areas and could remarkably reduce the model acquisition time.