• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.4
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• pp.226-234
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• 2004

A rapid Prototyping system that laser-cuts and laminates thick layers can fabricate 3D objects promptly with a variety of materials. Building such a system must consider the surface distortions due to both vertical-cut layers and triangular surfaces. We developed a tangential layer-cutting algorithm by rearranging tangential lines such that they reconstruct 3D surfaces more closely and also constitute smoother laser trajectories. An energy function that reflects the surface-closeness with the tangential lines was formulated and then the energy was minimized by a gradient descent method. Since this simple method tends to cause many local minima for complex 3D objects, we tried to solve this problem by adding a simulated annealing process to the proposed method. To view and manipulate 3D objects, we also implemented a 3D visual environment. Under this environment, experiments on various 3D objects showed that our algorithm effectively approximates 3D surfaces and makes laser-trajectory feasibly smooth.

• Journal of Advanced Information Technology and Convergence
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• v.9 no.1
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• pp.89-102
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• 2019

Collagen can be used in building artificial skin replacements for treatment of burns and towards the reconstruction of bone as well as researching cell behavior and cellular interaction. The strength of collagen in connective tissue rests on the characteristics of collagen fibers. 3D confocal imaging of collagen fibers enables the characterization of their spatial distribution as related to their function. However, the image stacks acquired with confocal laser-scanning microscope does not clearly show the collagen architecture in 3D. Therefore, we developed a new method to reconstruct, visualize and characterize collagen fibers from fluorescence confocal images. First, we exploit the tensor voting framework to extract sparse reliable information about collagen structure in a 3D image and therefore denoise and filter the acquired image stack. We then propose to segment the collagen fibers by defining an energy term based on the Hessian matrix. This energy term is minimized by a min cut-max flow algorithm that allows adaptive regularization. We demonstrate the efficacy of our methods by visualizing reconstructed collagen from specific 3D image stack.

• Structural Engineering and Mechanics
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• v.52 no.1
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• pp.115-136
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• 2014

In this study, an extended Kantorovich method, employing multi-term displacement functions, is applied to analyze the vibration problem of symmetrically laminated plates with arbitrary boundary conditions. The vibration behaviors of laminated plates are determined based on the variational principle of total energy minimization and the iterative Kantorovich method. The out-of-plane displacement is represented in the form of a series of a sum of products of functions in x and y directions. With a known function in the x or y directions, the formulation for the variation of total potential energy is transformed to a set of governing equations and a set of boundary conditions. The equations and boundary conditions are then numerically solved for the natural frequency and vibration mode shape. The solutions are verified with available solutions from the literature and solutions from the Ritz and finite element analysis. In most cases, the natural frequencies compare very well with the reference solutions. The vibration mode shapes are also very well modeled using the multi-term assumed displacement function in the terms of a power series. With the method used in this study, it is possible to solve the angle-ply plate problem, where the Kantorovich method with single-term displacement function is ineffective.

• Journal of Institute of Control, Robotics and Systems
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• v.1 no.2
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• pp.112-118
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• 1995

In designing assembly lines, it is required that the lines should not only meet the demand of the product, but also minimize the assembly cost associated with the line. For such a purpose, numerous research efforts have been made on either the assembly sequence generation or the assembly line balancing. However, the works dealing with both the research problems have been seldom reported in literature. When assembly sequences are generated without consideration of line balancing, additional cost may be incurred, because the sequences may not guarantee the minimum number of workstations. Therefore, it is essential to consider line balancing in the generation of cost-effective assembly sequences. To incorporate the two research problems into one, this paper treats a single-model and deterministic (SMD) assembly line balancing (ALB) problem, and proposes a new method for generating line-balanced robotic assembly sequences by using a simulated annealing. In this method, an energy function is derived in consideration of the satisfaction of assembly constraints, and the minimization of both the assembly cost and the idle time. Then, the energy function is iteratively minimized and occasionally perturbed by the simulated annealing. When no further change in energy occurs, an assembly sequence with consideration of line balancing is finally found. To show the effectiveness of the proposed scheme, a case study for an electrical relay is presented.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.3
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• pp.210-217
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• 2003

We introduced a scheme for finding an optimal data association matrix that represents the relationships between the measurements and tracks in multi-target tracking (MIT). We considered the relationships between targets and measurements as Markov Random Field and assumed a priori of the associations as a Gibbs distribution. Based on these assumptions, it was possible to reduce the MAP estimate of the association matrix to the energy minimization problem. After then, we defined an energy function over the measurement space that may incorporate most of the important natural constraints. To find the minimizer of the energy function, we derived a new equation in closed form. By introducing Lagrange multiplier, we derived a compact equation for parameters updating. In this manner, a pair of equations that consist of tracking and parameters updating can track the targets adaptively in a very variable environments. For measurements and targets, this algorithm needs only multiplications for each radar scan. Through the experiments, we analyzed and compared this algorithm with other representative algorithm. The result shows that the proposed method is stable, robust, fast enough for real time computation, as well as more accurate than other method.

• Structural Engineering and Mechanics
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• v.70 no.3
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• pp.289-301
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• 2019

Hysteretic energy is defined as energy dissipated through inelastic deformations during a ground motion by the system. It includes frequency content and duration of ground motion as two remarkable parameters, while these characteristics are not seen in displacement spectrum. Since maximum displacement individually cannot be the appropriate criterion for damage assessment, hysteretic energy has been evaluated in this research as a more comprehensive seismic demand parameter. An innovative methodology has been proposed to establish a new equivalent linear model to estimate hysteretic energy spectrum for bilinear SDOF models under two different sets of earthquake excitations. Error minimization has been defined in the space of equivalent linearization concept, which resulted in equivalent damping and equivalent period as representative parameters of the linear model. Nonlinear regression analysis was carried out for predicting these equivalent parameter as a function of ductility. The results also indicate differences between seismic demand characteristics of far-field and near-field ground motions, which are not identified by most of previous equations presented for predicting seismic energy. The main advantage of the proposed model is its independency on parameters related to earthquake and response characteristics, which has led to more efficiency as well as simplicity. The capability of providing a practical energy based seismic performance evaluation is another outstanding feature of the proposed model.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.11
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• pp.39-49
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• 2011

Smart Grid has two main objectives on both supply and demand aspects which are to distribute the renewable energy sources on supply side and to develop realtime price responses on demand side. Renewable energy does not consume fossil fuels, therefore it improves the eco-friendliness and saves the cost of power system operation at the same time. Demand response increases the flexibility of the power system by mitigating the fluctuation from renewable energies, and reduces the capacity investment cost by shedding the peak load to off-peak periods. Currently Smart Grid technologies mainly focus on energy monitoring and display services but it has been proved that enabling technologies can induce the higher demand responses through many pilot projects in USA. On this context, this paper provides a price responsive algorithm for HEMS (home energy management system) on the real time pricing environment. This paper identifies the demand response as a core function of HEMS and classifies the demand into 3 categories of fixed, transferable, and realtime responsive loads which are coordinated and operated for the utility maximization or cost minimization with the optimal usage combination of three kinds of demand.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.6 no.8
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• pp.1146-1152
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• 2002

This paper proposed a scheme for finding an optimal adaptive data association for multi-target between measurements and tracks. First, we assume the relationships between measurements as Mrkov Random Field. Also assumed a priori of the associations as a Gibbs distribution. Based on these assumptions, it was possible to reduce the MAP estimate of the association matrix to the energy minimization problem. After then, we defined an energy function over the measurement space, that may incorporate most of the important natural constraints. Through the experiments, we analyzed and compared this algorithm with other representative algorithms. The result is that it is stable, robust, fast enough for real timecomputation, as well as more accurate than other methods.

• Journal of the Institute of Convergence Signal Processing
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• v.1 no.2
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• pp.138-144
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• 2000

This paper introduced a scheme for finding an optimal association matrix that represents the relationships between the measurements and tracks in multi-target tracking of Radar system. We considered the relationships between targets and measurements as MRF and assumed a priori of the associations as a Gibbs distribution. Based on these assumptions, it was possible to reduce the MAP estimate of the association matrix to the energy minimization problem. After then, we defined an energy function over the measurement space, that may incorporate most of the important natural constraints.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.1
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• pp.213-221
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• 1996

An assembly sequence is considered to be optimal when is minimizes assembly cost while satisfying assembly constraints. To derive such an optimal sequence for robotic assembly, this paper proposes a method using a simulated annealing algorithm. In this method, an energy funciton is derived inconsideration of both the assembly constraints and the assembly cost. The energy function thus derived is iteratively minimized until no further change in energy occurs. During the minimization, the energy is occationally perturbed probabilistically in order to escape from local minima. The minimized energy yields an optimal assembly sequence. To show the effectiveness of the proposed method, case studies are presented for industrial products such as an electrical relay and an automobil alternator. The performance is analyzed by comparing the results with those of a neural network-based method, based upon the optimal solutions of an expert system.