• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1995.10a
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• pp.60-63
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• 1995

The behavior of the work materials in the chip-tool interface in extremely high strain rates and temperatures is more that of viscous liquids than that of normal solid metals. In these circumstances the principles of fluid mechanics can be invoked to describe the metal flow in the neighborhood of the cutting edge. In the present paper an Eulerian finite element model is presented that simulates metal flow in the vicinity of the cutting edge when machining a low carbon steel with carbide cutting tool. The work material is assumed to obey visco-plastic (Bingham solid) constitutive law and Von Mises criterion. Heat generation is included in the model, assuming adiabatic conditions within each element. the mechanical and thermal properties of the work material are accepted to vary with the temperature. The model is based on the virtual work-stream function formulation, emphasis is given on analyzing the formation of the stagnant metal zone ahead of the cutting edge. The model predicts flow field characteristics such as material velocity effective stress and strain-rate distributions as well as built-up layer configuration

• Journal of KIISE:Software and Applications
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• v.34 no.3
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• pp.246-254
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• 2007

Local search algorithms start from a certain candidate solution and probe its neighborhood to find ones with improved quality. This paper proposes a method of probabilistically filtering out bad-looking neighbors based on a simple low-cost preliminary evaluation heuristics. The probabilistic filtering enables us to save time wasted on fully evaluating those solutions that will eventually be trashed, and thus improves the search efficiency by allowing us to spend more time on examining better looking solutions. Experiments with two large-scaled real-world problems, which are a traffic signal control problem in traffic network and a load balancing problem in production scheduling, have shown that the proposed method finds better quality solutions, given the same amount of CPU time.

• The Journal of the Korea Contents Association
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• v.17 no.3
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• pp.42-52
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• 2017

Panorama image is a single image obtained by combining images taken at several viewpoints through matching of corresponding points. Existing panoramic image generation methods that find the corresponding points are extracting local invariant feature points in each image to create descriptors and using descriptor matching algorithm. In the case of video sequence, frames may be a lot, so therefore it may costs significant amount of time to generate a panoramic image by the existing method and it may has done unnecessary calculations. In this paper, we propose a method to quickly create a single panoramic image from a video sequence. By assuming that there is no significant changes between frames of the video such as in locally, we use the FAST algorithm that has good repeatability and high-speed calculation to extract feature points and the Lucas-Kanade algorithm as each feature point to track for find the corresponding points in surrounding neighborhood instead of existing descriptor matching algorithms. When homographies are calculated for all images, homography is changed around the center image of video sequence to warp images and obtain a planar panoramic image. Finally, the spherical panoramic image is obtained by performing inverse transformation of the spherical coordinate system. The proposed method was confirmed through the experiments generating panorama image efficiently and more faster than the existing methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.930-939
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• 2021

In recent years, the use of broadband bandwidth and redundant links for stable transmission in networks has resulted in excessive energy consumption and reduced transmission efficiency. In this paper, we propose an optimization algorithm that reduces the number of transmission links and minimizes transmission energy by removing redundant traffic in networks where traffic redundancy is allowed. The optimization algorithm proposed in this paper uses the meta-heuristic method using Tabu search algorithm. The proposed optimization algorithm minimizes transmission energy by designing a neighborhood generation method that efficiently routes overlapping traffic. The performance evaluation of the proposed optimization algorithm was performed in terms of the number of links used to transmit all traffic generated in the network and the transmission energy consumed. From the performance evaluation results, it was confirmed that the proposed algorithm is superior to other algorithms previously proposed.

• Journal of the HCI Society of Korea
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• v.1 no.1
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• pp.53-61
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• 2006

In this paper, we propose a novel method for 3D reconstruction of an indoor scene using a multi-view camera. Until now, numerous disparity estimation algorithms have been developed with their own pros and cons. Thus, we may be given various sorts of depth images. In this paper, we deal with the generation of a 3D surface using several 3D point clouds acquired from a generic multi-view camera. Firstly, a 3D point cloud is estimated based on spatio-temporal property of several 3D point clouds. Secondly, the evaluated 3D point clouds, acquired from two viewpoints, are projected onto the same image plane to find correspondences, and registration is conducted through minimizing errors. Finally, a surface is created by fine-tuning 3D coordinates of point clouds, acquired from several viewpoints. The proposed method reduces the computational complexity by searching for corresponding points in 2D image plane, and is carried out effectively even if the precision of 3D point cloud is relatively low by exploiting the correlation with the neighborhood. Furthermore, it is possible to reconstruct an indoor environment by depth and color images on several position by using the multi-view camera. The reconstructed model can be adopted for interaction with as well as navigation in a virtual environment, and Mediated Reality (MR) applications.

• Journal of the Korea Computer Industry Society
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• v.7 no.5
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• pp.455-466
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• 2006

In this paper, 3D objects is created from the real scene that is used by an active sensor, which gets depth and RGB information. To get the depth information, this paper uses the $Zcam^{TM}$ camera which has built-in an active sensor module. <중략> Thirdly, calibrate the detailed parameters and create 3D mesh model from the depth information, then connect the neighborhood points for the perfect 3D mesh model. Finally, the value of color image data is applied to the mesh model, then carries out mapping processing to create 3D object. Experimentally, it has shown that creating 3D objects using the data from the camera with active sensors is possible. Also, this method is easier and more useful than the using 3D range scanner.

• Wind and Structures
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• v.24 no.1
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• pp.1-24
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• 2017

Wind environment in urban residential areas is an important index to consider when evaluating the living environment. However, due to the complexity of the flow field in residential areas, it is difficult to specify the correct inflow boundary conditions in the large eddy simulation (LES). In this paper, the weighted amplitude wave superposition (WAWS) is adopted to simulate the fluctuating velocity data, which satisfies the desired target wind field. The fluctuating velocity data are given to the inlet boundary of the LES by developing an UDF script, which is implemented into the FLUENT. Then, two numerical models - the empty numerical wind tunnel model and the numerical wind tunnel model with spires and roughness elements are established based on the wind tunnel experiment to verify the present method. Finally, the turbulence generation approach presented in this paper is used to carry out a numerical simulation on the wind environment in an urban residential area in Lisbon. The computational results are compared with the wind tunnel experimental data, showing that the numerical results in the LES have a good agreement with the experimental results, and the simulated flow field with the inlet fluctuations can generate a reasonable turbulent wind field. It also shows that strong wind velocities and turbulent kinetic energy occur at the passageways, which may affect the comfort of people in the residential neighborhood, and the small wind velocities and vortexes appear at the leeward corners of buildings, which may affect the spreading of the pollutants.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1477-1486
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• 2012

In this paper, we propose Multi-view CGH Making System using method of generation of virtual view-point depth image. We acquire reliable depth image using TOF depth camera. We extract parameters of reference-view cameras. Once the position of camera of virtual view-point is defined, select optimal reference-view cameras considering position of it and distance between it and virtual view-point camera. Setting a reference-view camera whose position is reverse of primary reference-view camera as sub reference-view, we generate depth image of virtual view-point. And we compensate occlusion boundaries of virtual view-point depth image using depth image of sub reference-view. In this step, remaining hole boundaries are compensated with minimum values of neighborhood. And then, we generate final depth image of virtual view-point. Finally, using result of depth image from these steps, we generate CGH. The experimental results show that the proposed algorithm performs much better than conventional algorithms.

• Journal of Biosystems Engineering
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• v.27 no.5
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• pp.433-450
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• 2002

The daily food intake for dairy cows has to be effectively controlled to breed a sound group of cows as well as to enhance the productivity of the cows. But, feed stuffs are fed in the common bulk for a group of cows in most cases despite that the individual food intake has to be varied. To obtain the feed for each cow, both the nutrient requirements and the nutrient composition of fred have to be provided in advance, which are based on the status of cows such as weigh marginal weight amount of milk, fat concentration in milk, growth and milking stages, and rough feed ratio, etc. Then, the mixed ration fur diet would be computed by the nutrient requirements constraints. However, when TMR (Total Mixed Ration) is conventionally supplied for a group of cows, it is almost impossible to get an optimal feed mixed ration meeting the nutrient requirements of each individual cow since the constraints are usually conflicting and over-constrained although they are linear. Hence, addressed in this paper is a simulated annealing (SA) technique to find the food intake for dairy cows, considering the characteristics of individual or grouped cows. Appropriate parameters fur the successful working of SA are determined through preliminary experiments. The parameters include initial temperature, epoch length. cooling scheduling, and stopping criteria. In addition, a neighborhood solution generation method for the effective improvement of solutions is presented. Experimental results show that the final solution for the mixture of feed fits the rough feed ratio and some other nutrient requirements such as rough fiber, acid detergent fiber, and neutral detergent fiber, with 100 percent, while fulfilling net energy for lactating, metabolic energy, total digestible nutrients, crude protein, and undegraded intake protein within average five percent.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.2
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• pp.79-86
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• 2020

To make a satisfactory decision regarding project scheduling, a trade-off between the resource-related cost and project duration must be considered. A beneficial method for decision makers is to provide a number of alternative schedules of diverse project duration with minimum resource cost. In view of optimization, the alternative schedules are Pareto sets under multi-objective of project duration and resource cost. Assuming that resource cost is closely related to resource leveling, a heuristic algorithm for resource capacity reduction (HRCR) is developed in this study in order to generate the Pareto sets efficiently. The heuristic is based on the fact that resource leveling can be improved by systematically reducing the resource capacity. Once the reduced resource capacity is given, a schedule with minimum project duration can be obtained by solving a resource-constrained project scheduling problem. In HRCR, VNS (Variable Neighborhood Search) is implemented to solve the resource-constrained project scheduling problem. Extensive experiments to evaluate the HRCR performance are accomplished with standard benchmarking data sets, PSPLIB. Considering 5 resource leveling objective functions, it is shown that HRCR outperforms well-known multi-objective optimization algorithm, SPEA2 (Strength Pareto Evolutionary Algorithm-2), in generating dominant Pareto sets. The number of approximate Pareto optimal also can be extended by modifying weight parameter to reduce resource capacity in HRCR.