• Journal of KIISE:Computing Practices and Letters
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• v.7 no.6
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• pp.582-592
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• 2001

Video indexing plays an important role in the applications such as digital video libraries or web VOD which archive large volume of digital videos. Video indexing is usually based on video segmentation. In this paper, we propose a software tool called V2Web Studio which can generate video clips utilizing shot boundary detection algorithm. With the V2Web Studio, the process of clip generation consists of the following four steps: 1) Automatic detection of shot boundaries by parsing the video, 2) Elimination of errors by manually verifying the results of the detection, 3) Building a modeling structure of logical hierarchy using the verified shots, and 4) Generating multiple video clips corresponding to each logically modeled segment. The aforementioned steps are performed by shot detector, shot verifier, video modeler and clip generator in the V2Web Studio respectively.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_2
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• pp.1063-1069
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• 2022

In modern industry, vacuum has grown into an indispensable industrial field. The performance of the vacuum pump in the degasser system among mud treatment system facilities was verified by a numerical analysis method. The degasser system is an equipment for removing the gas contained in the mud, and it is a work process that requires a vacuum. This study analyzed the vacuum pump performance of the degasser used in drilling for resource development of onshore and offshore plants. The vacuum pump used in the degasser system was designed with a discharge rate of 0.099kg/s. The DM(Design Modeler) program of ansys workbench 17.2 was used to modify the model of the vacuum pump used in the degasser system. And for performance analysis, CFX, which is known to be suitable for rotating system analysis, was used. Finally the performance analysis results of the vacuum pump and the prototype performance test results were compared and analyzed.

• ETRI Journal
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• v.44 no.1
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• pp.135-146
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• 2022

The importance of big data analytics has become apparent with the increasing volume of data on the Internet. The amount of data will increase even more with the widespread use of Internet of Things (IoT). One of the most important application areas of the IoT is healthcare. This study introduces new real-time data analytics architecture for an IoT-based smart healthcare system, which consists of a wireless sensor network and a radio-frequency identification technology in a vertical domain. The proposed platform also includes high-performance data analytics tools, such as Kafka, Spark, MongoDB, and NodeJS, in a horizontal domain. To investigate the performance of the system developed, a diagnosis of Wolff-Parkinson-White syndrome by logistic regression is discussed. The results show that the proposed IoT data analytics system can successfully process health data in real-time with an accuracy rate of 95% and it can handle large volumes of data. The developed system also communicates with a riverbed modeler using Transmission Control Protocol (TCP) to model any IoT-enabling technology. Therefore, the proposed architecture can be used as a time-saving experimental environment for any IoT-based system.

• International conference on construction engineering and project management
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• 2011.02a
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• pp.176-181
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• 2011

A role of cost modeler is that of facilitating design process by the systematic application of cost factors so as to maintain sensible and economic relationships between cost, quantity, utility and appearance. These relationships help to achieve the client's requirements within an agreed budget. The purpose of this study is to develop a parametric cost estimating model for the early design stage by using the multi-dimensional system of OLAP (On-line Analytical Processing) based on the case of quantity data related to architectural design features. The parametric cost estimating models have been adopted to support decision making in the early design stage. These models typically use a similar instance or a pattern of historical case. In order to effectively use this type of data model, it is required to set data classification and prediction methods. One of the methods is to find the similar class in line with attribute selection measure in the multi-dimensional data model. Therefore, this research is to analyze the relevance attribute influenced by architectural design features with the subject of case-based quantity data used for the parametric cost estimating model. The relevance attributes can be analyzed by Analytical Characterization. It helps determine what attributes to be included in the OLAP multi-dimension.

• Korean Chemical Engineering Research
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• v.49 no.4
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• pp.423-431
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• 2011

Recentincreasing awareness of the environmental damage caused by the $CO_2$ emission of fossil fuelsstimulated the interest in alternative and renewable sources of energy. Fuel cell is a representative example of hydrogen energy utilization. In this study, Molten Carbonate Fuel Cell system is simulated by using $Aspen^{TM}$. Stack model is consisted of equilibrium reaction equations using $ACM^{TM}$(Aspen Custom Modeler). Balance of process of fuel cell system is developed in Aspen $Plus^{TM}$ and simulated at steady-state. Analysis of performance of the system is carried out by using sensitivity analysis tool with main operating parameters such as current density, S/C ratio, and fuel utilization and recycle ratio.In Aspen $Dynamics^{TM}$, dynamics of MCFC system is simulated with PID control loops. From the simulation, we proposed operation range which generated maximum power and efficiency in MCFC power plant.

• Korean Journal of Remote Sensing
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• v.25 no.5
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• pp.411-421
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• 2009

This study refers to develop a semi-automatic extraction of agricultural land use and vegetation information using high resolution satellite images. Data of IKONOS-2 satellite images (May 25 of 2001, December 25 of 2001, and October 23 of 2003), QuickBird-2 satellite images (May 1 of 2006 and November 17 of 2004) and KOMPSAT-2 satellite image (September 17 of 2007) which resemble with the spatial resolution and spectral characteristics of KOMPSAT-3 were used. The precise agricultural land use classification was tried using ISODATA unsupervised classification technique, and the result was compared with on-screen digitizing land use accompanying with field investigation. For the extraction of crop growth information, three crops of paddy, com and red pepper were selected, and the spectral characteristics were collected during each growing period using ground spectroradiometer. The vegetation indices viz. RVI, NDVI, ARVI, and SAVI for the crops were evaluated. The evaluation process was developed using the ERDAS IMAGINE Spatial Modeler Tool.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2008.04a
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• pp.216-221
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• 2008

Shape design optimization for linear elasticity problem is performed using isogeometric analysis method. In many design optimization problems for real engineering models, initial raw data usually comes from CAD modeler. Then designer should convert this CAD data into finite element mesh data because conventional design optimization tools are generally based on finite element analysis. During this conversion there is some numerical error due to a geometry approximation, which causes accuracy problems in not only response analysis but also design sensitivity analysis. As a remedy of this phenomenon, the isogeometric analysis method is one of the promising approaches of shape design optimization. The main idea of isogeometric analysis is that the basis functions used in analysis is exactly same as ones which represent the geometry, and this geometrically exact model can be used shape sensitivity analysis and design optimization as well. In shape design sensitivity point of view, precise shape sensitivity is very essential for gradient-based optimization. In conventional finite element based optimization, higher order information such as normal vector and curvature term is inaccurate or even missing due to the use of linear interpolation functions. On the other hands, B-spline basis functions have sufficient continuity and their derivatives are smooth enough. Therefore normal vector and curvature terms can be exactly evaluated, which eventually yields precise optimal shapes. In this article, isogeometric analysis method is utilized for the shape design optimization. By virtue of B-spline basis function, an exact geometry can be handled without finite element meshes. Moreover, initial CAD data are used throughout the optimization process, including response analysis, shape sensitivity analysis, design parameterization and shape optimization, without subsequent communication with CAD description.

• The KIPS Transactions:PartB
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• v.12B no.5 s.101
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• pp.567-576
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• 2005

This paper proposes an image-based modeling method which recovers 3D models using projected line segments in multiple images. Using the method, a user obtains accurate 3D model data via several steps of simple manual works. The embedded nonlinear minimization technique in the model parameter estimation stage is based on the distances between the user provided image line segments and the projected line segments of primitives. We define an error using a finite line segment and thus increase accuracy in the model parameter estimation. The error is defined as the sum of differences between the observed image line segments provided by the user and the predicted image line segments which are computed using the current model parameters and camera parameters. The method is robust in a sense that it recovers 3D structures even from partially occluded objects and it does not be seriously affected by small measurement errors in the reconstruction process. This paper also describesexperimental results from real images and difficulties and tricks that are found while implementing the image-based modeler.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.2
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• pp.230-235
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• 2009

This paper describes an automatic finite element mesh generation for finite element analysis of three-dimensional structures. It is consisting of fuzzy knowledge processing, bubble meshing and solid geometry modeler. This novel mesh generation process consists of three subprocesses: (a) definition of geometric model, i.e. analysis model, (b) generation of bubbles, and (c) generation of elements. One of commercial solid modelers is employed for three-dimensional solid structures. Bubble is generated if its distance from existing bubble points is similar to the bubble spacing function at the point. The bubble spacing function is well controlled by the fuzzy knowledge processing. The Delaunay method is introduced as a basic tool for element generation. Automatic generation of finite element for three-dimensional solid structures holds great benefits for analyses. Practical performances of the present system are demonstrated through several mesh generations for 3D geometry.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.9
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• pp.2183-2188
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• 2009

This paper describes an automatic mesh generation system for finite element analysis of three-dimensional cracks. It is consisting of fuzzy knowledge processing, bubble meshing and solid geometry modeler. This novel mesh generation process consists of three sub-processes: (a) definition of geometric model, i.e. analysis model, (b) generation of bubbles, and (c) generation of elements. One of commercial solid modelers is employed for three-dimensional crack structures. Bubble is generated if its distance from existing bubble points is similar to the bubble spacing function at the point. The bubble spacing function is well controlled by the fuzzy knowledge processing. The Delaunay method is introduced as a basic tool for element generation. Practical performances of the present system are demonstrated through several mesh generations for 3D cracks.