• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.10 no.2
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• pp.11-16
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• 2015

A lot of factor effects on the enterprise's innovation and business performance, for instance CEO and members intention etc.. Niehoff et al. says, The success factors of innovation enterprise's management lead to members of vision, innovation, innovation activities and support for an aggressive attitude of the enterprise members. However, today's products consumers wanted diverse and complex needs. CEO and members of the enterprise has been the diversity effort. The increase cost savings as well as in the profit improve factors that enterprise's participated a education and training, Subgroup activities, process quality, eliminate waste, improve yields, lead time reduction, process capability increasing, ets. This paper is a report of an empirical survey performed to 277 small and medium-sized enterprise in the korea. Cronbach's alpha coefficient is employed to analyze the reliability of the data. The effect analysis of each group is performed by the SEM(structural equation model). We use the SPSS' Amos program to analyze the equation modeling and test the hypotheses of the model.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.144-152
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• 2007

We propose a 3D modeling method for surface inspection of non-linear moving object. The laser lines reflect the surface curvature. We can acquire 3D surface information by analyzing projected laser lines on object. ill this paper, we use multi-line laser to make use of robust of single stripe method and high speed of single frame. Binarization and channel edge extraction method were used for robust laser line extraction. A new labeling method was used for laser line labeling. We acquired sink information between each 3D reconstructed frame by feature point matching, and registered each frame to one whole image. We verified the superiority of proposed method by applying it to container damage inspection system.

• Journal of the Korean Institute of Intelligent Systems
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• v.25 no.1
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• pp.78-84
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• 2015

Depth estimation is often required for robot vision, 3D modeling, and motion control. Previous method is based on the focus measures which are calculated for a series of image by a single camera at different distance between and object. This method, however, has disadvantage of taking a long time for calculating the focus measure since the mask operation is performed for every pixel in the image. In this paper, we estimates the depth by using the focus measure of the boundary pixels located between the objects in order to minimize the depth estimate time. To detect the boundary of an object consisting of a straight line and a circle, we use the Hough transform and estimate the depth by using the focus measure. We performed various experiments for PCB images and obtained more effective depth estimation results than previous ones.

• Journal of Korea Multimedia Society
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• v.12 no.9
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• pp.1217-1232
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• 2009

In this paper, we propose a semi-automatic 3D building reconstruction method using uncalibrated images which includes the facade of target building. First, we extract feature points in all images and find corresponding points between each pair of images. Second, we extract lines on each image and estimate the vanishing points. Extracted lines are grouped with respect to their corresponding vanishing points. The adjacency graph is used to organize the image sequence based on the number of corresponding points between image pairs and camera calibration is performed. The initial solid model can be generated by some user interactions using grouped lines and camera pose information. From initial solid model, a detailed building model is reconstructed by a combination of predefined basic Euler operators on half-edge data structure. Automatically computed geometric information is visualized to help user's interaction during the detail modeling process. The proposed system allow the user to get a 3D building model with less user interaction by augmenting various automatically generated geometric information.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2844-2851
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• 2015

How to recover from the multiple 2D images into 3D object has been widely studied in the field of computer vision. In order to improve the accuracy of the recovered 3D shape, it is more important that noise must be minimized and the number of image frames must be guaranteed. However, potential noise is implied when tracking feature points. And the number of image frames which is consisted of an observation matrix usually decrease because of tracking failure, occlusions, or low image resolution, and so on. Therefore, it is obviously essential that the number of image frames must be secured by recovering the missing feature points under noise. Thus, we propose the analytic approach which can control directly the error distance and orientation of missing feature point by the geometrical properties under noise distribution. The superiority of proposed method is demonstrated through experimental results for synthetic and real object.

• Journal of the Korean Operations Research and Management Science Society
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• v.35 no.1
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• pp.19-45
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• 2010

Virtual Communities, which are formed on the Internet, are expected to serve the needs of members for e-collaboration, e-communication, information and knowledge sharing. The executives of organizations should consider virtual community as a new innovation or knowledge pool since members share knowledge. However, many virtual community have failed due to members' low willingness to engage and furthermore to share knowledge with other members. Thus, there is a need to understand and foster the determinants of members' sense of belonging behavior in virtual community. This study develops an integrated model designed to investigate and explain the relationships between contextual factors, personal perceptions of virtual community, usability, trust and sense of belonging in using a certain virtual community. Empirical data was collected from 201 and tested using structural equation modeling (SEM) to verify the fit of the hypothetical model. The results show that the perceived usability and community trust of members significantly influences sense of belonging in using the virtual community, and information quality, system quality, familiarity on the virtual community are significantly influence the usability but not reputation. And I confirmed that perceived shared vision and responsiveness play the role of determinants in making the member's trust, perceived risk influence the making community trust in directly. The results of the study can be used to identify the motivation underlying members' sense of belonging in a certain virtual community by investigating the impacts of contextual factors and personal perceptions on virtual community, the integrated model better explains behavior than other proposed models. This study might help executives of virtual communities and organizations to manage and promote these determinants of sense of belonging to stimulate members' willingness to engage the community and futhermore enhance their virtual community loyalty.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.383-388
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• 2005

Depth recovery in robot vision is an essential problem to infer the three dimensional geometry of scenes from a sequence of the two dimensional images. In the past, many studies have been proposed for the depth estimation such as stereopsis, motion parallax and blurring phenomena. Among cues for depth estimation, depth from lens translation is based on shape from motion by using feature points. This approach is derived from the correspondence of feature points detected in images and performs the depth estimation that uses information on the motion of feature points. The approaches using motion vectors suffer from the occlusion or missing part problem, and the image blur is ignored in the feature point detection. This paper presents a novel approach to the defocus technique based depth from lens translation using sequential SVD factorization. Solving such the problems requires modeling of mutual relationship between the light and optics until reaching the image plane. For this mutuality, we first discuss the optical properties of a camera system, because the image blur varies according to camera parameter settings. The camera system accounts for the camera model integrating a thin lens based camera model to explain the light and optical properties and a perspective projection camera model to explain the depth from lens translation. Then, depth from lens translation is proposed to use the feature points detected in edges of the image blur. The feature points contain the depth information derived from an amount of blur of width. The shape and motion can be estimated from the motion of feature points. This method uses the sequential SVD factorization to represent the orthogonal matrices that are singular value decomposition. Some experiments have been performed with a sequence of real and synthetic images comparing the presented method with the depth from lens translation. Experimental results have demonstrated the validity and shown the applicability of the proposed method to the depth estimation.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.14 no.3
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• pp.15-20
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• 2015

After the US government declared 3D printing technology a next-generation manufacturing technology, there have been many practical studies conducted to expand 3D printing technology to manufacturing technologies, called AMERICA MAKES. In particular, the Keck Center, located at the University of Texas at El Paso, has studied techniques for easily combing the 3D stacking process with space mobility and expanded these techniques to simultaneous staking techniques for multiple materials. Additionally, it developed convergence manufacturing techniques, such as direct inking techniques, in order to produce a module structure that combines electronic circuits and components, such as CUBESET. However, in these studies, it is impossible to develop a unified system using traditional independent through simple sequencing connections. This is because there are many problems in the integration between the stacking modeling of 3D printers and post-machining, such as thermal deformations, the precision accuracy of 3D printers, and independently driven coordinate problems among process systems. Therefore, in this paper, the integration method is suggested, which combines these 3D printers and subsequent machining process systems through an Internet-based cloud. Additionally, the sequential integrated system of a 3D printer, an NC milling machine, machine vision, and direct inking are realized.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.166-172
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• 2014

Image classification is an important problem in computer vision. However, it is a very challenging problem due to the variability, ambiguity and scale change that exists in images. In this paper, we propose a method of a hypergraph based modeling can consider the higher-order relationships of semantic attributes of a scene image and apply it to a scene image classification. In order to generate the hypergraph optimized for specific scene category, we propose a novel search method based on a probabilistic subspace method and also propose a method to aggregate the expression values of the member semantic attributes that belongs to the searched subsets based on a linear transformation method via likelihood based estimation. To verify the superiority of the proposed method, we showed that the discrimination power of the feature vector generated by the proposed method is better than existing methods through experiments. And also, in a scene classification experiment, the proposed method shows a competitive classification performance compared with the conventional methods.

• International Journal of Fluid Machinery and Systems
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• v.2 no.4
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• pp.286-294
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• 2009

Hydroelectric power plants are known for their ability to cover variations of the consumption in electrical power networks. In order to follow this changing demand, hydraulic machines are subject to off-design operation. In that case, the swirling flow leaving the runner of a Francis turbine may act under given conditions as an excitation source for the whole hydraulic system. In high load operating conditions, vortex rope behaves as an internal energy source which leads to the self excitation of the system. The aim of this paper is to identify the influence of the full load excitation source location with respect to the eigenmodes shapes on the system stability. For this, a new eigenanalysis tool, based on eigenvalues and eigenvectors computation of the nonlinear set of differential equations in SIMSEN, has been developed. First the modal analysis method and linearization of the set of the nonlinear differential equations are fully described. Then, nonlinear hydro-acoustic models of hydraulic components based on electrical equivalent schemes are presented and linearized. Finally, a hydro-acoustic SIMSEN model of a simple hydraulic power plant, is used to apply the modal analysis and to show the influence of the turbine location on system stability. Through this case study, it brings out that modeling of the pipe viscoelastic damping is decisive to find out stability limits and unstable eigenfrequencies.