• Journal of the Optical Society of Korea
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• v.20 no.2
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• pp.321-324
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• 2016

Transformation optics methodology provides a new pathway for designing novel devices. It is based on changing a material’s permittivity and permeability. A design for changing the appearance of an object by transformation optics methodology is proposed here. Through a certain transformation, the relations of the metric spaces and the calculation of the material parameters are derived, and the aim of changing the apparent size of an object can be realized. Full wave simulations are performed to validate the proposed device’s performance. It is possible to think that the methodology will improve the flexibility of designing interesting applications in microwave and optical regimes.

• Journal of KIISE:Software and Applications
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• v.31 no.7
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• pp.883-900
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• 2004

As object-oriented development technology that increases extensibility and reusability has been widely spread, it can shorten development period and enhance quality by reusing verified object-oriented artifacts. Thus we can construct high quality component-based system at short time transforming component-based model using verified object-oriented artifacts. In this paper, we propose techniques to transform available object-oriented design model into component-based model using formal specification techniques in order to increase accuracy of transformation. First, formal specification language for component is defined for formal specification of component-based design. And, techniques for formal specification of object-oriented design using Object-Z, a formal specification language, is proposed in structural, functional, and dynamic aspects. Next, we present techniques for transforming formal specification of object-oriented design into formal specification of component-based design. Through a case study we apply the proposed transformation techniques and show the transformation process of object-oriented formal specification into component-based formal specification.

• Proceedings of the Korea Database Society Conference
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• 1998.09a
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• pp.406-420
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• 1998

Users want to browse various stoups of nested attribute values of an object. On the other hand, in case of the presentation of a multimedia object, the form-based presentation is superior to the graph-based presentation. Therefore we propose o form-based presentation transformation scheme that allows users to reorganize the presentation layout to ft the limited screen and to show the values of all the needed attributes. For the representation of the presentation scenario of an object a presentation information class and the presentation transformation operations are defined. We show how these operations transform the default presentation into the wanted presentation by navigating through a multimedia object with the COMIB (COMposite Icon Browser).

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.193-200
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• 2013

In this paper, underwater acoustic image classification of a cylindrical object using the Hough transformation is proposed. Hough transformation is often used to classify a cylindrical object in the optical systems. However, it is difficult to apply to the underwater acoustic image system because of lower resolution and noisier underwater environments. Thus, the cylindrical object was modeled and its geometric depth(GD) pixels were restored in order to make them suitable for the Hough transformation by using moving average filter and a polynomial interpolation method. As a result, restored GD pixels are similar to original ones and test results show high performance in classification.

• Journal of KIISE
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• v.42 no.11
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• pp.1410-1422
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• 2015

In order to design a system, software developers use an object model such as the UML class diagram. Object-Relational Transformation Methodology (ORTM) is a methodology to transform the relationships that are expressed in the object model into relational database tables, and it is applied for the implementation of the designed system. Previous ORTM studies have suggested a number of transformation methods to represent one relationship. However, there is an implementation problem that is difficult to apply because the usage criteria for each transformation method do not exist. Therefore, this paper proposes a binary decision diagram-based modeling rule for each relationship. Hence, we define the conditions for distinguishing the transformation methods. By measuring the query execution time, we also evaluate the modeling rules that are required for the verification. After evaluation, we re-define the final modeling rules which are represented by propositional logic, and show that our proposed modeling rules are useful for the implementation of the designed system through a case study.

• The Journal of Korea Robotics Society
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• v.4 no.3
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• pp.185-191
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• 2009

This paper presents a new shape-based algorithm using affine category shape model for object category recognition and model learning. Affine category shape model is a graph of interconnected nodes whose geometric interactions are modeled using pairwise potentials. In its learning phase, it can efficiently handle large pose variations of objects in training images by estimating 2-D homography transformation between the model and the training images. Since the pairwise potentials are defined on only relative geometric relationship betweenfeatures, the proposed matching algorithm is translation and in-plane rotation invariant and robust to affine transformation. We apply spectral matching algorithm to find feature correspondences, which are then used as initial correspondences for RANSAC algorithm. The 2-D homography transformation and the inlier correspondences which are consistent with this estimate can be efficiently estimated through RANSAC, and new correspondences also can be detected by using the estimated 2-D homography transformation. Experimental results on object category database show that the proposed algorithm is robust to pose variation of objects and provides good recognition performance.

• Journal of KIISE:Computing Practices and Letters
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• v.11 no.2
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• pp.124-132
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• 2005

We propose a method using a transformation of an object and a scene tree in order to author MPEG-4 contents for mobile devices in this paper. The method transforms media objects in the scene into geometry objects in order to reduce initial loading time of the contents, and reduces an external form of each object in a scene of the content for presenting it efficiently on the small interface of mobile devices. Therefore, the contents for mobile devices are reconstructed by the method. An original object in the scene is presented on a mobile device when a user clicks a related geometry object. The method was applied to a conventional authoring tool, so we could find that the method showed an efficient presentation of MPEG-4 contents on mobile devices.

• Journal of KIISE:Software and Applications
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• v.27 no.5
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• pp.473-487
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• 2000

SDL-92, the language for specification and description of system, has held on to the communication method that based on processes and signals in the adoption of object-oriented concept to embrace the previous documents of system specification and description and users. It has caused problems, not only the absence of corresponding concepts in automatic generation to object-oriented language program based on method and object, but also some side effects accompanied by them like visibility and communication method. So, in this paper, we present a general object-oriented language model, which based on method and object, make a study of problems in the transformation fromSDL-92 to proposed model, and then propose conceptual transformation methods to solve them. The proposed transformation method can utilize the built-in parallelism in objects and guarantee the compiler level portability in translated program by providing translation into the syntax of target language.

• Journal of Multimedia Information System
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• v.6 no.4
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• pp.235-238
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• 2019

In real world object detection is an active research topic for understanding different objects from images. There are different models presented in past and had significant results. In this paper we are presenting vehicle logo detection using previous object detection models such as You only look once (YOLO) and Faster Region-based CNN (F-RCNN). Both the front and rear view of the vehicles were used for training and testing the proposed method. Along with deep learning an image pre-processing algorithm called perspective transformation is proposed for all the test images. Using perspective transformation, the top view images were transformed into front view images. This algorithm has higher detection rate as compared to raw images. Furthermore, YOLO model has better result as compare to F-RCNN model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.7 no.12
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• pp.3180-3199
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• 2013

While non-predefined object segmentation (NDOS) distinguishes an arbitrary self-assumed object from its background, predefined object segmentation (DOS) pre-specifies the target object. In this paper, a new and novel method to segment predefined objects is presented, by globally optimizing an orientation-based objective function that measures the fitness of the object boundary, in a discretized parameter space. A specific object is explicitly described by normalized discrete sets of boundary points and corresponding normal vectors with respect to its plane shape. The orientation factor provides robust distinctness for target objects. By considering the order of transformation elements, and their dependency on the derived over-segmentation outcome, the domain of translations and scales is efficiently discretized. A branch and bound algorithm is used to determine the transformation parameters of a shape model corresponding to a target object in an image. The results tested on the PASCAL dataset show a considerable achievement in solving complex backgrounds and unclear boundary images.