• The Journal of Information Technology and Database
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• v.5 no.1
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• pp.109-119
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• 1998

Users want to browse various groups 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 a form-based presentation transformation scheme that allows users to reorganize the presentation layout to fit 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).

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.4
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• pp.166-171
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• 2001

Object-oriented programming is a solution for problems in the development, maintenance, and update of large software such as power system analysis software. However, many applications in the electrical industry critically depend on the computational efficiency of the implementation. In order to be flexible and reduce the computation time, this paper represents an efficient method for constructing a Jacobian matrix and for factorizing it, and designs the class hierarchy for power system. This method is applied to four different power systems for load flow calculation. The performance of the object-oriented program developed in C++ is assessed in computer simulation.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.335-337
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• 2024

This paper presents a new open-world object detection method emphasizing uncertainty representation in machine learning models. The focus is on adapting to real-world uncertainties, incrementally updating the model's knowledge repository for dynamic scenarios. Applications like autonomous vehicles benefit from improved multi-class classification accuracy. The paper reviews challenges in existing methodologies, stressing the need for universal detectors capable of handling unknown classes. Future directions propose collaboration, integration of language models, to improve the adaptability and applicability of open-world object detection.

• International Journal of Computer Science & Network Security
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• v.24 no.5
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• pp.129-134
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• 2024

Object Detection is an emerging technology in the field of Computer Vision and Image Processing that deals with detecting objects of a particular class in digital images. It has considered being one of the complicated and challenging tasks in computer vision. Earlier several machine learning-based approaches like SIFT (Scale-invariant feature transform) and HOG (Histogram of oriented gradients) are widely used to classify objects in an image. These approaches use the Support vector machine for classification. The biggest challenges with these approaches are that they are computationally intensive for use in real-time applications, and these methods do not work well with massive datasets. To overcome these challenges, we implemented a Deep Learning based approach Convolutional Neural Network (CNN) in this paper. The Proposed approach provides accurate results in detecting objects in an image by the area of object highlighted in a Bounding Box along with its accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.57-57
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• 2000

The purpose of this paper is show that an chip mounter can be modeled by stochastic petri nets, and that the simulator to verify a fitness of the program to assemble. The chip mounter can be constructed by using the petri net class (CPetriNet) based on the object-oriented programming. By using this simulator, we can get the information about the description of motion of the chip mounter, and moreover, we can evaluate the productivity.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1999.10c
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• pp.69-74
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• 1999

Upland Irrigation Network Analysis System(UINAS) used Object-Oriented Programming (OOP). The results of using OOP is definition of objects and class hierarchy for UINAS, Objects of UINAS are consist of the Pipe , Sprinkler, Valve , Pump, Tee , Bend and Contractions. The classj hierarchy have cooperative design for FEM in analysing the irrigation network. Therefore UINAS have a flexiblility in additioning the network components.

• Proceedings of the KIEE Conference
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• 1998.07a
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• pp.393-395
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• 1998

This paper presents a modeling of railway facilities based on object-oriented software development technique for train operation simulation program. Railway network is decomposed by Line Structure Model and Signal System Model which can be composed to make the train routes and train performance calculation. A brief explanation of class design about these model is provided.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.324-327
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• 2001

본 논문은 Chidamber와 Kemerer가 제안한 객체지향 설계를 위한 척도를 바탕으로 이를 확장하여 클래스 상속 구조의 유지보수성을 이해성과 변경성 측면에서 측정하는 새로운 객체지향 척도를 제안했다. 그리고 클래스 상속 구조의 예를 들어 비교 평가를 함으로써 Chidamber와 Kemerer의 척도 및 Henderson-Sellers의 척도보다 우수함을 보였다.

• Proceedings of the Korean Society for Cognitive Science Conference
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• 2000.05a
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• pp.226-231
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• 2000

객체지향 패러다임의 상속성은 코드 재사용 및 확장을 용이하게 하여 소프트웨어 생산성을 높여준다. 그러나 상속을 남용하여 상속 계층구조(class inheritance hierarchy)의 상속 깊이가 깊게 되면 프로그램을 이해하는데 어려움을 준다. 이러한 관점에서 볼 때 상속성의 이용에 제한을 둘 필요가 있다. 본 논문은 상속 계층구조의 상속 깊이에 대한 기준을 세우기 위하여 인지실험을 행하고 그 결과를 보고한다. 본 논문의 목적은 객체지향의 특성 중 상속성의 장점을 잘 이용하면서 이해하기 쉬운 객체지향 소프트웨어 개발을 돕는 것이다.

• The Pure and Applied Mathematics
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• v.21 no.3
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• pp.207-218
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• 2014

The principal object of this paper is to study a class of matrix polynomials associated with Humbert polynomials. These polynomials generalize the well known class of Gegenbauer, Legendre, Pincherl, Horadam, Horadam-Pethe and Kinney polynomials. We shall give some basic relations involving the Humbert matrix polynomials and then take up several generating functions, hypergeometric representations and expansions in series of matrix polynomials.