• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1140-1142
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• 1998

This paper presents object-oriented dynamic programing formulation of the unit commitment problem. This approach features the classification of generating units into related groups so called class. All object which share the same set of attributes and methods are grouped together in classes and designed inheritance hierarchy to minimize the number of unit combination which must be tested without precluding the optimal path. So this programming techniques will maximize the efficiency of unit commitment.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.2033-2036
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• 2004

A novel approach to estimate the real time moving trajectory of an object is proposed in this paper. The object position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Kalman filter and neural networks are utilized. Since the Kalman filter needs to approximate a non-linear system into a linear model to estimate the states, there always exist errors as well as uncertainties again. To resolve this problem, the neural networks are adopted in this approach, which have high adaptability with the memory of the input-output relationship. Kohonen Network(Self-Organized Map) is selected to learn the motion trajectory since it is spatially oriented. The superiority of the proposed algorithm is demonstrated through the real experiments.

• 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.

• Journal of information and communication convergence engineering
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• v.7 no.2
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• pp.119-124
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• 2009

In this paper, we propose a novel approach to estimating the real-time moving trajectory of an object is proposed in this paper. The object's position is obtained from the image data of a CCD camera, while a state estimator predicts the linear and angular velocities of the moving object. To overcome the uncertainties and noises residing in the input data, a Extended Kalman Filter(EKF) and neural networks are utilized cooperatively. Since the EKF needs to approximate a nonlinear system into a linear model in order to estimate the states, there still exist errors as well as uncertainties. To resolve this problem, in this approach the Kohonen networks, which have a high adaptability to the memory of the input-output relationship, are utilized for the nonlinear region. In addition to this, the Kohonen network, as a sort of neural network, can effectively adapt to the dynamic variations and become robust against noises. This approach is derived from the observation that the Kohonen network is a type of self-organized map and is spatially oriented, which makes it suitable for determining the trajectories of moving objects. The superiority of the proposed algorithm compared with the EKF is demonstrated through real experiments.

• Journal of KIISE:Software and Applications
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• v.34 no.4
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• pp.317-327
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• 2007

In this paper, a systematic approach of developing detail 00 designs from Component-and-Connector Architectures (CCAs) is proposed. In this approach, an intermediate model between the architecture model and the detail design model specified with class diagrams or sequence diagrams is introduced to narrow the wide gap between the two abstraction levels. Once a CCA is designed, candidate classes and their relationships are identified per each architectural element. In order to show the efficacy of this approach, we apply it to an industry software development project and verify that quality attributes supported by the CCA are equally maintained by the detail design.

• The KIPS Transactions:PartD
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• v.11D no.7 s.96
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• pp.1443-1450
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• 2004

The clustering characteristics for a number of classes, and defining the inheritance relations between the classes is a difficult and complex problem in an early stage of object oriented software development. We discuss a traditional iterative approach for the reuse of the existing classes in a library and an integrated approach to creating a number of new classes presented in this study. This paper formulates a character-istic clustering problem for zero-one integer programming and presents a network solution method with illustrative examples and the basic rules to define the inheritance relations between the classes. The network solution method for a characteristic clustering problem is based on a distance parameter between every pair of objects with characteristics. We apply the approach to a real problem taken from industry.

• The KIPS Transactions:PartA
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• v.10A no.6
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• pp.605-614
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• 2003

In this paper we introduce a new style multiparadigm language named Argos which applies a compositional approach [20] to multiparadigm programming. Argos is a superset of the Java, and its grammar has an extension point which allows other languages to be used in Argos programs. Therefore, Argos can support object-oriented programming and multiparadigm programming by enabling each method in a class to be implemented with one of the Java, C, Prolog, Python, and XML languages. Since Argos allows the existing languages to be used, it has advantages such as easiness of learning and high reusability. The Argos compiler is implemented according to the delegating compiler object (DCO) model[28,29]. The compiler partitions a program Into several parts according to the languages used in methods and delivers the parts the languages' processors which compile the parts.

• Journal of Ship and Ocean Technology
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• v.6 no.4
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• pp.1-12
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• 2002

A control system for an automated line heating process is developed by use of object-oriented methodology. The main function of the control system is to provide real-time heating information to technicians or automated machines. The information includes heating location, torch speed, heating order, and others. The system development is achieved by following the five steps in the object-oriented procedure. First, requirements are specified and corresponding objects are determined. Then, the analysis, design, and implementation of the proposed system are sequentially carried out. The system consists of six subsystems, or modules. These are (1) the inference module with an artificial neural network algorithm, (2) the analysis module with the Finite Element Method and kinematics analysis, (3) the data access module to store and retrieve the forming information, (4) the communication module, (5) the display module, and (6) the measurement module. The system is useful, irrespective of the heating sources, i.e. flame/gas, laser, or high frequency induction heating. A newly developed automated line heating machine is connected to the proposed system. Experiments and discussions follow.

• Journal of KIISE:Software and Applications
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• v.31 no.9
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• pp.1131-1141
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• 2004

Cohesion refers to the degree of the relatedness of the elements in a module, and it is widely accepted that the module of higher cohesion is easier to understand, maintain, and reuse. Recently, several cohesion metrics have been proposed to measure the cohesiveness of classes in an object-oriented program. However, the existing cohesion metrics do not consider the characteristics of dependent instance variables that are commonly used in a class and, thus, do not properly reflect the cohesiveness of the class. This paper presents an approach for improving the cohesion metrics by considering the characteristics of the dependent instance variables in an object-oriented program. To demonstrate the importance of the dependent instance variables, a case study has been conducted on a class library.

• Journal of Information Technology Applications and Management
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• v.14 no.3
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• pp.49-77
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• 2007

Role-based access control (RBAC) models are recently receiving considerable attention as a generalized approach to access control. In line with the increase in applications that deal with spatial data. an advanced RBAC model whose entities and constraints depend on the characteristics of spatial data is required. Even if some approaches have been proposed for geographic information systems. most studies focus on the location of users instead of the characteristics of spatial data. In this paper. we extend the traditional RBAC model in order to deal with the characteristics of spatial data and propose new spatial constraints. We use the object-oriented modeling based on open GIS consortium geometric model to formalize spatial objects and spatial relations such as hierarchy relation and topology relation. As a result of the formalization for spatial relations. we present spatial constraints classified according to the characteristics of each relation. We demonstrate our extended-RBAC model called OOGIS-RBAC and spatial constraints through case studies. Finally. we compare our OOGIS-RBAC model and the DAC model in the management of access control to prove the efficiency of our model.