• Journal of KIISE:Software and Applications
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• v.31 no.8
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• pp.980-990
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• 2004

The component-based development methodology aims at the high state of abstraction and the reusability with components larger than classes. It is indispensible to measure the component so as to improve the quality of the component-based system and the individual component. And, the quality of the component should be improved through putting the results into the process of the development. So, it is necessary to study the component metric which can be applied in the stage of the component analysis and design. Hence, in this paper, we propose component cohesion, coupling, independence metrics reflecting the information extracted in the step of component analysis and design. The proposed component metric bases on the similarity information about behavior patterns of operations to offer the component's service. Also, we propose the redesigning process for the improvement of component design. That process uses the techniques of clustering and is for the thing that makes the component as the independent functional unit having the low complexity and easy maintenance. And, we examine that the component design model can be improved by the component metrics and the component redesigning process.

• Transactions of Materials Processing
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• v.10 no.6
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• pp.493-499
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• 2001

An optimal robust design methodology has been developed to minimize warpage in injection-molded pats. The response surface methodology was applied to obtain a functional relationship between design variables and warpage value, and the modified complex method was used as an optimization tool to search for an optimal design solution over prescribed design region. To attain robustness against process variations, Taguchi's SN ratio was introduced as the design metric. The proposed optimal design procedure was applied to an actual part, the Guide-ASF model of a fax machine, and the usefulness of the methodology was shown through the CAE simulation using a commercial injection molding software package.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.2 no.1
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• pp.70-77
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• 2002

This paper describes a design driven approach to drive intelligent test plan generation based on adaptive use case (3,5). Its foundation is an object-oriented software design approach which partitions design schema into design architecture of functional components called “design component”. A use case software development methodology of adaptive use case approach developed in I.I .T is employed which preserves this unit architecture on through to the actual code structure. Based on the partition design schema produced during the design phase of this methodology, a test plan is generated which includes a set of component and scenario based test. A software metric is introduced which produces an ordering of this set to enhance productivity and both promote and capitalize on test case reusability, This paper contains an application that illustrates the proposed approach.

• Journal of Magnetics
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• v.19 no.3
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• pp.266-272
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• 2014

In this paper, we suggest reliability as a metric to evaluate the robustness of a design for the optimal design of electromagnetic devices, with respect to constraints under the uncertainties in design variables. For fast numerical efficiency, we applied the sensitivity-assisted Monte Carlo simulation (S-MCS) method to perform reliability calculation. Furthermore, we incorporated the S-MCS with single-objective and multi-objective particle swarm optimization algorithms to achieve reliability-based optimal designs, undertaking probabilistic constraint and multi-objective optimization approaches, respectively. We validated the performance of the developed optimization algorithms through application to the optimal design of a superconducting magnetic energy storage system.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.2_1
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• pp.239-248
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• 2023

In this paper, we conduct a study on the design that can secure the safety of the EPLA system by performing safety activities based on the ISO 26262 standard for vehicle functional safety. In the case of a company developing a detailed system, it is responsible for verification through hardware design and safety analysis in the overall flow of safety activities, and safety analysis according to the ASIL safety level must be properly performed. At this time, there are cases where the safety goal quantitative metric value suggested by the ISO 26262 standard cannot be satisfied only by the hardware design of the basic function, so it is necessary to design and install the safety mechanism. Based on ISO 26262 safety activities, it is possible to derive an effective design plan through hardware safety analysis.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.12A
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• pp.1387-1395
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• 2004

Turbo decoder inherently requires large memory and intensive hardware complexity due to iterative decoding, despite of excellent decoding efficiency. To decrease the memory space and reduce hardware complexity, various design issues have to be discussed. In this paper, various design issues on Turbo decoder are investigated and the tradeoffs between the hardware complexity and the performance are analyzed. Through the various simulations on the fixed-length analysis, we decided 5-bits for the received data, 6-bits for a priori information, and 7-bits for the quantization state metric, so the performance gets close to that of infinite precision. The MAX operation which is the main function of Log-MAP decoding algorithm is analyzed and the error correction term for MAX* operation can be efficiently implemented with very small hardware overhead. The size of the sliding window was decided as 32 to reduce the state metric memory space and to achieve an acceptable BER.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.206-212
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• 2004

This paper is application of System Assurance(SA) for the rolling stock. As railway systems become more complex, design teams are increasingly under pressure to deliver, design solutions, which integrate both technical and Systems Assurance(SA). Systems Assurance is the application of management methods and analysis techniques to ensure that a design meets Reliability, Availability, Maintainability and Safety (RAMS) criteria. It should be clearly understood that the intent of System Assurance is not just to provide analytical techniques as a metric on performance, but more importantly it should provide a management tool with which to co-ordinate and assure the whole design. System Assurance encompasses the ongoing requirement to consider safety, and RAM through each stage of a Project, from feasibility study through to commissioning and operation. If System Assurance is undertaken properly at feasibility study at the design stages of a Project, the benefits of such analyses can be significant in identifying potential problems early enough for action to be taken before manufacture or installation. At commissioning, RAMS demonstration activities are undertaken to validate the predictive and analytical techniques undertaken during the design.

• Korean Journal of Computational Design and Engineering
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• v.16 no.4
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• pp.268-276
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• 2011

The product-level carbon footprint (PCF) is a comprehensive and widely accepted metric for sustainable product development. However, since a full PCF study in general is time and cost intensive, it is not feasible for the product development team to synchronize the activity to the main product development process. In addition, the current dedicated life cycle assessment (LCA) tools for calculating PCF, separated from the main product data management systems, have limitations to provide timely PCF information for design decision makings and collaborations between design and environment engineers. This paper examines the possibility of the extension of the current product data model that can support the PCF calculation with PDM (Product Data Management) databases. The product data model can represent not only the content of products but also context or system information of the products. The product data model can be implemented as a PDM database that can satisfy the needs for handy and timely PCF calculations from the consistent product data for dynamic design decision makings and engineering collaborations.

• Journal of KIISE:Software and Applications
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• v.36 no.8
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• pp.633-641
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• 2009

In this paper, we proposed a new pattern classifier which can be incrementally learned, be added new class in learning time, and handle with analog data. Proposed pattern classifier has hierarchical structure and the classification rate is improved by using different metric for each levels. Proposed model is based on the Gaussian ARTMAP which is an artificial neural network model for the pattern classification. We hierarchically constructed the Gaussian ARTMAP and proposed the Principal Component Emphasis(P.C.E) method to be learned different features in each levels. And we defined new metric based on the P.C.E. P.C.E is a method that discards dimensions whose variation are small, that represents common attributes in the class. And remains dimensions whose variation are large. In the learning process, if input pattern is misclassified, P.C.E are performed and the modified pattern is learned in sub network. Experimental results indicate that Hierarchical Gaussian ARTMAP yield better classification result than the other pattern recognition algorithms on variable data set including real applicable problem.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.24 no.3
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• pp.281-288
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• 2006

Recent increase in the number of pixels of a non-metric digital camera encourages to use it for close-range photogrammetry such as modeling cultural asset and buildings. However, these cameras have to be calibrated far close-range photogrammetry application. For self-calibration, an appropriate pbotograrnmetric network and object field should be designed. In this paper, we studied the effect on self-calibration accuracy changes according to the change of the number of ground control points, dimensions of the ground control points, and the combination of images. We concluded that self-calibration with three photos including a vertical photo can give the stable accuracy of interior orientation parameters and 10 ground control points on a plane can give high accuracy for object reconstruction.