• Journal of KIISE:Software and Applications
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• v.31 no.6
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• pp.728-740
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• 2004

The increasing complexity and shorter life cycle of software have made it necessary to reuse software. Object-oriented development had not provided extensive reuse and computing infrastructures are evolving from mainframe to distributed environments. However, components provide more advanced means of structuring, describing and developing system, because they are more coarse-grained and have more domain-specific aspects than objects. And they are also suited for distributed environment due to their reusability and granularity. In this paper, we present a process including the static metrics and guidelines that can be applied to transform object-oriented systems into component-based systems. Our process consists of two parts: First, basic components are created based upon composition and inheritance relationships between classes. Second, intermediate system is refined into component-based system with the static metrics and guidelines we propose.

• Journal of KIISE:Computer Systems and Theory
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• v.34 no.2
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• pp.65-72
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• 2007

As embedded system has strict cost and space constraints, it is impossible to apply conventional fault-tolerant techniques directly for increasing the dependability of embedded system. In this paper, we propose software fault-tolerant mechanism which requires only minimum redundancy of system component. We define an utility metric that reflects the dependability of each embedded system component, and then measure the defined utility of each reconfiguration combinations to provide fault tolerance. The proposed utility evaluation process shows exponential complexity. However we reduce the complexity by hierachical subgrouping at the software level of each component. When some components of embedded system are tailed, reconfiguration operation changes the system state from current faulty state to pre-calculated one which has maximum utility combination.

• Journal of Broadcast Engineering
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• v.19 no.1
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• pp.31-43
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• 2014

A depth map is an important component for stereoscopic image generation. Since the depth map acquired from a depth camera has a low resolution, upsamling a low-resolution depth map to a high-resolution one has been studied past decades. Upsampling methods are evaluated by objective evaluation tools such as PSNR, Sharpness Degree, Blur Metric. As well, the subjective quality is compared using virtual views generated by DIBR (depth image based rendering). However, works on the analysis of the relation between depth map upsampling and stereoscopic images are relatively few. In this paper, we investigate the relationship between subjective evaluation of stereoscopic images and objective performance of upsampling methods using cross correlation and linear regression. Experimental results demonstrate that the correlation of edge PSNR and visual fatigue is the highest and the blur metric has lowest correlation. Further, from the linear regression, we found relative weights of objective measurements. Further we introduce a formulae that can estimate 3D performance of conventional or new upsampling methods.

• Journal of KIISE:Databases
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• v.33 no.4
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• pp.372-383
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• 2006

Among the approaches to image database management, content-based image retrieval (CBIR) is viewed as having the best support for effective searching and browsing of large digital image libraries. Typical CBIR systems allow a user to provide a query image, from which low-level features are extracted and used to find 'similar' images in a database. However, there exists the semantic gap between human visual perception and low-level representations. An effective methodology for overcoming this semantic gap involves relevance feedback to perform feature re-weighting. Current approaches to feature re-weighting require the number of components for a feature representation to be the same for every image in consideration. Following this assumption, they map each component to an axis in the n-dimensional space, which we call the metric space; likewise the feature representation is stored in a fixed-length vector. However, with the emergence of features that do not have a fixed number of components in their representation, existing feature re-weighting approaches are invalidated. In this paper we propose a feature re-weighting technique that supports features regardless of whether or not they can be mapped into a metric space. Our approach analyses the feature distances calculated between the query image and the images in the database. Two-sided confidence intervals are used with the distances to obtain the information for feature re-weighting. There is no restriction on how the distances are calculated for each feature. This provides freedom for how feature representations are structured, i.e. there is no requirement for features to be represented in fixed-length vectors or metric space. Our experimental results show the effectiveness of our approach and in a comparison with other work, we can see how it outperforms previous work.

• Korean Institute of Interior Design Journal
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• v.21 no.1
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• pp.148-158
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• 2012

The objective of this study is to find a possible application of small space utilization of GangSo Housing, so called compact-but-effective housing, through analyzing that of Japanese small housing. We analyze openness of view and flexibility of spaces divided by the physical and architectural aspects as first component and the psychological and interior space aspects as second component. The results showed that Japanese small houses have various unit plan compared to uniformity of Korean houses. Openness of view in Japanese small housing is accomplished by letting in light from the outside using position and shape of the window, looking more spacious using courtyard, void spaces, or sliding door hanging from the ceiling, and creating deception of view using floor-wall plan and appropriate materials. Flexibility of spaces is achieved by combination of first and second components, multipurpose of space and furniture, and variety of storage methods. It is necessary to improve spatial efficiency with consideration of volume-metric planing rather than flat-plane and develop various unit plans to meet residents' needs and demands on compact-but-effective houses.

• Journal of Korea Multimedia Society
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• v.17 no.1
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• pp.34-42
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• 2014

In this paper an embedding algorithm based on commute time is implemented by organizing patches according to the graph-based metric, and its performance is analyzed by comparing with the results of principal component analysis embedding. It is usual that the dimensionality reduction be done within some acceptable approximation error. However this paper shows the proposed manifold embedding method generates the intrinsic geometry corresponding to the signal despite severe approximation error, so that it can be applied to the areas such as pattern classification or machine learning.

• Journal of KIISE:Software and Applications
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• v.30 no.7_8
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• pp.618-641
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• 2003

Various quality models using quality factor, quality criteria and metrics have been proposed in order to evaluate quality of software products. However, a customized quality model which is specific to the characteristics of software component is required. In this paper, we propose external quality prediction techniques enable us to predict what external quality the final software product will have by using metrics as with internal attributes of software in development. We also propose a model not only for measuring quality by using metrics but also for applying internal attributes of ISO 9126 into artifacts of software component development.

• KIEAE Journal
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• v.17 no.3
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• pp.35-44
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• 2017

Purpose: This study questioned the efficiency of daylight factor as a daylight adequacy and investigated a method of how to complement its weakness by considering a direct sunlight component under a clear sky condition. Method: The Snowdon visitor centre cafe was chosen as a case study building and various techniques such as BRE formula, BRE sky protractor, Pilkington dot diagram and mock-upscale model under the artificial sky simulator were used to analyse and compare daylight factor values. An analysis of direct sunlight component under the clear sky condition was carried out by Climate Consultant 5.5, sun path diagram, and the artificial sky simulator. Result: The result of daylight factor analysis differed by the adopted techniques and it was also contradictory to the results on a direct sunlight penetration. The result not only showed the limitation of daylight factor as a metric but also suggested an improvement by combining it with direct sunlight analysis. The techniques used in this study had a merit of being applied in the early design stage and thus be beneficial to many design professions in order for early daylight performance analysis.

• ETRI Journal
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• v.37 no.3
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• pp.541-550
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• 2015

In this paper, we propose a classification-based approach for hybridizing statistical machine translation and rulebased machine translation. Both the training dataset used in the learning of our proposed classifier and our feature extraction method affect the hybridization quality. To create one such training dataset, a previous approach used auto-evaluation metrics to determine from a set of component machine translation (MT) systems which gave the more accurate translation (by a comparative method). Once this had been determined, the most accurate translation was then labelled in such a way so as to indicate the MT system from which it came. In this previous approach, when the metric evaluation scores were low, there existed a high level of uncertainty as to which of the component MT systems was actually producing the better translation. To relax such uncertainty or error in classification, we propose an alternative approach to such labeling; that is, a cut-off method. In our experiments, using the aforementioned cut-off method in our proposed classifier, we managed to achieve a translation accuracy of 81.5% - a 5.0% improvement over existing methods.

• Agricultural and Biosystems Engineering
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• v.5 no.1
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• pp.25-29
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• 2004

Fluorescence spectroscopy was used to characterize chicken carcass diseases. Spectral signatures of three different disease categories of poultry carcasses (airsacculitis, cadaver and septicemia) were obtained from fluorescence emission measurements in the wavelength range of 360 to 600 nm with 330 nm excitation. Principal Component Analysis (PCA) was used to select the most significant wavelengths for the classification of poultry carcasses. These wavelengths were analyzed for pathologic correlation of poultry diseases. Using a Soft Independent Modeling of Class Analogy (SIMCA) of principal components with a Mahalanobis distance metric, poultry carcasses were individually classified into different classes with $97.9\%$ accuracy.