• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.897-902
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• 2002

Because of rapid evolution of software technique, numerous software professionals have been concerned with component based development methodologies. However, it is hard to find out a systematic technique for the selection of COTS (Commercial Off The Shelf) component in consumer position. Up to date, the major of component quality evaluation is object-oriented metric based evaluation methodology. But this paper present four step process and evaluation criteria based on MCDM (Multiple Criteria Decision Making) technique for optimal COTS component selection in consumer position. We considered funtionality, efficiency, usability based on IS0/IEC 9126 for Quality measurement and executed practical analysis about commercial EJB component in internet. This paper show that the proposed selection technique is applicable to optimal COTS component selection.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10b
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• pp.524-529
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• 1993

Component Cost Analysis considers any given system driven by a white noise process as an interconnection of different components, and assigns a metric called "component cost" to each component. These component costs measure the contribution of each component to a predefined quadratic cost function. One possible use of component costs is for model reduction by deleting those components that have the smallest component cost. The theory of Component Cost Analysis is extended to include finite-bandwidth colored noises. The results also apply when actuators have dynamics of their own. When the dynamics of this input are added to the plant, which is to be reduced by CCA, the algorithm for model reduction process will be called Weighted Component Cost Analysis (WCCA). Closed-form analytical expressions of component costs for continuous time case, are also derived for a mechanical system described by its modal data. This is very useful to compute the modal costs of very high order systems beyond Lyapunov solvable dimension. A numerical example for NASA's MINIMAST system is presented.presented.

• 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 Broadcast Engineering
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• v.17 no.3
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• pp.459-470
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• 2012

In this paper, we propose a method to upsample a low-resolution depth map to a high-resolution version. While conventional camera sensors produce high-resolution color images, the sizes of the depth maps of range/depth sensors are usually low. In this paper, we consider the utilization of high-frequency components to the conventional depth map interpolation methods such as bilinear, bicubic, and bilateral. The proposed method is composed of the three steps: high-frequency component extraction, high-frequency component application, and interpolation. Two objective evaluation measures such as sharpness degree and blur metric are used to examine the performance. Experimental results show that the proposed method significantly outperforms other conventional methods by a factor of 2 in terms of sharpness degree. As well, a blur metric is reduced by a factor of 14 %.

• The Journal of Society for e-Business Studies
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• v.8 no.2
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• pp.113-129
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• 2003

Component-based software development (CBSD) has been recognized effective reuse techniques for software development by many of researchers and companies. The purpose of CBSD is to produce a high quality software system quickly through using verified software component which is contained fine-grained business logics. This paper suggests the metrics and techniques for to extract component and its interface from legacy object oriented application. For extract component, we apply metrics to measure complexity, cohesion and coupling to the legacy system.

• Journal of Korean Society for Geospatial Information Science
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• v.17 no.2
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• pp.91-99
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• 2009

In the field of geospatial information, 3D shape information has been considered as a frame data for GIS. Many kind of physical shape information is, especially, required for the works related with space, such as planning, maintenance, management, etc. Conventional photogrammetry was implemented under the conditions with expensive metric cameras and analytical plotters operated by experts. Nowadays, however, the metric cameras and analytical plotters are replaced by low price non-metric digital cameras and personal computers by virtue of the progress in digital photogrammetry. This study aims to investigate the technology to easily and promptly produce 3D shape information required in geospatial information system using close-range photogrammetry with non-metric digital cameras. As the results of this study, 3D shape of an experimental object was made out with a common compact digital camera and only a known length of a line component in the object and the accuracy of the dimension of 3D shape was analyzed to be less than one pixel.

• Journal of Construction Engineering and Project Management
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• v.2 no.1
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• pp.27-34
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• 2012

Recent requirements in component management of building systems have focused on the requirement for improving methods and metric tools to support component condition assessment and appropriate decisions for infrastructure owned facilities. Although engineers and researchers have focused on developing methodologies for component assessment in recent years but there is not enough attention dedicate to facilities and components that have been constructed. This paper is a literature study of scientific papers within the topic of component condition index system (CCIS) in the period 1976 to 2009. Infrastructure component condition index had existed for some 40 years. The purpose of this paper is to provide an overview of CCIS to identify the suitable method for component condition assessment during its service life. This paper finds that the focus of CCIS, surveyed in several aspects during the 40 years that have been investigated, from technology to measurement and from assessment function to component maintenance as an integrated part of the infrastructure component management. This study offers help to researchers in understanding the selection of an appropriate method for component condition assessment in building and non-building systems.

• Communications for Statistical Applications and Methods
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• v.31 no.3
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• pp.309-322
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• 2024

Identifying algae in water is important for managing algal blooms which have great impact on drinking water supply systems. There have been various microscopic approaches developed for algae classification. Many of them are based on the morphological features of algae. However, there have seldom been mathematical frameworks for comparing the shape of algae, represented as a planar continuous curve obtained from an image. In this work, we describe a recent framework for computing shape distance between two different algae based on the elastic metric and a novel functional representation called the square root velocity function (SRVF). We further introduce statistical procedures for multiple shapes of algae including computing the sample mean, the sample covariance, and performing the principal component analysis (PCA). Based on the shape distance, we classify six algal species in watersheds experiencing algal blooms, including three cyanobacteria (Microcystis, Oscillatoria, and Anabaena), two diatoms (Fragilaria and Synedra), and one green algae (Pediastrum). We provide and compare the classification performance of various distance-based and model-based methods. We additionally compare elastic shape distance to non-elastic distance using the nearest neighbor classifiers.

• Journal of Korean Society on Water Environment
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• v.40 no.5
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• pp.243-257
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• 2024

Although lakes are an important part of freshwater, research on biological methods for assessing ecological integrity of Korean lakes is insufficient. Therefore, this study aimed to develop Lakes Benthic Macroinvertebrates Multi-Metric Index (LBMMI) to assess the ecological integrity of lakes in Korea to further understand Korean lake's ecosystem. We used biological data from 388 sampling units of national lake monitoring programs from 2022 to 2023 and water quality data from Water Environment Information System (WEIS). As a result, firstly, reference points and disturbed points were selected through Principal Component Analysis (PCA). Secondly, six core metric elements (Pielou's Evenness index (J), Total number of taxa (To.t), Percent of taxa in insecta (% I.t), Percent of individuals in Oligochaeta and chironomidae(tuble) (% OliCht.i), Percent of taxa in Predator (% Pe.t), and Percent of taxa in Clingers (% CL.t) were selected through discriminant analysis and relationship-test. Lastly, LBMMI was calculated for each sampling point by scoring using core metric elements and five grades were assigned for LBMMI scores using a Beta probability distribution model, with the suitability of LBMMI reviewed by comparing it with TSI_KO. LBMMI developed in this study is expected to appropriately assess ecological integrity of Korean lakes and provide a basis for further research on lake environment conservation.

• The Transactions of the Korean Institute of Power Electronics
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• v.25 no.5
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• pp.385-393
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• 2020

This study introduces an analysis and control method for the variation of neutral point current in a grid-tied three-level neutral point clamped (NPC) converter under various grid imbalance operating conditions. Various fault cases with unbalanced amplitude and phase are systematically categorized and described using a unified metric called the imbalance factor. The fundamental component of neutral point current is generated under grid imbalance cases. The pattern and behavior of this fundamental component of neutral point current highly depend on the imbalance factor regardless of the particular type of grid fault cases. The control scheme for regulating the negative sequential component of AC input current effectively reduces the size of the fundamental component of neutral point current under a wide range of grid imbalance cases. The control scheme will enable a grid-tied three-level NPC converter to operate reliably and stably under various types of grid faults.