• Ocean and Polar Research
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• v.42 no.4
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• pp.271-281
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• 2020

We investigated mesozooplankton in the Yellow Sea in spring to understand its community structure and relationship with environmental factors. Total mesozooplankton density ranged from 1,542 to 7,367 ind. m-3 and the biomass ranged from 3 to 42 mg C m-3. The total density and biomass had a positive relationship with chlorophyll-a (chl-a) concentration. The mesozooplankton community was divided into two groups at 125.5 E by cluster analysis: one was an inshore group and the other was an offshore group. The inshore group of mesozooplankton was of high density but low diversity, while the offshore group was of high diversity but low density. Copepod Acartia hongi and its copepodites were the most abundant species, comprising 27.8% of the total mesozooplankton density. A. hongi was especially abundant at the inshore, serving as the indicator species of the inshore group. Redundancy analysis found a positive relationship between the density of A. hongi and chl-a concentration. Oithona similis and Centropages abdominalis were 2nd and 3rd dominant species comprising 9 and 7% of the total density, respectively. The density of O. similis was positively related to water depth, but C. abdominalis was related to chl-a concentration. Chl-a concentration seems to influence significantly the mesozooplankton community structure in the Yellow Sea in spring, rather than water temperature or salinity.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.11a
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• pp.175-176
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• 2020

As the concrete pouring work relies on manual work, there is a lot of room for automated equipment development. In this study, as a basic study on the development of an automated system for pouring concrete, the trend of patent applications by year, country and detailed technology was investigated. Related technologies were classified into screed automation, CPB automation, and concrete pouring integrated system to analyze patent application trends. As a result, since 1999, patent applications have been steadily in progress, repeating increases and decreases in Japan, Korea, the United States, and Europe. In addition, the growth stage of the market is in the early stages of maturity, and patent applications for related technologies are expected to continue. In the future, based on the patent application trend analyzed in this study, the development direction of the automated concrete pouring system will be reviewed and the redundancy of similar technologies will be reviewed.

• Smart Structures and Systems
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• v.33 no.3
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• pp.177-188
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• 2024

The fatigue-induced sequential failure of a structure having structural redundancy requires system-level analysis to account for stress redistribution. System reliability-based design optimization (SRBDO) for preventing fatigue-initiated structural failure is numerically costly owing to the inclusion of probabilistic constraints. This study incorporates the Branch-and-Bound method employing system reliability Bounds (termed the B³ method), a failure-path structural system reliability analysis approach, with a metaheuristic optimization algorithm, namely grey wolf optimization (GWO), to obtain the optimal design of structures under fatigue-induced system failure. To further improve the efficiency of this new optimization framework, an additional bounding rule is proposed in the context of SRBDO against fatigue using the B³ method. To demonstrate the proposed method, it is applied to complex problems, a multilayer Daniels system and a three-dimensional tripod jacket structure. The system failure probability of the optimal design is confirmed to be below the target threshold and verified using Monte Carlo simulation. At earlier stages of the optimization, a smaller number of limit-state function evaluation is required, which increases the efficiency. In addition, the proposed method can allocate limited materials throughout the structure optimally so that the optimally-designed structure has a relatively large number of failure paths with similar failure probability.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.7A
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• pp.697-705
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• 2010

In Wireless Sensor Networks (WSNs), blanket (area) coverage analysis is generally carried to find the minimum number of active sensor nodes required to cover a monitoring interest area with the desired fractional coverage-threshold. Normally, the coverage analysis is performed using the stochastic geometry as a tool. The major component of such coverage analysis is the assumed sensing model. Hence, the accuracy of such analysis depends on the underlying assumption of the sensing model: how well the assumed sensing model characterizes the real sensing phenomenon. In this paper, we review the coverage analysis for different deterministic and probabilistic sensing models like Boolean and Shadow-fading model; and extend the analysis for Exponential and hybrid Boolean-Exponential model. From the analytical performance comparison, we demonstrate the redundancy (in terms of number of sensors) that could be resulted due to the coverage analysis based on the detection capability mal-characterizing sensing models.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.4
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• pp.71-85
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• 2012

This paper aims to develop an event-driven failure analysis and prognosis system that is able to monitor ship status in real time, and efficiently react unforeseen system failures. In general, huge amount of recorded sensor data must be effectively interpreted for failure analysis, but unfortunately noise and redundant information in the gathered sensor data are obstacles to a successful analysis. This paper therefore applies 'Equal-frequency binning' and 'Entropy' techniques to extract only important information from the raw sensor data while minimizing information loss. The efficiency of the developed failure analysis system is demonstrated with the collected sensor data from a marine diesel engine.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1C
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• pp.65-71
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• 2004

We improved the MLLR speaker adaptation algorithm with reduction of the order of HMM parameters using PCA(Principle Component Analysis) or ICA(Independent Component Analysis). To find a smaller set of variables with less redundancy, we adapt PCA(principal component analysis) and ICA(independent component analysis) that would give as good a representation as possible, minimize the correlations between data elements, and remove the axis with less covariance or higher-order statistical independencies. Ordinary MLLR algorithm needs more than 30 seconds adaptation data to represent higher word recognition rate of SD(Speaker Dependent) models than of SI(Speaker Independent) models, whereas proposed algorithm needs just more than 10 seconds adaptation data. 10 components for ICA and PCA represent similar performance with 36 components for ordinary MLLR framework. So, compared with ordinary MLLR algorithm, the amount of total computation requested in speaker adaptation is reduced by about 1/167 in proposed MLLR algorithm.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.7-14
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• 2006

This paper presents an efficient face recognition method using both first moment of image and basis images. First moment which is a method for finding centroid of image, is applied to exclude the needless backgrounds in the face recognitions by shifting to the centroid of face image. Basis images which are the face features, are respectively extracted by principal component analysis(PCA) and fixed-point independent component analysis(FP-ICA). This is to improve the recognition performance by excluding the redundancy considering to second- and higher-order statistics of face image. The proposed methods has been applied to the problem for recognizing the 48 face images(12 persons*4 scenes) of 64*64 pixels. The 3 distances such as city-block, Euclidean, negative angle are used as measures when match the probe images to the nearest gallery images. The experimental results show that the proposed methods has a superior recognition performances(speed, rate) than conventional PCA and FP-ICA without preprocessing, the proposed FP-ICA has also better performance than the proposed PCA. The city-block has been relatively achieved more an accurate similarity than Euclidean or negative angle.

• Journal of Environmental Science International
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• v.26 no.8
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• pp.927-938
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• 2017

This study was conducted to determine correlations and similarity between the ozone and $PM_{10}$ data of 19 air quality monitoring stations in Busan from 2013 to 2016, using correlation and cluster analyses. Ozone concentrations ranged from $0.0278{\pm}0.0148ppm$ at Gwangbok to $0.0378{\pm}0.017ppm$ at Taejongdae and were high in suburban areas, such as Yongsuri and Gijang, as well as in coastal areas, such as Jaw, Gwangan, Taejongdae and Noksan. $PM_{10}$ concentrations ranged from $37.2{\pm}25.0ug/m^3$ at Gijang to $58.3{\pm}32.2ug/m^3$ at and Jangrim. $PM_{10}$ concentrations were high in the west, exceeding the annual ambient air quality standard of $50ug/m^3$. Positive correlations were observed for ozone at most stations, ranging from 0.61 between Taejongdae and Sujeong to 0.92 between Bugok and Myeongjang. The correlation coefficients of $PM_{10}$ between stations ranged from 0.62 between Jangrim and Jaw to 0.9 between Gwangbok and Sujeong. Yeonsan, Daeyeon, and Myeongjang were highly correlated with other stations, so they needed to be reviewed for redundancy. Ozone monitoring stations were initially divided into two sections, north-western areas and suburban-coastal areas. The suburban-coastal areas were subsequently divided into three sections. $PM_{10}$ monitoring stations were initially divided into western and remaining areas, and then the remaining areas were subsequently divided into three sections.

• Proceedings of KOSOMES biannual meeting
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• 2004.11a
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• pp.137-141
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• 2004

Ship structures are basically an assembly of plate elements and the load-carrying capacity or the ultimate strength is one of the most important criteria for safety assessment and economic design. Also, Structural elements making up ship plated structures do not work separately, resulting in high degree of redundancy and complexity, in contrast to those of steel framed structures. To enable the behavior of such structures to be analyzed, simplifications or idealizations must essentially be made considering the accuracy needed and the degree of complexity of the analysis to be used. On this study, to investigate effect of modeling range, the finite element method are used and their results are compared varying the analysis ranges. The model has been selected from bottom panels of large merchant ship structures. For FEA, three types of structural modeling are adopted in terms of the extent of the analysis. The purpose of the present study is to numerically calculate the characteristics of ultimate strength behavior according to the analysis ranges of stiffened panels subject to uniaxial compressive loads.

• The Journal of the Acoustical Society of Korea
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• v.22 no.6
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• pp.452-456
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• 2003

We discuss how to reduce the number of inverse matrix and its dimensions requested in MLLR framework for speaker adaptation. To find a smaller set of variables with less redundancy, we adapt PCA (principal component analysis) and ICA (independent component analysis) that would give as good a representation as possible. The amount of additional computation when PCA or ICA is applied is as small as it can be disregarded. 10 components for ICA and 12 components for PCA represent similar performance with 36 components for ordinary MLLR framework. If dimension of SI model parameter is n, the amount of computation of inverse matrix in MLLR is proportioned to O(n⁴). So, compared with ordinary MLLR, the amount of total computation requested in speaker adaptation is reduced by about 1/81 in MLLR with PCA and 1/167 in MLLR with ICA.