• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.26 no.3
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• pp.315-322
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• 2016

Room acoustic properties of coupled rooms connected by an aperture has been analyzed using statistical acoustic model based on the diffused sound field assumption, which has limitation in dealing with the parameters such an room geometries and non uniform absorptivity of the boundary surfaces. In order to overcome these difficulties the acoustic diffusion model has been introduced, by which distribution of the acoustic energy density can be analyzed for various shapes and wall absorptivity. In this study acoustic properties of coupled rooms connected by an aperture(e.g. door) is analyzed using acoustic diffusion equation, which is solved numerically. The mean energy densities of two rooms obtained by the diffusion model are compared with those from the statistical model. The results show good agreement for various coupling aperture sizes and absorption coefficients. For a limiting case when the partition wall is substituted by an aperture and the two rooms eventually forms a single room, results of coupled room analysis using diffusion model show good agreement with those of a single room.

• Applied Chemistry for Engineering
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• v.17 no.6
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• pp.625-632
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• 2006

Dependence of the critical micelle concentration (CMC) on temperature is examined from a statistical-mechanical point of view. A simple and primitive model examined in this article yields ln CMC= A+BT+C/T+D ln T with T being temperature and A, B, C, D being constants depending on the properties of the surfactant molecules which comprise the micelles. The resulting equation combines Muller's and Lim's equations, which have already been proven to fit well measured CMC data with temperature. The statistical-mechanical model on micellization discussed in this article provides a theoretical basis on these equations.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.3
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• pp.219-234
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• 2009

This paper presents a novel approach for extracting simultaneously human daily activity patterns and discovering the temporal relations of these activity patterns. It is necessary to resolve the services conflict and to satisfy a user who wants to use multiple services. To extract the simultaneous activity patterns, context has been collected from physical sensors and electronic devices. In addition, a context model is organized by the proposed incremental statistical method to determine conflicts and to infer user intentions through analyzing the daily human activity patterns. The context model is represented by the sets of the simultaneous activity patterns and the temporal relations between the sets. To evaluate the method, experiments are carried out on a test-bed called the Ubiquitous Smart Space. Furthermore, the user-intention simulator based on the simultaneous activity patterns and the temporal relations from the results of the inferred intention is demonstrated.

• Journal of Biomedical Engineering Research
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• v.20 no.1
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• pp.59-68
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• 1999

In this paper, we propose an algorithm to locate the corpus callosum automatically from midsagittal brain MR images using the statistical characteristics and shape information of the corpus callosum. In the proposed algorithm, we first extract regions satisfying the statistical characteristics of the corpus callosum and then find a region matching the shape information. In order to match the shape information, a new directed window region-growing algorithm is proposed instead of using conventional contour matching algorithms. Using the proposed algorithm, we adaptively relax the statistical requirement until we find a region matching the shape information. Experiments show promising results.

• Environmental Engineering Research
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• v.19 no.3
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• pp.197-203
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• 2014

This study estimated spatial and seasonal variation of water quality to understand characteristics of Nakdong river basin, Korea. All together 11 parameters (discharge, water temperature, dissolved oxygen, 5-day biochemical oxygen demand, chemical oxygen demand, pH, suspended solids, electrical conductivity, total nitrogen, total phosphorus, and total organic carbon) at 22 different sites for the period of 2003-2011 were analyzed using multivariate statistical techniques (cluster analysis, principal component analysis and factor analysis). Hierarchical cluster analysis grouped whole river basin into three zones, i.e., relatively less polluted (LP), medium polluted (MP) and highly polluted (HP) based on similarity of water quality characteristics. The results of factor analysis/principal component analysis explained up to 83.0%, 81.7% and 82.7% of total variance in water quality data of LP, MP, and HP zones, respectively. The rotated components of PCA obtained from factor analysis indicate that the parameters responsible for water quality variations were mainly related to discharge and total pollution loads (non-point pollution source) in LP, MP and HP areas; organic and nutrient pollution in LP and HP zones; and temperature, DO and TN in LP zone. This study demonstrates the usefulness of multivariate statistical techniques for analysis and interpretation of multi-parameter, multi-location and multi-year data sets.

• Analytical Science and Technology
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• v.22 no.1
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• pp.82-91
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• 2009

Preparation and evaluation of the limestone samples for a proficiency test using domestic limestone have been performed. We have used statistical method for evaluation of the XRF and instrumental analysis results. We have found that there were some outliers from XRF and ICP-OES instrumental analysis results for each sample. After removal of 5 outliers among the 50 samples we could obtain the homogeneous samples which have within a reliability of 95% from a statistical analysis result.

• Structural Engineering and Mechanics
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• v.91 no.3
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• pp.279-289
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• 2024

The purpose of this study is to represent a useful alternative for the preliminary seismic vulnerability assessment of existing reinforced concrete buildings by introducing a statistical approach employing the binary logistic regression technique. Two different predictive statistical models, namely full and reduced models, were generated utilizing building characteristics obtained from the damage database compiled after 1999 Düzce earthquake. Among the inspected building parameters, number of stories, overhang ratio, priority index, soft story index, normalized redundancy ratio and normalized lateral stiffness index were specifically selected as the predictor variables for vulnerability classification. As a result, normalized redundancy ratio and soft story index were identified as the most significant predictors affecting seismic vulnerability in terms of life safety performance level. In conclusion, it is revealed that both models are capable of classifying the set of buildings being severely damaged or collapsed with a balanced accuracy of 73%, hence, both are able to filter out high-priority buildings for life safety performance assessment. Thus, in this study, having the same high accuracy as the full model, the reduced model using fewer predictors is proposed as a simple and viable classifier for determining life safety levels of reinforced concrete buildings in the preliminary seismic risk assessment.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1377-1381
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• 2003

This paper describes real time object tracking of 3D objects in 2D image sequences. The moving objects are segmented from the image sequence using morphological operations. The moving objects are segmented by the method of differential image followed by the process of morphological dilation. The moving objects are recognized and tracked using statistical moments. The direction of moving objects are determined by the Hough transform. The straight lines in the moving objects are found with the help of Hough transform. The direction of the moving object is calculated from the orientation of the straight lines in the direction of the principal axes of the moving objects. The direction of the moving object and the displacement of the object in the image sequence is used to calculate the velocity of the moving objects. The simulation results of the proposed method are promising on the test images.

• Journal of Korea Multimedia Society
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• v.19 no.10
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• pp.1747-1758
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• 2016

In this paper, we propose a new fast Hough transform to improve the processing time and line detection of Hough transform that is widely used in various vision systems. First, for the fast processing time, we reduce the number of features by using multi-statistical methods and also reduce the dimension of angle through six separate directions. Next, for improving the line detection, we effectively detect the lines of various directions by designing the line detection method which detects line in proportion to the number of features in six separate directions. The proposed method was evaluated with previous methods and obtained the excellent results. The processing time was improved in about 20% to 50% and line detection was performed better in various directions than conventional methods with experimental images.

• Journal of Korean Society of Water and Wastewater
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• v.18 no.1
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• pp.5-14
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• 2004

A feasibility of using Particle Entrainment Simulator (PES) to evaluate model variables describing sediment entrainment in a river system was investigated. PES in a laboratory was utilized to simulate the sediment resuspension phenomenon in the river and the subsequent relationship between shear rate and sediment entrainment was developed. The total suspended solids (TSS) data from PES was incorporated into statistical models in an effort to describe behaviors of net particle movement in the river. PES was found to be adequate for simulating particle entrainment phenomenon in a river system. Statistical analysis was used to assess propriety of PES data for predictive purposes. The results showed good relationships between PES results and system variables, such as average stream velocity and net particle movement.