• Smart Structures and Systems
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• v.32 no.1
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• pp.1-7
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• 2023

In modal analysis, the mode shape reflects the vibration characteristics of the structure, and thus it is widely performed for finite element model updating and structural health monitoring. Generally, the acceleration-based mode shape is suitable to express the characteristics of structures for the translational vibration; however, it is difficult to represent the rotational mode at boundary conditions. A tilt sensor and gyroscope capable of measuring rotational mode are used to analyze the overall behavior of the structure, but extracting its mode shape is the major challenge under the small vibration always. Herein, we conducted a feasibility study on a multi-mode shape estimating approach utilizing a single physical quantity signal. The basic concept of the proposed method is to receive multi-metric dynamic responses from two sensors and obtain mode shapes through bridge loading test with relatively large deformation. In addition, the linear transformation matrix for estimating two mode shapes is derived, and the mode shape based on the gyro sensor data is obtained by acceleration response using ambient vibration. Because the structure's behavior with respect to translational and rotational mode can be confirmed, the proposed method can obtain the total response of the structure considering boundary conditions. To verify the feasibility of the proposed method, we pre-measured dynamic data acquired from five accelerometers and five gyro sensors in a lab-scale test considering bridge structures, and obtained a linear transformation matrix for estimating the multi-mode shapes. In addition, the mode shapes for two physical quantities could be extracted by using only the acceleration data. Finally, the mode shapes estimated by the proposed method were compared with the mode shapes obtained from the two sensors. This study confirmed the applicability of the multi-mode shape estimation approach for accurate damage assessment using multi-dimensional mode shapes of bridge structures, and can be used to evaluate the behavior of structures under ambient vibration.

• Korean Journal of Environmental Biology
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• v.31 no.2
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• pp.96-104
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• 2013

The objectives of this study were to analyze chemical the water quality related to the fish community and to evaluate the ecosystem health based on the faunal composition and guild structure in 2007 in Baekma River. Mean concentrations of biological oxygen demand (BOD) and chemical oxygen demand (COD) were 2.8 and $4.0mg\;L^{-1}$, respectively and total nitrogen (TN) and total phosphorus (TP) were $5.0mg\;L^{-1}$ and $158{\mu}g\;L^{-1}$, which is indicating that the river is in an eutrophic state. Especially, organic pollution and eutrophication occurred in the downstream reach of Baekma River. A total of 19 fish species were collected during the study and the most dominant species was Opsariichthys uncirostris amurensis accounted 48% of the total abundances. The proportion of sensitive species was low (2.3%), compared with that of tolerant species (71.8%). These results suggest that tolerant species and the biotic quality of the fish community was severely degraded. According to the multi-metric model, the Index of Biological Integrity (IBI), the mean model value of the fish community in Baekma River was estimated as 14.8 indicating a "poor" condition. The minimum values of the IBI were observed in the downstreams, and this was mainly attributed to chemical pollutions of nutrients (N, P) and organic matters.

• International Journal of Quality Innovation
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• v.3 no.2
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• pp.113-131
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• 2002

The relationships among multi-dimensional data (such as medical examination data) with ambiguity and variation are difficult to explore. The traditional approach to building a data classification system requires the formulation of rules by which the input data can be analyzed. The formulation of such rules is very difficult with large sets of input data. This paper first describes two classification approaches using back-propagation (BP) neural network and Mahalanobis distance (MD) classifier, and then proposes two classification approaches for multi-dimensional feature selection. The first one proposed is a feature selection procedure from the trained back-propagation (BP) neural network. The basic idea of this procedure is to compare the multiplication weights between input and hidden layer and hidden and output layer. In order to simplify the structure, only the multiplication weights of large absolute values are used. The second approach is Mahalanobis-Taguchi system (MTS) originally suggested by Dr. Taguchi. The MTS performs Taguchi's fractional factorial design based on the Mahalanobis distance as a performance metric. We combine the automatic thresholding with MD: it can deal with a reduced model, which is the focus of this paper In this work, two case studies will be used as examples to compare and discuss the complete and reduced models employing BP neural network and MD classifier. The implementation results show that proposed approaches are effective and powerful for the classification.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2003.05a
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• pp.8-13
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• 2003

This paper considers a continuous-review two-echelon inventory control problem with one-to-one replenishment policy incorporated and with lost sales allowed where demand arrives In a stationary Poisson process The problem Is formulated using METRIC-approximation in a combined approach of pricing and (S-1.S) Inventory policy, for which an iterative solution algorithm is derived with respect to the corresponding one-warehouse multi-retailor supply chain. Specifically, decisions on retail pricing and warehouse inventory policies are made in integration to maximize total profit in the supply chain. The objective function of the model consists of sub-functions of revenue and cost (holding cost and penalty cost). To test the effectiveness and efficiency of the proposed algorithm, numerical experiments are performed The computational results show that the proposed algorithm is efficient and derives quite good decisions

• Smart Structures and Systems
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• v.23 no.2
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• pp.123-139
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• 2019

Impact forces induced by external object collisions can cause serious damages to civil engineering structures. While accurate and prompt identification of such impact forces is a critical task in structural health monitoring, it is not readily feasible for civil structures because the force measurement is extremely challenging and the force location is unpredictable for full-scale field structures. This study proposes a novel approach for identification of impact force including its location and time history using a small number of multi-metric observations. The method combines an augmented Kalman filter (AKF) and Genetic algorithm for accurate identification of impact force. The location of impact force is statistically determined in the way to minimize the AKF response estimate error at measured locations and then time history of the impact force is accurately constructed by optimizing the error co-variances of AKF using Genetic algorithm. The efficacy of proposed approach is numerically demonstrated using a truss and a plate model considering the presence of modelling error and measurement noises.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2021.06a
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• pp.105-108
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• 2021

Generative adversarial networks (GANs) have reached a great result at creating the synthesis image, especially in the face generation task. Unlike other deep learning tasks, the input of GANs is usually the random vector sampled by a probability distribution, which leads to unstable training and unpredictable output. One way to solve those problems is to employ the label condition in both the generator and discriminator. CelebA and FFHQ are the two most famous datasets for face image generation. While CelebA contains attribute annotations for more than 200,000 images, FFHQ does not have attribute annotations. Thus, in this work, we introduce a method to learn the attributes from CelebA then predict both soft and hard labels for FFHQ. The evaluated result from our model achieves 0.7611 points of the metric is the area under the receiver operating characteristic curve.

• Journal of Information Processing Systems
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• v.10 no.4
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• pp.503-522
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• 2014

In the cursive handwriting recognition process, script trajectory segmentation and modeling represent an important task for large or open lexicon context that becomes more complicated in multi-writer applications. In this paper, we will present a developed system of Arabic online handwriting modeling based on graphemes segmentation and the extraction of its geometric features. The main contribution consists of adapting the Fourier descriptors to model the open trajectory of the segmented graphemes. To segment the trajectory of the handwriting, the system proceeds by first detecting its baseline by checking combined geometric and logic conditions. Then, the detected baseline is used as a topologic reference for the extraction of particular points that delimit the graphemes' trajectories. Each segmented grapheme is then represented by a set of relevant geometric features that include the vector of the Fourier descriptors for trajectory shape modeling, normalized metric parameters that model the grapheme dimensions, its position in respect to the baseline, and codes for the description of its associated diacritics.

• Journal of Ecology and Environment
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• v.39 no.1
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• pp.71-80
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• 2016

The main goal of this study is to develop a multi-metric fishway assessment model (M_m-FA) and evaluate the efficiency of fishway. The M_m-FA model has three major fishway components with nine metrics: structural characteristics, hydraulic/hydrologic features, and biological attributes. The model was developed for diagnosing and assessing fishway efficiency and tested to Juksan Weir at the Yeongsan River Watershed. Structural characteristics of fishway included slope of the fishway (M₁), ratios of fishway width to stream width (M₂), and the proportion of orifice clogging and orifice size (M₃). Hydraulic/hydrologic characteristics included depth of fishway entrance head (M₄), depth of exit tail (M₅), and current velocity of inner fishway (M₆). Biological characteristics included fish species ratio of inner fishway to upper-lower weir (M₇), fish length distribution (M₈), and the proportion of migratory fish species to the total number of species (M₉). Overall, the assessment of fishway efficiency showed the total score of the M_m-FA model was 25 in the Juksan Weir, indicating "good condition" by the criteria of the five-level classification system. The M_m-FA model may be used as a key tool for the assessment of fishway efficiency, especially on the 16 weirs constructed for the "Four Rivers Restoration Project" after a partial calibration of M_m-FA model.

• Journal of Environmental Impact Assessment
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• v.21 no.6
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• pp.841-857
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• 2012

Preliminary ecological environmental assessments including physico-chemical constituents, water quality, fish fauna analysis, physical habitat health, and ecological health assessment were conducted as a primary step for Jeungchon micro-habitat ecosystem restoration in 2012. Water chemistry analysis of conductivity, dissolved oxygen, chlorophyll-a and etc. indicated that there were no significant differences(p < 0.05) among 6 sites between the headwaters and downstream. Multi-metric model analysis of Qualitative Habitat Evaluation Index(QHEI) showed that brooklets were at "good condition" as a mean QHEI of 158.7(n = 6) and the longitudinal differences of the model values between the sites were minor(QHEI range: 153 - 165). Total fish species and the number of individuals were 12 and 481, respectively, and dominant species were Zacco platypus(49.5%) and Zacco koreanus(36.8%). Tolerance guild analysis showed that the proportion of sensitive species($S_S$) had a negative linear function[$S_S=86.35-0.31(D_H)$; $R^2$ = 0.892, p < 0.01] with a distance from the headwaters, while the proportion of tolerant species($T_S$) had a positive linear function($R^2$ = 0.950, F = 90.28, p < 0.001) with the distance. Trophic feeding guild analysis showed that the proportion of insectivore species($I_n$) had a negative linear function($R^2$ = 0.934, p < 0.01) with a distance from the headwaters, while the proportion of omnivore species($O_m$) had a positive linear function($R^2$ = 0.958, p < 0.001) with the distance. Index of Biological Integrity(IBI) model, based on fish assemblages, showed a "fair condition" as a mean IBI of 23(n = 6), and there was a distinct differences of ecological health between the headwaters(S1 = 30; "good condition") and the downstreams(S6 = 14; "poor condition"). Overall, the preliminary environmental impact assessments suggest that water quality, physical habitat conditions(QHEI model), and ecological health(IBI model) were maintained well, even if the state was not an excellent conditions.

• Journal of Ecology and Environment
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• v.39 no.1
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• pp.61-70
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• 2016

Major objectives of the study were to analyze chemical and biological influences of the river ecosystem on the artificial weir construction at three regions of Sejong-Weir (S_j-W), Gongju-Weir (G_j-W), and Baekje-Weir (B_j-W) during 2008-2012. After the weir construction, the discharge volume increased up to 2.9 times, and biological oxygen demand (BOD) and electrical conductivity (EC) significantly decreased (p < 0.05). Also, the decrease of total phosphorus (TP) was also evident after the weir construction, but still hyper-eutrophic conditions, based on criteria by , were maintained. Multi-metric model of Index of Biological Integrity (IBI) showed that IBI values averaged 21.0 (range: 20-22; fair condition) in the B_wc, and 14.3 (range: 12-18; poor condition) in the A_wc. The model values of IBI in S_j-W and G_j-W were significantly decreased after the weir construction. The model of Self-Organizing Map (SOM) showed that two groups (cluster I and cluster II) of B_wc and A_wc were divided in the analysis based on the clustering map trained by the SOM. Principal Component Analysis (PCA) was similar to the results of the SOM analysis. Taken together, this research suggests that the weir construction on the river modified the discharge volume and the physical habitat structures along with distinct changes of some chemical water quality. These physical and chemical factors influenced the ecosystem health, measured as a model value of IBI.