• Title/Summary/Keyword: coefficient-based method

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Reliability Based Design Optimization with Variation of Standard Deviation (표준편차의 변동을 고려한 신뢰성 최적설계)

  • Lim, O-Kaung;Kim, Hyung-Wook;Choi, Eun-Ho
    • Journal of the Computational Structural Engineering Institute of Korea
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    • v.21 no.5
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    • pp.413-419
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    • 2008
  • Deterministic design optimization (DO) does not explicitly deal with a variety of factors from inherent randomness and uncertainties. Reliability based design optimization(RBDO) is necessary to use in engineering systems in order to guarantee quality and performance of product. In this paper, design variables are considered as random variables. Standard deviation according to change of design variables have changed as much as coefficient of variation. And, if the standard deviation is error of manufacturing, standard deviation-mean relation is concave form. We obtain reliability index using advanced first order second moment method(AFOSM). This paper is examined by solving two examples and the results are compares with DO, RBDO and suggested RBDO.

A Comparative Study on Clustering Methods for Grouping Related Tags (연관 태그의 군집화를 위한 클러스터링 기법 비교 연구)

  • Han, Seung-Hee
    • Journal of the Korean Society for Library and Information Science
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    • v.43 no.3
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    • pp.399-416
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    • 2009
  • In this study, clustering methods with related tags were discussed for improving search and exploration in the tag space. The experiments were performed on 10 Delicious tags and the strongly-related tags extracted by each 300 documents, and hierarchical and non-hierarchical clustering methods were carried out based on the tag co-occurrences. To evaluate the experimental results, cluster relevance was measured. Results showed that Ward's method with cosine coefficient, which shows good performance to term clustering, was best performed with consistent clustering tendency. Furthermore, it was analyzed that cluster membership among related tags is based on users' tagging purposes or interest and can disambiguate word sense. Therefore, tag clusters would be helpful for improving search and exploration in the tag space.

Diffusion-hydraulic properties of grouting geological rough fractures with power-law slurry

  • Mu, Wenqiang;Li, Lianchong;Liu, Xige;Zhang, Liaoyuan;Zhang, Zilin;Huang, Bo;Chen, Yong
    • Geomechanics and Engineering
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    • v.21 no.4
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    • pp.357-369
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    • 2020
  • Different from the conventional planar fracture and simplified Newton model, for power-law slurries with a lower water-cement ratio commonly used in grouting engineering, flow model in geological rough fractures is built based on ten standard profiles from Barton (1977) in this study. The numerical algorithm is validated by experimental results. The flow mechanism, grout superiority, and water plugging of pseudo plastic slurry are revealed. The representations of hydraulic grouting properties for JRCs are obtained. The results show that effective plugging is based on the mechanical mechanisms of the fluctuant structural surface and higher viscosity at the middle of the fissure. The formulas of grouting parameters are always variable with the roughness and shear movement, which play a key role in grouting. The roughness can only be neglected after reaching a threshold. Grouting pressure increases with increasing roughness and has variable responses for different apertures within standard profiles. The whole process can be divided into three stationary zones and three transition zones, and there is a mutation region (10 < JRCs < 14) in smaller geological fractures. The fitting equations of different JRCs are obtained of power-law models satisfying the condition of -2 < coefficient < 0. The effects of small apertures and moderate to larger roughness (JRCs > 10.8) on the permeability of surfaces cannot be underestimated. The determination of grouting parameters depends on the slurry groutability in terms of its weakest link with discontinuous streamlines. For grouting water plugging, the water-cement ratio, grouting pressure and grouting additives should be determined by combining the flow conditions and the apparent widths of the main fracture and rough surface. This study provides a calculation method of grouting parameters for variable cement-based slurries. And the findings can help for better understanding of fluid flow and diffusion in geological fractures.

Design of FPGA-based Signal Processing of EWRG for Localized Heavy Rainfall Observation (국지성 호우 관측을 위한 FPGA 기반의 전파강수계 신호처리 설계)

  • Choi, Jeong-Ho;Lee, Bae-Kyu;Park, Hyeong-Sam;Park, Jeong-Min;Lim, Sang-Hun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.24 no.9
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    • pp.1215-1223
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    • 2020
  • Recently, the number of natural disasters caused by inclement weather conditions such as localized heavy rainfall, Typhoon, etc. is increasing in Korea, which requires relevant prevention and water management measures. Rain gauges installed on the ground have strengths in continuously·directly measures ground precipitation but cannot provide accurate information on spatial precipitation distribution in the areas without the rain gauges. The present research has designed and developed an electromagnetic-based multi-purpose precipitation gauge(EWRG, Electromagnetic Wave Rain Gauge) that can measure rainfall at the real time, by overcoming spatial representativeness. In this paper, we propose an FPGA-based signal processing design method for EWRG. The signal processing of the EWRG was largely designed by calculating the ADC and DDC of the LFM waveform, pulse compression, correlation coefficient and estimating the precipitation parameter. In this study, the LFM waveform and pulse compressed signal were theoretically analyzed.

A comparison study of Bayesian variable selection methods for sparse covariance matrices (희박 공분산 행렬에 대한 베이지안 변수 선택 방법론 비교 연구)

  • Kim, Bongsu;Lee, Kyoungjae
    • The Korean Journal of Applied Statistics
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    • v.35 no.2
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    • pp.285-298
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    • 2022
  • Continuous shrinkage priors, as well as spike and slab priors, have been widely employed for Bayesian inference about sparse regression coefficient vectors or covariance matrices. Continuous shrinkage priors provide computational advantages over spike and slab priors since their model space is substantially smaller. This is especially true in high-dimensional settings. However, variable selection based on continuous shrinkage priors is not straightforward because they do not give exactly zero values. Although few variable selection approaches based on continuous shrinkage priors have been proposed, no substantial comparative investigations of their performance have been conducted. In this paper, We compare two variable selection methods: a credible interval method and the sequential 2-means algorithm (Li and Pati, 2017). Various simulation scenarios are used to demonstrate the practical performances of the methods. We conclude the paper by presenting some observations and conjectures based on the simulation findings.

Two-dimensional curved panel vibration and flutter analysis in the frequency and time domain under thermal and in-plane load

  • Moosazadeh, Hamid;Mohammadi, Mohammad M.
    • Advances in aircraft and spacecraft science
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    • v.8 no.4
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    • pp.345-372
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    • 2021
  • The analysis of nonlinear vibrations, buckling, post-buckling, flutter boundary determination and post-flutter behavior of a homogeneous curved plate assuming cylindrical bending is conducted in this article. Other assumptions include simply-supported boundary conditions, supersonic aerodynamic flow at the top of the plate, constant pressure conditions below the plate, non-viscous flow model (using first- and third-order piston theory), nonlinear structural model with large deformations, and application of mechanical and thermal loads on the curved plate. The analysis is performed with constant environmental indicators (flow density, heat, Reynolds number and Mach number). The material properties (i.e., coefficient of thermal expansion and modulus of elasticity) are temperature-dependent. The equations are derived using the principle of virtual displacement. Furthermore, based on the definitions of virtual work, the potential and kinetic energy of the final relations in the integral form, and the governing nonlinear differential equations are obtained after fractional integration. This problem is solved using two approaches. The frequency analysis and flutter are studied in the first approach by transferring the handle of ordinary differential equations to the state space, calculating the system Jacobin matrix and analyzing the eigenvalue to determine the instability conditions. The second approach discusses the nonlinear frequency analysis and nonlinear flutter using the semi-analytical solution of governing differential equations based on the weighted residual method. The partial differential equations are converted to ordinary differential equations, after which they are solved based on the Runge-Kutta fourth- and fifth-order methods. The comparison between the results of frequency and flutter analysis of curved plate is linearly and nonlinearly performed for the first time. The results show that the plate curvature has a profound impact on the instability boundary of the plate under supersonic aerodynamic loading. The flutter boundary decreases with growing thermal load and increases with growing curvature.

Correlation Between Knee Muscle Strength and Maximal Cycling Speed Measured Using 3D Depth Camera in Virtual Reality Environment

  • Kim, Ye Jin;Jeon, Hye-seon;Park, Joo-hee;Moon, Gyeong-Ah;Wang, Yixin
    • Physical Therapy Korea
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    • v.29 no.4
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    • pp.262-268
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    • 2022
  • Background: Virtual reality (VR) programs based on motion capture camera are the most convenient and cost-effective approaches for remote rehabilitation. Assessment of physical function is critical for providing optimal VR rehabilitation training; however, direct muscle strength measurement using camera-based kinematic data is impracticable. Therefore, it is necessary to develop a method to indirectly estimate the muscle strength of users from the value obtained using a motion capture camera. Objects: The purpose of this study was to determine whether the pedaling speed converted using the VR engine from the captured foot position data in the VR environment can be used as an indirect way to evaluate knee muscle strength, and to investigate the validity and reliability of a camera-based VR program. Methods: Thirty healthy adults were included in this study. Each subject performed a 15-second maximum pedaling test in the VR and built-in speedometer modes. In the VR speedometer mode, a motion capture camera was used to detect the position of the ankle joints and automatically calculate the pedaling speed. An isokinetic dynamometer was used to assess the isometric and isokinetic peak torques of knee flexion and extension. Results: The pedaling speeds in VR and built-in speedometer modes revealed a significantly high positive correlation (r = 0.922). In addition, the intra-rater reliability of the pedaling speed in the VR speedometer mode was good (ICC [intraclass correlation coefficient] = 0.685). The results of the Pearson correlation analysis revealed a significant moderate positive correlation between the pedaling speed of the VR speedometer and the peak torque of knee isokinetic flexion (r = 0.639) and extension (r = 0.598). Conclusion: This study suggests the potential benefits of measuring the maximum pedaling speed using 3D depth camera in a VR environment as an indirect assessment of muscle strength. However, technological improvements must be followed to obtain more accurate estimation of muscle strength from the VR cycling test.

An effective automated ontology construction based on the agriculture domain

  • Deepa, Rajendran;Vigneshwari, Srinivasan
    • ETRI Journal
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    • v.44 no.4
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    • pp.573-587
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    • 2022
  • The agricultural sector is completely different from other sectors since it completely relies on various natural and climatic factors. Climate changes have many effects, including lack of annual rainfall and pests, heat waves, changes in sea level, and global ozone/atmospheric CO2 fluctuation, on land and agriculture in similar ways. Climate change also affects the environment. Based on these factors, farmers chose their crops to increase productivity in their fields. Many existing agricultural ontologies are either domain-specific or have been created with minimal vocabulary and no proper evaluation framework has been implemented. A new agricultural ontology focused on subdomains is designed to assist farmers using Jaccard relative extractor (JRE) and Naïve Bayes algorithm. The JRE is used to find the similarity between two sentences and words in the agricultural documents and the relationship between two terms is identified via the Naïve Bayes algorithm. In the proposed method, the preprocessing of data is carried out through natural language processing techniques and the tags whose dimensions are reduced are subjected to rule-based formal concept analysis and mapping. The subdomain ontologies of weather, pest, and soil are built separately, and the overall agricultural ontology are built around them. The gold standard for the lexical layer is used to evaluate the proposed technique, and its performance is analyzed by comparing it with different state-of-the-art systems. Precision, recall, F-measure, Matthews correlation coefficient, receiver operating characteristic curve area, and precision-recall curve area are the performance metrics used to analyze the performance. The proposed methodology gives a precision score of 94.40% when compared with the decision tree(83.94%) and K-nearest neighbor algorithm(86.89%) for agricultural ontology construction.

Soft computing based mathematical models for improved prediction of rock brittleness index

  • Abiodun I. Lawal;Minju Kim;Sangki Kwon
    • Geomechanics and Engineering
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    • v.33 no.3
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    • pp.279-289
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    • 2023
  • Brittleness index (BI) is an important property of rocks because it is a good index to predict rockburst. Due to its importance, several empirical and soft computing (SC) models have been proposed in the literature based on the punch penetration test (PPT) results. These models are very important as there is no clear-cut experimental means for measuring BI asides the PPT which is very costly and time consuming to perform. This study used a novel Multivariate Adaptive regression spline (MARS), M5P, and white-box ANN to predict the BI of rocks using the available data in the literature for an improved BI prediction. The rock density, uniaxial compressive strength (σc) and tensile strength (σt) were used as the input parameters into the models while the BI was the targeted output. The models were implemented in the MATLAB software. The results of the proposed models were compared with those from existing multilinear regression, linear and nonlinear particle swarm optimization (PSO) and genetic algorithm (GA) based models using similar datasets. The coefficient of determination (R2), adjusted R2 (Adj R2), root-mean squared error (RMSE) and mean absolute percentage error (MAPE) were the indices used for the comparison. The outcomes of the comparison revealed that the proposed ANN and MARS models performed better than the other models with R2 and Adj R2 values above 0.9 and least error values while the M5P gave similar performance to those of the existing models. Weight partitioning method was also used to examine the percentage contribution of model predictors to the predicted BI and tensile strength was found to have the highest influence on the predicted BI.

Validity assessment for competency development in clinical dental hygiene education based on dental hygiene process of care (치위생과정에 기반한 임상치위생학 교육과정 역량 개발을 위한 타당도 평가)

  • Jin-Sun Choi;Sun-Jung Shin;Bo-Mi Shin;Hyo-Jin Lee;Hye-Young Yoon;Soo-Myoung Bae
    • Journal of Korean society of Dental Hygiene
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    • v.24 no.1
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    • pp.45-56
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    • 2024
  • Objectives: Before implementing a competency-based clinical dental hygiene curriculum, it is essential to establish competency development as a foundational educational objective. Therefore, this study aimed to develop the competency of clinical dental hygiene with secured validity using the Delphi survey method. Methods: Dental hygiene competencies were categorized within the dental hygiene process stages, and questions were formulated accordingly. A Delphi survey involving ten qualified experts was conducted to refine the final items based on their review opinions. Results: The expert Delphi survey confirmed that all items met stability criteria, with CVI values of 0.80 or higher, CVR values of 0.60 or higher, and a CV coefficient of variation of 0.5 or less. In total, 42 items were derived. Conclusions: Clinical dental hygiene can contribute to developing specialized dental hygienists if the competencies derived from this study are well applied to the standardized curriculum and operations.