• Title/Summary/Keyword: analysis parameters

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Dynamic response analysis of closed loop control system for intelligent truss structures based on probability

  • Gao, W.;Chen, J.J.;Ma, H.B.;Ma, X.S.;Cui, M.T.
    • Structural Engineering and Mechanics
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    • 제15권2호
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    • pp.239-248
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    • 2003
  • The dynamic response analysis of closed loop control system based on probability for the intelligent truss structures with random parameters is presented. The expressions of numerical characteristics of structural dynamic response of closed loop control system are derived by means of the mode superposition method, in which the randomness of physical parameters of structural materials, geometric dimensions of active bars and passive bars, applied loads and control forces are considered simultaneously. The influences of the randomness of them on structural dynamic response are inspected by several engineering examples and some significant conclusions are obtained.

비주거 건축물의 외피요소에 대한 민감도 분석 (Sensitivity Analysis of Building Envelope of Non-Dwelling Buildings)

  • 김경아;박진서;유기형;문현준
    • 한국태양에너지학회 논문집
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    • 제35권1호
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    • pp.53-60
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    • 2015
  • The ECO2 building energy simulation program is used on the assessment project for building energy certification of non-dwelling buildings in Korea. In the design of energy efficient buildings, it is beneficial to identify the most important design parameters in oder to more efficiently develop alternative design solutions or reach optimized design solutions. The sensitivity analyses will be used at a reasonable early stage of the building design process, where it is still possible to influence the most important design parameters. In this study, the sensitivity analysis is focused on building envelope parameters such as U-values, SHGC and Wall-window ration.

Reliability analysis of tunnel face stability considering seepage effects and strength conditions

  • Park, Jun Kyung
    • Geomechanics and Engineering
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    • 제29권3호
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    • pp.331-338
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    • 2022
  • Face stability analyses provides the most probable failure mechanisms and the understanding about parameters that need to be considered for the evaluation of ground movements caused by tunneling. After the Upper Bound Method (UBM) solution which can consider the influence of seepage forces and depth-dependent effective cohesion is verified with the numerical experiments, the probabilistic model is proposed to calculate the unbiased limiting tunnel collapse pressure. A reliability analysis of a shallow circular tunnel driven by a pressurized shield in a frictional and cohesive soil is presented to consider the inherent uncertainty in the input parameters and the proposed model. The probability of failure that exceeding a specified applied pressure at the tunnel face is estimated. Sensitivity and importance measures are computed to identify the key parameters and random variables in the model.

성대 폴립 환자를 대상으로 한 GRBAS 척도와 MDVP 측정치 간의 상관관계 연구 (The Correlation between GRBAS Scales and MDVP Parameters on the Pathologic Voices of the Patients with Vocal Polyps)

  • 표화영;최성희;임성은;심현섭;최홍식;김광문
    • 대한후두음성언어의학회지
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    • 제10권2호
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    • pp.154-163
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    • 1999
  • GRBAS scale, the tool fir the perceptual evaluation of voice, demands the experience of judges, and MDVP parameters of CSL, the tool for the objective measurements of voice quality demands the exact interpretation of the analyzed results. The two tools should be used as compensatory evaluation methods, so the experimental study was performed to investigate the correlation between GRBAS scales and MDVP parameters by using the pathologic voice of the 30 patients with vocal polyps, and to know the significant MDVP parameters which the inexperienced GRBAS scale judges should attend to. The 30 subjects voices, saved in MDVP of CSL were analyzed by its own analysis program, and three experienced voice therapists judged the same voices by using GRBAS scales. The correlations between them were analyzed by Spearman Rank Correlation Coefficient. As results, among the 29 MDVP parameters, 22 parameters showed statistically significant correlation with Grade(G) scale(p<0.05). And it was found that Roughness(R) scale showed significant correlation with 18 parameters, Breathiness(B) scale with 17 parameters, Strain(S) scale with 12 parameters. In Asthenicity(A) scale, no parameter showed significant correlation. On the whole, significantly high correlation were found in the parameters related with pitch ind amplitude perturbation, especially, the amplitude perturbation.

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Development of Parameters for Diagnosing Laryngeal Diseases

  • Kim, Yong-Ju;Wang, Soo-Geun;Kim, Gi-Ryun;Kwon, Soon-Bok;Jeon, Kye-Rok;Back, Moo-Jin;Yang, Byung-Gon;Jo, Cheol-Woo;Kim, Hyung-Soon
    • 음성과학
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    • 제10권1호
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    • pp.117-129
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    • 2003
  • Many people suffer from various laryngeal diseases. Since we can notice voice change easily, acoustic analysis can be helpful to diagnose the diseases. Several attempts have been made to clarify the relation between the parameters and the state of sick vocal folds but any decisive parameters are not found yet. The purpose of this study was to select and develop those parameters useful for diagnosing and differentiating laryngeal diseases. We examined eight MDVP parameters, and two additional MFCC and LPC parameters obtained from the production of an open vowel by 252 subjects with or without laryngeal diseases. Using a statistical procedure through the artificial neural networks, we attempted to differentiate laryngeal disease groups. Results showed that the LPC parameters indicated the highest differentiating rate by the networks followed by the MFCC and the MDVP parameters. In addition, Jita, Shim and NHR among the MDVP parameters came out better parameters in diagnosing laryngeal diseases.

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Estimation of ultimate torque capacity of the SFRC beams using ANN

  • Engin, Serkan;Ozturk, Onur;Okay, Fuad
    • Structural Engineering and Mechanics
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    • 제53권5호
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    • pp.939-956
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    • 2015
  • In this study, in order to propose an efficient model to predict the torque capacity of steel fiber reinforced concrete (SFRC) beams, the existing experimental data related to torsional response of beams is reviewed. It is observed that existing data neglects the effects of some parameters on the variation of torque capacity. Thus, an experimental research was also conducted to obtain the effects of neglected parameters. In the experimental study, a total of seventeen SFRC beams are tested against torsion. The parameters considered in the experiments are concrete compressive strength, steel fiber aspect ratio, volumetric ratio of steel fibers and longitudinal reinforcement ratio. The effect of each parameter is discussed in terms of torque versus unit angle of twist graphs. The data obtained from this experimental research is also combined with the data got from previous studies and employed in artificial neural network (ANN) analysis to estimate the ultimate torque capacity of SFRC beams. In addition to parameters considered in the experiments, aspect ratio of beam cross-section, yield strengths of both transverse and longitudinal reinforcements, and transverse reinforcement ratio are also defined as parameters in ANN analysis due to their significant effects observed in previous studies. Assessment of the accuracy of ANN analysis in estimating the ultimate torque capacity of SFRC beams is performed by comparing the analytical and experimental results. Comparisons are conducted in terms of root mean square error (RMSE), mean absolute error (MAE) and coefficient of efficiency ($E_f$). The results of this study revealed that addition of steel fibers increases the ultimate torque capacity of reinforced concrete beams. It is also found that ANN is a powerful method and a feasible tool to estimate ultimate torque capacity of both normal and high strength concrete beams within the range of input parameters considered.

정상군 및 허혈성 심질환 환자군에서의 심자도 파라미터 비교 (Comparison of Magnetocardiogram Parameters Between a Ischemic Heart Disease Group and Control Group)

  • 박종덕;허영;진승오;전성채
    • 대한전기학회논문지:시스템및제어부문D
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    • 제54권11호
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    • pp.680-688
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    • 2005
  • The electrical current generated by heart creates not only electric potential but also a magnetic field. We have observed electrophysiological phenomena of the heart by measuring components of magnetocardiogram(MCG) using 61 channel superconducting quantum interference device(SQUD) system. We have analyzed the possibility and characteristics of MCG parameters for diagnosis of ischemic heart disease. A technique for automatic analysis of MCG signals in time domain was developed. The methods for detecting the position, the interval, the amplitude ratio, and the direction of single current dipole were examined in the MCG wave. The position and interval parameters were obtained by calculating the gradients of a envelope curve which could be formed by the difference between the maximum and minimum envelope of multi-channel MCG signals. We show some differences of the frequency contour map between the normal MCG and the abnormal (ischemic heart disease) MCG. The direction of single current dipole can be defined by rotating the magnetic field according to Biot-Savart's law at each point of MCG signals. In this study, we have examined the direction of single current dipole from searching for the centroids of positive and negative magnetic fields. The amplitude ratio parameters for measuring 57 deviation consisted of A$_{T}$/A$_{R}$ and other ratios. and We developed a new analysis method, which is based on the frequency contour map of electromagnetic field. Using theses parameters, we founded significant differences between normal subjects and ischemic patients in some parameters.

Prediction of Cobb-angle for Monitoring System in Adolescent Girls with Idiopathic Scoliosis using Multiple Regression Analysis

  • Seo, Eun Ji;Choi, Ahnryul;Oh, Seung Eel;Park, Hyun Joon;Lee, Dong Jun;Mun, Joung H.
    • Journal of Biosystems Engineering
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    • 제38권1호
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    • pp.64-71
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    • 2013
  • Purpose: The purpose of this study was to select standing posture parameters that have a significant difference according to the severity of spinal deformity, and to develop a novel Cobb angle prediction model for adolescent girls with idiopathic scoliosis. Methods: Five normal adolescents girls with no history of musculoskeletal disorders, 13 mild scoliosis patients (Cobb angle: $10^{\circ}-25^{\circ}$), and 14 severe scoliosis patients (Cobb angle: $25^{\circ}-50^{\circ}$) participated in this study. Six infrared cameras (VICON) were used to acquire data and 35 standing parameters of scoliosis patients were extracted from previous studies. Using the ANOVA and post-hoc test, parameters that had significant differences were extracted. In addition, these standing posture parameters were utilized to develop a Cobb-angle prediction model through multiple regression analysis. Results: Twenty two of the parameters showed differences between at least two of the three groups and these parameters were used to develop the multi-linear regression model. This model showed a good agreement ($R^2$ = 0.92) between the predicted and the measured Cobb angle. Also, a blind study was performed using 5 random datasets that had not been used in the model and the errors were approximately $3.2{\pm}1.8$. Conclusions: In this study, we demonstrated the possibility of clinically predicting the Cobb angle using a non-invasive technique. Also, monitoring changes in patients with a progressive disease, such as scoliosis, will make possible to have determine the appropriate treatment and rehabilitation strategies without the need for radiation exposure.

Efficient parameters to predict the nonlinear behavior of FRP retrofitted RC columns

  • Mahdavi, Navideh;Ahmadi, Hamid Reza;Bayat, Mahmoud
    • Structural Engineering and Mechanics
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    • 제70권6호
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    • pp.703-710
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    • 2019
  • While fiber-reinforced plastic (FRP) materials have been largely used in the retrofitting of concrete buildings, its application has been limited because of some problems such as de-bonding of FRP layers from the concrete surface. This paper is the part of a wide experimental and analytical investigation about flexural retrofitting of reinforced concrete (RC) columns using FRP and mechanical fasteners (MF). A new generation of MF is proposed, which is applicable for retrofitting of RC columns. Furthermore, generally, to evaluate a retrofitted structure the nonlinear static and dynamic analyses are the most accurate methods to estimate the performance of a structure. In the nonlinear analysis of a structure, accurate modeling of structural elements is necessary for estimation the reasonable results. So for nonlinear analysis of a structure, modeling parameters for beams, columns, and beam-column joints are essential. According to the concentrated hinge method, which is one of the most popular nonlinear modeling methods, structural members shall be modeled using concentrated or distributed plastic hinge models using modeling parameters. The nonlinear models of members should be capable of representing the inelastic response of the component. On the other hand, in performance based design to make a decision about a structure or design a new one, numerical acceptance should be determined. Modeling parameters and numerical acceptance criteria are different for buildings of different types and for different performance levels. In this paper, a new method was proposed for FRP retrofitted columns to avoid FRP debonding. For this purpose, mechanical fasteners were used to achieve the composite behavior of FRP and concrete columns. The experimental results showed that the use of the new method proposed in this paper increased the flexural strength and lateral load capacity of the columns significantly, and a good composition of FRP and RC column was achieved. Moreover, the modeling parameters and acceptance criteria were presented, which were derived from the experimental study in order to use in nonlinear analysis and performance-based design approach.

SHAP 분석 기반의 넙치 질병 분류 입력 파라미터 최적화 (Optimizing Input Parameters of Paralichthys olivaceus Disease Classification based on SHAP Analysis)

  • 조경원;백란
    • 한국전자통신학회논문지
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    • 제18권6호
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    • pp.1331-1336
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    • 2023
  • 머신러닝을 이용한 텍스트 기반 어류 질병 분류에서 머신러닝 모델의 입력 파라미터가 너무 많은 문제가 존재하지만, 성능의 문제로 임의로 입력 파라미터를 줄일 수 없다. 본 논문에서는 이 문제를 해결하고자 SHAP 분석 기법을 활용해 넙치 질병 분류에 특화된 입력 파라미터 최적화 방안을 제시한다. 제안한 방법은 SHAP 분석 기법을 적용하여 넙치 질병 문진표에서 추출한 질병 정보의 데이터 전처리와 AutoML을 활용한 머신러닝 모델 평가 과정을 포함한다. 이를 통해 AutoML의 입력 파라미터의 성능을 평가하고, 최적의 입력 파라미터 조합을 도출한다. 본 연구에서 제안 방법은 필요한 입력 파라미터 수를 감소시키면서도 기존의 성능을 유지할 수 있을 것으로 기대되며, 이는 텍스트 기반 넙치 질병 분류의 효율성 및 실용성을 높이는 데 기여할 것이다.