nonlinear static procedure (nsp) is a common technique to predict seismic demands on various building structures by subjecting a monotonically increasing horizontal loading (pushover) to the structure. therefore, the pushover analysis is an important part of each nsp. accordingly, the current paper aims at investigating the efficiencyof various algorithms of lateral load patterns applied to the...

In the present study, an adaptation of the Markov Random Field (MRF) segmentation model, by means of the stationary wavelet transform (SWT), applied to complementary DNA (cDNA) microarray images is proposed (WMRF). A 3-level decomposition scheme of the initial microarray image was performed, followed by a soft thresholding filtering technique. With the inverse process, a Denoised image was crea...

The unanticipated brittle fracture of connection of the steel moment resisting frame (SMRF) occurred in 1994 the Northridge earthquake. Since then, the researches for the vulnerability of connection of the existing SMRF and for rehabilitation of those buildings were conducted. This paper suggests performance-based optimal seismic retrofit technique using connection upgrade. For optimal design, ...

Abstract This study presents the impact of near-field and far-field earthquakes on seismic design Intermediate Moment Resisting Frame (IMRF) Special (SMRF) structures through FEMA (Federal Emergency Management Agency) P695 methodology to highlight importance probabilistic collapse as well performance factors these structures. The purpose this is investigate steel intermediate special moment res...

The present work is aimed at assessing the impact of strong column-weak beam (SCWB) criterion on seismic performance of optimally designed steel moment frames. To this end, different SCWB ratios are considered for steel special moment resisting frame (SMRF) structures and performance-based design optimization process is implemented with the aid of an efficient metaheuristic. The seismic collaps...

In this paper, we address the problem of robustly recovering several instances of a curve model from a single noisy data set with outliers. Using M-estimators revisited in a Lagrangian formalism, we derive an algorithm that we call SMRF, which extends the classical Iterative Reweighted Least Squares algorithm (IRLS). Compared to the IRLS, it features an extra probability ratio, which is classic...

In this paper, we address the problem of robustly recovering several instances of a curve model from a single noisy data set with outliers. Using M-estimators revisited in a Lagrangian formalism, we derive an algorithm that we call Simultaneous Multiple Robust Fitting (SMRF), which extends the classical Iterative Reweighted Least Squares algorithm (IRLS). Compared to the IRLS, it features an ex...