Sharif Digital Repository

The main motivation of this study is to address the challenges due to high penetration of renewable distributed energy resources (DERs) and efficiently benefit from DERs in distribution system planning (DSP). This paper considers a decentralized enhanced platform for DSP which is coordinated with bulk power system planning (PSP) to keep the optimality and security of the whole power system. In the proposed coordinated approach, distribution system operators (DSOs) plan and operate DERs to upgrade their local distribution areas (LDAs), supply forecasting local load growth, and avoid or defer costly generation and transmission expansion planning at the bulk power system. The proposed DSP model... 

This paper presents a synthesis strategy for impact force localization and identification of framed structures in time-domain using a two-step wavelet-based fitness evaluation scheme in conjunction with genetic and water cycle algorithms. For this purpose, a straightforward approach is developed for sensitivity analysis of accelerations and spatial signal connecting the peak values. The proposed scheme is capable of using diverse scales of wavelet functions at considerably small sampling rates. A decimal genetic algorithm (GA) coding system and a recently developed water cycle algorithm (WCA) are improved to be used for impact localization and identification, respectively. The fitness... 

In this paper, a computational technique is presented based on a concrete plastic-damage model to investigate the effect of FRP strengthening of reinforced concrete arches. A plastic-damage model was utilized to capture the behavior of concrete. The interface between the FRP and concrete was modeled using a cohesive fracture model. In order to validate the accuracy of the damage-plastic model, a single element was employed under monotonic tension, monotonic compression, and cyclic tension loads. An excellent agreement was observed between the predefined strain-stress curve and that obtained by the numerical model. Furthermore, the accuracy of the cohesive fracture model was investigated by... 

In this paper, a computational technique is presented based on a concrete plastic-damage model to investigate the effect of FRP strengthening of reinforced concrete arches. A plastic-damage model was utilized to capture the behavior of concrete. The interface between the FRP and concrete was modeled using a cohesive fracture model. In order to validate the accuracy of the damage-plastic model, a single element was employed under monotonic tension, monotonic compression, and cyclic tension loads. An excellent agreement was observed between the predefined strain-stress curve and that obtained by the numerical model. Furthermore, the accuracy of the cohesive fracture model was investigated by... 

Damage detection and structural health monitoring using the electromechanical impedance method has been accepted as an effective technique between various approaches of nondestructive evaluation. Many efforts have been made on experimental methods for obtaining the impedance of structures. However, expensive experimental methods encourage researchers to develop theoretical models. In this paper, a new theoretical model is developed for damage detection of L-shaped beams, which are basic components in frame structures, with an embedded piezoelectric wafer active sensor. For this purpose, a chirp signal of voltage is used to activate a piezoelectric patch for inducing local strains that lead... 

A three-dimensional model has been developed to describe the multiphase release of macromolecular drugs encapsulated in a hydrogel. The heterogeneity of network mesh size was considered by assigning varying diffusion coefficients to the network lattices randomly. Using a stochastic approach, the random nature of diffusion of drug molecules was captured within the network. The simplest form of distribution containing two diffusion coefficients was tested. To generate the drug release profiles for experimental validation under the limitation of computational cost, a simple scaling relationship was employed. Unlike the single-diffusivity model, the dual-diffusivity model showed good agreement... 

Quantitative Structure - Activity Relationship (QSAR) models for the inhibition action of some 1-phenylbenzimidazoles on platelet-derived growth are constructed using Genetic Algorithm and Artificial Neural Network (GA-ANN) method. The statistical parameters of R2 and root-mean-square error are 0.82 and 0.21, respectively using this method. These parameters show a considerable improvement compared to the stepwise multiple linear regression combined with ANN (stepwise MLR-ANN). Ten-fold shuffling crossvalidations are carried out to select the most important descriptors. Five descriptors of index of Balaban (J), average molecular weight (AMW), 3D-Wiener index (W3D), mean atomic van der Waals... 

In this paper the two-point boundary value problem (BVP) of the cantilever deflection at nano-scale separations subjected to van der Waals and electrostatic forces is investigated using analytical and numerical methods to obtain the instability point of the beam. In the analytical treatment of the BVP, the nonlinear differential equation of the model is transformed into the integral form by using the Green's function of the cantilever beam. Then, closed-form solutions are obtained by assuming an appropriate shape function for the beam deflection to evaluate the integrals. In the numerical method, the BVP is solved with the MATLAB BVP solver, which implements a collocation method for... 

This paper compares the Shuffling-Adaptive Neuro Fuzzy Inference System (Shuffling-ANFIS) with conventional ANFIS as the method for selecting the features of nonlinear systems. Shuffling-ANFIS technique uses the advantage of data splitting with the ANFIS as a powerful feature selection method to select the most important factors affecting nonlinear phenomena. In this technique, the features with the largest percent of frequency can be found by running the conventional ANFIS sequential forward search on the large number of training and test sets using leave-one-out validation criteria. The superiority of Shuffling-ANFIS over the conventional ANFIS was evaluated by using two synthetic and one... 

Aiming at operating optimally minimizing error of tracking and designing control effort, this study presents a novel generalizable methodology of an optimal torque control for a 6-degree-of-freedom Stewart platform with rotary actuators. In the proposed approach, a linear quadratic integral regulator with the least sensitivity to controller parameter choices is designed, associated with an online artificial neural network gain tuning. The nonlinear system is implemented in ADAMS, and the controller is formulated in MATLAB to minimize the real-time tracking error robustly. To validate the controller performance, MATLAB and ADAMS are linked together and the performance of the controller on the... 

Context: Tangled commits are changes to software that address multiple concerns at once. For researchers interested in bugs, tangled commits mean that they actually study not only bugs, but also other concerns irrelevant for the study of bugs. Objective: We want to improve our understanding of the prevalence of tangling and the types of changes that are tangled within bug fixing commits. Methods: We use a crowd sourcing approach for manual labeling to validate which changes contribute to bug fixes for each line in bug fixing commits. Each line is labeled by four participants. If at least three participants agree on the same label, we have consensus. Results: We estimate that between 17% and... 

As concerning with water insecurity driven by water scarcity threatens the lives and livelihoods of humanity worldwide, urban water demand management is focused on promoting residential water conservation behaviors (WCBs) as a critical policy response to water scarcity. However, urban water conservation initiatives cannot be successful unless households involve in residential WCBs voluntarily by adopting water curtailment and/or water-efficiency actions. Thus, understanding motivations and mechanisms underlying accepting these two types of WCBs and interpreting their distinctions are primary policy considerations to make sustainable water consumption behaviors. Hence, the purpose of this... 

One of the main concerns in source water protection and supply relates to the savings in water consumption in the building sectors. Office buildings are responsible for a considerable amount of water consumption worldwide. Thus, regulations on office buildings' water consumption would substantially reduce water consumption in the city as a whole. In order to achieve this objective, water indicators should be determined using an appropriate method. The present study focuses on the evaluation of water consumption patterns in an office building as well as the determination of the fundamental indicators for water conservation and optimization of water consumption patterns. To design and... 

This contribution focuses on the use of ladder particle swarm optimisation (LPSO) on modelling of oxadiazole- and triazolesubstituted naphthyridines as human immunodeficiency virus-1 integrase inhibitors. Artificial neural network (ANN) and Monte Carlo cross-validation techniques were combined with LPSO to develop a quantitative structure-activity relationship model. The techniques of LPSO, ANN and sample set partitioning based on joint x-y distances were applied as feature selection, mapping and model evaluation, respectively. The variables selected by LPSO were used as inputs of Bayesian regularisation ANN. The statistical parameters of correlation of deterministic, R2, and... 

Background: Cardiotocography (CTG) is the most widely used tool for fetal surveillance. The visual analysis of fetal heart rate (FHR) traces largely depends on the expertise and experience of the clinician involved. Several approaches have been proposed for the effective interpretation of FHR. In this paper, a new approach for FHR feature extraction based on empirical mode decomposition (EMD) is proposed, which was used along with support vector machine (SVM) for the classification of FHR recordings as 'normal' or 'at risk'.Methods: The FHR were recorded from 15 subjects at a sampling rate of 4 Hz and a dataset consisting of 90 randomly selected records of 20 minutes duration was formed from... 

STUDY DESIGN.: Cross-sectional validation study to investigate psychometric properties of adapted Persian version of the Scoliosis Research Society-22r (SRS-22r) questionnaire. OBJECTIVES.: To translate the SRS-22r into Persian and to evaluate the internal consistency, reliability, and validity of the Persian SRS-22r. SUMMARY OF BACKGROUND DATA.: The SRS-22r has not been translated and validated for Persian-speaking patients with idiopathic scoliosis. This was to provide a validated instrument to measure health-related quality of life in patients with idiopathic scoliosis in Iran. METHODS.: The translation and cultural adaptation of the original questionnaire were carried out in accordance... 

The dummies currently used for predicting vehicle occupant response during frontal crashes or whole-body vibration provide insufficient information about spinal loads. Although they aptly approximate upper-body rotations in different loading scenarios, they overlook spinal loads, which are crucial to injury assessment. This paper aims to develop a modified dummy finite element (FE) model with a detailed viscoelastic lumbar spine. This model has been developed and validated against in-vitro and in-silico data under different loading conditions, and its predicted ranges of motion (RoM) and intradiscal pressure (IDP) maintain close correspondence with the in-vitro data. The dominant frequency... 

Spinal fusion surgery is usually followed by accelerated degenerative changes in the unfused segments above and below the treated segment(s), i.e., adjacent segment disease (ASD). While a number of risk factors for ASD have been suggested, its exact pathogenesis remains to be identified. Finite element (FE) models are indispensable tools to investigate mechanical effects of fusion surgeries on post-fusion changes in the adjacent segment kinematics and kinetics. Existing modeling studies validate only their intact FE model against in vitro data and subsequently simulate post-fusion in vivo conditions. The present study provides a novel approach for the comprehensive validation of a lumbar... 

Objectives. Stressors have a serious role in precipitating mental and somatic disorders and are an interesting subject for many clinical and community-based studies. Hence, the proper and accurate measurement of them is very important. We revised the stressful life event (SLE) questionnaire by adding weights to the events in order to measure and determine a cut point. Methods. A total of 4569 adults aged between 18 and 85 years completed the SLE questionnaire and the general health questionnaire-12 (GHQ-12). A hybrid model of genetic algorithm (GA) and artificial neural networks (ANNs) was applied to extract the relation between the stressful life events (evaluated by a 6-point Likert scale)... 

Purpose: Despite the proven utility of multiparametric magnetic resonance imaging (MRI) in radiation therapy, MRI-guided radiation treatment planning is limited by the fact that MRI does not directly provide the electron density map required for absorbed dose calculation. In this work, a new deep convolutional neural network model with efficient learning capability, suitable for applications where the number of training subjects is limited, is proposed to generate accurate synthetic computed tomography (sCT) images from MRI. Methods: This efficient convolutional neural network (eCNN) is built upon a combination of the SegNet architecture (a 13-layer encoder-decoder structure similar to the...