S
Saba Kalantary
Researcher at Tehran University of Medical Sciences
Publications - 26
Citations - 452
Saba Kalantary is an academic researcher from Tehran University of Medical Sciences. The author has contributed to research in topics: Nanofiber & Electrospinning. The author has an hindex of 8, co-authored 25 publications receiving 233 citations. Previous affiliations of Saba Kalantary include Arak University of Medical Sciences & University of Tehran.
Papers
More filters
Journal Article
Association of Sick Building Syndrome with Indoor Air Parameters
Mohammad Jafari,Ali Asghar Khajevandi,Seyed Ali Mousavi Najarkola,Mir Saeed Yekaninejad,Mohammad Amin Pourhoseingholi,Leila Omidi,Saba Kalantary +6 more
TL;DR: The results suggested that SBS symptoms were more common in women than men and recycling of air in rooms using fan coils, traffic noise, poor lighting, and buildings located in a polluted metropolitan area were the main causes.
Journal ArticleDOI
The evaluation on artificial neural networks (ANN) and multiple linear regressions (MLR) models for predicting SO2 concentration
TL;DR: In this paper, the authors compared the performance of multiple linear regression (MLR) and multi-layer perceptron (MLP) for predicting SO2 concentration in the air of the Tehran.
Journal ArticleDOI
Application of ANN modeling techniques in the prediction of the diameter of PCL/gelatin nanofibers in environmental and medical studies
TL;DR: In this article, the authors compared the multi-layer perceptron (MLP), radial basis function (RBF), and support vector machine (SVM) models to develop mathematical models for the diameter prediction of poly(e-caprolactone) (PCL)/gelatin (Gt) nanofibers.
Journal Article
The effects of occupational noise on blood pressure and heart rate of workers in an automotive parts industry
TL;DR: Exposure to industrial noise may increase the heart rate of workers, and rises in heart rate, systolic, and diastolic blood pressure of workers in the case group were observed after exposure to noise, the values of heart rate and blood pressure were in the normal range.
Journal ArticleDOI
MLR and ANN Approaches for Prediction of Synthetic/Natural Nanofibers Diameter in the Environmental and Medical Applications
TL;DR: An artificial neural network (ANN) modeling and multiple regression (MLR) analysis approaches to predict the diameter of nanofibers and the values of weight ratio, distance, injection rate, and voltage were identified as the most significant parameters which influence PDNFM.