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Yaghouby F.,University of Kentucky | Ayatollahi A.,Iran University of Science and Technology | Bahramali R.,University of Applied Science and Technology of Iran | Yaghouby M.,Azad University of Mashhad | Alavi A.H.,Iran University of Science and Technology
Computers in Biology and Medicine | Year: 2010

In this study, new methods coupling genetic programming with orthogonal least squares (GP/OLS) and simulated annealing (GP/SA) were applied to the detection of atrial fibrillation (AF) episodes. Empirical equations were obtained to classify the samples of AF and Normal episodes based on the analysis of RR interval signals. Another important contribution of this paper was to identify the effective time domain features of heart rate variability (HRV) signals via an improved forward floating selection analysis. The models were developed using the MIT-BIH arrhythmia database. A radial basis function (RBF) neural networks-based model was further developed using the same features and data sets to benchmark the GP/OLS and GP/SA models. The diagnostic performance of the GP/OLS and GP/SA classifiers was evaluated using receiver operating characteristics analysis. The results indicate a high level of efficacy of the GP/OLS model with sensitivity, specificity, positive predictivity, and accuracy rates of 99.11%, 98.91%, 98.23%, and 99.02%, respectively. These rates are equal to 99.11%, 97.83%, 98.23%, and 98.534% for the GP/SA model. The proposed GP/OLS and GP/SA models have a significantly better performance than the RBF and several models found in the literature. © 2010 Elsevier Ltd.


Yaghouby F.,University of Kentucky | Ayatollahi A.,Iran University of Science and Technology | Bahramali R.,University of Applied Science and Technology of Iran | Yaghouby M.,Azad University of Mashhad
Expert Systems | Year: 2012

In this study, two variants of genetic programming, namely linear genetic programming (LGP) and multi-expression programming (MEP) are utilized to detect atrial fibrillation (AF) episodes. LGP- and MEP-based models are derived to classify samples of AF and Normal episodes based on the analysis of RR interval signals. A weighted least-squares (WLS) regression analysis is performed using the same features and data sets to benchmark the models. Another important contribution of this paper is identification of the effective time domain features of heart rate variability (HRV) signals upon an improved forward floating selection (IFFS) analysis. The models are developed using MIT-BIH arrhythmia database. The diagnostic performances of the LGP and MEP classifiers are evaluated through receiver operating characteristics (ROC) analysis. The results indicate that the LGP and MEP models are able to diagnose the AF arrhythmia with an acceptable high accuracy. The proposed models have significantly better diagnosis performances than the regression and several models found in the literature. © 2011 Blackwell Publishing Ltd.


Hejazi M.,Azad University of Mashhad | Nezamdoost Z.,Azad University of Mashhad | Saghebjoo M.,Birjand University
Iranian Journal of Endocrinology and Metabolism | Year: 2014

Introduction: This study was conducted to determine the effect of twelve weeks of aerobic training on serum levels of leptin, vaspin, total antioxidant capacity (TAC) and malondialdehyde (MDA) in obese middle-aged women. Materials and Methods: In this quasi-experimental study, 30 sedentary, middle-aged women (mean±SD age 48.30±3.02 yr, body mass index 30.89±3.23 kg/m2 and body fat 32.88 ±2.71%) were randomized into the experimental (n=15) and control (n=15) groups. The experimental group performed twelve weeks aerobic training (3 times per week at an intensity of 65-75 % of maximum heart rate reserve). Blood samples were collected 24h before and 48h after the training. Data was analyzed by Student's t-test (P< 0.05). Results: Results showed a significant decrease in serum levels of leptin and MDA (P values 0.009 and 0.01 respectively) while TAC significantly increased (P=0.01) in the experimental group. Body fat percentage significantly decreased in the experimental group (0.0001), but serum vaspin levels were not significantly different between the two groups (P=0.93). Conclusions: Regular aerobic training is associated with weight loss and reduced body fat in obese women. As leptin production occurs in adipose tissue, subsequent decrease in body fat percent, serum leptin levels also occurred. On the other hand, aerobic training can improve oxidation/anti-oxidation in the body by reducing MDA concentration and increasing TAC.


Kashefi F.,North Khorasan University of Medical Sciences | Ziyadlou S.,Shiraz University of Medical Sciences | Khajehei M.,Curtin University Australia | Ashraf A.R.,Shiraz University of Medical Sciences | And 2 more authors.
Complementary Therapies in Clinical Practice | Year: 2010

Objective: We conducted this study to assess the effect of acupressure at the Sanyinjiao point on primary dysmenorrhea. Methods: Eighty-six students participated in the study. All participants met the inclusion criteria. The study group received acupressure at Sanyinjiao point, while the control received sham acupressure. The severity of dysmenorrhea was assessed at the following time periods: prior to the intervention, 30. min, 1, 2 and 3. h following the intervention. Data were analyzed using SPSS. Results: The acupressure caused decline in the severity of dysmenorrhea immediately after intervention in both groups during their first menstrual cycle, although, there difference was not significant (p>0.05). In addition, during the same cycle, the severity of the dysmenorrhea decreased more in study group rather than control group at 30. min, 1, 2 and 3. h after intervention (p<0.05). During the second menstrual cycle, acupressure made dysmenorrhea reduced in both study and control groups; however, the decline was more salient among participants of the study group at all stages after the intervention (p<0.05). Conclusions: Acupressure at Sanyinjiao point can be an effective, feasible, cost-effective intervention for improving primary dysmenorrhea. © 2010 Elsevier Ltd.


Mozaheb Z.,Mashhad University of Medical Sciences | Aledavood A.,Mashhad University of Medical Sciences | Farzad F.,Azad University of Mashhad
Pan African Medical Journal | Year: 2012

Background: The role of dietary factors in the epidemiology of Non-Hodgkin's lymphoma (NHL) remains largely undefined. Dietary habits may play a role in the etiology of NHL by influencing the immune system. Methods: Dietary patterns and the risk of NHL were analyzed in a case control study; including 170 NHL cases and 190 controls. All subjects completed a validated food-frequency questionnaire. The dietary pattern was investigated separately and in nine nutritional groups. Crosstab tables were used to estimate the odds ratios (OR), and Ptrend. Results: Consumption of highest versus lowest quartile of proteins (OR, 8.088 Ptrend=0.000), fats (OR, 6.17 Ptrend=0.000) and sweets (OR, 8.806 Ptrend=0.000) were associated with a significantly increased NHL risk. The inverse association was found for fresh fruits (OR, 0.117 Ptrend=0.000) and vegetables (OR, 0.461 Ptrend =0.010). Conclusion: An association between dietary intake and the risk of NHL is biologically plausible due to immunosuppressive effects of fat and animal proteins, and antioxidant properties of vegetables and fruits. © Zahra Mozaheb et al.


Niazmand S.,Mashhad University of Medical Sciences | Khoshnood E.,Azad University of Mashhad
Iranian Journal of Basic Medical Sciences | Year: 2011

Objective(s): Achillea genius is widely used in traditional medicine for gastrointestinal disorders. The aim of this study was to investigate the effects of aqueous-ethanol extract of Achillea wilhelmsii on rat's gastric motility in basal and vagal stimulated conditions. Materials and Methods: Twenty four Wistar rats were randomly divided into two groups: control and test. The extract was prepared by maceration which was used to prepare three 0.5 ml samples of three doses (0.5, 1 and 2 mg/kg) in the test group. The same volume of saline was used in the control group. Gastric motility was measured by inserting a small balloon in the stomach which was connected to a pressure transducer. The data were recorded for 25 min duration after each dose and these data were analyzed for 3 intermittent five min intervals (t1= 0-5, t2=10-15 and t3= 20-25 min). Results: The extract at basal condition decreased intragastric pressure (IGP) by 1 mg/kg dose in the t3 and 2 mg/kg in the t2 and t3 intervals. The extract at vagal stimulated condition decreased IGP by 1 and 2 mg/kg doses in the t2 and t3 intervals. The extract reduced contraction amplitude at basal condition by 2 mg/kg dose in the t2 and t3 intervals. At vagal stimulated condition contraction amplitude was reduced by 1 mg/kg dose in the t2 and t3 by 2 mg/kg in all three intervals. The extract showed no effect on frequency of gastric contraction in either basal or vagal stimulated conditions. Conclusion: The extract showed an inhibitory effect on gastric motility in both basal and vagal stimulated condition. This inhibitory effect may be exerted by an antagonistic effect on acetylcholine dependent calcium influx or release of calcium from intracellular storage in gastric smooth muscle.


Parvaneh V.,Shahrood University of Technology | Parvaneh V.,Azad University of Mashhad | Shariati M.,Shahrood University of Technology
Acta Mechanica | Year: 2011

In this paper, the influence of various vacancy and Stone-Wales defects on the Young's modulus of single-walled carbon nanotubes is investigated via a structural model. Dispersion in experimental results is the motivation for this work. Our results show that the type of method used (loading and boundary condition) for the prediction of the Young's modulus of SWCNTs is very important for the results. The effect of different types of defects on the Young's modulus is also studied for zigzag and armchair nanotubes with various aspect ratios (length/diameter). A comparison of our results with those of experimental methods indicates that for the exact prediction of the Young's modulus of SWCNTs we need to apply the correct conditions. © 2010 Springer-Verlag.


Bidokhti H.S.,Azad University of Mashhad | Enferadi J.,Azad University of Mashhad
International Conference on Robotics and Mechatronics, ICROM 2015 | Year: 2015

In recent years neural networks have been considered as an apposite method for solving problems which come to system of nonlinear equations. On the other hand, in opposite to inverse kinematics problem of parallel manipulators, their direct kinematics problem has very complicated analytical solution which are dependent to solving system of nonlinear equations with numerical methods. Therefore this problem can be a good case for using artificial neural networks. In this paper, direct kinematics problem of a 3-RRR planar parallel robotic manipulator, is solved by using two different models of artificial neural networks, one a back propagation neural network and the other one a radial basis neural network. The proposed networks use training data set which is made by solving the inverse kinematics of the robot. After making the database for training the networks, different parameters of the neural networks are changed in a wide range and finally the best ones for each of BPNN and RBFNN models are selected. Then the number of the data used for training is minimized. So that computation time is optimized. Mean squared error of the proposed BP and RBF neural networks are 7.5×10-6 and 5 × 10-17. Much more precise results in solving FKP of the 3-RRR manipulator and also less computational time of RBFNN is obtained in this study. The designing approach of the proposed solution is presented in detail, and effectiveness of the solution is demonstrated by comparing a simulated spiral path with its real path. Finally the total error during the simulated path is calculated and the average of 4. 5 × 10-4 for BPNN and 1. 59 × 10-6 for RBFNN confirms the reliability of these methods. © 2015 IEEE.


Hasanzadeh F.,Azad University of Mashhad | Naghibzadeh M.,Ferdowsi University of Mashhad
Proceedings of the 2013 3rd IEEE International Advance Computing Conference, IACC 2013 | Year: 2013

The issue in reachability problem of graph G = (V, E) is whether there is a path between two given nodes or not. This problem plays a key role in areas such as Bioinformatics, Semantic Web, Computer Networks and Social Networks, which have very large graph-structured data. Also, the reachability problem is employed considerably in the graph management and graph algorithms. In this paper, we propose a novel labeling approach for large directed graphs. Our presented method is called GRU (Graph Reachability indexing using United intervals), that can answer reachability queries in constant time even for large graphs. The significant point in this approach is that all the reachability information is computed after indexing time. In addition, this computation is performed only with one time DFS (post-order) traverse and labels are calculated precisely and stored in an efficient way. Analytical and experimental results reveal that effectiveness of our method is more than other interval labeling methods. Furthermore, our approach results show improvement in query time in comparison with GRAIL, which is only a scalable index for reachability queries. © 2013 IEEE.


Shaddel M.,Ferdowsi University of Mashhad | Javan D.S.,Ferdowsi University of Mashhad | Baghernia P.,Azad University of Mashhad
Renewable and Sustainable Energy Reviews | Year: 2016

Today, for providing clean energy, solar capturing facilities such as photovoltaic panels (PV) or solar thermal collectors (SCTs) have been increasingly installed worldwide. On the other side, lack of solar radiation data is one of the barriers for developing these technologies locally. Short-time step calculation of solar global irradiation (SGI) on inclined planes is required regarding to predict precise performance of solar systems, leading to enhance security operation's conditions and economic cost saving. Moreover, SGI values on tilted absorbers have a nonlinear relationship with several variables such as Horizontal Solar Global Irradiation, Extraterrestrial Horizontal Global Irradiation, and number of days, collector angle, solar altitude angle and the latitude of the location. Thus computation of SGI is neither readily to obtain nor easy to forecast. This paper is proposed on estimating accurate values of SGI on tilted planes via Artificial Neural Network (ANN). Indeed, ANNs are effective tools to model nonlinear systems and are widely used simulation software incorporated in MATLAB. Mashhad the second megacity of Iran is taken into account for the case study. The ANN is developed and optimized using every 30 min of SGI data (6.00 AM until 5.00 PM) in 2013 on zero, 45° and 60° inclined planes respectively. These data have been gauged by pyranometers which are installed in Air & Solar Institute of Ferdowsi University of Mashhad. Meanwhile, the accuracies including R2 (Correlation Coefficient), MAE (Mean Absolute Error) and RMSE (Root Mean Square Error) are obtained 0.9242, 0.0284, 0.055 and 0.9302, 0.0269, 0.0549 for 60 and 45 tilted collectors respectively. Eventually it is concluded that ANN can be a reliable network and well capable for forecasting solar energy on slope solar absorbers in Mashhad. © 2015 Elsevier Ltd.

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