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Articles by M. Mahdavi
Total Records ( 7 ) for M. Mahdavi
  S. Jalilzadeh , H. Shayeghi , M. Mahdavi and H. Hadadian
  Transmission Network Expansion Planning (TNEP) was studied considering voltage level, network losses and number of bundle lines using decimal codification based genetic algorithm (DCGA). TNEP determines the characteristic and performance of the future electric power network and directly influences the operation of power system. Up till now, various methods have been presented for the solution of the Static Transmission Network Expansion Planning (STNEP) problem. However, in all of these methods, STNEP problem has been solved regardless of voltage level of transmission lines. For this reason and according to various voltage levels and different number of bundle lines used in real transmission network which caused different annual losses, STNEP was studied considering voltage level, network losses and number of bundle lines using genetic algorithm. Genetic Algorithms (GAs) have demonstrated the ability to deal with non-convex, nonlinear, mixed-integer optimization problems, like the TNEP problem, better than a number of mathematical methodologies. The proposed method was tested on an actual transmission network of the Azerbaijan regional electric company, Iran, to illustrate its robust performance. The results were shown that considering the network losses in a network with different voltage levels and the number of bundle lines considerably decreased the operational costs and the network can be satisfied the requirement of delivering electric power more safely and reliably to load centers.
  H. Abghari , M. Mahdavi , A. Fakherifard and A. Salajegheh
  The artificial intelligence modeling of nonstationary rainfall-runoff has some restriction in accuracy of simulation base on complexity and nonlinearity of training patterns. Statistical preprocessing of trainings could determine homogeneity of rainfall-runoff patterns before modeling in artificial intelligence. In this study, the new hybrid model of artificial intelligence in conjunction with statistical clustering is introduced. Statistical pre-processing effects of 360 rainfall-runoff patterns considered before modeling using Radial Basis Function Neural Networks (RBFNNs). In the first step all 360 monthly rainfall-runoff patterns classify by cluster analysis in 4 groups and each class modeled by different RBFNNs topology. Results of 4 cluster base-RBFNNs compare with no action one and the optimized structure of Hybrid Cluster base-RBFNN models of Nazloochaei river flow present. Results show that clustering of rainfall-runoff patterns and modeling of each dataset by different RBFNNs has higher accuracy than no preprocessing of patterns in prediction and modeling of river flow.
  Z.M. Hanapi , M. Ismail , K. Jumari , M. Mahdavi and H. Mirvaziri
  In this study, different collection window’s size is been analyzed to investigate the impact on network performance: packet delivery ratio, message overhead and end to end delay on the Dynamic Window Secured Implicit Geographic Forwarding (DWIGF) routing protocol where this protocol is based on a dynamic collection window approached. Its method on using dynamic window’s size has minimized the probability of selecting attackers and guaranteed high packet delivery ratios when there is a blackhole attack in the communication link. The DWSIGF is then compared with the best chosen window’s size to analyze the network performance with and without attacker in the communication line, respectively. The DWIGF is able to minimize a Clear To Send (CTS) rushing attack that leads to a blackhole and selectively forwarding attack with a guaranteed of high packet delivery ratios where a selection of a failed node and an attacker is minimized, respectively. As a result, this routing protocol is promising a dynamic and secured communication without inserting any existing security mechanism inside.
  M. Mahdavi , M. Ismail , K. Jumari and Z.M. Hanapi
  Sensing coverage and network connectivity are two main requirements which maintain perfect operation of wireless sensor network. Joint scheduling method has considered both requirements by using random scheduling for sensing coverage, which divides sensor nodes to k subsets. Each sensor nodes randomly selects one defined subset. Then, the algorithm turns on extra sensor nodes, if necessary for network connectivity. As Extra-on sensor nodes participate in other nodes routing, some of them may be subject of many times transmission and reception. Furthermore, some of Extra-on nodes should be active the whole time to create network connectivity. Both mentioned reasons can drain out energy of those extra active nodes and may lead to network partitioning. Hence, reducing number of Extra-on nodes is important. In this study, we utilize probing mechanism scheduling in joint scheduling method to reduce the number of extra on sensor nodes. By using probing mechanism that some nodes change their working schedule, number of extra on nodes reduces by 20%.
  M. Mahdavi and S.F. Ghazizadeh
  In this study, we investigate the self-generated the electric and magnetic fields effects of fast electrons beam on plasma and beam characteristics. The fields effect as; columbic transverse electric field, radial space charge potential, longitudinal plasma wakefield and transverse self magnetic field on beam propagational characteristics as; a collimated or focused and filamented beam and the plasma density perturbation are investigated. Also the hollowing effect due to self magnetic field which can generate an annular pattern in electrons beam is investigated.
  M. Mahdavi and S.F. Ghazizadeh
  In this study, we investigated some effective parameters related to the plasma and the laser characteristics on linear absorption mechanisms such as; plasma scale length, plasma density profile, laser intensity and laser pulse duration. We classify different approaches which lead to different solutions for the wave equation in plasma medium. We showed that, there are some restrictions with applying the linear theory in absorption. Finally we pointed out that there are some restrictions to apply linear theory in absorption. We will see in which regimes collisional or resonance absorption is dominant.
  H. Karami , K. Vahidshahi , M. Kosarian , H. Karami , S. Shahmohammadi , M. Dabirian , M. Vafainezhad , E. Yousefi , L. Sarparast , R. Alizade , M. Mahdavi and M.B. Hashemi
  A high incidence of thromboembolic events have been reported among thalassemia intermedia patients especially in splenectomized patients. This study has been conducted to evaluate the coagulation state of patients referred to thalassemia research center at Booali Sina Teaching Hospital, Sari, Iran. This descriptive- cross sectional study was performed in 2007. Sixty thalassemia intermedia patients aged older than 10 years were enrolled. After recording demographic and therapeutic data of the participants, the plasma levels of Coagulant factors were measured. Obtained Data were analyzed using SPSS 13 software and t-test and chi-square tests. Of 60 studied patients, 62% were female. The mean age of the patients was 26.6±9.3 years. ASA tablet were used in 53.3%. None of the patients have experienced thromboembolic events. Decrease in protein C has been observed in 60%. Antithrombin III was decreased in 42% and protein S declined in 10% of the patients. Mutation in factor V leiden was seen in 3%. Splenectomy performed in 53.3% and there was no significant relation between low level of protein C and protein S, antithrombin III and presence of factor V leiden with splenectomy (p>0.05). Regarding to the high incidence of low levels of protein C, protein S and antithrombin III among thalassemia intermedia patients, there is an increased risk of thromboembolic events in the patients.
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