Knowing the students' learning styles in the educational system and using the related teaching method with it  to teach students will facilitate the learning process and its further improving. The aim of this study was to determine the learning styles and its related factors in the students of Guilan University of Medical Sciences based on the Vermunt model. This descriptive cross-sectional research was conducted on 247 students, were selected by stratified-random sampling method in 2014-15. Data were collected by valid Vermunt learning styles Scale Contains 120 items, and then analyzed with SPSS-V.21, descriptive and inferential statistics tests (Kolmogorov-Smirnov test, Pearson correlation coefficient, analysis of variance and t-test). Mostly of students were female (90.3%) and nursing (21.5%) with a mean age of 22.89±2.54 years. The mean score of students’ learning style was 382.23±49.63 from 600 scores. The regulation strategies component (the majority decentralized control, 49.8%)and the opinions and beliefs of the learning component (the majority did not believe in acquiring and using knowledge, 57.9%)were more weaknesses in students. Also, there was no statistically significant relationship between demographic variables and learning style scores. According to the results, it is suggested that educational managers pay more attention to the weaknesses of their students and based on that teaching process be considered.

Teachers'' professional identity, professional vitality and creativity are three major factors that appear to affect teachers'' professional life in EFL contexts. The main purpose of this study was to scrutinize the network of associations among these three variables and their respective subscales. Participants of this study were 300 Iranian EFL teachers from secondary school. We used teacher''s professional identity questionnaire developed by Beijaard, Verloop, and Vermunt (2000), a modified version of professional vitality; one of the sub-scale of Skovholt Practitioner Professional Resiliency and Self-Care Inventory (2010) and creativity style questionnaire developed by Kumar & Holman (1997), to measure the variables. The results of Structural Equation Modeling (SEM) analysis confirmed the hypothesized model of relationships among the study variables. The final model of the network of associations among variables also revealed significant correlations among various subscales of the study. The findings of this study have various implications for language teachers and psycholinguistic researchers.

The aim of present research was to investigate the effects of metacognitive states، processing and regulation strategies on academic performance of university students. 410 students engaged in studying in various fields of humanities، University of Gilan that were in the age range of 17-33 years، responded to State Metacognitive Inventory (Oneil & Abedi،1996) and Vermunt’s inventory of learning styles (1994). Recent grade point average of students was considered as indicator of academic performance. By stepwise multiple regression analysis، the results showed that self-regulated strategy (β= 0. 364، P<0. 0001) is the best predictor of students’ academic performance (F= 32. 289، P<0. 0001)، and other variables were excluded due to the insignificant impact of the final model. In this study، the accelerator engine of students’ academic performance was recognized self-regulated strategy; thus we can expect formulation of educational interventions in which students learn to have adequate supervision on their learning process and its resulting، significant impact in promoting learning and ultimately improve the academic performance of students.

The purpose of this study was to investigate the role of motivational constructs(academic self-efficacy & study interest) and information processing strategies in regulation of learning (self-regulated learning and external regulation). The data were obtained from eleventh-grade students (138 female and 126 male) in Noor city. The sample was selected based on a multistage cluster random sampling. Our questionnaires in this study consisted of regulation of learning subscale from Inventory of Learning Styles (Vermunt, 1998), Academic Self-Efficacy Scale (Mccllory & Bunting, 2002), Study Interest Questionnaire (Schefele’s et al, 1993) and learning strategies from Motivated Strategies for Learning Questionnaire (Pintrich & Degroot, 1994). The structural equations model has been used for data analysis. The results indicated that academic self-efficacy and study interest have significant effects on the deep and surface information processing strategies and information processing strategies have significant effects on regulation of learning. In result academic self-efficacy and study interest predict significantly regulation learning by mediating of effects on the information processing strategies.

Aspects of pitching and plunging motions on unsteady aerodynamic behavior of an aircraft model were studied. Extensive wind tunnel tests were performed on a standard dynamics model, SDM, oscillating in both pitch and plunge modes. Up to now, there has been little or no result on the plunging behavior of an aircraft or missile as a whole and the present experiments can be considered as one of the first attempts to study the compressible flow field over a model undergoing both pitching and plunging motions. The experiments involved measuring normal force and pitching moment of the model at Mach numbers of 0.4, 0.6 and 1.5 and oscillation frequencies of 1.25, 2.77 and 6.00 Hz. The longitudinal dynamic derivatives were then calculated from the measured data. The pitching results have been compared with the available data on the same model and good agreement has been achieved. However no plunging data on the same or a similar model was available in the literature to be compared with the present findings.

AbstractDriven by Beijaard, Verloop and Vermunt’s (2000) theory of Professional Identity (PI), this study aims to investigate teachers’ perception of their PI in relation to the English textbooks they use in EFL classes. In-depth interview with four Iranian EFL teachers and the school principal was conducted. The teachers’ reports were employed to investigate their PI in relation to the textbooks they used. Furthermore, the school curriculum was analyzed through an interview with the school principal and examining the school documents. Content analysis of the interview data revealed that all the teachers viewed the content knowledge dimension of their PI reliant on the textbooks. Over the years, they had gained more autonomy in adapting the content or selecting more supplementary sources. Overall, the participants in this research highlighted the pivotal role of textbooks in the construction of their PI, most importantly in the formation of their content knowledge and the least in the development of their pedagogical knowledge. The analysis of the school curriculum revealed a heavy reliance of many decisions on textbooks directly or indirectly. The findings in this study will provide more insights for curriculum developers, language school managers, teacher educators and teachers who have a say in curriculum decisions when learning about the crucial role of textbooks in PI.

Application of the nonlinear H¥ identification method to identify a synchronous generator model is investigated in this paper. The linear H¥ identification method has been well established in the literature for robust modeling despite noise and system uncertainities. Since many practical systems such as synchronous generators are nonlinear, linear models identified for particular operating conditions do not perform well for other operating conditions. To overcome this shortcoming, the linear H¥ identification method has been modified to cover some nonlinearities of the systems such as saturation in synchronous machines. The derived proposed algorithm is then applied to a seventh order nonlinear model of a synchronous machine with saturation effect. In this study, the field voltage is considered as the input and the active output power and the terminal voltage are considered as the outputs of the synchronous machine. Simulation results show good accuracy of the identified models.

In this paper, a new effective and computationally reduced method for congestion control in high speed dynamic computer networks is introduced. The controller is designed using the well-known predictive functional control (PFC) scheme and an ARMarkov model representation that considers the system delay explicitly. Use of the multi-step-ahead predictive ARMarkov model structure within the PFC results in a simple algebraic control law that does not require recursive model output computation in the so-called prediction horizon performed in the other Model Predictive Controllers (MPC). This combination not only reduces the required computational load, but the accumulative error due to the model uncertainties decrease considerably. Packet-level simulations based on ns-2 are provided to show good performance of ARM-PFC in a large variety of topology and traffic mixtures for both queue regulation and resource utilization. Fast response, low queue fluctuations (and consequently low delay and jitter), high link utilization, good disturbance rejection, scalability, and low packet marking probability are other features of the proposed method with respect to the well-known AQM methods such as RED, PI, and REM, which are also simulated for comparison.

A modified three-dimensional dispersion model of our previous work5 was modified and used to investigate the effect of droplet size distribution in addition to droplet concentration distribution for the prediction of liquid droplet dispersion and particulate removal efficiency in a venturi type scrubber. For the sake of including droplet size distribution into the model properly, it was assumed that droplet size distribution obeys Rosin-Rammler distribution. The experimental data of Viswanathan et. al. [1] for liquid droplet dispersion and Brink and Contant [2] for particle removal efficiency were used to test the results of this new mathematical model. The results from the model show that by taking droplet size distribution into account the results of the model will be in better agreement with the experimental data.