The aim of this study is to test the valuation method in which in addition to the fundamental features of the stock, pay attention to investor sentiment and its impact on stock pricing. in this regard, Fundamental information and stock prices of 95 manufacturing and industrial companies listed in the Tehran Stock Exchange during the years 2009 to 2013 are collected and valued using the behavioral model stock image and traditional models (residual income, discount dividend and free cash flow). This research using panel data and regression equations developed for each model, has compared the performance of models based on Akaike(ACI) index. The results of the proposed model compared to traditional models implies less uncertainty of this model. The proposed behavioral model can explain the role of behavioral factors in stock pricing and helpful for stockholders in the active portfolio management because they can buy or sell their securities based on this model

Quranic sciences include those obtainable from the holy Quran. All Quranic statement, therefore, are known as Quranic sciences. These sciences and statements are various and unlimited and, therefore, they should be classified. The paper has intended to introduce and evaluate classifying models of Quranic science including traditional and non-traditional ones. The former includes those found in Imami’s traditions and have been classified differently from two classes to ten classes. These models have been appropriate to the conditions of their own time and differ from current common models. Non-traditional models, however, include those given by Imami’s scholars the most systematic of which contains those of religion-based, human-based and Divine-based. All models have been based upon religious texts and have their own properties, though none may be known as the most logical one.

This work is an updated phylogenetic study on the huge genus Astragalus using nuclear ribosomal DNA internal transcribed spacer (ITS) data. Seven groups, each encompassing several sections, corresponding to the same number of clades appeared, were recognized in the phylogenetic tree. A short description for each group along with the name of appropriate sections as well as a diagnostic key regarding new reliable morphological characters for these groups is provided.

Despite the individual differences of learners such as their abilities, goals, knowledge, learning styles and backgrounds, most of the electronic learning systems has presented an equal learning content for all of the learners. This is happening while producing a specialized content for the individuals. Increasing appliances of artificial memory in teaching the adaptation learning systems will require recommended teaching methods which are appropriate to the learner’ s individual differences. In order to grouping learners based on their learning styles in their own similar groups, we are presenting a new method in this text. This method is mainly about combining the result of clustering methods which is certainly reducing choosing an unreliable method. Meanwhile it is preventing method`s complication which is because of using simpler and more useful clustering algorithms that subsequently will cause a better result and it may happen due to the fact that different methods will overlap each other’ s defections. In this article we are using Felder-Silverman learning style which consist of 5 dimensions: processing (active-reflective), input (visual-verbal), understanding (sequential-global), perception (sensing-intuitive) and organization (inductive-deductive). Firstly, proper behavioral indicators to different learning style dimension of Silverman-Feedler will recognize and then based on these behaviors learners will be able to be groups by one of these 5 methods. In the case of evaluating the proposed method, utilizing the c++ programming electronic teaching period information is necessary. Learner members of experiment environment were 98 ones which were extracting the expressed indicators connected to their network behaviors in 4 dimensions of Perception, process, input and understanding of Felder-Silverman model. On the other hand students were asked to fill the questionnaire forms and their learning styles were calculated between 0-11 and then based on the behavioral information they were being grouped. We are using 5 clustering grouping methods k-means, FCM, KNN, K-Medoids and SVM to produce ensemble clustering in generation step and co-occurrence samples or majority votes were used in Integration step. Evaluating the results will require the followings: Davies-bouldin index, Variance index, and gathering purity index. Due to the fact that the expressed methods are not able to indicate automatically the best cluster, clustering 3, 4, 5, 6, 7 clusters were using this method. And with calculating Davies-bouldin index the best cluster in each method were selected. In FCM each data were contributed to the cluster which has the most dependence to that. Numerical results of Davies-bouldin index have shown that ensemble clusters have the exact accumulation clusters among the others. Clustering variance in different size is indicating that ensemble clustering has the most accumulation and the least dispersion and also purity-gathering results has shown that proposed grouping method has the ability to gather learners with the similar style in each cluster and has a better efficiency compared to the others. So with this idea while maintaining simplicity, more accurate results based on the Davies-bouldin index, Variance index, and gathering purity index is obtained. Due to the importance of high accuracy and high speed and low computational complexity in the clustering methods, instead of a more complex approach, combining the weaker and easier clustering methods, better and more accurate results reached.

In order to study the grouping of Agropyron tauri populations, 13 populations were investigated in a randomized complete blocks design with three replications. The study was performed in research field of Islamic Azad University of Tabriz in 2010. In this study, a number of traits including plant height, tiller number, leaf number, flag leaf length, first leaf length, second leaf length, first internode length, second internode length, crown cover, fresh yield, dry yield, fresh weight of single plant and dry weight per plant were evaluated. Analysis of variance showed significant differences among populations for all measured traits. Thirteen populations were classified into three clusters by cluster analysis of standardized data, based on Euclidean distance and Ward method. This result was in consistent with the height of geographic regions from which populations were collected. In principal components analysis, four components were introduced, and the traits of fresh and dry yield showed high and positive coefficients in first component. Results of cluster analysis were confirmed by results of principal components analysis.