The desert areas of the playas are important due to the diversity of geomorphological landforms and the great potential for geo-tourism development. These areas can be provided using statistical and quantitative models to determine the areas with a higher geomorphological diversity value to land planners for the sustainable development. This research was conducted to evaluate the geomorphodiversity in Mesileh playas in Namak Lake and Hoz-e- Sultan region. The geomorphological landforms in this area were extracted using satellite images and field studies, Fragstats software and the eight quantitative indicators of the landscape metrics include Patch Richness Density, Relative Patch Richness, Simpsons Evenness Index, Index Shannon Evenness, Shannons Diversity Index, Simpson's Diversity Index, Modified Simpson's Diversity Index, Modified Sahanon Evenness Index were exerted to evaluate the richness of geomorphological units in Masileh playas. The results indicate that the geomorphological units of alluvial fans, salt flats, salt mud flats and dunes, respectively, have the highest value among the landscape metrics. In addition, from the point of view of the landscape metrics, the northwest regions of Kashan and Abuzeydabad have the most incredible variety of geomorphology. This research showed that geomorphological units could be used as a suitable indicator in evaluating the diversity of the landscape, especially in flat areas with morphometric and geological diversity.

The purpose of this study was to design educational content of Green Chemistry metrics for undergraduate chemistry students. Based on the purpose of the research, it was an applied-development type, and in terms of collecting and analyzing the data; a descriptive-analytical type is used. The statistical sample was a collection of books, articles, journals, and dissertations related to green chemistry which were selected and analyzed up to getting theoretical saturation. By reviewing related literature and investigating various sources on how to design the educational contents of the chemistry green, and also by directions of the field experts, during several revers phases of core coding, chapters were determined, then, according to the designated chapters, objectives were written for each topic in the target-content table. The results of this study showed that for the design of the content of training green chemistry measurements, two categories of mass measurements and environmental measurements can often be quantitatively evaluated in the twelve principles of green chemistry. In these two categories, there are various methods for assessing the greenness of a reaction (organic reaction synthesis) were identified, including atomic economy, reaction mass efficiency, material recovery parameter, environmental factor, process mass intensity, and effective mass efficiency are presented in a conceptual framework.

Purpose: To determine the impact of document summarization parameters on the evaluation metrics of Classification algorithms for Persian texts. Methodology: 1000 news texts were collected from yjc. ir news agency website based on the number of visits, with at least 100 and at most 350 words, out of which 250 were selected randomly. Titles, summaries, and the texts of the 250 docs were included in three groups. The number of documents were increased by 100 percent in two stages, to 500 and 1000. After text preprocessing and deleting stop words by programming code, TF-ISF summarization technique was implemented on them. 12 Excel files were created from the words of original texts. Then, Bayesian, Decision tree, SVM and Rulebased algorithms implemented by Rapid Miner software, which provided 120 Excel output files for verifying accuracy, precision, and recall. Finally, five comparisons between the results were considered including comparing of results with 100% increase in the number of documents, comparing the parameters of TF and ISF summarizer, comparison of Bayesian Classification algorithms, decision tree, Rule and SVM, comparing the original text and summary and comparison of the documents labels. Findings: The results indicated the superiority of evaluation criteria in Classification of 1000 documents relative to those of 250 and 500, which in 84% of cases. Meanwhile, the ISF summarizer method compared to TF in 82% of comparison showed a greater impact on Classification accuracy. In addition, the values of the accuracy in Bayesian Classification and the SVM were better. The highest value obtained from the accuracy (96. 67%) in the SVM Classification by 1000 documents of original text and ISF summarizer technique. Conclusion: Appropriate parameters for summarization and efficient Classification techniques can improve the accuracy of Persian text Classification process, while the required time also decreases. The best results obtained in the evaluations show that ISF summarizer, Bayesian and SVM algorithms, 1000 documents, as well as the main text are more effective.

In this paper, we study the class of C 3-like Finsler metrics which contains the class of semi-C-reducible Finsler metric. We find a condition on C 3-like metrics under which the notions of Landsberg curvature and mean Landsberg curvature are equivalent.

In this paper we consider some (a, b)- metrics such as generalized Kropina, Matsumoto and F=(a+b)2/a metrics, and obtain necessary and sufficient conditions for them to be Einstein metrics when b is a constant Killing form. Then we prove with this assumption that the mentioned Einstein metrics must be Riemannian or Ricci flat.