With characteristics such as flexible teaching and learning techniques, the safeguarding of education in even the most distant areas and guaranteeing equal educational opportunities specially for people with special requirements ( Homemakers, physically impaired, … ) the distant learning system paints a bright picture of the availability of education to all in the future. Iran Payamenoor University currently catering for approximately one million students is the only existing university in Iran active in offering distant learning opportunities at associate, bachelor, masters and PhD levels in 400 educational centers and units. As Payamenoor University has been active in education and research, an investigation of how the aim of this educational system "anyone, anywhere, anytime can again access to higher education" has been accomplished in its educational centers and units is essential. A research entitled "a study of the Payamenoor University's educational demand evaluation based upon distant learning system" was conducted over a two year period. A descriptive-evaluative technique was employed and the statistic population included University lecturers, students and administrators of Payamenoor University educational centers and units (70 in total) in the country's 30 provinces. Applying a classified-random sampling system and utilizing Cockrun's Formula, 3000 students, 300 members of the university faculty and 30 administrators were selected as the statistical sample. Three surveys were prepared using an evaluativedocumentative method (A survey directed at students, one directed at lecturers and a third directed at the administrators). The reliability of these surveys was estimated using the Gronbach Alpha and was found to be 82% for students, 80% for lecturers, and 78% for administrators. The data was then prepared for analysis using Microsoft Excel and analyzed through the statistical software package SPSS and after the examination of the hypothesis the results indicated: There is significant discrepancy in the distribution of the educational facilities and service of the educational centers and units of the Payamenoor University. There are discrepancies between the educational facility distribution and educational service distribution of the educational centres and units of the Payamenoor University. A relationship is detected between the distribution of the educational facilities and service and the type of the educational centres and units of the Payamenoor University.There is discrepancy between the findings of the surveys conducted among the members of the university faculty and among students with the proportion of facilities and benefits in the educational centres and units of Payamenoor University.

Epistemology, as a branch of Philosophy, studies the process by which knowledge is obtained and evaluated. As such it can, in relation to the approach to truth and knowledge which are the main goals in education, open new vistas to planners and teachers alike. This applies to the original planners of Open and Distant Education as well, since the epistemological view of the time has informed the planners' perceptions of student, teacher, curriculum, and teaching/learning strategies, as the main constituents of these systems.In this paper, the relationship between epistemology and education, especially Open and Distant Education, is discussed and in the light of that, positivist, interpretive, and critical epistemological approaches are introduced. Furthermore, the two educational systems are portrayed in general and their requirements in relationship to the teaching/learning strategies are explored from these three epistemological perspectives.

The purpose of the present research was to study the driving factors in integration and application of distant education in PhD courses of Payame Noor University. In order to identify the fundamental factors, a researcher-made questionnaire, consisting of 5 scales and 36 sub-scales, was given to 30 distant education experts.. From a population of 1082 people, 136 were selected as the sample, using random sampling and Cochran’s formula, and the questionnaire was distributed among them. Descriptive statistics as well as inferential analysis; mean, slandered diviation, Pearson correlation coefficient, and exploratory analysis were applied for data analysis in SPSS 18 and LISREL 8.53. Based on the initial findings, these were the self-sufficiency, technological skillfulness, practicality, easy access, and comprehensive support which were identified as the driving factors in integration and application of distance education. The correlation coefficients for these factors were 64%, 52%, 49%, 47%, and 39%, respectively. The final results of LISREL analysis showed that the coefficients of determination for the above factors are 27%, 66%, 77%, 61%, and 80%, respectively, indicating the positive relationship of these factors with integration, application, and modeling of distant education. Chi-square to df ratio (2.172) was less than 3, the value of RMSEA (0.0018) was less than the threshold (), -value (0.2132) was greater than the threshold (), and the values of GFI (0.91) and AGFI (0.90) were equal to or greater than the threshold (0.90), all suggesting the goodness of fit of the model and indicating significant relationships between the five main scales.

Distributed Denial of Service (DDoS) attacks are among the primary concerns in internet security today. Machine learning can be exploited to detect such attacks. In this paper, a multi-layer perceptron model is proposed and implemented using deep machine learning to distinguish between malicious and normal traffic based on their behavioral patterns. The proposed model is trained and tested using the CICDDoS2019 dataset. To remove irrelevant and redundant data from the dataset and increase learning accuracy, feature selection is used to select and extract the most effective features that allow us to detect these attacks. Moreover, we use the grid search algorithm to acquire optimum values of the model’s hyperparameters among the parameters’ space. In addition, the sensitivity of accuracy of the model to variations of an input parameter is analyzed. Finally, the effectiveness of the presented model is validated in comparison with some state-of-the-art works.

The present study is focused on the species belonging to the genus Maiestas Distant, 1917 (Hemiptera: Cicadellidae: Deltocephalinae, Deltocephalini) in Iran, based on some specimens collected during 2016 to 2019 from Southeast Iran and species that have been previously reported: M. horvathi (Then, 1896), M. pruthii (Metcalf, 1967), M. schmidtgeni (Wagner, 1939), and M. trifasciata (Lindberg, 1954). M. pruthii, previously known from the Oriental region (India and Pakistan), is recorded for the first time in the Palaearctic region from Southeast Iran and M. horvathi is a new record for the fauna of Sistan and Baluchestan Province. An identification key and distribution maps for the Iranian Maiestas species are provided.