درخت حوزه‌های تخصصی

External factorsexert an enormous influence on the exigencies of changing the technological course of individualsectors. Digitalizationrepresents not a new milestone in the evolution of education, but its technological and methodological development. Due to a period of constraints, caused by COVID-19 pandemic, educational institutions at all levels in most countries have been forced to resort to digitalization of the learning process. Intelligent learning software provide their users with a variety of options to design and individualize the learning process, as well as independence from time and space. Teachers benefit from flexible content generation and just-in-time assessment of learners' progress, evaluation of large task sets, knowledge sharing with other teachers and knowledge institutions. Learners benefit from anytime availability of learning tools and just-in-time feedback. In our investigation, we consider the current state-of-the-art of educational software. Considering the results of quantitative empirical study and analysis of educational issues solvable by artificial intelligence, we present a developed and tested framework for selected educational problem.

Due to the importance of public transportation, which has become today an important urban problem with special conditions, this study was conducted aimed at determining the parameters affecting the mathematical programming model of the appropriate transportation system. The study was performed by modeling method, and the problem was solved in three different sizes (small, medium and large) to show the efficiency of the model and the proposed solution methods. Some common test problems in the literature were selected and the required characteristics of the problem under study were defined for them as needed, since there are no sample test problems in the literature to examine the performance of the developed algorithms. The results indicated that some of the most important parameters affecting the designed mathematical model were movement risks, fatigue and drowsiness while driving, demands at the source node, demands at the destination node, number of vehicles across the network, the time interval between requests, and the time interval between two consecutive requests. The mentioned parameters were so effective that little changes in parameters such as demands at the source node, demands at the destination node, and the number of vehicles across the network significantly increased time and decreased profitability. the company has a significant effect on the debt cost rate and capital cost rate and does not have a significant effect on stock prices. Finally, the share price shows little sensitivity to the company's financial structure.

The purpose of this research is to design a model for evaluating the policies of proportionalization of administrative system formations in Iranian National Oil Company. In this regard, the research method was a combination of qualitative and quantitative methods and tools with an applied orientation along with survey strategy and inductive approach. The qualitative part of the research included a review of the records and background of the research and conducting library studies based on the content analysis and meta-composition methods and the Delphi technique, and in the quantitative part, several techniques and tools were used, including interpretive structural modeling and structural equations, factor analysis, pairwise comparison matrix, and questionnaire tools. By carrying out the qualitative stage and refining and screening and verifying the achievements in the quantitative stage, finally 89 indicators in the form of 11 dimensions and 35 components, under the four main concepts of "policy evaluation", "proportionalization", "administrative system formations" and "macro environment" were counted and classified. In the next step, by identifying the relationship and mutual effect of the identified factors, the evaluation model of the design policy and finally the validity and reliability of the model was put into the test and approved. The issue of the optimal size of the government and the public policies related to it has been discussed and debated among political and economic experts for about three decades in the documents of the government and the ruling space of the country with different expressions such as "downsizing", "privatization" and "rationalization". Following the studies conducted in this research, with the premise that on one hand, the correct and scientific evaluation of public policies has an undeniable role in the successful implementation of policies, and on the other hand, in our country, the issue of evaluating public policies has always been like a missing link in the space that governs this territory and better management of resources in Iranian National Oil Company.

The focus of this study is on lecturer’s use of online technology in the higher education context. Precisely, this study aims to understand the effect of personal innovativeness in IT (PI) in determining technology adoption behavior of lecturers in the higher education institutes in Sri Lanka. In this study, the variable of personal innovativeness in IT is integrated with the UTAUT framework and thereby the causal paths which effects VLE adoption intention of individuals is examined. Literature suggests that domain-specific innovativeness is a crucial factor in determining an individual’s adoption of technological innovations. Therefore, understanding the multifaceted effects of this factor along with other significant factors can help higher education institutes to effectively endorse online technology among lectures, generating productive payoffs in the long run. The quantitative method was used for data collection, which yielded # 1253 responses through the Question Pro online survey tool. The targeted respondents were the registered lecturers in higher education institutes of Sri Lanka, selected based on simple random sampling method. Structural equation modelling (SEM) procedure was employed for data analysis using IBM SPSS (ver.21) and AMOS (Ver.26). The structural path analysis resulted in partial mediation, confirming that “lecturer’s innovativeness in IT” exerts its influence on VLE adoption intention by altering the mediators set in the study. Further, the study validated a unique set of factors that determine lecturer’s acceptance of VLE in a higher education setting.

Trust establishment (TE) among sensor nodes has become a vital requirement to improve security, reliability, and successful cooperation. Existing trust management approaches for large scale WSN are failed due to their low cooperation (i.e., dependability), higher communication and memory overheads (i.e., resource inefficient). This paper provides a new and comprehensive hybrid trust estimation approach for large scale WSN employing clustering to improve cooperation, trustworthiness, and security by detecting selfish sensor nodes with reduced resource (memory, power) consumption. The proposed scheme consists of unique features like authentication based data trust, scheduler based node trust, and attack resistant by giving the high penalty and minimum reward during node misbehavior. A task scheduling mechanism is employed for scheduling the significant task to reduce computation overhead. The proposed trust model would be capable to provide security against blackhole attack, grey hole attack, and badmouthing attack. Moreover, the proposed trust model feasibility has been tested with MATLAB. Simulation results exhibit the great performance of our proposed approach in terms of trust evaluation cost, prevention, and detection of malicious nodes with the help of analyzing consistency in trust values and communication overhead.