درخت حوزه‌های تخصصی

As a symbol of the Islamic spiritual economy, Waqf has been always present and alive in all aspects of the Islamic countries, and it has attracted the attentions of many researchers of different fields due to its multidimensional functional. Based on their desire for eternity, they defined Waqf in terms of a proverb saying “I benefit from whatever I endow”. In several tourists’ travelogues such as travelogues by Nasir Khusraw, Jean Chardin, etc. has mentioned this spiritual tradition as a humanistic economy showing the effects of Waqf on perceiving the tourist destination. Since the modern generation of tourists look for new experiences, thus obtaining a rich content of this spiritual heritage can satisfy them and help the promotion of humanistic models of economy such as Waqf . In terms of its objective, this is a practical research, and it is descriptive-analytical based on its data collection method. The results are obtained in meta-synthesis of documents, articles and travelogues relation to the Waqf tradition. Indeed, the main objective of this article is to provide the mentioned introduction, promotion and reinforcement to understand the different aspects of Waqf tradition based on the travelogues in order to reinforce the perceived value by the tourists of Iranian cities so that the modeling of these concepts leads to the promotion of this spiritual economy model among the other cultures. The results show that considering the perceivable aspects of Waqf , this intangible heritage can be introduced to the tourists in terms of four main aspects including the emotional, cognitive, functional and social aspects and to promote this spiritual heritage based on the religious background of tourists at the international level with regard to the environmental-humanistic aspects of economy; as in Iranian culture, it is believed that “give bread to everyone who enters this house and don’t ask his faith, because the one who deserves a life for god, deserves a bread for us”.

The secret to achieving your organization's goals in complex and challenging environments is to make the right managerial and rational decisions. In this regard, the accounting information system as one of the sources of information for the decision of managers is of particular importance. Therefore, in order to achieve these goals, it is necessary to have an accounting information system with dynamic capabilities. The dynamic capability of the accounting information system (hidden variable) was measured by the observed variables of flexibility, continuous evaluation, continuous investment and system variability. Therefore, based on this argument, the aim of the present study is to provide a dynamic capability model of the accounting system based on the financial effectiveness of the management accounting system. Data envelopment analysis is a well-known methodology that is applied to evaluate the selected firms based on the most important features. The results of analysis of the proposed method on 86 companies listed on the Tehran Stock Exchange and analysis and analysis of data by structural equation modeling show that the dynamic capability of the accounting information system consists of (flexibility, continuous evaluation, continuous investment and system variability). The result indicate that the management accounting system is effective.

Cloud Computing has drastically simplified the management of IT resources by introducing the concept of resource pooling. It has led to a tremendous improvement in infrastructure planning. The major goals of cloud computing include maximization of computing resources with minimization of cost. But the truth is that everything has a price and cloud computing is no different. With Cloud computing there comes a number of security concerns which need to be addressed. Cloud forensics plays a vital role to address the security issues related to cloud computing by identifying, collecting and studying digital evidence in cloud environment. The aim of the research paper is to explore the concept of cloud forensic by applying optimization for feature selection before classification of data on cloud side. The data is classified as malicious and non-malicious using convolutional neural network. The proposed system makes a comparison of models with and without feature selection algorithms before applying the data to CNN. A comparison of different metaheuristics algorithms- Particle Swarm Optimization, Shuffled Frog Leap Optimization and Fire fly algorithm for feature optimization is done based on convergence rate and efficiency.