درخت حوزه‌های تخصصی

This research aims to investigate the effect of conservative reporting on the investors' opinion divergence at the time of earnings announcement in a 5 year period during 2012-2016; the required data have been collected from Tehran Securities and Stock Exchange Organization and the population is consisted of 585 corporates-years which have been selected by the systematic removal sampling. To investigate the research hypotheses, linear regression and correlation were used and to analyze data and test the hypotheses, Eviews software has been utilized. In conclusion, it can be pointed out that the conservative measures are negatively related to the proxies of investors' opinion divergence at the time of earnings announcement and the relationship is stronger when the corporate reports bad news; also, conservation information content is stronger when the market is shocked by an announcement.Key words: Investors' opinion divergence at the time of earnings announcement, conservative reporting, bad news

Negative relation between unemployment and inflation is known as the Philips model, which states, when inflation is high, unemployment gently decries and when unemployment is low, salaries will increase rapidly. While economic planners of the country tend to impart this situation highly, it would fall down, because frequent increase of inflation with the hope of keeping unemployment low permanently, ultimately will cause rise in expected inflation of organizations and lead to change in their recruitment decisions. In a section of this model, it has also analyzed, relation between income, investment, and consumption. Regular Philips model with derivative deals with first and second level of calculations, however this model has faced many weaknesses and deficiencies in economic cycle of Iran. Regarding its implementation in the economy of Iran, in this research, through substitution of Caputo fractional-order derivatives, we reach out “Philips model of Fractional-order”. Moreover, by numerical calculation of resulted equations and using Maple software, we over reach to Philips curve of Fractional-order in multiple various orders. According to achieved results, this model highly depends on derivation orders and different outcomes will be acquired through various derivation orders. Acquired model in the economy of Iran (situational format in Sugar and Sugar cube Industries) has been studied through phasic technic which proves meaningfulness of relations between variables of the model.

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 cemetery has been used as an indigenous urban space, a place for social interactions, the memories of survivors, and the cultural identity of the legibility of urban areas in the past. For example, Takht-e-Foolad Cemetery is one of the most valuable cemeteries in the Shiite world. Takht-e Foulad Cemetery is one of the successful architectural examples of the attitude towards spiritual tourism. The tomb’s architecture shows the depth of the Iranian spirit of belief in the spiritual dimension of life. In most parts of Iran, this type of architecture, mostly in the form of shrines (Imamzadeh) or the tombs of people with honors, and sometimes family tombs, can be found. Tomb architecture in Iran has been different according to time and place. One factor that has had a significant impact on the type of architecture is each period's cultural, social, and spiritual conditions. Despite their socio-historical importance, family tombs are among the buildings that have been less studied and considered in tomb architecture. Family tombs have different functions according to different definitions. Although they have gradually lost their function and importance over time, recognizing them seems necessary.  The difference in the performance of these buildings (family tombs) in each period creates the motivation to study and analyze them from a historical and cultural perspective. With a qualitative research approach, analytical-comparative research method, and field research with studies, the present study is a library to address the role of family tombs in the development of spiritual tourism that is part of tomb architecture. It should be acknowledged that the spatial and temporal realm of this research includes the family tombs of Takht-e-Foolad Cemetery in Isfahan.

The special issue aims to cover the latest research topics in designing and deploying visual information analytics and management techniques using deep learning. It is intended to serve as a platform to researchers who want to present research in deep learning. The special issue focuses explicitly on deep learning and its application in visual computing and signal processing. It emphasizes on the extent to which Deep Learning can help specialists in understanding and analyzing complex images and signals. The field of Visual Information Analytics and Management is considered in its broadest sense and covers both digital and analog aspects. This involves development of techniques for image analysis, understanding and restoration. Deep learning techniques are effective for visual analytics. Deep learning is a fast growing area and is gaining impetus for application in various fields. Therefore, in this special issue, the objective is to publish articles related to deep learning in various problems of visual information analytics and management.

Online reviews have become essential aspect in E-commerce platforms due to its role for assisting customers’ buying choices. Furthermore, the most helpful reviews that have some attributes are support customers buying decision; therefore, there is needs for investigating what are the attributes that increase the Review Helpfulness (RH). This research paper proposed novel model called inclusive review helpfulnessmodel (IRHM) can be used to detect the most attributes affecting the RH and build classifier that can predict RH based on these attributes. IRHM is implemented on Amazon.com using collection of reviews from different categories. The results show that IRHM can detect the most important attributes and classify the reviews as helpful or not with accuracy of 94%, precision of 0.20 and had excellent area under curve close to 0.94.