فهرست مطالب zahra saadati

The data generated in the Internet of Things (IoT) ecosystem requires continuous and timely processing. Transferring generated data to cloud data centers is costly and unsuitable for real-time applications. To increase the speed of service delivery, resources should be placed as close as possible to the user, i.e. at the edge of the network. A new paradigm called fog computing was introduced and added as a layer in the IoT architecture to meet this challenge. Fog computing provides the processing and storage of IoT data locally in the vicinity of IoT devices rather than in the cloud. Fog computing can provide less latency and better service quality for real-time applications than cloud computing. In general, there are theoretical foundations for fog computing, but the issue of locating IoT services to fog nodes remains a challenge and has attracted a great deal of research.

In this research, a conceptual computing framework based on cloud-fog control software is proposed to optimally locate IoT services. The proposed model is formulated as an autonomous planning model for managing service requests due to some constraints, considering the heterogeneity of programs and resources. To solve the problem of locating IoT services, an autonomous evolutionary approach based on enhanced learning approaches has been proposed with the aim of making maximum use of fog-based resources and improving service quality. A heterogeneous advantage operator-criterion algorithm is used as a new reinforcement learning approach aimed at maximizing long-term cumulative reward.

The results of the comparisons showed that the proposed reinforcement learning-enabled framework performs better than the advanced methods of the literature. The results of the proposed method compared to FSP-ODMA, SPP-GWO, CSA-FSPP, and GA-FSP methods indicate 4.6%, 2.4%, 3.4%, and 1.1% improvement, respectively.

Experimental studies were performed on a simulated artificial environment based on various metrics including fog usage, services performed, response time, and service delay. The proposed reinforcement learning-enabled framework outperforms the previous works and shows better scalability.Analysis of parallel heuristic algorithms to find a more accurate localization than evolutionary approaches is another aspect of future work. We intend to consider new reinforcement learning approaches such as the Asynchronous Advantage Actor Critic (A3C) algorithm along with the long-term cumulative reward maximization policy for locating services. Also, future efforts will explore reinforcement learning approaches for failure recovery towards Cloud-Fog-IoT architecture, where parallel processing architecture of IoT services can be considered in the location process.

Job burnout is a psychological syndrome and is most commonly seen in occupations that have long been associated with humans. the purpose of this study is to predict the burnout of elementary teachers based on religious beliefs and mindfulness with regard to the mediating role of resilience. The purpose of this study is descriptive and correlational. the statistical population consisted of elementary school teachers in Yazd in the school year of 2021-2022. Using simple random sampling method, 299 teachers were selected based on Cochran formula. information was collected using the four Maslach Burnout Questionnaires (2014), Connor-Davidson Resilience Questionnaire, Freiburg Mindfulness Questionnaire (2006), and Ganji and Nayebzadeh's religious beliefs (2014). Also, Data were also analyzed Path analysis analysis and Sabel test. The results showed that there is a linear and inverse relationship between the variables of religious beliefs, mindfulness and burnout, and the higher the resilience criterion in teachers, the lower the burnout of teachers. thus the variables of religious beliefs, mindfulness and resilience predict the burnout of Yazd elementary school teachers. In addition, the findings showed that mediation resilience is a relationship between religious beliefs and job burnout, and mindfulness predicts job burnout directly and indirectly

Bioaerosols are airborne particles that contain bacteria, viruses, and fungi. Human reactions to bioaerosols are very different. This study attempted to determine indoor and outdoor fungal density in nursery schools in Birjand city and compares the relationship between air fungus density and particulate matter (PM) with mean temperature and relative humidity (RH) in three seasons: Fall, Winter, and Spring. This cross-sectional study was conducted in six nursery schools within a period of 2017-2018. Bioaerosols sampling from the indoor and outdoor air was performed by air-trapping method (28.3 L/min) for 35 min, collected in Sabouraud dextrose agar medium. The air temperature and relative humidity (RH) were measured. The mean temperature of indoor and outdoor was 23.49±4.259 and 20.87±5.57, and the relative humidity of 36.04±12.86 and 22.4±7, respectively. The most isolated fungal species was Penicillium spp. There is a difference between the dispersal of fungi and suspended particles and the humidity of the two environments (p=0.001). Moreover, there is only a difference in the distribution of fungi in fall (p=0.035). Generally, the contamination of indoor is linked to a load of outdoor airborne fungal spores. It can be safely concluded that bioaerosol has outdoor sources and ventilation plays an important role in improving the quality of the indoor air.

The importance of leisure is not overlooked by anyone in today's world full of tension, where people often feel tired because of their busy work. On the other hand, there is deviant leisure which can have many consequences as an activity that violates the ethical, moral and legal norms of the community. It endangers social security in society. This study examines the effect of self-control dimensions on the deviant leisure of youth. The general theory of crime admits that low self-control providing the context of deviant behavior. In this study, survey method was used and questionnaire was used to collect information. The population of this analysis includes all 18-35 years old youths in Babolsar. 400 youth with Cochran formula were selected by using multistage cluster sampling. We used face validity and Cronbach's alpha as reliability. Deviant leisure explained in two types of obvious deviant leisure and latent deviant leisure. Latent deviant leisure was more than obvious deviant leisure. The results of Pearson correlation indicate that there is a significant relationship between low self-control and with deviant leisure. According to the research theoretical model test, which was carried out using structural equation modeling, it was found a positive effect of low self-control on deviant leisure (Beta=0/65). Also, the research components altogether could explain 43% of the variations of dependent variable (deviant leisure).in all it can says that persons that have low self-control more do deviant leisure action in leisure times.

Bioaerosols are airborne particles that contain bacteria, viruses and fungi. Human reaction to bioaerosols is very different. The aim of this study was performed to determine the density of bacterial particles cultivable in the air of inside and outside kindergartens in Birjand.

This descriptive-analytical cross-sectional study was performed. Birjand city was divided into 5 regions based on geographical location and 6 kindergartens were randomly selected. Sampling was done in the morning shift from 6 selected kindergartens.The culture medium used was triptic soy agar for bacteria. Sampling was performed at a flow rate of 28.3 L/Min in 35 minutes at a distance of 0.8 to 1 M above the ground in the center of each class. Statistical analysis was performed using SPSS (Version.16) software and Mann-Whitney and Kruskal-Wallis statistical tests and a significance level (P<0.05) was considered.

The results showed that the highest mean bacterial microbial load in February was (3.83±8.04) CFU/m3 and suspended particles in March (196.13±382.54) CFU/m3. There was no significant relationship between bacterial density with suspended particles and temperature (P>0.05). There was a significant relationship between bacterial density and total suspended particles (P<0.05). There was a significant relationship between the amount of suspended particles (PM1, PM2.5, PM10) with the environment inside and outside the kindergarten (P<0.05).

From the findings of this study, the concentration of bacterial contamination in terms of quantity and type of identified species and the amount of airborne particles can be identified to prevent adverse health effects.

Simulation models that illustrate the effects of water on crop yield are useful tools to optimize water productivity and improve farm level water management. In this study, the performance of AquaCrop model to simulate canopy cover, biomass and yield of the sugar beet and soil water content under six irrigation treatments was evaluated. The irrigation treatments were consisted of full irrigation (T1) as control, removing last irrigation (T2), applying irrigation water at 10% greater than control (T3), applying irrigation water at 10 (T4), 20 (T5) and 30% (T6) less than control. The experiment was conducted at Aleshtar in Lorestan province during growing seasons of 2014 and 2015, using a randomized complete block design. The first and second year’s data were used for calibrating and validating of the model, respectively. Evaluation of the model was performed using the coefficient of residual mass, root mean square error, normalized root mean square error, index of agreement and coefficient of determination. According to the results, the normalized root mean square error in the canopy cover and soil water content simulations for calibration was 5.18 to 9.41 percent and 9.91 to 17.23 percent, respectively and for validation was 6.64 to 9.2 percent and 12.36 to 25.77 percent, respectively. Also, the normalized root mean square error in the yield and biomass simulations for calibration was 7.3 and 8.67 percent and for validation was 7.69 and 9.82 percent, respectively. The results indicated a good performance of the AquaCrop Model in simulating the canopy cover development, biomass and yield of sugar beet and soil water content under different irrigation managements. Therefore, the AquaCrop model can be used to explore management scenarios to improve the sugar beet water management over the study region.

The purpose of this research is to study the littering as indicator of social disorder.Therefore, this article tries to explain tourist’s leisure behavior with to emphasize littering.Therefore tourism is stated as the most important issues in contemporary societies The research is of the survey type, and the research data were collected from tourists in mazandaran province questionnaires. The sample in included 384 people, selected with multistep clustering method. The theory used in this research is broken windows theory. The research data were analyzed via SPSS and AMOS software. The results obtained from the correlation test demonstrate that there is a positive, significant relationship between littering as an instance of tourists deviant leisure behavior and weak social control, others littering, polluted environment, positive attitude toward littering, and environmental in responsibility. These variables enforce littering among tourists. Testing the theoretical model demonstrates that these variables have successfully explained 22 percent of the changes in the dependent variable.

The simulation models of yield response to water are expected to play an increasingly important role in the optimization of water productivity (WP) in agriculture. In this study, the CERES-Wheat model was used to simulate of wheat yield response under different irrigation-cultivar treatments with three irrigation treatments in main plots and Five wheat cultivars in sub plots consisted of C1:C-75-5, C2: C-78-4, C3:C-78-8, C4: C-79-6 and C5: C-79-16 in Mashhad region during the years of 2002-2003 and 2003-2004. According to the results, the relative root mean square error of grain yield simulation by CERES-Wheat model was 7 and 10 % for 2002-2003 and 2003-2004 years, respectively. Because, the relative root mean square error was less than 10 percent, so done well simulation. Also, the root mean square error calculated for grain yield for both years was less than 10 percent of the observed mean. The results are indicating a good match to the simulation results of the model. The value water productivity based on crop evapotranspiration and irrigation water value in I3-C-79-6 treatment has the value highest for both years of 2002-2003 and 2003-2004. Therefore, the noted irrigation management (I3) and wheat cultivar (C-79-6) can be recommended in the study area. The overall findings of this study to confirm the optimal performance of the model CERES-Wheat in the growth process simulation and the water impact on yield in the study area.

The modeling of yield response to water is expected to play an increasingly important role in the optimization of crop water productivity (WP) in agriculture. In this study, the CropSyst model was used to simulate two local rice varieties yield response under five irrigation treatments consisting of continuous flooding irrigation and irrigation at 0, 3, 6 and 9 days after the disappearance of water from the soil surface. The experiment was conducted at Rasht region during two growing seasons of 2003 and 2004. The model was calibrated using the first year data and validation of that was done using the second year data set. The result of F test shows that there was not a significant difference between the measured and simulated yield at confidence level of 99%. The relative errors of yield estimation were obtained between -0.81 to 12.58% and -2.4 to 19.42% for Binam and Hasani cultivars in 2003, respectively. These values were 0.83 to 16.4% and -2.82 to 21.27% in 2004, respectively. The results showed that due to the CropSyst model ability in simulating yield of rice under different irrigation regimes, this model can be used to explore management optimum options to improve rice water productivity