Sharif Digital Repository

As the infrastructure-centric model of peer-to-peer streaming, recent overlay construction schemes compose a hierarchical topology of peers by grouping them into clusters. There is a server in each cluster that receives data from the source and relays it to its cluster members. In this paper, we propose an alternative infrastructure-centric peer-to-peer framework called BAHMO that constructs a hierarchical multicast tree. BAHMO does not utilize server bandwidth and rely only on peer bandwidth for data transfers. It achieves both the stability of the infrastructure-centric model and the bandwidth efficiency of the fully-distributed model. Bandwidth assignment for inter-cluster data transfers... 

This study provides a stochastic dynamic programming model with a Markov chain that explicitly focuses on the customer as well as a new model for valuing the customers in the banking industry. The proposed framework calculates individual customer’s lifetime value dynamically. The study follows a stochastic dynamic programming model that is based on the Markov chain. The deduced findings are illustrated with supplementary context from an outstanding case study. The findings underline the importance of the stochastic model for calculating customer lifetime value based on customer behavior. The presented framework provides a beneficial way for future research and valuable insight for allocating... 

Efforts have been targeted at providing a comprehensive simulation of a centrifugal compressor undergoing surge. In the simulation process, an artificial neural network was utilized to produce an all-inclusive performance map encompassing those speeds not available in the provided curves. Two positive scenarios for the shaft speed, constant, and variable, were undertaken, and effects of load line on the dynamic response of the compressor have been studied. In order to achieve high-fidelity simulation in the variable speed case, an artificial neural network was utilized to produce an all-inclusive performance map encompassing those speeds not available in the provided curves. Moreover,... 

A novel technique based on image processing inspired by the simple assumption for the first time to assess the roughness of nanofibrous mats based on grayscale variations is proposed. The height of a nanofibrous mat in different regions of the surface is simulated by grayscale variations in the image while the relation between grayscale and height is obtained as a linear function. The roughness is obtained by measuring height variations in the surface profile. Statistical roughness parameters of nanofibrous mats are also obtained from direct measurement with roughness profilometry and atomic force microscopy (AFM) for comparison of the roughness of nanofibrous mats between direct measurement... 

Twitter as one of the most important microblogging online social networks has attracted more than 200 million users in recent years. Although there have been several attempts on characterizing the Twitter by using incomplete sampled data, they have not been very successful to estimate the characteristics of the whole network. In this paper, we characterize Twitter by sampling from its social graph and user behaviors through a random walk based sampling technique called Respondent-Driven Sampling (RDS). To the best of our knowledge, for the first time RDS method and its estimator are used in order to obtain uniform unbiased estimation of several key structural and behavioral properties of... 

Remotely sensed data inherently contain noise. The development of inverse modelling methods with a low sensitivity to noise is in demand for the estimation of geophysical variables from remotely sensed data. The Active Learning Method (ALM) is well known to have a low sensitivity to noise. For the first time, ALM was utilized for the inversion of radiative transfer calculations with the aim of estimating chlorophyll a (Chl a), coloured dissolved organic matter (CDOM), and suspended particulate matter (SPM) in the Caspian Sea using MERIS (MEdium Resolution Imaging Spectrometer) data. ALM training is straightforward and fast. The ALM inversion models revealed the most relevant variables and... 

Due to the noise that is present in remote sensing data, a robust method to retrieve information is needed. In this study, the active learning method (ALM) is applied to spectral remote sensing reflectance data to retrieve in-water pigment. The heart of the ALM is a fuzzy interpolation method that is called the ink drop spread (IDS). Three datasets (SeaBAM, synthetic and NOMAD) are used for the evaluation of the selected ALM approach. Comparison of the ALM with the ocean colour 4 (OC4) algorithm and the artificial neural network (ANN) algorithm demonstrated the robustness of the ALM approach in retrieval of in-water constituents from remote sensing reflectance data. In addition, the ALM... 

All of the man-made objects and anthropogenic activities related to the oil industries in water bodies (e.g. drilling, equipment installation, construction of oil platfonns and especially oil spillages) have enviromnental impacts on water ecosystems. The assessment of oil field operations and oil platfonns impacts on water quality have become a necessity throughout the world. Phytoplanktons have the lowest trophic level in water enviromnent; therefore the life of all of the other marine animals is highly relevant to phytoplanktonic population. Hence it seems necessary to monitor the spatiotemporal effects of different activities and events, related to oil industries on phytoplanktons.... 

A double burden of malnutrition occurs when individuals, household members or communities experience both undernutrition and overweight. Here, we show geospatial estimates of overweight and wasting prevalence among children under 5 years of age in 105 low- and middle-income countries (LMICs) from 2000 to 2017 and aggregate these to policy-relevant administrative units. Wasting decreased overall across LMICs between 2000 and 2017, from 8.4% (62.3 (55.1–70.8) million) to 6.4% (58.3 (47.6–70.7) million), but is predicted to remain above the World Health Organization’s Global Nutrition Target of <5% in over half of LMICs by 2025. Prevalence of overweight increased from 5.2% (30 (22.8–38.5)... 

An amendment to this paper has been published and can be accessed via a link at the top of the paper. © 2020, The Author(s)  

Anemia is a globally widespread condition in women and is associated with reduced economic productivity and increased mortality worldwide. Here we map annual 2000–2018 geospatial estimates of anemia prevalence in women of reproductive age (15–49 years) across 82 low- and middle-income countries (LMICs), stratify anemia by severity and aggregate results to policy-relevant administrative and national levels. Additionally, we provide subnational disparity analyses to provide a comprehensive overview of anemia prevalence inequalities within these countries and predict progress toward the World Health Organization’s Global Nutrition Target (WHO GNT) to reduce anemia by half by 2030. Our results...