Sharif Digital Repository

By generalising dictionary learning (DL) algorithms to multidimensional (MD) mode and using them in applications where signals are inherently multidimensional, such as in three-dimensional (3D) inverse synthetic aperture radar (ISAR) imaging, it is possible to achieve much higher speed and less computational complexity. In this study, the formulation of the multidimensional dictionary learning (MDDL) problem is expressed and two algorithms are proposed to solve it. The first one is based on the method of optimum directions (MOD) algorithm for 1D dictionary learning (1DDL), which uses alternating minimisation and gradient projection approach. As the MDDL problem is non-convex, the second... 

The rapid shrinkage of Lake Urmia over the past two decades has raised serious environmental concerns. Several restoration plans have been proposed to reduce agricultural water consumption to supply a remarkable fraction of the lake's environmental flow requirement. However, an accurate and realistic evaluation of the effectiveness of these plans in reducing agricultural water consumption across the basin is still poorly understood. This study assessed the water-saving potential of agricultural alteration in a snow-dominated catchment in the Lake Urmia Basin. In particular, we explored the impact of crop pattern alteration via reducing the cultivation area and employing different irrigation... 

Public concern over environmental issues such as ecosystem degradation is high. However, restoring coupled human-natural systems requires integration across many science, technology, engineering, management, and governance topics that are presently fragmented. Here, we synthesized 544 peer-reviewed articles published through September 2020 on the desiccation and nascent recovery of Lake Urmia in northwest Iran. We answered nine questions of scientific and popular interest about causes, impacts, stabilization, recovery, and next steps. We find: (1) Expansion of irrigated agriculture, dam construction, and mismanagement impacted the lake more than temperature increases and precipitation... 

Over the past decades, there has been a dramatic increase in the frequency of natural disasters, which are the leading causes of large-scale power outages. This paper, therefore, assesses the significance and role of optimal tie-line construction in improving the service restoration performance of unbalanced power distribution systems in the aftermath of high-impact low-probability incidents. In doing so, a restoration process aware stochastic mixed-integer linear programming model is developed to find the optimal locations for new tie-line construction in unbalanced three-phase distribution systems. In particular, the restoration process of distribution systems, including the fault... 

Event-related potential (ERP) extraction from ongoing electroencephalograph (EEG) and its enhancement is one of the long-established problems in EEG signal processing. Most of the previous studies have focused mainly on the ERP enhancement without considering the multi-dimentional structure of the signal. In order to take advantage of this property, we propose a tensor-based solution with trial-by-trial concatenated ERP data. Then we develop an algorithm based on low-rank Tucker decomposition to detect single trial ERP component with maximized signal to noise ratio (SNR). In other words, by using tensor algebra we consider both self-similarity in intratrials and global correlation in spatial... 

Extreme weather events can devastate parts of power grids. Thus, the appropriate post-disaster reaction is a crucial duty for power utilities. To address this important concern, a new two-stage framework is proposed in this paper. Stage I optimally coordinates disaster mutual assistance between affected and supporting utilities. To this end, distance between the damaged and supporting utilities, extent of damage, and repair resources are taken into consideration as decision criteria. Then, a novel formulation in the form of mixed integer linear programming (MILP) is developed for mutual aid management problem. The results of stage I are used as inputs to stage II. A new multi-horizon... 

In recent decades, population growth, agricultural development and climate change have caused environmental problems in the world, especially in the arid and semi-arid regions such as Iran. Urmia Lake, one of the unique biosphere reserves of the world, has suffered from these problems in the last 20 years. Although many studies conducted to the negative impacts of human-induced activities, especially agricultural expansion on the lake, few studies focused on providing restoration plans for that. This study uses a system dynamics method for modelling the restorations scenarios of Urmia Lake based on the prey-predator approach. This method is helpful to simplify the complicated feedbacks and... 

Flat plate solar collectors lose a massive part of heat accumulated near the contact region because of the poor thermal characteristics of the working fluid. A new cost-effective design is numerically studied to cover up such deficiency by equipping the flat plate collector with revolutionary tubes and magnetic field inducer to affect Fe3O4/water working nanofluid in the collector tubes. Results substantiate that each of the applied rotary tubes and magnetic field inducer improves the convection mechanism in the tubes by circulating the flow inside the tubes and saves more of available solar energy. Results reveal that 27.8% and 10.44% of lost energy are restored in the solar collector... 

Bathymetric mapping for an accurate estimation of stored water volume in drying lakes is a key information for an effective monitoring of their recession or restoration status. Extraction of bathymetry in shallow saline lakes using remote sensing techniques has always been challenging due to the complex influences imposed by the physical properties of substrate and the spatial variability of salinity. In this study, we developed a machine learning-based model to quantify the implicit, non-linear relationship between water depth and surface reflectance by leveraging extensive in-situ data and high-resolution satellite imagery. We trained and tested the learning model in the hyper-saline Lake... 

Lake Urmia is the second-largest hypersaline lake in the world. There has been a drastic water level drop of 7.2 m from 1995 to 2016. Beginning in October 2013, the Lake Urmia Restoration Plan (LURP) launched a 10-year program. An increase in water level and a relative improvement in Lake Urmia condition has been observed since 2017. It is an undecided and controversial issue whether the recent positive trend of Lake Urmia has been due to the LURP activities or it is a natural contribution of climate factors variations. To shed some light on this issue, we examine three other lakes, adjacent to the Lake Urmia basin, with similar rainfall variability to investigate their status during the... 

Lake Urmia in Iran has undergone catastrophic desiccation due to increasing anthropogenic development, especially in the agricultural sector. A paramount national goal is to restore the lake to its former healthy condition, but corresponding water governance and restoration efforts have encountered various, mostly human-related, challenges. We argue here that these challenges stem from lack of awareness and insufficient consideration of the local social conditions and the subtleties of human-water interactions, which we collectively refer to as socio-hydrological barriers. Ignorance of such socio-hydrological barriers can lead to policy efforts that are mismatched with local realities and,... 

Over the past decades, there has been a dramatic increase in the frequency of natural disasters, which are the leading causes of large-scale power outages. This paper, therefore, assesses the significance and role of optimal tie-line construction in improving the service restoration performance of unbalanced power distribution systems in the aftermath of high-impact low-probability incidents. In doing so, a restoration process aware stochastic mixed-integer linear programming model is developed to find the optimal locations for new tie-line construction in unbalanced three-phase distribution systems. In particular, the restoration process of distribution systems, including the fault... 

Carbonaceous materials (CMs) have been applied extensively for enhancing the catalytic performance of environmental catalysts, however, the self-catalytic mechanism of CMs for groundwater remediation is rarely investigated. Herein, we unveiled the catalytic ability of various CMs via Fe(III) reduction through polyvinyl alcohol-coated calcium peroxide nanoparticles (PVA@nCP) for trichloroethylene (TCE) removal. Among selected CMs (graphite (G), biochar (BC) and activated carbon (AC)), BC and AC showed enhancement of TCE removal of 89% and 98% via both adsorption and catalytic degradation. BET and SEM analyses showed a higher adsorption capacity of AC (27.8%) than others. The generation of... 

Carbonaceous materials (CMs) have been applied extensively for enhancing the catalytic performance of environmental catalysts, however, the self-catalytic mechanism of CMs for groundwater remediation is rarely investigated. Herein, we unveiled the catalytic ability of various CMs via Fe(III) reduction through polyvinyl alcohol-coated calcium peroxide nanoparticles (PVA@nCP) for trichloroethylene (TCE) removal. Among selected CMs (graphite (G), biochar (BC) and activated carbon (AC)), BC and AC showed enhancement of TCE removal of 89% and 98% via both adsorption and catalytic degradation. BET and SEM analyses showed a higher adsorption capacity of AC (27.8%) than others. The generation of... 

Socio-ecological systems include diverse resources of complexity involving complicated interactions, feedback, dynamic behavior patterns, heterogeneity in agents’ characteristics and behaviors, as well as system uncertainties. Agent-based modeling is introduced as a tool to simulate different levels of stakeholders and interactions, including individual, group, and institutional agents in complex socio-ecological systems. In the present study, an agent-based model was developed to explore sustainable solutions in uncertain conditions for groundwater restoration of a critical aquifer in the Lake Urmia Basin, Iran. Different projects for aquifer restoration such as wells monitoring, license... 

A procedure based on the linear amplitude sweep (LAS) test has been developed to determine the optimum rejuvenator content for restoring the properties of aged asphalt binders. The LAS test was employed to assess the damage tolerance, fatigue resistance, and fracture behavior of rejuvenated aged binders. In case of fracture analysis, a crack-based indicator to govern the stable crack propagation was defined to characterize fracture resistance of asphalt binders. While rejuvenators improved all of these properties, higher contents were required to restore the cracking behavior of the original binder. The linear relationship between the integrated damage-fatigue-fracture indicator and... 

Recently, deep convolutional neural networks (DCNN) that leverage the adversarial training framework for image restoration and enhancement have significantly improved the processed images' sharpness. Surprisingly, although these DCNNs produced crispier images than other methods visually, they may get a lower quality score when popular measures are employed for evaluating them. Therefore it is necessary to develop a quantitative metric to reflect their performances, which is well-aligned with the perceived quality of an image. Famous quantitative metrics such as Peak signal-to-noise ratio (PSNR), The structural similarity index measure (SSIM), and Perceptual Index (PI) are not well-correlated... 

This paper reports on the NTIRE 2021 challenge on perceptual image quality assessment (IQA), held in conjunction with the New Trends in Image Restoration and Enhancement workshop (NTIRE) workshop at CVPR 2021. As a new type of image processing technology, perceptual image processing algorithms based on Generative Adversarial Networks (GAN) have produced images with more realistic textures. These output images have completely different characteristics from traditional distortions, thus pose a new challenge for IQA methods to evaluate their visual quality. In comparison with previous IQA challenges, the training and testing datasets in this challenge include the outputs of perceptual image... 

Background:: Since the cornea is responsible for transmitting and focusing light into the eye, injury or pathology affecting any layer of the cornea can cause a detrimental effect on visual acuity. Aging is also a reason for corneal degeneration. Depending on the level of the injury, conservative therapies and donor tissue transplantation are the most common treatments for corneal diseases. Not only is there a lack of donor tissue and risk of infection/rejection, but the inherent ability of corneal cells and layers to regenerate has led to research in regenerative approaches and treatments. Methods:: In this review, we first discussed the anatomy of the cornea and the required properties for... 

The remediation of nonaqueous phase liquids (NAPLs) enhanced by surfactant and nanoparticles (NP) has been investigated in numerous studies. However, the role of NP-assisted surfactants in the dissolution process is still not well discussed. Besides, there is a lack of empirical dissolution models considering the effects of initial residual saturation Strap, NAPL distribution, and surfactant concentration in NAPL-aqueous phase systems. In this work, micromodel experiments are conducted to quantify mass transfer coefficients for different injected aqueous phases including deionized water, SDS surfactant solutions, and NP-assisted solutions with different levels of concentrations and flow...