Sharif Digital Repository

Blockchain technology brings about an opportunity to maintain decentralization in several applications, such as cryptocurrency. With the agents of a decentralized system operating independently, it calls for a consensus protocol that helps all nodes to agree on the state of the ledger. Most of the existing blockchains rely on Proof of Work (PoW) as the underlying consensus algorithm, resulting in a significant amount of electricity power consumption. Furthermore, it demands the miner to buy specific computation devices. Besides, a protocol to gather the society-related taxes such as public education funding and charities is lacking in existing consensus algorithms. In response, this paper... 

Public transport is amongst critical infrastructures in modern cities, especially megacities, home to millions of people. The reliability of these systems is highly crucial for both citizens and service providers. If service providers overlook system reliability, a considerable amount of expenses will be wasted. Several factors such as vehicle failure, accident, lack of budget weather factors, and traffic congestion cause unreliability, among which vehicle failure plays a prominent role. The brake system is the most vulnerable and vital component of a public transportation bus. Brake reliability depends on driver's expertise, component quality, passenger loading, line situation, etc.... 

Natural disasters threaten the sustainability of electric power supply. This fact highlights the importance of enhancing technological resourcefulness to handle the upcoming events. Once a natural disaster occurs, the most urgent undertaking is to rapidly pinpoint and assess component damages and dispatch the repair crews towards the most critical impaired elements. Practical efforts confirm that utilising a drone, which is an unmanned aerial vehicle, can notably reduce the duration of post-disaster distribution system damage assessment (DA) and increase the resilience of power systems. This study presents an optimisation model to determine the optimal number and type of drones required for... 

Natural disasters threaten the sustainability of electric power supply. This fact highlights the importance of enhancing technological resourcefulness to handle the upcoming events. Once a natural disaster occurs, the most urgent undertaking is to rapidly pinpoint and assess component damages and dispatch the repair crews towards the most critical impaired elements. Practical efforts confirm that utilising a drone, which is an unmanned aerial vehicle, can notably reduce the duration of post-disaster distribution system damage assessment (DA) and increase the resilience of power systems. This study presents an optimisation model to determine the optimal number and type of drones required for... 

Both frequency and intensity of natural disasters have intensified in recent years. It is, therefore, essential to design effective strategies to minimize their catastrophic consequences. Optimizing recovery tasks, including distribution system reconfiguration (DSR) and repair sequence optimization (RSO), are the key to enhance the agility of disaster recovery. This article aims to develop a resilience-oriented DSR and RSO optimization model and a mechanism to quantify the recovery agility. In doing so, a new metric is developed to quantify the recovery agility and to identify the optimal resilience enhancement strategies. The metric is defined as 'the number of recovered customers divided... 

Electricity demand forecast is necessary for power systems' operation scheduling and management. However, power consumption is uncertain and depends on several factors. Moreover, since the onset of covid-19, the electricity consumption pattern went through significant changes across the globe, which made the forecasting demand more challenging. This is mainly due to the fact that pandemic-driven restrictions changed people's lifestyles and work activities. This calls for new forecasting algorithms to more effectively handle these conditions. In this paper, ensemble-based machine learning models are utilized for this task. The lockdown temporal policies are added to the feature set in order... 

Distribution system reconfiguration is an effective solution to reduce the consequences of a disaster through transferring loads to another feeder via automatic switches. Meanwhile, an optimal sequence of damage components repairments provides the operator with the opportunity to utilize components that play a critical role in restoring loads sooner. Motivated by the rise in penetration of renewable distributed generators in modern distribution systems, this paper aims to develop a robust reconfiguration and crew routing co-optimization method to cope with renewable and demand uncertainties while recovering from a disaster. The method optimizes the grid recovery process for the worst... 

Various damage indexes have been introduced in recent years incorporating different parameters for estimating structural damage. Amongst these indexes, Plastic Ductility and Drift have been the center of attention of standards and building codes, like FEMA-356, because of their straightforward physical interpretation and ease of calculation. In this paper, several steel moment frames have been considered and their responses have been evaluated under a set of scaled earthquakes. A group of various damage indexes, which included cumulative and non cumulative, cyclic fatigue based, deformation based and modal parameter based, has been considered and the damage to structures has been evaluated... 

The main objective of this study was to compare the removal efficiency of nutrients using Lactuca sativa, Medicago sativa and Phragmites australis in subsurface flow constructed wetlands with horizontal flow. In order to test water quality, fabricated reactors designed and the plants cultivated in the soil while their root were inside the wastewater. A long time study carried out from spring till end of autumn (9 months) in order to evaluate the difference in removal rate based on the seasonal changes. The highest removal rate was during summer which followed by spring and autumn. Thus, the effect of plants on the removal efficiency of organic matter (COD, BOD), TSS and nutrient (P and TN)... 

Discrimination of chiral targets is generally achieved with chiral nanomaterials. However, the limited number of intrinsic chiral nanostructures as well as their complex synthesis procedure has led to the production of chirality-induced nanomaterials as alternatives. Chirality can be induced in nanomaterials by either chirality transfer or the formation of chiral assemblies. Using the latter approach, in this work, we have provided chiral supramolecular assemblies of CdTe quantum dots (QDs) from achiral starting materials. CTAB-QD assemblies showed chiroptical activities, and their orange emission in combination with the blue emission of carbon dots was utilized as a ratiometric chiral... 

Discrimination of chiral targets is generally achieved with chiral nanomaterials. However, the limited number of intrinsic chiral nanostructures as well as their complex synthesis procedure has led to the production of chirality-induced nanomaterials as alternatives. Chirality can be induced in nanomaterials by either chirality transfer or the formation of chiral assemblies. Using the latter approach, in this work, we have provided chiral supramolecular assemblies of CdTe quantum dots (QDs) from achiral starting materials. CTAB-QD assemblies showed chiroptical activities, and their orange emission in combination with the blue emission of carbon dots was utilized as a ratiometric chiral... 

Levodopa [L-3, 4-dihydroxyphenylalanine, or L-DOPA] is an important neurotransmitter used for the treatment of neural disorders such as Parkinson's disease. Abnormal L-Dopa concentrations in biological fluids can be used for the evaluation of such diseases. In this work, a rapid and sensitive method for L-DOPA detection has been reported which is based on in situ formation of polylevodopa nanoparticles. Under alkaline conditions, L-DOPA is spontaneously oxidized to its quinone derivative and shows fluorescence properties. The fluorescence signal of the oxidation product has been monitored and used for the determination of L-DOPA in the presence of dopamine, uric acid, ascorbic acid and other... 

Numerical modeling of periodically patterned graphene sheets (PPGS) embedded in planar multilayered media using Fourier-based methods suffers from very slow convergence because of the fact that the conductivity is zero in unfilled areas of the patterned surface and, thus, the so-called Li's inverse rule is not applicable. In this paper, a simple and efficient approach is proposed to overcome this problem such that the exact boundary condition can be applied and the surface current density on PPGS can be obtained accurately. Here, the PPGS is modeled as a conductive surface and only its conductivity representation by the Fourier series is modified. The proposed method can be used easily for... 

In this paper, we propose CodedSketch, as a distributed straggler-resistant scheme to compute an approximation of the multiplication of two massive matrices. The objective is to reduce the recovery threshold, defined as the total number of worker nodes that the master node needs to wait for to be able to recover the final result. To exploit the fact that only an approximated result is required, in reducing the recovery threshold, some sorts of pre-compression are required. However, compression inherently involves some randomness that would lose the structure of the matrices. On the other hand, considering the structure of the matrices is crucial to reduce the recovery threshold. In... 

In this paper, we propose CodedSketch, as a distributed straggler-resistant scheme to compute an approximation of the multiplication of two massive matrices. The objective is to reduce the recovery threshold, defined as the total number of worker nodes that the master node needs to wait for to be able to recover the final result. To exploit the fact that only an approximated result is required, in reducing the recovery threshold, some sorts of pre-compression are required. However, compression inherently involves some randomness that would lose the structure of the matrices. On the other hand, considering the structure of the matrices is crucial to reduce the recovery threshold. In... 

One of the major challenges in using distributed learning to train complicated models with large data sets is to deal with stragglers effect. As a solution, coded computation has been recently proposed to efficiently add redundancy to the computation tasks. In this technique, coding is used across data sets, and computation is done over coded data, such that the results of an arbitrary subset of worker nodes with a certain size are enough to recover the final results. The major drawbacks with those approaches are (1) they are limited to polynomial functions, (2) the number of servers that we need to wait for grows with the degree of the model, (3) they are not numerically stable for... 

[No abstract available]  

In an acceptance-sampling plan, where items of an incoming batch of products are inspected one by one, if the number of conforming items between successive non conforming items falls below a lower control threshold, the batch is rejected. If it falls above an upper control threshold, the batch is accepted, and if it lies within the thresholds then the process of inspecting the items continues. The purpose of this article is to develop an optimization model to determine the optimum values of the thresholds such that constraints on the probability of Type I and Type II errors are satisfied. This article starts by developing a Markovian model to derive the expected total cost of the inspection...