Sharif Digital Repository

One of the main components of any solar power plant is its thermal heat storage system. Heat storage reduces the cost of power generation by increasing the capacity factor of the system. This paper aims to model and optimize the operation of a consecutive multi-layer Phase Change Material (PCM) thermal heat storage system, named Cascade Latent Heat Storage (CLHS), using the method of characteristics and genetic algorithm. The model is validated through comparison with experimental data available in the literature. The model can predict fluid and PCM temperature, PCM phase and the energy absorbed by PCM. A sensitivity analysis is employed for both the PCM and the fluid parameters. The PCM... 

Space-time transmit diversity results in coupling of transmitted symbols across different antennas, which increases the complexity of maximum-likelihood decoding. Symbol coupling can be completely or partially avoided if the space-time code (STC) satisfies specific decoupling conditions; examples of such codes are orthogonal space-time block codes and quasi-orthogonal codes. In this letter, we study decoupling conditions for a linear full-diversity STC. Quasi-decoupled codes are proposed as a partially decoupled full-diversity STC of any rate for any number of transmit antennas with minimum decoding delay. By optimizing the coding gain of quasi-decoupled codes, it is shown that... 

An efficient approach for controlling processes with completely unknown dynamics subject to input nonlinearity and in the absence of state measurements is presented. To handle the system input nonlinearity, this constrain has been included in the system unknown dynamics and a new input has been defined. An unknown Lyapunov function has been considered, and the terms appearing in its time derivative are estimated by neural networks and the stability of the closed-loop system has been established. The effectiveness of the proposed control scheme has been demonstrated by applying the scheme to different bioreactors with unknown dynamics under input saturation. The performances of designed... 

In this chapter, we provide the reader with three fundamental acceleration approaches that are actively used in today’s signal processing research trends. As is clear, Artificial Intelligence and Machine Learning algorithms are getting much more attention from the researchers. Since the emerging of popular Deep Learning algorithms in the last two decades, there has always been a vast demand for processing resources. Hence, it seems necessary to understand recently used methods to accelerate them. Knowing the optimization methods to be the core of various machine learning algorithms, we focus on first-order optimization methods. Considering iterative algorithms that try to reconstruct a... 

Since plasma is rich in many biomarkers used in clinical diagnostic experiments, microscale blood plasma separation is a primitive step in most of microfluidic analytical chips. In this paper, a passive microfluidic device for on-chip blood plasma separation based on Zweifach–Fung effect and plasma skimming was designed and fabricated by hot embossing of microchannels on a PMMA substrate and thermal bonding process. Human blood was diluted in various times and injected into the device. The main novelty of the proposed microfluidic device is the design of diffuser-shaped daughter channels. Our results demonstrated that this design exerted a considerable positive influence on the separation... 

Since plasma is rich in many biomarkers used in clinical diagnostic experiments, microscale blood plasma separation is a primitive step in most of microfluidic analytical chips. In this paper, a passive microfluidic device for on-chip blood plasma separation based on Zweifach–Fung effect and plasma skimming was designed and fabricated by hot embossing of microchannels on a PMMA substrate and thermal bonding process. Human blood was diluted in various times and injected into the device. The main novelty of the proposed microfluidic device is the design of diffuser-shaped daughter channels. Our results demonstrated that this design exerted a considerable positive influence on the separation... 

Sports scheduling has become an important area of applied operations research in recent years, since satisfying fans and teams' requests and revenues of a sports league and TV networks may be affected by quality of the league schedule. While this type of scheduling problem can be solved by mathematical methods and exact solutions are accessible, it computationally leads to hard problems. The travelling tournament problem (TTP) is defined as minimising total travelling distance for all teams in a league. In this study, a new mathematical model for the TTP with the no-repeater constraint is presented. In addition, a very fast hybrid metaheuristic algorithm is proposed, which combines particle... 

Sports scheduling has become an important area of applied operationsresearch in recent years, since satisfying the fans and teams' requests andrevenues of a sports league and TV networks may be affected by the quality ofthe league schedule. While this type of scheduling problem can be solvedtheoretically by mathematical methods, it computationally leads to hardproblems. The Traveling Tournament Problem (TTP) is defined as minimizing totaltraveling distance for all teams in the league. In this study, a newmathematical model for the TTP with no-repeater constraint is presented. Inaddition, a very fast hybrid metaheuristic algorithm is proposed, which combinesParticle Swarm Optimization (PSO)... 

Iterative methods have led to better understanding and solving problems such as missing sampling, deconvolution, inverse systems, and impulsive and Salt and Pepper noise removal problems. However, the challenges regarding the speed of convergence and or the accuracy of the answer still remain. In order to improve the existing iterative algorithms, a non-linear method is discussed in this paper. The mentioned method is analyzed from different aspects, including its convergence and its ability to accelerate recursive algorithms. We show that this method is capable of improving Iterative Method (IM) as a non-uniform sampling reconstruction algorithm and some other iterative sparse recovery... 

The classical economic production quantity (EPQ) model is a well-known and commonly used inventory control technique. A common assumption in the EPQ model is that all units produced are of perfect quality, since in practice non-conforming product or scrap items are possible, this assumption will underestimate the actual required quantity. The objective of this paper is to provide a framework to integrate product of imperfect quality items, inspection errors, rework and scrap items into a single EPQ model. To achieve this objective a suitable mathematical model is defined and the optimal production lot size which minimizes the total cost is obtained  

The objective of this paper is to provide a framework to integrate the existence of products with imperfect-quality items, inspection errors, rework and scrap items into a single Economic Production Quantity (EPQ) model. To achieve this objective, a suitable mathematical model is defined and the optimal production lot size that minimises the total cost is obtained. Sensitivity analysis is carried out for this model. The sensitivity analysis results indicate that the model is very sensitive to defective proportions and type 1 errors of inspection. Nowadays, given the progress made, inspection errors are often ignored. But the findings of this study show that the values of EPQ and total cost...