Sharif Digital Repository

Design, fabrication and performance of the reciprocating micropumps with actuated fluid slug have been investigated. In these micropumps, pumping principle is based on reciprocating movement of a fluid slug. The fluid slug must be conductive in magnetohydrodaynamic micropump to be actuated by Lorentz force and have good magnetic properties in ferrofluidic micropumps to be actuated by an external magnetic field.
On the other hand, a theory is developed in ahead of design and fabrication process to diagnose the critical and the most influential parameters. Magnetohydrodynamic micropumps in 4 distinict design using nozzle-diffuser element, passive ball valve and active mercury valve have... 

Mobile Worldwide Interoperability for Microwave Access (Mobile WiMAX) is a wireless access technology based on IEEE 802.16e. Mobile WiMAX supports mobility and a wide range of Quality of Service (QoS) requirements for several applications. This wireless technology introduces handover mechanisms to avoid disruption of services running on Mobile Stations (MS) through moving. In this thesis, we have focused on balancing the load of the system, using handover mechanisms suggested by mobile WiMAX. The proposed algorithm, WQLB, concentrates on controlling the system load and keeping it in a balanced state by using a handover process. Also, the algorithm is designed to utilize resources... 

In this thesis, a novel method for the design of adaptive wavelet transforms based on the lifting scheme structure is presented. We have compared the proposed adaptive wavelet design method with the exisiting algorithms by providing a brief survey of the recent adaptive lifting scheme techniques. In addition, object detection is selected as the target application and two novel template matching algorithms based on the proposed adaptive lifting scheme transform, called LAPT and RASIM, are presented. As the main building block of the proposed algorithms, given an object as a template, we first select a set of coefficients as object features in the wavelet transform domain and then build an... 

The Global Navigation Satellite System (GNSS) is widely utilized for positioning and navigation purposes; however, its continuous accessibility is not guaranteed. Challenges such as signal disruption at the source, interference, or the transmission of erroneous signals targeting the communication between receivers and the system have consistently posed significant obstacles to its reliable use. This research aims to develop a passive and opportunistic positioning method leveraging Low Earth Orbit (LEO) satellites, with a particular focus on the Starlink constellation. This approach effectively addresses the aforementioned challenges to a significant extent while offering a highly... 

Software engineers have long realized that they cannot use existing methodologies for all project situations, as every software development project has its own specific characteristics. Therefore, a branch of software engineering–known as Situational Method Engineering (SME)–has emerged which helps develop bespoke methodologies to fit the specific characteristics of each and every project situation. As in software development, SME too involves rigorous Requirements Engineering (RE), so much so that if requirements elicitation and definition is botched in any way, methodology development will most likely fail as a result. In software engineering, requirements engineering has long been the... 

In multi-agent systems (MAS), collective behavior of autonomous agents and complexities arisen by their interactions are studied, while they are exploited to solve real-world complex problems. Machine learning methods are frequently used for problem solving in MAS, because complexities in these systems prevent a programmer to thoroughly describe the agents’ behaviors and the rules governing them.Reinforcement learning (RL) is one of the most commonly used learning methods for intelligent agents,because it does not need a model of the environment and learns agents’ policies through trial and error.Conventional RL algorithms store and update utilities for every possible state in a table. One... 

Enzyme-powered motors self-propel through the catalysis of biofuels, which makes them excellent candidates for biomedical applications. However, fundamental issues such as their movement in biological fluids and understanding the mechanism of propulsion are important aspects that must be considered before application in biomedicine. Building active systems based on biocompatible materials that use non-toxic fuels to power their vehicles have always been challenging. In this study, self-propelled micromotors consist of titanium dioxide black spheres asymmetrically coated with a thin layer of gold. Cysteine was used to bind urease enzyme due to thiol binding. By biocatalytically converting... 

Developing algorithms in engineering and decision making systems based on psychological and biological mechanisms is a promising area of research. The challenging part of any psychological or biological system development is its learning necessity to adapt itself to random incidents, inherent in the environment. Goals, as defined in engineering problems, are the performance functions that continuously evaluate the responses of environment. They have a duty of directing the learning system to the desirable state. If the environment is corrupted by a variety of disturbances that cannot be predicted from the outset, adapting the parameter of learning agent is inevitable. In this work, we... 

Wishart processes are popular models for stochastic correlation and volatility of financial assets due to their convenient analytical properties. However, they cannot reproduce the sudden and sustained surges in correlation and volatility observed during market crises. Moreover, the Wishart process (like the CIR model) does not impose a positive lower bound on variances, allowing them to approach zero. This thesis introduces a new stochastic process, called the Markov-Modulated Shifted Wishart (MMSW) process, to address these shortcomings. The MMSW process extends the Wishart model by adding a constant “shift” matrix to keep variances away from zero and by using a Markov chain to switch... 

In this thesis, we want to present methods that are able to solve the assignment tasks problem in a heterogeneous computing system. These methods are two hybrid methods that are constructed by composing Hopefield Neural Networks with Genetic Algorithms and the Simulated Annealing. First, we solve the relaxed problem by applying Genetic Algorithms and the Simulated Annealing and we compare the results of these ways with other traditional methods. Then, we solve the constrained problem with mentioned hybrid methods. The definition of the problem is as following: Consider a distributed computing system which is comprised of set of processors with different speeds but the same structure. We want...