Sharif Digital Repository

In this work we study control independence in embedded processors. We classify control independent instructions to data dependent and data independent and measure each group's frequency and behavior. Moreover, we study how control independent instructions impact power dissipation and resource utilization. We also investigate control independent instructions' behavior for different processors and branch predictors. Our study shows that data independent instructions account for 34% of the control independent instructions in the applications studied here. We also show that control independent instructions account for upto 12% of the processor energy and 15.6%, 11.2% and 8.6% of the instructions... 

A distributed embedded system consists of different processing elements (PEs) communicating via communication links. PEs have various power characteristics and in turn, have different thermal profiles. With new technologies, processor power density is dramatically increased which results in high temperature. This alarming trend underscores the importance of temperature management methods in system design. The majority of proposed techniques to address thermal issues, impose severe penalties on performance and reliability. We present Schedule Swapping, a technique for reducing peak temperature in distributed embedded systems while satisfying real-time constraints. Contrary to many other... 

Symmetric T junctions have been used widely in microfluidics to generate equal-sized microdroplets, which are applicable in drug delivery systems. A newly proposed method for generating unequal-sized microdroplets at a T junction is investigated theoretically and experimentally. Asymmetric T junctions with branches of identical lengths and different cross sections are utilized for this aim. An equation for the critical breakup of droplets at asymmetric T junctions and one for determining the breakup point of droplets are developed. A good agreement was observed between the theories (present and previous) and the experiments  

Feed-in tariff (FiT) is one of the most efficient ways that many governments throughout the world use to stimulate investment in renewable energies (REs) technology. For governments, financial management of the policy could be challenging as it needs a considerable amount of budget to support RE producers during the long remuneration period. In this paper, it has been illuminated that the early growth of REs capacity could be a temporary boost. And the socio-economic structure of the system will backlash the policy if some social mechanisms are not considered. Social tolerance for paying REs tax and potential investors’ trust emanated from budget-related mechanisms -which have rarely been... 

Convection heat transfer below a horizontal, hot, and isothermal strip of infinite length and width of 2L embedded in fluids with different Prandtl number (Pr) and Nusselt number (Nu) is analyzed with the aid of integral method. A new concept is utilized to determine the boundary layer thickness at the strip's edge, which is based on matching the flow rate of the boundary layer below the strip at its edge and the flow rate of the plume, which forms after the heated fluid detaches from the strip's edge. In addition to these novelties, a numerical model is developed to verify the analytical framework, and an excellent agreement is observed between the analytical and numerical models  

This article provides an agent-based model of a hypothetical standalone electricity network to identify how the feed-in tariffs and the installed capacity of wind power, calculated in percentage of total system demand, affect the electricity consumption from renewables. It includes the mechanism of electricity pricing on the Day Ahead Market (DAM) and the Imbalance Market (IM). The extra production volumes of Electricity from Renewable Energy Sources (RES-E) and the flexibility of electrical consumption of industries is provided as reserves on the IM. Five thousand simulations were run by using the agent-based model to gather data that were then fit in linear regression models. This helped...