Sharif Digital Repository

Excessive usage of fossil fuels and emissions of GreenHouse Gases (GHG) have led to many environmental problems such as climate change. The carbon dioxide emission accounts for 82% of GHG emissions and has the highest retention time in the atmosphere. The study on carbon dioxide is an important issue recently. The carbon dioxide emission from the energy and industrial sectors are 30% and 21%, respectively. It is possible to capture carbon dioxide from the flue gas may be utilized as material and fuel. Developing the utilization of carbon dioxide to replace storage is a solution for implementing carbon capture. The carbon planning model, is based on the selection of technology that is... 

Given the growth of the world's population along with the increase in the percentage of urban population by 2050, the way of responding to food consumption will change in the future. Controlled Environment Agriculture will largely account for future food supply. Vertical Farming is one of these systems. But despite the efficiency of these systems in terms of land and water and also not being affected by weather conditions, the main challenge in these systems is the consumption of energy use per unit of crop production. The cost of energy is about 25 to 40 percent of the total costs. The purpose of this study is to develop an integrated dynamic model for the determination of vertical farm... 

Deep Neural Networks (DNNs) are widely used as a promising machine learning method in different applications and come with intensive computation and storage requirements. In recent years, several pieces of prior work have proposed different accelerators to improve DNNs processing. We observe that although the state-of-the-art DNN accelerators effectively process some network layers of certain shapes, they fail to keep computation resources fully utilized for many other layers. The reason is twofold: first, the mapping algorithm is unable to employ all compute cores for processing some layer types and dimension sizes, and second, the hardware cannot perform data distribution and aggregation... 

Deep Neural Networks (DNNs) are widly used in various domains, such as medicine, engineering, industry, financial markets, mathematics and management. DNNs are composed of several layers, such as convolutional and fully connected layers. Increasing the number of layers in DNNs provides different application with their required accuracy. In recent years, there have been many accelerator aiming to execute DNNs. However, the high computation and memory demands in DNNs are the main challenges to execute DNNs. To reduce computation and memory requirements, various methods such as pruning and quantization, have been proposed. Pruning and quantization methods make the DNNs sparse and increase the... 

Nowadays, implementing a complex system, which executes various applications with different levels of assurance, is a growing trend in modern embedded real- time systems to meet cost, space, timing, and power consumption requirements. Medical devices, automotive, and avionics industries are the most common safety- critical applications, exploiting these systems known as Mixed-Criticality (MC) systems. MC applications are real-time, and to ensure the correctness of these applications, it is essential to meet strict timing requirements as well as functional specifications. The correct design of such MC systems requires a thorough understanding of the system’s functions and their importance to...