Sharif Digital Repository

The use of IoT-based technologies is expanding in many areas today. The use of audio and video processing in IoT systems has been used as an alternative to human operators by increasing power and reducing processing costs. Due to the large volume of audio and video data and bandwidth limitations, complete data transfer to cloud processing servers is not cost-effective in terms of efficiency and energy consumption. As a result, the solution that has provided good results is to discharge these device tasks to the available clouds. In other words, the capacity of resources in the environment can be used to optimize the total latency of the system and energy consumption. In this dissertation, we... 

Among different enhanced oil recovery (EOR) methods, low salinity waterflooding (LSWF) has been attractive to researchers because of its relative simplicity and lower environmental problems compared to other conventional EOR methods. Numerous researchers have attempted to find the main cause of the low salinity effect (LSE). According to previous studies, several experimental techniques have been proposed for predicting LSE and screening potential field candidates. However, there is a lack of a systematic investigation of all (or even some of) the methods to compare and determine their LSE predictive capability. Predictive capability development is essential because it saves costs and time... 

In the recent years, increasing concerns about the environmental issues necessitatecientists and industrial people to introduce clean and zero emissions vehicles to the global market. Relying on this acute demand,Hybrid Electric Vehicles (HEVs) are knownas one potential solution to lessen the negative effects of transportation industry on ecological systems.HEVs combine an Internal Combustion Engine (ICE) with an Electric Motor/Generator (EMG) and an Energy Storage System (ESS) to produce a fuel efficient and low or zero pollutant powertrain. Increasing the number of components in the powertrain requires a sophisticated strategy to control all drive-line components suitably. Surely, the best... 

One of the important questions in mathematics is generalized. In case of metric spaces, one of the questions is: Can we extend notions of Riemannian geometry to arbitrary metric spaces smoothly? Ricci curvature is one of the most important concepts in differential geometry. Ricci curvature is defined for the Riemannian manifold and has many applications in mathematics and physics like Einstein’s equation in relativity theory. There is a good notion for a metric space having “sectional curvature bounded below by K” or “sectional curvature bounded above by K”, due to Alexandrov. Can we define the concept of Ricci curvature in metric space? A motivation for this question comes from Gromov’s... 

Seismic design codes reduce loads by using response modification factor. Because of the reserved strength in structural elements and capacity of structure to dissipate energy, structures can be designed for lower seismic loads. This factor has modified over time. In this thesis, the effect of the reduction in behavior factor on the response of two kinds of reinforced concrete systems were evaluated. Moment resisting frames and dual systems with different heights and regularity in plan, heve been design according to the behavior factor which is recommended in the 3rd edition of the Iranian codes of practice for seismic resistance design of buildings (Standard No. 2800). Drift and... 

Generally, nowadays, machine learning methods are used in many different areas for their superiority over other methods of prediction. Although being a tough task, stock market prediction with machine learning approaches is being spread due to satisfying results published ever yday. Machine learning methods usually use varied kinds of data ,including structured data such as market data, technical indicators and some fundamental data as well as unstructured one entailing text and graph data in order to enhance their predictability capacity. In this thesis we aimed to find out more about the importance and the contribution of structured data in prediction and we tried to attain a framework... 

This thesis presents an inventory control system which is based on Meta-heuristic Algorithms.In this thesis we will optimize the input values of our tree-echelon inventory model (keeping costs,stock worth,reorder costs,...) with these Algorithms. The presented method is able to determine the optimal stock level, costs of system and number of shipments in the system. The method is basically a decision support system (DES) and it is able to provide the order scheduling parameters of goods at operational level. The aim of the current research is to demonstrate that a Meta-heuristic algorithmis capable of solving complex inventory problems and with future improvements it is able to achieve... 

In the first part of this research, a ratiometric fluorescent sensor array has been developed on nanocellulose platform towards chemical discrimination applications. Bacterial nanocellulose (BC) was utilized for the first time as a novel, flexible and transparent substrate in optical sensor arrays for developing portable and high performance sensor array.. To fabricate this platform, the hydrophobic walls on BC nanopaper substrates were successfully created using laser printing technology. In addition, we have used the properties of immobilized ratiometric fluorescence sensor elements (Carbon Dots- Rhodamine B (CDs-RhB) nanohybrids) on nanopaper platform to improve the visual...