Sharif Digital Repository

The importance of using a fast and automatic method to classify variable stars for large amounts of data is undeniable. There have been many attempts for classifying variable stars by traditional algorithms, which require long pre-processing time. In recent years, neural networks as classifiers have come to notice. This thesis proposes the Hierarchical Classification technique, which contains several models with the same network structure. Our pre-processing method produces input data by using light curves and the period. We use OGLE-IV variable stars database to train and test the performance of Convolutional Neural Networks based on the Hierarchical Classification technique. We see that... 

Quantum-Dot Cellular Automata (QCA) is a novel field of nanotechnology which is being designed and implemented in molecular scales. It has major advantageous over transistor based technology such as: low power consumption, high information transition speed, small size and high density. It has been shown that conventional transistor based circuits can be implemented in this nanotechnology with less complexity. Furthermore, binary circuits can be implemented in QCA technology since QCA cells have only two independent and equivalent states. So, QCA provides appropriate space for computational circuits. The aim of computational circuits design is to achieve small size and high speed processors.... 

In the last years, we have seen a rapid growth of data generation that leads to an increasing need for data analysis and big data technologies. Meanwhile, cloud computing witnessed great popularity and has become one of the best platforms for big data analytics due to its flexibility and scalability. However, there is not an obvious method for choosing the right cluster configuration for running big data jobs in clouds. Because different big data applications, workloads and cloud configurations can lead to different costs. Moreover, a heterogeneous cluster can use the benefits of distinguished properties of each machine to reduce the cost and execution time of the big data application. The... 

A single-degree-of-freedom model is considered for flexible exercise bars based on the lumped-element approach. By considering the side segment of a flexible exercise bar as a cantilever beam with an equivalent mass at the free end, its free-vibration response and forced one under excitation of the grip of the flexible bar is written parametrically. Some experiments are performed on a specific flexible bar to obtain numerical values for the parameters in the model to have it quantitatively known. In the next step, simulation of the model results in the response of the flexible bar under a considered excitation. The response is imported into a multi-segment musculoskeletal software, AnyBody,... 

Cloud storage provides an accessible and cheap space for data storage. There is usually no trust between users and the Cloud. Consequently, to maintain confidentiality, outsourcing and storing sensitive data in an encrypted form is necessary. In applications where data sharing between several users is required, ciphertext-policy attribute-based encryption(CP-ABE) has been considered a promising solution, but the lack of efficiency and flexibility limits its usage in applications such as IoT. These problems are usually related to both the underlying structure and the required peripheral processes, such as key revocation. In this thesis, two schemes with the same basic structure and different... 

Today, factors such as the growing energy consumption in the world, followed by the reduction of fossil fuel reserves, and more importantly, the global warming phenomenon due to excessive consumption of fossil fuels have caused attention towards clean energy, especially solar energy, to increase significantly. Researchers throughout the world are looking for solar cells with high efficiency and stability, and of course affordable. In today's world, one of the materials that has grabbed the researchers' attention is perovskite. The reason behind this is that in the last decade, there has been a significant increase in the efficiency of perovskite solar cells to surpass that of Silicon solar... 

Given an event O and a set of experts E, we describe a method for finding a subset of experts S whose aggregated opinions best predict the outcome of O. Therefor, the problem can be regarded as team formation for performing a prediction task. In order to estimate competency of each team we propose measure Sum Squared Error which uses experts’ records of predictions during past k days. For simplicity, opinion pooling is selected as the method of information aggregation. we prove in case of simple averaging of opinions,finding best team is NP-hard. we suggest some rounding and heuristic algorithms for finding near optimal solutions. Simulation results show that a variation of tabu search used...