Sharif Digital Repository

In recent years considerable effort has been made to advance the hardware Artificial Neural Networks where in most cases, many neurons are placed on a VLSI chip. This research attempts to build individual neurons and connect them to build a hybrid of analog and digital neural network. In fact, every neuron is an AVR microcontroller which has a number of inputs and outputs. The data transfer between neurons are done by both analog (PWM- ADC) and digital (UART). In the first part, the necessary voltage source and programmer and how to build are discussed. Next A\D convertor, PWM technique, UART and their usage in this project are demonstrated. After that, the neurons are calibrated to improve... 

Cable-driven robots are referred to as parallel robots actuated with cables. In fact,in such robots rigid links are replaced by cables, which may be extended to desired lengths without making mechanism much heavy. This robot possesses a number of unique properties that makes it suitable for many industrial applications. The main factor which makes cable robots analysis different from other parallel robots is the incapability of cables to push objects. Hence, obtaining the workspace of a cable robot is one of the most important subjects associated with this type of robot.The goal of this thesis is to design a spatial translational cable driven robot, which may be used for object handling. For... 

Uncertain fuel prices and also global climate changes are accompanied by some state initiatives such as renewable portfolio standards (RPS). This has caused a fast growth in the amount of renewable energy installed worldwide especially wind energy over last decades. However, the intrinsic characteristics of wind farms output power, i.e. intermittency and volatility of wind speed along with being non-dispatchable in output generation of wind turbine raises many new technical and financial challenges for power system operators and planners. Up to these issues, large level of wind power penetration causes a growing concern in wind energy curtailment issue which the wind farm’s operator may be... 

In recent decades the use of FRP materials for strengthening structures has been developed extensively, thanks to their high strength, sufficient stiffness, high durablity, and ease of use. A great deal of research has been conducted on strengthening reinforced concrete beams and columns with FRP composites. By contrast, not many researches are performed on slabs, especially two-way slabs. In these few researches, the loading and boundary conditions are limited to simplest ones. Therefore, in this thesis, the focus of attention is on strengthening reinforced concrete slabs under various loads and boundary conditions using FRP composites.
In this thesis, first, FRP composites and their... 

Access to global memory is one of the bottlenecks in performance and energy in GPUs. Graphical processors uses multi-thread in streaming multiprocessors to reduce memory access latency. However, due to the high number of concurrent memory requests, the memory bandwidth of low level memorties and the interconnection network are quickly saturated. Recent research suggests that adjacent thread blocks share a significant amount of data blocks. If the adjacent thread blocks are assigned to specific streaming multiprocessor, shared data block can be rused by these thread blocks. However the thread block scheduler assigns adjacent thread blocks to different streaming multiprocessors that increase... 

One of the key subjects in the area of mathematical optimization is a class of problems known as combinatorial optimization. We can find the optimal solution of continuous optimization problems feasible in time. But, in combinatorial optimization, we aim to obtain the optimal solution of the problem over a finite set. These problems are NP-hard and no polynomial-time solution has been proposed for this class of problems so far. Thus, in practical scenarios, we often use heuristic methods for solving NP-hard problems. There are lots of heuristic methods and choosing the best one in different situations might be challenging. In recent years, with the advances in deep neural networks,... 

Design of complex systems requires different challenges to be met simultaneously. Yet the current methods lack a sound theoretic framework and thus designers normally rely on heuristic or empirical methods; based on available experiences. Such approaches to the system design entail both technical and business risks and subsequently increase the probability of long-term problems. In this research, along with the theoretical framework of the systems design concepts, we discuss number of important models. The main concentration of the work, however, is to; somehow, correlate Axiomatic Design Matrix (ADM) with Design Structure Matrix (DSM). Here we exploit mathematical model based on sets and by... 

Nowadays, thanks to improvement of processing hardware and plenty of data available, artificial intelligence and specifically Deep Learning are being one of the powerful tools for solving different problems. Also graph is one of the powerful tools for modeling different data structures. Graph matching is one of the problems in the field of graph problems.In this thesis we consider the problem of graph matching in Erdos-Renyi graphs. The graph matching problem refers to recovering the node-to-node correspondence between two correlated graphs. Previous works theoretically showed that recovering is feasible in sparse Erdos-R´enyi graphs if and only if the probability of having an edge between a... 

Distillation is the most widely-used but the most energy-consuming separation process in the chemical industry. The thermal energy added at the reboiler is used to evaporate a liquid mixture and is wasted when liquefying the vapor flow at the condenser to obtain a reflux liquid flow. However, the thermal energy recovered at the condenser cannot be used to heat other flows in the same distillation column since its temperature is lower than the other stages. To improve the low energy efficiency of distillation, various new ideas have been proposed in the literature. One of them is the internally heat-integrated distillation column (HIDiC). In a conventional distillation column, the temperature... 

The main goal in many fields in the empirical sciences is to discover causal relationships among a set of variables from observational data. PC algorithm is one of the promising solutions to learn underlying causal structure by performing a number of conditional independence tests. In this paper, we propose a novel GPU-based parallel algorithm, called cuPC, to execute an order-independent version of PC. The proposed solution has two variants, cuPC-E and cuPC-S, which parallelize PC in two different ways for multivariate normal distribution. Experimental results show the scalability of the proposed algorithms with respect to the number of variables, the number of samples, and different graph...