Sharif Digital Repository

The olfactory sense in rats provides crucial information for identifying food sources, detecting threats, and facilitating social interactions. The olfactory bulb is one of the key brain regions involved in the initial processing of olfactory information and its transmission to higher brain areas for more complex processing. However, more advanced cognitive processes such as evaluation and decision-making rely on interactions between other brain regions. Among these, the striatum, as a part of the basal ganglia, plays a role in reward evaluation, reward-based learning, and shaping behaviors associated with sensory stimuli. This region contributes to learning, decision-making, and action... 

We consider a special class of Congestion Games enhanced with a notion of time.Network Routing problems, such as road traffic networks, computer neworks, and evacuation problems are some applications of this class of games. Two subclasses of these games, namely atomic and non-atomic is considered in this article, both of them introduced in 2009. Some of the existing results are Nash equilibria existence proof for “single-source single-sink” case, and a mechanism for improving price of anarchy in the non-atomic subclass. There are also some results in the atomic subclass of this game.We extend both models of atomic and non-atomic subclasses to “multi-source,multi-sink” configurations. We call... 

The objective of OCR systems is to retrieve machine-encoded text from a raster image. Despite the abundance of powerful OCR algorithms for English, there are not many for Farsi. Our proposed algorithm is comprised of pre-processing, line detection, sub-word detection and segmentation, feature extraction and classification. Furthermore, hardware implementation and acceleration of this system on a GPGPU is presented. This algorithm was tested on 5 fonts including Titr, Lotus,Yekan, Koodak and Nazanin and an average accuracy above 90% was achieved  

Spiking Neural Networks(SNN) are networks which are consisted of layers of neurons, like other typical artificial neural networks. The main difference between SNN and other neural networks is the type of data transportation among neurons which is done by spikes. Spiking neural networks and their models are considered as the nearest networks and neurons to animals’ nervous systems. In aspects of hardware implementation, the type of data transportation in SNN causes them to be ultra-low power. So, implementation of these networks on chips like FPGA and also usage of SNN in applications with high processing load have startling germination, recently. In this work, we have tried to propose some... 

There have been many works on generative networks and image generation in the past few years, but the problem with this work is that there is no control over the generated images. The goal of disentangled image synthesis is to generate new images with specific detail and have control over the generated images. Image-based virtual try-on aims to synthesize the customer image with an in-shop clothes image to acquire seamless and natural try-on results, which have attracted increasing attention. The main procedures of image-based virtual try-on usually consist of clothes image generation and try-on image synthesis. In contrast, prior arts cannot guarantee satisfying clothes results when facing... 

Many mobile applications running on smartphones, wearable devices, tiny autonomous robots and IoT devices would potentially benefit from the accuracy and scalability of deep CNN-based machine learning algorithms. However,performance and energy consumption limitations make the execution of such computationally intensive algorithms on embedded mobile devices prohibitive.We present a GPU-accelerated engine, dubbed mCNN, for execution of trained deep CNNs on mobile platforms. The proposed solution takes the trained model as input and automatically optimizes its parallel implementation on the target mobile platform for efficient use of hardware resources such as mobile GPU threads and SIMD units.... 

Many chip manufacturers have recently introduced high-performance deep-learning hardware accelerators. In modern GPUs, programmable tensor cores accelerate the heavy operations involved in deep neural networks. This paper presents a novel solution to re-purpose tensor cores in modern GPUs for high-throughput implementation of turbo decoders. Turbo codes closely approach Shannon’s limit on channel capacity, and are widely used in many state-of-the-art wireless systems including satellite communications and mobile communications. Experimental evaluations show that the proposed solution achieves about 1.2 Gbps throughput, which is higher compared to previous GPU-accelerated solutions  

In the current era, artificial intelligence and machine learning have become vital and widely used technologies across various industries. These technologies enable companies and organizations to optimize processes, predict trends, and uncover hidden patterns in data with high accuracy and speed. However, fully leveraging the capabilities of AI and ML requires the effective and efficient deployment of ML models in production environments. MLOps, a combination of DevOps and ML concepts, aids in managing the lifecycle of ML models from development to deployment and maintenance. In this research, due to international sanctions and limited access to external services such as Google Vertex AI,... 

In this project, a method is emoloyed to implement a Viterbi decoder on GPGPU. This method is based on combining all steps of the algorithm. This combination has some challenges that are related to differences between different steps of the algorithm. So in this project, some solutions are found to handle these challenges and a high-throughput Viterbi decoder is acheived  

The aim of this research is to investigate the effect of speed and direction of current on ship fuel consumption. A KCS benchmark model has been numerically studied in calm water and fourteen current and wind conditions with the same speed and different directions to determine how the ship performance is dependent on flow conditions. The model has been simulated in an artificial basin propelled by a single right-handed propeller via a CFD commercial code. Numerical results revealed a linear relationship between the deviation of current and wind from head-sea or following-sea conditions and the rudder angle. The head-sea and following-sea currents and winds increased and decreased the lateral...