Sharif Digital Repository

Smart wellsareunconventional wells with down-hole devices installed on their production tubing. Such wells allow us to continuouslymonitor flow rates, pressures, temperature and periodically adjust down-holevalves setting without any production intervention. This makes smart well technology to be considered as one of the most significantbreakthroughs in reservoir management technologies. So, modeling and simulating smart wellsautomated action represents a challenge in forecastingtheir performances.One of the easiest ways to model such wells is to transform theminto a multi-segment well with the ability tocontrol each segment independently. By using the commercial reservoir simulator,... 

Strain imaging is a non-invasive ultrasound modality for assessing cardiac function in echocardiography systems. In this thesis, we implemented a fully automated strain imaging system containing 5 steps: 1) echocardiographic view recognition, 2) cardiac cycle phase detection, i.e., the events of end-diastole (ED) and end-systole (ES), 3) segmentation of left ventricular (LV) myocardium, 4) motion estimation of this wall and 5) strain calculation. In this work, we propose a novel deep learning-based framework for phase detection of cardiac cycle by the use of echocardiographic images in multibeat videos. Further, by applying the augmentation technique, the model has been able to detect events... 

Event cameras are bio-inspired sensors. They have outstanding properties compared to frame based cameras: high dynamic range (120 vs 60), low latency, no motion blur. Event cameras are appropriate for using in challenging scenarios such as vision system in self-driving cars and they have been used for high level machine vision tasks such as semantic segmentation, depth estimation. In this project, we worked on semantic segmentation using an event camera for self-driving cars. i) We introduce a large dataset, our dataset was produced using Carla simulator and it contains RGB images, events and semantic segmentation labels. ii) This project introduces new event based semantic segmentation... 

For radiotherapy and removal of cancerous tissues, it is necessary to determine the location of the tumor and the vulnerable structures around the tumor before treating and irradiating the high-energy beam. To do this, the images received from the patient need to be segmented. This is usually done manually, which is not only time consuming but also very expensive.Various methods for segmenting these images are presented automatically and semi-automatically, among which methods based on machine learning and deep learning have shown much higher accuracy than other methods. Despite this superiority, these methods have problems such as high computational costs, inability to learn the shape and... 

Recent approaches in the field of semantic image segmentation rely on deep networks that are trained by pixel-level labels. This level of labeling requires a lot of time for the labeler person; because these networks require large training datasets to achieve optimal accuracy and the lack of data at the labeled pixel level causes a significant drop in their performance. In order to overcome this problem, weakly supervised segmentation approaches have been proposed. In these approaches, weaker labels such as image-level labels, bounding boxes, scribbles, etc. have been introduced to train the networks.In this thesis, a method for segmentation of kidney and kidney tumor in CT scan images based... 

Wall detection, as a part of scene understanding and indoor 3D modeling, can be used in robotic, architecture, and augmented reality. In robotic, scene analysis and understanding is knows as one of the main steps in robot navigation and simultaneous localization and mapping and walls need to be detected to form a 3D map of indoor environment. Ceiling and floor are also important elements of an indoor environment, therefore we can see our problem as a room layout estimation if we consider ceiling and floor. Using a deep learning structure, we estimate room layout in a semantic segmentation manner. Our approach is real-time. Our proposed method uses a deep fully-convolutional network, layout... 

Employing high-temperature superconducting (HTS) tapes, instead of copper or aluminum wires for winding in a superconducting transformer, results in a series of significant advantages; such as: smaller volume, lighter weight, higher efficieny, greatly extended overload capability, better voltage regulation, lower life cycle cost, fault current limiting capability, lower environmental pollution and lower risk potential against fire hazards.In this thesis, optimal design of flux diverter using genetic algorithm for axial short circuit force reduction in HTS transformers has been performed. Then, multilayered flux diverters have been proposed for reduction of weight and losses. The impact of... 

Environment Identification and recognizing surrounding objects is an exigent need in future applications. For example one of the emerging technologies in car industry is driverless cars. In driverless cars, navigation system should be able to detect and recognize pedestrians, traffic signs, roads, surrounding cars and so on. Therefore, conventional single-object recognition systems are not capable of handling the needs of advanced machine vision based applications. In recent years, designing and analyzing multi-class object detection and recognition systems have become a big challenge in machine vision. In this thesis our goal is to identify and analyze the existing problems in designing... 

In this study a variational framework for joint segmentation and motion estimation is provided for inspecting heart in Cine MRI sequences. In the first work, a functional including Mumford-Shah segmentation and optical flow based dense motion estimation is proposed. However, the motion estimation technique is replaced with warping estimation in the second work to reach in more regular and smooth motion field based on tracking of cardiac boundaries. Both of these functionals are then approximated by using the phase-field method to make them suitable for extracting Euler-Lagrange equations. Numerical solution to the optimization problem, when the time and image spaces are discretized by finite... 

Recent developments of internet technology and digital media have led to the rapid growth of the steganography systems. Steganography is the art and science of concealing a secret message in a cover without leaving a perceptible or detectable trace of the message. Therefore, steganography methods, capable of embedding the largest possible amount of data with least distortion to the cover media, are highly demanding. The LSB steganography is a primary and simple method with high embedding capacity, where higher robustness is achieved if it is applied to the cover signal in the transform domain. However, regardless of the embedding domain, an essential robustness issue with the LSB... 

Development of strategically important processes which are environmentally benign with simple methodology and work-up by low toxic material is currently reciving considerable attention.In recent years, dithiocarbamates (DTCs) and their synthesis with a green procedure have received many attention because of their undeniable applications.These synthetic compounds play important roles either in academia and industry. Here a simple, efficient and regiospecific method for synthesis of dithiocarbamates is described by one-pot three-component reaction of an amine, CS2 and alkyl vinyl ether via Markovnikov addition reaction in poly ethylene glycol (PEG) under a mild and green procedure with... 

Skin cancer is a common type of cancer in the world. Melanoma is considered as the deadliest form of human skin cancer that causes approximately 75% of deaths associated with this cancer. However, melanoma is curable if diagnosed in an early stage. Due to high visual similarities and diverse characteristics of lesions, it is a challenging task to differentiate between different types of skin lesions. Therefore, it is worthwhile to develop a reliable automatic system increasing the accuracy and efficiency of pathologists. Here, we propose sparse representation and dictionary learning based methods for skin lesion segmentation and classification. First, we review the steps of a computer aided... 

The aim of this thesis is to investigate recent methods for Image Processing(Any signal process which it’s input is an image and it’s ouput is an image or a set of Image parameters) using Calculus of variation tools. Methods which are to be investigated has been divided into two well known parts of Image Processing : Image Restoration and Image Segmentation.Image Processing Chapter includes two sections: one calculus of variations methods(energy method), other methods based on PDEs(heat equation and Malik-Perona equation). In studing each of this methods, It has been tried to include experimental results and negative and positive points of them.In Image Segmentation Chapter, first... 

Level set methods (LSM) are a conceptual framework for using level sets as a tool for numerical analysis of surfaces and shapes. The advantage of the level set model is that one can perform numerical computations involving curves and surfaces on a fixed Cartesian grid without having to parameterize these objects (this is called the Eulerian approach). Also, the level set method makes it very easy to follow shapes that change topology, for example when a shape splits in two, develops holes, or the reverse of these operations. All these make the level set method a great tool for modeling time-varying objects, like inflation of an airbag, or a drop of oil floating in water  

3D face modeling is currently a popular area in Computer Graphics and Computer Vision. Many techniques have been introduced for this purpose, such as using one or more cameras, 3D scanners, and many other systems of sophisticated hardware with related software. But the main goal is to find a good balance between visual reality and the cost of the system. In this thesis, reconstruction of a 3D human face from a pair of orthogonal views, front face and side face is studied. Unlike many other systems, facial feature points are obtained automatically from two photographs with the help of an Active shape model algorithm for the frontal face and an edge detection algorithm for side view of the... 

The problem of partitioning vertices of a graph has been studied with different formulations according to their application. In this thesis we try to review some of these formulations and existing algorithms. In addition we try to investigate the correct definition for a specific application in image processing, namely image segmentation. At the end, we propose a new algorithm for partitioning vertices of a weighted graph according to the mentioned application and compare its performance with some similar algorithms  

Businesses need to narrow down their segmentation and divide customers into smaller groups because some low-loyalty customers have the potential to become loyal customers. Therefore, we have focused on non-loyal customers. This study proposes a framework in which customers with low loyalty value are examined in four six-month time periods and an overall two-year time period and divided into smaller periods. First, a clustering was performed with K-Means algorithm and RFM model, then the migration pattern of customers from one cluster to another was identified using the sequential pattern technique. The transition of customers and their potentiality was determined and according to these... 

Cloud infrastructure pricing framework is one of the challenges for many cloud economists and researchers, albeit its proper definition is one of the main requirements for business triumph. Efforts to focus on this issue have been extensively focused on a uniform market. Moreover, the models are mainly based on the cost factor and resources of cloud infrastructure, aiming to maximize revenue and profit margins for cloud service providers. Models that also consider the demand side and define criteria regarding the customer needs, preferences, and experiences are called value-based models, which provide a great competitive advantage for the providers aside from its higher profit margin and... 

One of the most important issues in the cloud computing space is the problem of combining services in which after receiving customer demand. Cloud Composition in Cloud manufacturing is explained to meet customer demands. Each of them is done by one (or several) manufacturing plants. This is important for improving cloud manufacturing.The main purpose of service composition is allocation of activities to vendors. Purposes such as minimizing cost and time and constraints such as confirmation minimum reliability and accessibility for vendors are considered. Providing a segmented production system as a service is another way to reduce costs and speed up response and the agility of the system has... 

Designing and evaluating the segmented production structures of the production system due to the variety of production systems is one of the important issues that have been considered in recent decade. In this research, the paradigm of designing a segmented production system has been studied to increase the adaptation of the organizational structure of production systems to changing and diverse behavior of the market as well as to increase the responsiveness to demand in the organization. The segmented production system provides production units to small, flexible and decentralized production units. The segmentation process used in this research uses an axiomatic design structure. The...