Sharif Digital Repository

Numerical simulations and large eddy simulations (LES) of turbulent flow downstream of diversion dam , pool-riffle bedform in different geometrical ratios (different lengths of riffle and pool) with flow Reynolds number of 3.0 E+04 to 3.3E+04, downstream of special case study "Mill and Moghan diversion dam" with Froude number of 0.5 are presented The calculations are performed using a computational fluid dynamics model, FLOW-3D, which solves the Navier-Stokes equations in three dimensions with finite volume method. Numerical simulations are validated by comparing the numerical results of time-averaged flow patterns downstream of pool-riffle sequence with that of the experimental... 

Probabilistic graphical models have great applications in studying and analyzing realworld data. For instance, these models have been used in reconstructing gene regularity networks. Specifically, learning the edges’ structure of graphical models is of great importance.Knowledge about the underlying structure of a graphical model brings about a valuable framework for the decomposition of the model’s distribution and reveals important information such as dependency among dimensions of samples, etc. Most existing methods for structure learning obtain the underlying structure of the model in a centralized fashion and without considering noise in data. In many applications, data exist in a... 

In recent years, with the advancement of genetics technologies, many data from this field have been made available to researchers. Therefore, many analytical problems have been defined for these data. Genome-wide association studies, or GWAS for short, is one of these issues that deals with finding genetic positions affecting traits or diseases. Common approaches to this problem either examine genetic variants one by one or fail to consider the specific structure of genetic data. Also, both mentioned approaches do not provide a guarantee to control the rate of false positives. In this thesis, an attempt has been made to propose a method to solve the GWAS problem by using the new statistical... 

In the realm of cancer treatment through radiation therapy, a primary hurdle has long been the impact of radiation on adjacent healthy tissues during treatment of cancerous tissues. To address this challenge, FLASH Proton Therapy (FPT) emerges as a promising solution, with a high dose rate exceeding 40Gy/s. This research endeavor focuses on the development and validation of a Monte Carlo (MC) based model for FPT, with the aim of extending its applicability to human treatment plans. Initially, the Proton Therapy System (PTS) employing spot scanning was modeled using the GATE software. Subsequent simulations were conducted to determine dosimetric and optical characteristics of the proton beam... 

In this study, the reconstruction of the neutron noise source in the core of the VVER-1000 reactor was carried out using fuzzy neural network and parallel processing of parallel process circuit design. The noise of power reactors is derived from neutron fluctuations. Which are affected by fluctuations in reactor characteristics. These oscillations can be caused by the displacement of the elements forming the core or due to changes in temperature or density and so on. It is clear that any change in the elements of a reactor will make itself a change in the corresponding to cross-section of material. These changes called as pertubation. In this project, by using neuro-fuzzy network... 

Since the beginning of discussion on neutron-gamma discrimination, different methods were suggested for this purpose. In early 2000s, Analogue methods were mainly used to discriminate the spectrum in mixed fields which mostly depends on electronic modules used in the lab setup; Nowadays, with improvements in digital pulse processing techniques, analyzing mixed neutron-gamma fields for pulse discrimination is also available.In this research, the recent MC developed toolkit called GEANT4 is used to simulate the 3-inch BC501A scintillation detector and 500 mCi Am-Be source (that emits neutron and gamma at the same time). For the next step, an experiment with same source and detector was done... 

Conventional MRI has been used to diagnose different types of brain injuries. However these methods have generally failed to diagnose mild types of injury. We are working on the specification of mild traumatic brain injury, using diffusion MRI data, based on a multi compartment simulation of white matter tissue. This effort is essential for better understanding of underlying tissue micro-structure changes in patients with trauma. Some studies have been used in similar data fitting approaches in order to estimate axon diameter distribution. Specifically, a comparative study between different Compartment Models has shown that “ActiveAx” model has the best agreement with underlying tissue... 

Neutron Radiography is one of the non-destructive testing methods of materials and due to its special application compared to gamma or X-ray imaging, it is highly regarded and developed in the world. A special application of neutron imaging is the imaging of materials with a low atomic number, even when coated with a material with a high atomic number. Neutron Radiography has different methods for capturing and recording images by neutrons. Among these methods, the following 7 methods can be mentioned: Neutron radiography (film), Track Etch, Digital neutron imaging, Neutron camera (DR System), Image plates (CR System), Flat panel silicon detectors (DR system) and Micro channel plates (DR... 

The present M.Sc. thesis consists of two sections including the static calculation and neutron noise calculation in rectangular and hexagonal geometries. The multi-group, two dimensional neutron diffusion equations and corresponding adjoint equations are solved in the static calculation. The spatial discretization of equations is based on Average Current Nodal Expansion Method (ACNEM). Size of nodes is the same size of the fuel assemblies in modeling both of rectangular and hexagonal geometries. The results are benchmarked against the valid results for BIBLIS-2D and IAEA-2D benchmark problems. In the second section, neutron noise calculations are performed for two types of noise sources,... 

Gene expression microarrays can be used for precision medicine and targeted therapies. The data generated by microarrays are high-dimensional causing statistical inference of any parameter a daunting task. In this thesis, it is shown that regardless of high-dimensional datasets produced by microarrays, the inference can be robust in the sense that random selection of features results in the same conclusion as far as the number of selected features are chosen appropriately. Stratifying patients with breast cancer based on their gene expression levels shows that patient subtypes are almost independent of the feature selection strategy. Moreover, using less noisy datasets coming from RNAseq... 

Bulk tissue RNA-seq data has been widely used for investigating the transcriptome and analyzing it for different purposes. A single bulk sample of a heterogeneous population includes different cell-types each in different proportions. Bulk tissue RNA-seq measures the average expression level of genes across these cell types and does not account for cross-subject variation in cell-type compositions. Furthermore, biological signals might be masked by taking the average of gene expressions. Because of these reasons, bulk-RNA-seq is not suffcient for studying complex tissues. Knowing these cell-type compositions are important, because studying cell-specific changes in the transcriptome might be... 

Compton imaging is an imaging technique in which Compton scattering is used to produce images from a gamma-ray source. Compton imaging systems are also known as Compton cameras. The basic design of Compton imaging systems consists of two-position detectors that are sensitive to the position and energy scattered from gamma rays. The gamma rays collide with the Compton scatterer detector and the scattered photons are absorbed in the absorber detector. Compton imaging performs well the ground radiation during the scattering processes through the separation of energy. The quality of images produced by Compton imaging depends on a variety of factors including detector energy resolution,... 

Entrance of air to close water conduits occurs in many ways. This phenomenon makes displeasing effects on water transport structures. Two-phase flows in closed conduits are studied experimentally, numerically and theoretically. Even after decades, due to the complexity of the subject, these studies still require development and reformation. Numerical and theoretical two-phase models are often limited to a special regime of flow."Volume Of Fluid"(VOF) is a model for non-mixing two-phase flows. "Fluent" software uses this model in this field of flows. Volume of fluid is used successfully in some problems like dam break or rising bubbles. Main disadvantage of this model is distribution of the... 

Frequently using Personal Identification Information has escalated the security concerns of bank accounts, emails, daily transactions, and other activities. Therefore, user access to such apps must be controlled. Traditional personal verification methods offer limited security because they might need to be remembered or stolen. Therefore, Biometric authentication, which identifies persons by their unique biological information, is gaining popularity. However, palm vein identification is highly secure because the vein patterns are not duplicated in other people, even in monozygotic twins. Moreover, it has a liveness detection and is convenient since the vein pattern cannot be faked,... 

One of the complex problems is routing. This problem becomes more difficult and important in certain situations, which cannot be solved straightforwardly. In this thesis, a model for vehicle (ambulance) routing problem during hospital evacuation in disaster conditions is described and solved using Gray Wolf Optimization (GWO) algorithm in combination with a local search algorithm called Great Deluge Algorithm (GDA). It is shown that the combination of GWO and GDA can improve the efficiency of GWO and avoid local optima. The results are compared with some metaheuristic algorithms. To test the model of 11 hospitals in Tehran, three different modes have been considered, and in each mode, 7... 

A DNA sequence is the information source of living kinds. Information of this sequence is at its constructing bases which has four different kinds. Sequencing DNA is necessary to resolve this information. At 1977, Sanger reported the first sequence of a DNA string. Recently, a human DNA string can be sequenced with 1000 in ~2 hours. Knowing DNA sequence helps to find function of each organism, predict and cure diseases (especially in cancer). Next Generation Sequencing (NGS) methods are based on shot-gun sequencing which fragmentize DNA strings and sequence each fragment. After sequencing, processing information of DNA is performed by the processing machine in two different types: alignment... 

Development of DNA sequencing technologies in the recent years magnifies the need for computational tools in genomic data processing, and thus has attracted inten- sive research interest to this area. Among them, Genome-Wide Association Study (GWAS) refers to discovering of causal relationships among genetic sequences of living organisms and the macroscopic phenotypes present in their physiological structure. Chosen phenotypes for genomic association studies are mostly vulnerability or im- munity to common genetic diseases. Conventional methods in GWAS consists of statistical hypothesis testing algorithms in case/control approaches; Most of which are based upon single-locus analysis and... 

Using statistical tools in machine learning and artificial intelligence to infer knowledge from high-dimensional data, namely data science, has attracted a siginificant research interest over the past two decades. The number of real databases around the world continues to grow with an increasing pace, which are used to store huge amounts of high-dimensional data points of various types. However, applying machine learning tools to high-dimensional data has also raised potential concerns, specially with respect to the fundamental capability of such tools to be useful in practical situations. In fact, the large dimension of a data could eventually damage the outcome of any statistical... 

In recent years, the use of Deep Neural Networks in solving various problems has grown considerably. Possessing a large number of parameters, these networks have the ability to reconstruct complex functions and relations from large amounts of data and have been able to achieve the best results in a wide range of problems. But using these models comes with its own problems. These networks typically require considerable resources in order to run. This makes it inefficient or impossible to use them in systems with limited processing capabilities, e.g mobile phones. The existing approaches, e.g. the deployment of the model on a powerful server and network compression, have their own drawbacks... 

The purpose of this study is to investigate the entrapment and movement of air pockets in the bottom outlet of dams and numerical simulation of the process of entrapment and entrainment of air pockets. One of the most common problems with bottom outlets is the air-water mixture flow. The main purpose of this study is to investigate the causes of air pockets in pressurized tunnels before service and emergency gates in the bottom outlets and to provide effective solutions to prevent the occurrence of unwanted air entrapment and many problems resulting from it. To do this, using FLOW-3D flow simulator, the way of entraping air pockets in the Bottom outlet of Darian Dam has been investigated and...