Sharif Digital Repository

Memory and recalling process has always been a basic question. Decoding the Long-Term_Memory is one of the first steps in answering this question. Since various experiments in the field of human long-term memory, was conducted. This research is motivated by a trial that in which, the Mgntvansfalvgram (MEG) has been recorded while recalling the color and orientation of a grading which is associated with an object, after the object has been shown. High accuracy in Decoding the mentioned color and direction, will be decoding the long-term memory. In order to enhance memory decoding, the research studies different classifiers such as sparse based classifiers and other popular one. It has also... 

In recent years there has been a great effort to enhance the computer-aided diagnosis systems, Since expertise elicited from past resolved cases plays an important role in medical applications, and images acquired from various cases have a great contribution to diagnosis of the abnormalities, Content based medical image retrieval has become an active research area for many scientists. In this project we proposed a new framework to retrieve visually similar images from a large database, in which visual similarity is regarded as much as the semantic category relevance, we used optimized wavelet transform as the multi-resolution analysis of the images and extracted various statistical SGLDM... 

Breast cancer is considered as the most common type of cancer in women worldwide and mammography is currently utilized as the principal method for screening the breast cancer. Breast Magnetic resonance imaging (MRI) can be used as a complementary imaging technique besides mammography. MRI technique involves scanning a patient before and repeatedly after the injection of the contrast agent (DCE-BMRI). This examination often takes 7-10 minutes and any movement of the patient’s breasts due to breath, heartbeat or deliberate movement, made in this relatively long acquisition period, leads to a distortion in images called motion artifact. This problem makes the quantitative analysis of the images... 

In this study pain level estimation using facial expression is investigated. To do this, there are two approaches, one approach is sequence level pain estimation and the other one is frame level pain estimation. In sequence level, after feature extraction from all frames of sequence, each sequence is represented by a fixed length feature vector, this feature vector is constructed by concatenating min, max and mean of frame features of that specific sequence, then KLPP is applied in order to reduce feature vector dimension and in the end a linear regression is implemented to predict the pain labels of the sequence. In the frame level, two approaches are introduced, the first one is based on... 

Autism spectrum disorders (ASD) have been defined as developmental disorders characterized by abnormalities in social interaction, communication skills, and behavioral flexibility. Over the past decades, studies using various genetic, neurobiological, cognitive and behavioral approaches have sought a single explanation for the heterogeneous manifestations of ASD, but no consensus on the etiology of ASD has emerged. Further studies aim to clarify the mechanism of disease.
Functional Magnetic Resonance Imaging (fMRI) is a new way of imaging which evaluates activity of brain by measuring magnetic difference caused by oscillation in blood oxygen level. fMRI has been widely used in recent... 

Image registration is an important preprocessing step in analysis of medical images. Detection, Treatment plan, disease grows process analysis and assistance in surgical applications are some of medical images applications. We need to be able to compare different modalities in medical images such as X-ray, PET, MRI, and CT... , or sometimes doctors need to take images of a patient in a same modality but in different times and directions. In which in order to be able to do theses comparisons we need to first align these images by using image registration methods. Image registration is an image processing method in which tries to find a geometrical transformation that would map different... 

The definition of human action recognition is classification of input visual elements based on the action which is done by a person in the scene. One of the most important topics in the filed which has lots of applications is human action recognition in videos. Some of these applications are surveillance, video retrieval, human computer interaction and smart houses. Due to increments in number of alone elderly people, surveillance of them is one of the important applications of human action recognition. The challenges of the task are, camera movement, differences of environment and differences in acting by different actors.The goal of the project is proposing a deep convolutional neural... 

Nowadays studying the brain's function in different Mental States like Resting-State or performing cognitive tasks is a very important component of research areas such as Biomedical Engineering, Neuroscience and Cognitive Sciences. The applications of studying the brain's function can be divided into two principal groups. In the first group of applications, the goal is understanding how the brain processes and response to external stimuli (like visual or audio stimuli) and internal states (like emotions). In these kinds of applications, particularly healthy subjects participate since the goal of these studies is finding healthy brain function in different states and stimuli. However, in the... 

Medical imaging is of interest because of information that will provide for doctors and registration is inevitable when we need to compare two or more images, taken from a subject at different times or with different sensors or when comparing two or more subjects together. Registration methods can be categorized in two major groups; methods based on feature and methods based on intensity. Methods in first group have three steps in common: feature extraction, finding matches and transform estimation. In second group it’s important to define a similarity measure and find the transform that minimizes this measure.
Manifold learning algorithms are mostly used as a dimensionality reduction... 

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... 

Sparse representation has attracted a lot of attention during the last few years. This adaptive representation has been used as an alternative of the classic transforms. In this kind of representation, signals are decomposed in terms of some basis functions. This basis functions are called “atoms” and their collection is called a “dictionary”. Dictionary learning should be such that signals have a sparse representation. Specified dictionary could apply some other properties except sparsity for the transform domain representation.In this thesis after study of methods convert the dictionary discriminative, we propose KLDA method for learning a discriminative dictionary. Also a new algorithm... 

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... 

Medical imaging is an indispensable component of modern medical research as well as clinical practice. However, Magnetic resonance Imaging and Computational tomography are expensive, and it is difficult to be used in many scenarios worldwide. As such, many parts of the world still do not have sufficient accessibility to these techniques. To make medical devices more accessible, affordable and efficient, it is crucial to reflect upon our current imaging paradigm for smarter imaging. According to Compressed Sensing theory, if there is information other than the signal bandwidth value, such as the being sparse in a suitable domain, nonlinear optimization methods can be used to accurately... 

Optical Coherence Tomography (OCT) has a great potential to elicit clinically useful information from tissues due to its high axial and transversal resolution. In practice, an OCT setup cannot reach to its theoretical resolution due to imperfections of its components, which make its images blurry. The blurriness is different alongside regions of image, thus they cannot be modeled by a unique point spread function (PSF). In this paper, we investigate the use of solid phantoms to estimate the PSF of each sub-region of imaging system. We then utilize Lucy-Richardson, steepest descent (SD) and total variation (TV) based iterative deconvolution methods for mitigating occurred spatially variant... 

Nowadays, the development of renewable energy sources is in line with the increasing capacity and installation of wind energy resources. Wind turbines, due to their installation in harsh areas, have high maintenance and repair costs, which is one of the main challenges for their further development. Given the high costs of repairs, predicting faults and planning for optimal maintenance can optimize performance and extend the useful life of the turbine. The aim of this research is to provide an approach to predict faults in wind turbines using data from the control and monitoring system. This data includes various parameters such as wind speed, output power, temperature of the generator... 

Predicting the Amino Acids that have a catalytic effect in the enzymes, is a big step in appointing the activity of the enzymes and classifying them. This is a very challenging job, because an Amino Acid can appear in a variety of active sites.The biological activity of a protein usually depends on the existence of a small number of Amino Acids. Detecting these Amino Acids from the sequence of Amino Acids has many applications. Usually, the Amino Acids that are preserved are known as the Amino Acids that build up the active site, but the algorithms for finding the preserved Amino Acids are much more complex. There are a lot of algorithms for predicting the active sites of Amino Acids, but... 

The most popular system for quantification of the facial behaviors and expressions is the Facial Action Coding System (FACS). FACS provides a description of all possible and visually detectable facial variations in terms of 33 Action Units (AUs). The activation of each AU leads to a slight variation in the facial appearance, and any facial expression can be modeled by a single AU or a combination of AUs. Definition of AUs is such that they are sparse in multiple domains. The goal of this dissertation is utilizing these sparsity properties to develop an effective algorithm for automatic intensity estimation of AUs. One of the sparsity domains of AUs is the spatial domain that means the... 

The gamma cameras, based on scintillation crystal followed by an array of photomultiplier tubes (PMTs), play a crucial role in nuclear medicine. The use of square PMTs provides the minimum dead zones in the camera. The camera with squared PMTs also reduces the number of PMTs relative to the detection area.In this thesis, we introduced a new read-out method whereby the total cost of the read-out board will be decreased by a factor of 2.4; in return, the energy and spatial resolution of the system will be reduced by 0.3% and 0.4% respectively. We also implemented a positioning module in the FPGA chip via that the transmission rate between FPGA and the computer will be tripled, and the... 

Methodology has always one of important issues in philosophy of science; especially in social sciences lots of challenges arise from this field. Each of positivistic and relativistic different schools, on their own ontology about human and society, had suggested different methods of social studies. Roy Bhaskar, as the others, offers a model for scientific method, on the base of his own critical realistic ontological principles; and tries to secure his model from the objections on previous models of scientific method. In this model, hi suppose empirical survey as an obvious and undoubted activity in science. Then, he transcendentally derives his ontological principles from this antecedent,... 

The philosophers of social sciences, in addition to epistemological questions-the questions about our knowledge of the social world- implicitly or explicitly, consider ontological issues: the questions about the nature of social world (society, structures and relations, people and actions). In Critical Realism, ontology and epistemology are linked. It means that what it is awarded, it is crucial that knowledge can be gained from it. This school, with a critique of Positivism and Hermeneutics, tries to authenticate ontological arguments and by reconstruction of concepts like causality, necessity, structure and stratification reality, forms the realist ontology and offers a novel solution to...