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karbalaee-aghajan--hamid
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Total 868 records
Capacitive Sensors for user Gesture Recognition in Smart Environments
, M.Sc. Thesis Sharif University of Technology ; Karbalaee Aghajan, Hamid (Supervisor)
Abstract
To create applications for smart environments we can select from a huge variety of sensors that measure environmental parameters within the premises. Capacitive proximity sensors use weak electric fields to recognize conductive objects, such as the human body. They can be unobtrusively applied or even provide information when hidden from view which make these sensor more popular. Furthermore, these sensors are low cost, precise and low power. In this thesis, we study the construction and operation of capacitive sensors and the challenges of using them. Then we use them to produce smart devices. Smart flooring is used on the ground and it can be used to track people or fall detection. Smart...
Reconstruction of Visual Experience from Brain’s Visual Cortex Data Using
Deep Learning
,
M.Sc. Thesis
Sharif University of Technology
;
Karbalaee Aghajan, Hamid
(Supervisor)
;
Soleymani, Mahdieh
(Co-Supervisor)
Abstract
e study of the brain’s neural activity is an active research area in computational neuroscience aiming to provide insights about the functionality of the brain as well as dysfunctions that underlie disorders. Functional Magnetic Resonance Imaging (fMRI) plays an important role in brain studies by providing non-invasive records of neural activities during a specific task with location sensitivity. Recent advances in statistics and machine learning offer powerful tools for paern recognition and processing of fMRI data. In this thesis, we decode information recorded via fMRI from the visual cortex to reconstruct images presented to subjects. Current reconstruction methods face numerous...
Study of Brain Oddball Response to Olfactory Stimuli as Indicator in Dementia Disorders
, M.Sc. Thesis Sharif University of Technology ; Karbalaee Aghajan, Hamid (Supervisor)
Abstract
High-frequency oscillations of the frontal cortex are involved in functions of the brain that fuse processed data from different sensory modules or bind them with elements stored in the memory. These oscillations also provide inhibitory connections to neural circuits that perform lower-level processes. Deficit in the performance of these oscillations has been examined as a marker for Alzheimer’s disease (AD). Additionally, the neurodegenerative processes associated with AD, such as the deposition of amyloid-beta plaques, do not occur in a spatially homogeneous fashion and progress more prominently in the medial temporal lobe in the early stages of the disease. This region of the brain...
Multi-Camera Action Recognition with Manifold Learning
, M.Sc. Thesis Sharif University of Technology ; Karbalaee Aghajan, Hamid (Supervisor)
Abstract
Human action recognition is one of the most attended topics in computer vision and robotics.One of the flavors of this problem relates to the situation in which the task of action recognition is carried out by data from several cameras. Different approaches have been proposed for combining information. Various reduction methods have been introduced to decrease the processing load. All of the methods in this particular field of study can be divided into two linear and non-linear methods. In the linear methods, we don’t pay attention to the non-linear structure of the data, and these kind of approaches are not reliable. Furthermore, combining different actions data is done before the dimension...
Comparative Analysis of the Effect of Gamma-band Entrainment through Auditory Stimulation in AD Patients and Healthy Controls
, M.Sc. Thesis Sharif University of Technology ; Aghajan, Hamid (Supervisor)
Abstract
As the most widespread form of mental disorders, Alzheimer’s disease (AD) remains among the main challenges in neurology and in the field of neuroscience. There are still no effective drugs to cure this disease or slow its progress, and prevention methods are still not even close to having established records. However, the onset of AD has been linked to certain dysfunctions of the oscillatory frequencies of the affected brain mainly in the gamma band. Hence, an approach to consider for reversing the damaging effects of AD could involve reviving such oscillations through stimulating the neuronal networks in the brain that are known to be the source of these oscillations. A recent research has...
Modeling the Brain’s Probabilistic Prediction of Oddball Paradigm
, Ph.D. Dissertation Sharif University of Technology ; Karbalai Aghajan, Hamid (Supervisor)
Abstract
The brain is constantly anticipating the future of sensory inputs based on past experiences. When new sensory data is different from predictions shaped by recent trends, neural signals are generated to report this surprise. Surprise leads to garnering attention, causes arousal, and motivates engagement. It motivates the formation of an explanation or updating of current models. Three models have been proposed for quantifying surprise as the Shannon, Bayesian, and confidence-corrected surprises. In this thesis, we analyze EEG and MEG signals recorded during oddball tasks to examine and statistically compare the value of temporal/ spatial components in decoding the brain’s surprise. We...
A Novel Approach for Seizure Prediction using EEG Signals
, M.Sc. Thesis Sharif University of Technology ; Karbalaei Aghajan, Hamid (Supervisor)
Abstract
As the fourth most common neurological disorder, epilepsy affects lots of people all around the world, some of whom have to live with unpredictable seizures uncontrollable by surgery or medication. Hence, Developing systems for detection and prediction of the epileptic seizures will help the patients to avoid the possible damages caused by sudden seizures. This study addresses the task of epileptic seizure prediction, using three different novel approaches. The first approach, which is based on anomaly detection, contains three steps: feature extraction from EEG signals, training a one-class SVM classifier, and a post-processing step. The second method exploits a recurrent neural network to...
Speech-Driven Facial Reenactment
, M.Sc. Thesis Sharif University of Technology ; Karbalaei Aghajan, Hamid (Supervisor)
Abstract
Creating talking heads from audio input is interesting from both scientific and practical viewpoints, e.g. constructing virtual computer generated characters, aiding hearing-impaired people, live dubbing of videos with translated audio, etc. Due to its wide variety of applications, audio to video has been the focus of intensive research in recent years. Mapping audio to facial images with accurate lip-sync is an extremely difficult task because it is a mapping form 2-Dimensional to 3-Dimensional space and also because humans are expert at detecting any out-of-sync lip movements with respect to an audio.Approaches to automatically generating natural looking speech animation usually involve...
Effects of 40Hz Auditory Entrainment on Phase-Amplitude Coupling and Connectivity Parameters of the Brain
, M.Sc. Thesis Sharif University of Technology ; Karbalaei Aghajan, Hamid (Supervisor)
Abstract
Alzheimer's disease is the most common type of dementia, which has been recognized as the seventh most common fatal disease in the elderly over 65 years of age. Despite all the research done to recognize and treat this disease, so far there is no cure for this disease, and even most of the chemical treatments that are prescribed for Alzheimer's patients are only effective towards reducing the symptoms of this disease and lose their effectiveness as it progresses. Therefore, in the last two decades, in order to find a way to better understand and even treat AD, scientists have reached a concept called brain frequency stimulation, which can improve people's cognitive performance without the...
Differences of the Brain’s Surprise Response Due to the Habituation Effect in Neurodegenerative Patients and Healthy People
, M.Sc. Thesis Sharif University of Technology ; Karbalaei Aghajan, Hamid (Supervisor)
Abstract
The brain is constantly placed in stochastic environments. This leads to the brain developing a probabilistic model for the environment. However, sometimes unexpected events occur that lead to surprise and a need for updating the probabilistic model. It can be concluded from this argument that reduction in brian’s surprise is a sign of learning. On the other hand, a probability distribution obtained from a probabilistic model contains an amount of uncertainty. Reducing this uncertainty can also be considered a sign of learning. Surprise and uncertainty can be obtained from a probability distribution using information theory concepts. Another important issue in learning is habituation, which...
Differentiating Signals Recorded from Rat Brain in Response to Different Olfactory Stimuli
, M.Sc. Thesis Sharif University of Technology ; Karbalaei Aghajan, Hamid (Supervisor)
Abstract
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...
Probabilistic Modelling of Fatigue Detection with Facial Features
, M.Sc. Thesis Sharif University of Technology ; karbalaie Aghajan, Hamid (Supervisor)
Abstract
Today, everyone is looking for ways to achieve comfort and safety in the workplace and, in so doing, appeals to various sciences. One of these sciences is "ergonomics", which examines the human relationship with the work. One of the areas that could be of great interest is the driving ergonomics. After all nowadays, many people use personal vehicles. The increasing use of personal vehicles has increased the number of accidents and deaths. In recent decades, many researches have been done in the field of driver fatigue detection. To avoid road accidents, researchers have focused on monitoring driver and vehicle behavior and tried to analyse status of the driver. Using computer vision, we can...
Determination of Correlation between Phase Amplitude Coupling and Surprise in Brain
, M.Sc. Thesis Sharif University of Technology ; Karblaei Aghajan, Hamid (Supervisor)
Abstract
The human brain needs to create a model of data surrounding it continuously. To do so, handling the dynamics of information through communication between the brain regions is a critical step. Having a model of this procedure in the brain not only provides a clear explanation of how cognition occurs in the brain, but also enables us to have a better view of the cognition impairments in the brain. Surprise is a process in the brain that brings various cognitive abilities, including attention and memory, into practical use. Furthermore, these abilities are about manipulating the input information in an optimized way. Memory is the ability to store information arriving at a specific time....
Analysis of Functional Brain Connectivity Using EEG Signals for Classification of Brain States
, M.Sc. Thesis Sharif University of Technology ; Karbalai Aghajan, Hamid (Supervisor) ; Mohamadzadeh, Hoda ($item.subfieldsMap.e)
Abstract
Different perceptual, cognitive, and emotional situations results in a kind of information flow in the brain by means of coordinated neuronal oscillations. Analysing these oscillations, especially synchronizations of different brain regions, can illustrate the brain response to the aforementioned situations. In the literature, connectivity between brain regions is divided into the three groups of structural, effective, and functional, s.t. the first one referes to the connectivity between nearby regions, while the second and third ones focus on the synchronization of oscillations of arbitrary located regions. Although EEG is not the best choice for analyzing functional connectivity between...
Alzheimer’s Disease Diagnosis using Description Test
, M.Sc. Thesis Sharif University of Technology ; Soleymani Baghshah, Mahdieh (Supervisor) ; Karbalaei Aghajan, Hamid (Supervisor)
Abstract
There are currently about 50 million people with Alzheimer's disease in the world, and this number is about 700 thousand in Iran. The symptoms of the disease include decreased awareness, disinterest in unfamiliar subjects, increased distraction, speech problems, and etc. which gradually leads to an absolute inability to perform daily activities and completely mute. The disease belongs to the category of neurological disorders and is the most common type of dementia for which no treatment has been offered so far. However, if the disease is diagnosed in its early stage, a series of pharmacological and behavioral therapy approaches can be prescribed to reduce the pace or progression of the...
Investigation of Strain Jumping and Its Effect on Evaluating Capacity of Steel Bracing Deformations
, M.Sc. Thesis Sharif University of Technology ; Moghaddam, Hassan (Supervisor)
Abstract
In this study, HSS and double angle braces subjected to cyclic loading in order to study the buckling and post buckling behavior have been investigated by Finite Element method. The results of FE analysis are fairly in good agreement with experiments. Analysis demonstrate that when local buckling occurs in middle span, subsequently, strain rises severely. Accordingly, this strain jumping causes early fracture in braces. Therefore, local buckling can be one of the primary reasons of fracture in braces. As a result, local buckling must be considered one of the primary limit state of Performance-Based design of steel braces. In addition, finding a way to predict local buckling can help us to...
Investigation of Brain Connectivity Changes during Seizure using Graph Theory
, M.Sc. Thesis Sharif University of Technology ; Karbalai Aghajan, Hamid (Supervisor) ; Mohammadzadeh, Hoda (Co-Supervisor)
Abstract
Epilepsy is a chronic neurological disorder characterized by recurrent and abrupt seizures. Seizures occur due to disturbances in the interactions between the distributed neuronal populations in the brain. Investigation of the brain functional connectivity networks is a way to better understand how the brain functions during seizure. To estimate the brain functional connectivity network, we need criteria that can estimate the functional connections between the brain regions from the recorded brain functional data such as electroencephalogram (EEG) signals. After estimating the functional brain connectivity networks, it is possible to create graphs corresponding to these estimated networks...
EEG-Based Markers of Major Depressive Disorder in Reinforcement Learning
, M.Sc. Thesis Sharif University of Technology ; Vosoughi Vahdat, Bijan (Supervisor) ; Karbalaei Aghajan, Hamid (Co-Supervisor)
Abstract
Major Depressive Disorder (MDD) is a common and serious mental health disorder characterized not only by mood disturbances but also by deficits in cognitive functions and decision-making processes. This disorder can affect all aspects of an individual’s life, including their relationships with family, friends, and society. Recent electroencephalography (EEG) studies have demonstrated that certain neuropsychiatric disruptions lead to alterations in specific brain signal metrics, which can serve as markers of brain dysfunction. Many studies have explored traditional linear EEG metrics, such as frequency band power, asymmetry in frequency band activity, and event-related potential components,...
Evaluation of Dose Change to Brain Tumor in Proton Therapy by Utilizing Magnetic Field
, M.Sc. Thesis Sharif University of Technology ; Vosoughi, Naser (Supervisor) ; Salimi, Ehsan (Supervisor)
Abstract
The use of protons and charged particles such as carbon in the treatment of cancerous tumors is one of the new methods of external radiation therapy. Proton therapy can achieve almost the same tumor dose coverage as traditional photon therapy with a greatly reduced dose to the normal organ. The radiation deviations caused by the magnetic field are an effective factor in reducing the dose of vital organs without sacrificing the dose coverage of tumors; Therefore, a new method of proton therapy, called magnetic field-modulated proton therapy, has been proposed, in which the Bragg peak positions of proton beams can be modulated under the cover of predesigned magnetic fields inside cancer...
Synthesis of Silica Nanoparticles Modified with Alumina and Its Performance in Compressive Strength of Concrete
, M.Sc. Thesis Sharif University of Technology ; Sajadi, Ali Akbar (Supervisor) ; Ghanbari, Bahram (Supervisor)
Abstract
Silica nanoparticles is one of the most important mineral particles. In this study, Sodium silicate, Sulfuric acid and Sodium aluminate is used in order to synthesis of the modified Silica nanoparticles. The effects of temperature, reaction time and the molar ratio of regents were tested and optimized. Synthesized nanoparticles were characterized by use of XRD, FT-IR and SEM techniques. The results show that by controlling the reaction conditions, nanoparticles with an average size of 26.2 nm is obtained. The increase of temperature and reaction time alters the structure of the particles of amorphous state to a crystalline needles. The particle surface modification process was performed by...