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Total 111 records
Forecasting Tractor Demand in Two Major Agricultural Crop-Producing Provinces of Iran
, M.Sc. Thesis Sharif University of Technology ; Rezapour Niari, Maryam (Supervisor)
Abstract
Today, demand function forecasting is one of the fundamental and critical challenges in organizational decision-making at both strategic and operational levels. Key decisions that significantly impact the success or failure of organizations -such as pricing, production planning, resource allocation, and market development- are directly influenced by the accuracy of demand forecasting. Since the demand function is typically affected by multiple factors including price, quality, economic conditions, social factors, and other variables shaping customer behavior, precise estimation requires employing diverse and accurate methods. Various approaches have been proposed in the literature for demand...
Seizure Detection in Generalized and Focal Seizure from EEG Signals
, M.Sc. Thesis Sharif University of Technology ; Hajipour, Sepideh (Supervisor)
Abstract
Epilepsy is one of the diseases that affects the quality of life of epileptic patients. Epileptic patients lose control during epileptic seizures and are more likely to face problems. Designing and creating a seizure detection system can reduce casualties from epileptic attacks. In this study, we present an automatic method that reduces the artifact from the raw signals, and then classifies the seizure and non-seizure epochs. At all stages, it is assumed that no information is available about the patient and this detection is made only based on the information of other patients. The data from this study were recorded in Temple Hospital and the recording conditions were not controlled, so...
Studying Time Perception in Musician and Non-musician Using Auditory Stimuli
, M.Sc. Thesis Sharif University of Technology ; Hajipour, Sepideh (Supervisor)
Abstract
Time perception is a concept that describes how a person interprets the duration of an event. Depending on the circumstances, people may feel that time passes quickly or slowly. So far, the understanding, comparison, and estimation of the time interval have been described using a simple model, a pacemaker accumulator, that is powerful in explaining behavioral and biological data. Also, the role of the frequency band, Contingent Negative Variation (CNV), and Event-Related Potential (ERP) components have been investigated in the passage of time and the perception of time duration. Still, the stimuli used in these studies were not melodic. Predicting is one of the main behaviors of the brain....
Evaluation Auditory Attention Using Eeg Signals when Performing Motion and Visual Tasks
, M.Sc. Thesis Sharif University of Technology ; Hajipour, Sepideh (Supervisor)
Abstract
Attention is one of the important aspects of brain cognitive activities, which has been widely discussed in psychology and neuroscience and is one of the main fields of research in the education field. The human sense of hearing is very complex, impactful and crucial in many processes such as learning. Human body always does several tasks and uses different senses simultaneously. For example, a student who listens to his/her teacher in the class, at the same time pays attention to the teacher, looks at a text or image, and sometimes writes a note.Using the electroencephalogram (EEG) signal for attention assessment and other cognitive activities is considered because of its facile recording,...
Emotion Recognition from EEG Signals using Tensor based Algorithms
, M.Sc. Thesis Sharif University of Technology ; Hajipour, Sepideh (Supervisor)
Abstract
The brain electrical signal (EEG) has been widely used in clinical and academic research, due to its ease of recording, non-invasiveness and precision. One of the applications can be emotion recognition from the brain's electrical signal. Generally, two types of parameters (Valence and Arousal) are used to determine the type of emotion, which, in turn, indicate "positive or negative" and "level of extroversion or excitement" for a specific emotion. The significance of emotion is determined by the effects of this phenomenon on daily tasks, especially in cases where the person is confronted with activities that require careful attention and concentration.In the emotion recognition problem,...
Diagnosis of Depressive Disorder using Classification of Graphs Obtained from Electroencephalogram Signals
, M.Sc. Thesis Sharif University of Technology ; Hajipour, Sepideh (Supervisor)
Abstract
Depression is a type of mental disorder that is characterized by the continuous occurrence of bad moods in the affected person. Studies by the World Health Organization (WHO) show that depression is the second disease that threatens human life, and eight hundred thousand people die due to suicide every year. In order to reduce the damage caused by depression, it is necessary to have an accurate method for diagnosing depression and its rapid treatment, in which electroencephalogram (EEG) signals are considered as one of the best methods for diagnosing depression. Until now, various researches have been conducted to diagnose depression using electroencephalogram signals, most of which were...
Recommendations on enhancing the efficiency of algebraic multigrid preconditioned GMRES in solving coupled fluid flow equations
, Article Numerical Heat Transfer, Part B: Fundamentals ; Volume 55, Issue 3 , 2009 , Pages 232-256 ; 10407790 (ISSN) ; Darbandi, M ; Sharif University of Technology
2009
Abstract
The algebraic multigrid (AMG) algorithm as a preconditioner to the Krylov subspace methods has drawn the attention of many researchers in solving fluid flow and heat transfer problems. However, the efficient employment of this solver needs experience, because users have to quantify several important parameters. In this work, we choose a hybrid finite-volume element method and quantify the optimum magnitudes for those parameters. To generalize our results, two sets of fluid flow governing equations, the thermobuoyant flow and confined diffusion flame, are studied and the optimum values are determined. The results indicate that the AMG can be very effective if a proper storage method is chosen...
Evaluation of The Informational Efficiency of Tehran Securities Market
, M.Sc. Thesis Sharif University of Technology ; Zamani, Shiva (Supervisor)
Abstract
In the present research, the weak level efficiency of securitise market is reviewed and examined .Therefore the “Random Walk Hypothesis” has been examined on the time series of daily efficiency index of TEHRAN SECURITISE MARKET. The main difference between this research and the previous researches which have been performed previously in Iran, is the method of Hypothesis Test. The” Variance Ratio Test” has been used as a method of Hypothesis’ Test. In the second chapter, the theoretical and experimental literatures of this research has been described in detail. In parallel with the ” Variance Ratio Test”, the impact of the Day of week and the “HETROSCEDASITY TEST” also has been...
Production of Nanostructured Composite Sheets of AA1100/St37 Using ARB Technique and Evaluation of Heat Treatment Effect on Grains Structure
, M.Sc. Thesis Sharif University of Technology ; Asgari, Sirous (Supervisor)
Abstract
In present work, nanostructured multilayer composites produced from AA1100 and St37 alloys and mechanical properties of resulted samples characterized using tension and micro hardness tests. Also dispersion pattern of second phase in matrix studied via optical microscopy. Thickness of second phase layers showed a little reduction after 2 ARB cycles; but their length decrease gradually. With increasing number of ARB cycles up to 6 cycles, sample's tensile strength first decrease rapidly and after that increased, but never reached initial value. In order to evaluation of heat treatment effects on samples grain structure, samples heat treated and tensile test carried on them. Annealing at 300...
Why and How did Philosophy of Science Come to Iran?
, M.Sc. Thesis Sharif University of Technology ; Golshani, Mehdi (Supervisor)
Abstract
The history of an Episteme is part of that Episteme. Without understanding the history of Episteme, one cannot get the right understanding of the Episteme. In order to understand the current coordinates of philosophy in Iran (as well as understanding the current state of philosophy in Iran), it must examine the history of its emergence and development. Part of the sources of recognition of this history is the “Erlbnis” of those who lived the event. Those who have been trying for its birth and development. Some other sources in understanding this history are the previous published works in this area. Another is the educational effort and the establishment and development of the institutions...
EEG-based Emotion Recognition Using Graph Learning
, M.Sc. Thesis Sharif University of Technology ; Hajipour Sardouie, Sepideh (Supervisor)
Abstract
The field of emotion recognition is a growing area with multiple interdisciplinary applications, and processing and analyzing electroencephalogram signals (EEG) is one of its standard methods. In most articles, emotional elicitation methods for EEG signal recording involve visual-auditory stimulation; however, the use of virtual reality methods for recording signals with more realistic information is suggested. Therefore, in the present study, the VREED dataset, whose emotional elicitation is virtual reality, has been used to classify positive and negative emotions. The best classification accuracy in the VREED dataset article is 73.77% ± 2.01, achieved by combining features of relative...
Detection of High Frequency Oscillations from Brain Electrical Signals Using Time Series and Trajectory Analysis
, M.Sc. Thesis Sharif University of Technology ; Hajipour Sardouie, Sepideh (Supervisor)
Abstract
The analysis of cerebral signals, encompassing both invasive and non-invasive electroencephalogram recordings, is extensively utilized in the exploration of neural systems and the examination of neurological disorders. Empirical research has indicated that under certain conditions, such as epileptic episodes, cerebral signals exhibit frequency components exceeding 80 Hz, which are designated as high frequency oscillations. Consequently, high frequency oscillations are recognized as a promising biomarker for epilepsy and the delineation of epileptic foci. The objective of this dissertation is to evaluate the existing methodologies for the detection of high frequency oscillations and to...
High Frequency Oscillation Detection in Brain Electrical Signals Using Tensor Decomposition
, M.Sc. Thesis Sharif University of Technology ; Hajipour, Sepideh (Supervisor)
Abstract
High-frequency oscillations (HFOs) in brain electrical signals are activities within the 80–500 Hz frequency range that are distinct from the baseline and include at least four oscillatory cycles. Research indicates that HFOs could serve as potential biomarkers for neurological disorders. Manual detection of HFOs is time-consuming and prone to human error, making automated HFO detection methods increasingly necessary. These automated methods typically rely on the signal's energy within the HFO frequency band. Tensor decompositions are mathematical models capable of extracting hidden information from multidimensional data. Due to the multidimensional nature of brain electrical signals, tensor...
Design of adaptive proportional-integral-weighted (PIw) controllers for control of a class of nonlinear uncertain systems
, Article 2017 25th Iranian Conference on Electrical Engineering, ICEE 2017, 2 May 2017 through 4 May 2017 ; 2017 , Pages 923-926 ; 9781509059638 (ISBN) ; Tavazoei, M. S ; Sharif University of Technology
2017
Abstract
Study on the potential abilities of the proportional-integral-weighted (PIw) controllers, as a recently proposed generalization for proportional-integral (PI) controllers, can be useful for improving the performance of traditional control systems. In this paper, adaptive PI and adaptive PIw controllers are designed to be used in control of a special class of nonlinear uncertain systems based on the Lyapanuv stability theorem. The effectiveness of the proposed controllers is illustrated by applying the proposed schemes to a Continuous Stirred-Tank Reactor (CSTR) system with an unknown parameter. Simulation results indicate that using adaptive PIw controllers, in comparison to using the...
Cluster-based adaptive SVM: a latent subdomains discovery method for domain adaptation problems
, Article Computer Vision and Image Understanding ; Volume 162 , 2017 , Pages 116-134 ; 10773142 (ISSN) ; Jamzad, M ; Sharif University of Technology
2017
Abstract
Machine learning algorithms often suffer from good generalization in testing domains especially when the training (source) and test (target) domains do not have similar distributions. To address this problem, several domain adaptation techniques have been proposed to improve the performance of the learning algorithms when they face accuracy degradation caused by the domain shift problem. In this paper, we focus on the non-homogeneous distributed target domains and propose a new latent subdomain discovery model to divide the target domain into subdomains while adapting them. It is expected that applying adaptation on subdomains increase the rate of detection in comparing with the situation...
Extraction of Event Related Potentials (ERP) from EEG Signals using Semi-blind Approaches
, M.Sc. Thesis Sharif University of Technology ; Hajipour Sardouie, Sepideh (Supervisor)
Abstract
Nowadays, Electroencephalogram (EEG) is the most common method for brain activity measurement. Event Related Potentials (ERP) which are recorded through EEG, have many applications. Detecting ERP signals is an important task since their amplitudes are quite small compared to the background EEG. The usual way to address this problem is to repeat the process of EEG recording several times and use the average signal. Though averaging can be helpful, there is a need for more complicated filtering. Blind source separation methods are frequently used for ERP denoising. These methods don’t use prior information for extracting sources and their use is limited to 2D problems only. To address these...
Design and Implementation of a P300 Speller System by Using Auditory and Visual Paradigm
, M.Sc. Thesis Sharif University of Technology ; Hajipour Sardouie, Sepideh (Supervisor)
Abstract
The use of brain signals in controlling devices and communication with the external environment has been very much considered recently. The Brain-Computer Interface (BCI) systems enable people to easily handle most of their daily physical activity using the brain signal, without any need for movement. One of the most common BCI systems is P300 speller. In this type of BCI systems, the user can spell words without the need for typing with hands. In these systems, the electrical potential of the user's brain signals is distorted by visual, auditory, or tactile stimuli from his/her normal state. An essential principle in these systems is to exploit appropriate feature extraction methods which...
An Investigation of Resting-State Eeg Biomarkers Derived from Graph of Brain Connectivity for Diagnosis of Depressive Disorder
, M.Sc. Thesis Sharif University of Technology ; Hajipour, Sepideh (Supervisor)
Abstract
Among the most costly diseases that affect a person's quality of life throughout his or her life, mental disorders (excluding sleep disorders) affect up to 25 percent of people in any community. One of the most common types of these disorders in Iran is depressive disorder, which according to official statistics, 13% of Iranians have some symptoms of it. Until now, the diagnosis of this disease has been traditionally done in clinics with interviews and questionnaires tests based on behavioral psychology and using symptom assessment. Therefore, there is a relatively low accuracy in the treatment process. Nowadays, with the help of functional brain imaging such as electroencephalogram (EEG)...
Shared Resource Management in DAG-Based Task Sets on Mixed-Criticality Multi-core Systems
, M.Sc. Thesis Sharif University of Technology ; Hessabi, Shaahin (Supervisor) ; Safari, Sepideh (Supervisor)
Abstract
In safety-critical systems, software tasks with varying criticality levels must execute in a coordinated manner under strict timing constraints on a multicore platform to ensure overall system safety. These tasks typically have temporal and logical dependencies and are not independent; in practice, mixed-criticality systems rely on structures of interdependent tasks with different criticality levels, which can be modeled using directed acyclic graphs (DAGs). Graph-based tasks may require access to shared resources during execution, and such access must preserve data integrity while preventing deadlocks and chained blocking. However, prior research has largely overlooked the critical issue of...
Type i shell galaxies as a test of gravity models
, Article Astrophysical Journal ; Volume 848, Issue 1 , 2017 ; 0004637X (ISSN) ; Kroupa, P ; Rahvar, S ; Sharif University of Technology
2017
Abstract
Shell galaxies are understood to form through the collision of a dwarf galaxy with an elliptical galaxy. Shell structures and kinematics have been noted to be independent tools to measure the gravitational potential of the shell galaxies. We compare theoretically the formation of shells in Type I shell galaxies in different gravity theories in this work because this is so far missing in the literature. We include Newtonian plus dark halo gravity, and two non-Newtonian gravity models, MOG and MOND, in identical initial systems. We investigate the effect of dynamical friction, which by slowing down the dwarf galaxy in the dark halo models limits the range of shell radii to low values. Under...