Design and Implementation of Electrical Dust Control System Using DSP Processors

, M.Sc. Thesis Sharif University of Technology Sheikhzade Tak Abi, Mahdi (Author) ; Vosoughi Vahdat, Bijan (Supervisor) ; Hashemi, Matin (Co-Advisor)

Assessment and comparison of اomogeneity and conformity indexes in step-and-shoot and compensator-based intensity modulated radiation therapy (IMRT) and three-dimensional conformal radiation therapy (3D CRT) in prostate cancer

, Article Journal of Medical Signals and Sensors ; Volume 7, Issue 2 , 2017 , Pages 102-107 ; 22287477 (ISSN) Salimi, M ; Shirani Tak Abi, K ; Nedaie, H. A ; Hassani, H ; Gharaati, H ; Samei, M ; Shahi, R ; Zarei, H ; Sharif University of Technology

2017

Abstract

Intensity modulated radiation therapy (IMRT) and three-dimensional conformal radiation therapy (3D CRT) are two treatment modalities in prostate cancer, which provide acceptable dose distribution in tumor region with sparing the surrounding normal tissues. IMRT is based on inverse planning optimization; in which, intensity of beams is modified by using multileaf collimators and also compensators with optimum shapes in step and shoot (SAS) and compensator-based method, respectively. In the recent study, some important parameters were compared in two IMRT and 3D CRT methods. Prescribed dose was 80 Gy for both IMRT procedures and 70 Gy for 3D CRT. Treatment plans of 15 prostate cancer...

Accuracy and Stability Properties of the Numerical Integration Method with Combined Implicit or Explicit Steps for Use in Hybrid Simulations

, M.Sc. Thesis Sharif University of Technology Abi, Amir Reza (Author) ; Ahmadizadeh, Mehdi (Supervisor)

Abstract

The increased need for experimental verification of the seismic performance of conventional and novel structural systems has resulted in highly sophisticated dynamic test procedures. Hybrid simulation is one of the most efficient experimental methods for assessment of dynamic and rate-dependent behavior of large-scale structural systems under earthquake excitation. Compared to earthquake simulations using shake tables, hybrid simulation may have significant advantages in terms of cost, scale, geometry, and required physical mass of structures. However, recent hybrid simulations have been limited to simplified structural models with only a few degrees of freedom. Currently, the major...

Comprehensive Modelling and Simulation of Stray Current in DC Railway System

, M.Sc. Thesis Sharif University of Technology Abdollahi Dam Abi, Hossein (Author) ; Mokhtari, Hossein (Supervisor)

Abstract

In urban rail (subway) substations, high voltage dc (750 V) is usually used to feed the traction motors of the wagons. This type of feeding raises issues, including the creation of stray currents in different parts of the structure. The cause of the stray current is the voltage difference between the two points of the rails, caused by the current flowing inside the rails. These currents accelerate the corrosion process in and around metallic equipment. One of the most dangerous issues is the corrosion of gas pipes near the subway that has caused disasters in the past. The stray current cannot be eliminated and its maximum reduction requires high costs. For this reason, different standards...

A deep reinforcement learning approach for uav path planning incorporating vehicle dynamics with acceleration control

, Article Unmanned Systems ; Volume 12, Issue 3 , 2024 , Pages 477-498 ; 23013850 (ISSN) Sabzekar, S ; Samadzad, M ; Mehditabrizi, A ; Tak, A. N ; Sharif University of Technology

2024

Abstract

Unmanned aerial vehicles (UAVs) are experiencing a rapid expansion in their applications across various domains, including goods delivery, video capturing, and traffic control. The crucial aspect for UAVs to execute successful target tracking and obstacle avoidance maneuvers lies in the accuracy of their path planning operations. This research paper aims to contribute to the existing body of knowledge by presenting a novel model that incorporates acceleration control, accounting for changing variables such as UAV velocity and altitude, while also incorporating vehicle dynamics. To enhance the realism of the model, we include drag force as a factor. In this study, we focus on exploring the...

Effects of soft marine fouling on wave-induced forces in floating aquaculture cages: Physical model testing under regular waves

, Article Ocean Engineering ; Volume 238 , 2021 ; 00298018 (ISSN) Nobakht Kolur, F ; Zeinoddini, M ; Aalami Harandi, M. M ; Abi, F. A ; Jadidi, P ; Sharif University of Technology

Elsevier Ltd 2021

Abstract

Previous experiments on the fouling/current and fouling/wave interactions were mostly limited to two dimensional (2D) net panels or isolated twines. The current paper deals with the wave-induced forces/moments in three dimensional (3D) physical models of a gravity net-cage. The colonial hydroid Ectopleura larynx, a common fouling organism in the aquaculture industry, was artificially modelled and considered in the current experiments. A clean cage and cages with different fouling lengths were tested under deep-water regular wave trains. The time series of the wave-induced forces/moments in the surge, sway, roll and pitch degrees of freedom were recorded and analysed. The experimental results...

Selection of the SFCL Type and its Design in order to Resolve the Problem Associated with the Rise of Grid Short-Circuit Level in a Sample Distribution and a Sample Sub-Transmission Substation of Tehran Regional Electric Company

, M.Sc. Thesis Sharif University of Technology Samizadeh, Ali (Author) ; Vakilian, Mahdi (Supervisor) ; Fardmanesh, Mahdi (Supervisor)

Abstract

In recent years, with the increase in generation capacity and the expansion of power networks, the grid short-circuit level has significantly risen, creating serious challenges for the protection of the network electrical equipment. One effective solution in this context is the use of Superconducting Fault Current Limiters (SFCLs), which, due to their fast transition from the superconducting state to the resistive state, can limit the high fault currents within a short period of time. In this thesis, after reviewing the operating principles, types, and applications of SFCLs, in the first step a semi-industrial prototype of a resistive-type SFCL is tested in the Superconductivity Laboratory...

Machine learning for construction crew productivity prediction using daily work reports

, Article Automation in Construction ; Volume 152 , 2023 ; 09265805 (ISSN) Sadatnya, A ; Sadeghi, N ; Sabzekar, S ; Khanjani, M ; Tak, A. N ; Taghaddos, H ; Sharif University of Technology

Elsevier B.V 2023

Abstract

Construction productivity estimation lacks a comprehensive, standard, and task-type-independent framework to generate and serialize Machine Learning (ML) models. This research aims to develop an ML management framework for estimating the work crew productivity (crew outputs over their working hours) by addressing various operation and project types. The framework takes advantage of historical data, including information regarding operations' progress, weather conditions, the number of resources, and their composition in a work crew. Daily work reports are used as a principal source of historical data. Various hyperparameters-tuned ML algorithms are adopted and ranked based on their...

MBBR and MBR Reactor Configuration for Better Performance

, M.Sc. Thesis Sharif University of Technology (Author) ; Borgheei, Mahdi (Supervisor)

Abstract

Membrane bioreactors (MBRs) which are commonly understood as the combination of membrane filtration and biological treatment using activated sludge have several advantages, but membrane fouling reduces the membrane efficiency, permeability and lifetime. An alternative is replacing a moving bed biofilm reactor (MBBR) with the activated sludge system which may reduce the effect of membrane fouling. The sludge produced in MBBRs has poor settling characteristics, therefore, their efficiency is limited by the sedimentation tank performance and they require a larger settling surface. The combination of moving bed biofilm reactors and membrane bioreactors can compensate for the drawbacks of both of...

Identification and Forecasting of Nuclear Power Plants Transients by Semi-Supervised Method with Change of Representation Technique

, M.Sc. Thesis Sharif University of Technology Mirzaei Dam-Abi, Ali (Author) ; Ghofrani, Mohamad Bagher (Supervisor) ; Moshkbar Bakhshayesh, Khalil (Supervisor)

Abstract

In this work, we aim to find a way to identify and forecast transients in nuclear power plants with the aid of semi-supervised machine learning algorithm. Forecasting and identifying transients in nuclear power plants at the early stages of formation are essential for safety considerations and precautionary measures. The use of machine learning algorithms provides an intelligent control mechanism that, along with the main operator of the power plant, raises the transient detection and identification rate. Our algorithm of choice is to change the way data is presented, which is a semi-supervised learning approach. The algorithm consists of two methods: quantum dynamics clustering...

Cooperative Throughput Maximization in a Multi-Cluster WPCN

, Article IEEE Transactions on Green Communications and Networking ; Volume 8, Issue 4 , 2024 , Pages 1505-1520 ; 24732400 (ISSN) Rezaei, O ; Masjedi, M ; Mahdi Naghsh, M ; Gazor, S ; Mahdi Nayebi, M ; Sharif University of Technology

2024

Abstract

This paper investigates a multi-cluster Wireless Powered Communication Network (WPCN) where user clusters cooperate with a Cluster Head (CH) and a Hybrid Access Point (HAP). Employing beamforming, the HAP supplies energy in the downlink phase, while users transmit signals to the HAP and CHs in the uplink phase. We optimize the Energy Beamforming (EB) matrix, user transmit covariance matrices, and time slot allocation to enhance both max-min and sum network throughput. To tackle the non-convexity of the optimization problems, we decompose them into two subproblems and reformulate each as convex Second Order Cone Programming (SOCP) and Quadratic Constraint Quadratic Programming (QCQP) for the...

Forecasting the effects of a Canada-US currency union on output and prices: A counterfactual analysis

, Article Journal of Forecasting ; Volume 32, Issue 7 , 2013 , Pages 639-653 ; 02776693 (ISSN) Mahdi Barakchian, S ; Sharif University of Technology

2013

Abstract

This paper is a counterfactual analysis investigating the consequences of the formation of a currency union for Canada and the USA: whether outputs increase and prices decrease if these countries form a currency union. We use a two-country cointegrated model to conduct the counterfactual analysis, where the conditional forecasts are generated based on the Gaussian assumption. To deal with structural breaks and model uncertainty, conditional forecasts are generated from different models/estimation windows and the model-averaging technique is used to combine the forecasts. We also examine the robustness of our results to parameter uncertainty using the wild bootstrap method. The results show...

Evaluation of Non-linear Combination Method (Neural Network) For Value-at-Risk Forecasting in Market

, M.Sc. Thesis Sharif University of Technology Rashnavadi, Leila (Author) ; Barakchian, Mahdi (Supervisor)

Abstract

Value at risk of an asset, is the asset’s expected maximum loss for a certain period of time and at a specified confidence level. Value-at-Risk can be calculated in the bank with its inter-nal method or standardized method. when a method have more violation number then bank need to keep more daily capital requirements. under the Basel 2 agreement if the violation of method more than 10 times in year, the Bank uses the standardized method.
There are trade off Between daily capital charge and violations. Therefore, existing methods for calculating the value at risk, usually lead to much daily capital charge or many violations. Studies show with combination of different methods to calculate...

Using Complex Network Metrics for Evaluating the Influence of Conference and Journal Papers in Computer Science

, M.Sc. Thesis Sharif University of Technology Habibi, Fatemeh (Author) ; Jalili, Mahdi (Supervisor)

Abstract

Journals and conferences in computer science are the major venue for publishing new achievement in the field. It is an expert opinion that a number of top conferences in computer science are even more important than journals. In this work we aim at studying this in terms of citation analysis. To this end, we took 100 top journals and 63 top conferences and extracted their citation graph through Scopus dataset. We then constructed the citation graph in which the nodes were the journals and conferences and the links corresponded to the citations of the papers. We used various measures to rank the nodes in the graph. The ranking methods included Prestige, PageRank, Eigenfactor, HITS and SALSA....

Design and Implementation of a VLSI Architecture for Time and Frequency Synchronization in the LTE

, M.Sc. Thesis Sharif University of Technology Golnari, Amene (Author) ; Shabany, Mahdi (Supervisor)

Abstract

The long term evolution (LTE) standard is introduced and developed by the 3rd generation partnership project (3GPP) based on orthogonal frequency division multiplexing (OFDM). OFDM systems, in spite of having many advantages such high performance in bandwidth usage, are very sensitive to inter carrier interference (ICI) as a drawback. In order to prevent ICI, the frequency offset, mainly caused by the miss-match between oscillators' frequency and also between the sampling frequency of the transmitter and the receiver, should be estimated and compensated. Frequency synchronization is a part of the tasks of a synchronizer. In this thesis, main tasks of a synchronizer are illustrated and...

A New Approach in Value-at-Risk (VaR) Estimation by Forecast Combination Methods

, M.Sc. Thesis Sharif University of Technology Seraj, Mostafa (Author) ; Barakchian, Mahdi (Supervisor)

Abstract

Value-at-Risk (VaR) is the most commontool for risk management. This tool is used to measure market risk and also used as a basis in determining financial standards for international financial institutions. VaR is the maximum loss of the asset portfolio at the specified confidence level and certain time horizon. Many parametric, nonparametric and semi parametric methods have been invented for VaR estimation. Each one of these methods has its advantages and disadvantages and different methods may perform better in differnet situations.When estimating VaR, we can choose one of these methods or we can combine the VaRs estimated by different methods. There are few researches conducted on VaR...

EEG Brain Functional Network Analysis in Cortex Level

, M.Sc. Thesis Sharif University of Technology Pedrood, Bahman (Author) ; Jalili, Mahdi (Supervisor)

Abstract

Complex networks science have received tremendous attention in recent years and the brain is one of the systems to which graph theoretical tools have been applied. Alzheimer’s disease (AD) is a neurodegenerative disease affecting many of elderly population. AD changes the anatomy of the brain, which subsequently results in changes in its functions. These changes have been frequently reported in signals recorded from the brain (such as MEG, fMRI and EEG). Among these neuroimaging techniques EEG is one of the most aproprate methods for extracting functional connectivites according to high temporal resolution. In this thesis, we aimed at analyzing the properties of EEG-based functional networks...

Learning Improvement in Phase Oscillator Models

, M.Sc. Thesis Sharif University of Technology Aghighi, Meysam (Author) ; Jalili, Mahdi (Supervisor)

Abstract

In the recent years, the problem of modeling a cognitive task using phase oscillators has been receiving a significant attention. In this view, single neurons are no longer elementary computational units. Rather, coherent oscillating groups of neurons are seen as nodes of networks performing cognitive tasks. From this assumption, we develop a model of stimulus-response learning and recognition. The most significant part of our work is defining learning methods for natural frequencies and coupling weights in a coupled phase oscillator network under Kuramoto conditions. In this thesis, we improved the previous models by not only emphasizing on the frequency of the oscillators but also taking...

Evaluation of Caviar Models Incorporated with Intraday Information ,the Case Study:Estimation Value at Risk of Gold

, M.Sc. Thesis Sharif University of Technology Karimi, Parvane (Author) ; Barakchian, Mahdi (Supervisor)

Abstract

Value at risk (VaR) is the maximum loss of the asset portfolio at the specified confidence level and certain time horizon. This tool is used to measure market risk and also used as a basis in determining financial standards for international financial instituation. Conditional Autoregressive Value at Risk models or CAViaR models introduced by Engle and Manganelli (2004). This models calculate VaR base on quantile regession approach and show some promising performance properties.
In order to propose a more accurate model for calcutating VaR , we develop CAViaR models by incorporating them with intraday information then we calculate VaR with this kind of models and CAViaR...

Design and Implementation of a Spectrum Sensor for Cognitive Radio

, M.Sc. Thesis Sharif University of Technology Safavi, Mahya (Author) ; Shabani, Mahdi (Supervisor)

Abstract

Frequency scarcity has emerged the necessity of opportunistic utilization of frequency bands, which can be realized through a cognitive radio system. During an agile communication between unlicensed users, a cognitive radio system must avoid collision with licensed users. Hence it should continuously observe the band of interest and report the presence of licensed user signals. This task is fulfilled by a vital part of a cognitive radio system, called the spectrum sensing core. Recently several techniques have been proposed for the spectrum sensing in literature. Some of them like matched filtering, cyclostationarity based detection are based on primary user signal features. However energy...