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Interference Coexisting SAR Imaging: A Joint Sparse Recovery and Waveform Design Method
, Article IEEE Transactions on Aerospace and Electronic Systems ; Volume 59, Issue 6 , 2023 , Pages 8455-8465 ; 00189251 (ISSN) ; Karbasi, M ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2023
Abstract
In this article, we design a compatible waveform for the purpose of high-quality synthetic aperture radar (SAR) imaging in conjunction with sparse recovery methods for image formation. Namely, we consider minimizing the mutual interference between our radar and coexisting licensed emitters and also minimizing the jamming signal power while enforcing some constraints over the waveform features, such as peak-to-average-power ratio. We introduce a new constraint to our proposed optimization problem and show its effectiveness. By nulling some frequency bands in the optimized waveform due to the interference sources (licensed or unlicensed), our sampled data in the frequency domain, which makes...
Effect of Principal Stresses Direction, Anisotropic Consolidation and Silt Content on the Behavior of Silty Sands by using Hollow Cylinder Apparatus
, Ph.D. Dissertation Sharif University of Technology ; Haeri, Mohsen (Supervisor)
Abstract
In this research, the effect of various parameters on the behavior of silty sands is evaluated under special loading conditions. To evaluate these parameters, the hollow cylinder apparatus of the Advanced soil mechanics at Sharif University is used. In this research the effect of principal stress directions, initial anisotropic consolidation, silt content, effective mean normal consolidation stress and intermediate principal stress are studied on the behavior of silty sands including the strength and pore water pressure. In order to evaluate these parameters, the specimens are made with wet tamping method with 0, 10, 20, 30 and 40 percent of silt. Before applying shear load to specimen, the...
Waveform Design for Interference Mitigation in SAR Imaging and Sparse Image Recovery
, M.Sc. Thesis Sharif University of Technology ; Karbasi, Mohammad (Supervisor)
Abstract
In this research, we design a compatible waveform for the purpose of high-quality synthetic aperture radar (SAR) imaging in conjunction with sparse recovery methods for image formation. The goal is to make the imaging system tolerable against the wide-band and narrowband electromagnetic interferences. Actually, we consider minimizing the mutual interference between our radar and coexisting licensed emitters and minimizing the jamming signal (unlicensed emitters) power while enforcing some constraints over the waveform features like peak-to-average-power ratio (PAPR). For the constrained optimization problem to design a proper waveform, we introduce a new constraint to the optimization...
Evaluation of the effect of anisotropic consolidation and principle stress rotation on undrained behavior of silty sands
, Article Scientia Iranica ; Volume 20, Issue 6 , 2013 , Pages 1637-1653 ; 10263098 (ISSN) ; Haeri, S. M ; Sharif University of Technology
Sharif University of Technology
2013
Abstract
The dependence of undrained behavior of silty sand on initial state of stress and direction of principal stresses with respect to vertical (ff) is assessed under generalized loading paths using hollow cylinder apparatus. During applying shear load, value of intermediate principal stress parameter (b) is held constant and ff value is increased from zero to the aimed value and held constant. Specimens are consolidated, both, isotropically and anisotropically to evaluate the effect anisotropic consolidation on the behavior of these soils. The wet tamping method was selected to prepare specimen. Shear loading was carried out under strain-controlled condition to capture post-peak strain-softening...
Stability and Traveling Waves of a Stage–structured (Predator-rey)Model with Holing Type-II Functional Response and Harvesting
, M.Sc. Thesis Sharif University of Technology ; Hesaaraki, Mahmoud (Supervisor)
Abstract
IN this upper ,we consider a reaction –diffusion predator-prey model with stage –structure, holling type –ll functional response. Nonlocal spatial impacat and harvesting The stability of the equilibria is investigated. Furthermore, by the cross-iteration schauder fixed point theorem, we deduce the existence of traveling wave solution which connects the zero solution and the positive constant eguilibrium
A Process Mining Approach to Analyze Customer Journeys to Improve Customer Experience
, M.Sc. Thesis Sharif University of Technology ; Hassannayebi, Erfan (Supervisor)
Abstract
With the growth of the number of online service providers and the need to innovate in these services, in this study, the processes and the journeys taken by visitors of a website that provides employment services and employment insurance has been analyzed. In this research, process mining techniques and predictive process monitoring were implemented. With the use of a supervised and unsupervised learning algorithm, it attempted to identify the customer journeys' output and the existing patterns that lead to the complaint. In the first step, the website event log is extracted. Afterward, by using frequency-based encoding methods, the journeys traveled by users were clustered based on the...
Predictive Business Process Monitoring Using Machine Learning Algorithms
, M.Sc. Thesis Sharif University of Technology ; Hassannayebi, Erfan (Supervisor)
Abstract
In order to survive in today's business world, which is changing at a very fast pace, organizations can detect deviations even before they occur, quickly and with a high percentage of confidence, by analyzing their processes, in order to prevent disruptions in the processes. by monitoring the information systems that automatically execute business processes, it is possible to ensure the correct implementation of the existing processes. For this purpose, various techniques for monitoring business processes have been presented so that managers have a comprehensive and real view of how implement processes and be able to identify possible deviations in the future and try to fix them because the...
Data-Driven Prediction for Monitoring Business Process Pperformances Based on Classification Algorithms
, M.Sc. Thesis Sharif University of Technology ; Hassannayebi, Erfan (Supervisor)
Abstract
In recent years, several studies have been conducted in the field of data mining techniques in the field of process mining with the aim of improving the performance of organizations. Predictive process monitoring is a data-driven approach that helps business managers to improve the status and conditions of their organization. In this approach, the event log, which includes a set of completed examples of a process, is received as input, and machine learning methods are used to predict the outcome and results of the organization's processes before the process is completed. This prediction can include the prediction of the final result, the next event, the time remaining until the completion of...
Operations Optimization in Supply Chain Systems using Simulation and Reinforcement Learning
, M.Sc. Thesis Sharif University of Technology ; Hassan Nayebi, Erfan (Supervisor)
Abstract
The inventory costs constitute a significant portion of the supply chain costs. Therefore, choosing an optimal inventory policy for orders is of great importance. The aim of this research is to find the optimal inventory policy for a distribution center in a three-tier supply chain consisting of a manufacturer, a distribution center, and a retailer. This research simulates a supply chain in agent-based framework and optimizes it using reinforcement learning. The optimization KPI in this research is the mean daily cost of the supply chain. Finally, the result obtained from reinforcement learning is compared with the optimized result of AnyLogic and the mean daily cost in the model optimized...
Predictive Process Monitoring Based on Optimized Deep Learning Methods
, M.Sc. Thesis Sharif University of Technology ; Hassannayebi, Erfan (Supervisor)
Abstract
Business processes are an essential part of every business as they provide insights on how to optimize and make them more efficient. Predictive Business Process Monitoring has garnered significant attention in recent years due to its capability to forecast process outcomes and predict the next activity within an ongoing process. In the last few years, there have been works that focused on deep learning and its applications in predicting the next activity. Some research used Long Term Short Memory, while others used Convolutional Neural Networks. However, long term short term memory models have the constraint of relatively slow training, while Convolutional Neural Networks are fast but may...
A novel torque hysteresis comparator for torque and current ripple reduction of direct torque control of induction machine
, Article 9th IEEE International Power Electronics Congress, CIEP 2004, Celaya, Gto, 17 October 2004 through 22 October 2004 ; 2004 , Pages 140-145 ; Zolghadri, M. R ; Haghbin, S ; Sharif University of Technology
2004
Abstract
The notable effeets of time delay aid time discretization on the torque and current ripple amplitude of the direct torque controlled induction motor scheme are investigated. A simply modified torque hysteresis comparator structure is proposed. It minimizes the undesirable effects of the time delay and time discretization on the torque ripple and allows a sensible reduction of torque and current ripple amplitudes and switching frequency in the whole rotor speed range. Numerical simulations and experimental tests have been carried out to validate the proposed torque comparator effect. © 2004 IEEE
An extended and improved discrete space vector modulation direct torque control for induction motors
, Article 2004 IEEE 35th Annual Power Electronics Specialists Conference, PESC04, Aachen, 20 June 2004 through 25 June 2004 ; Volume 5 , 2004 , Pages 3414-3420 ; 02759306 (ISSN); 0780383990 (ISBN) ; Zolghadri, M. R ; Homaifar, A ; Sharif University of Technology
2004
Abstract
In the classical DTC scheme, due to the limited number of the VSI voltage vectors, large and small errors can not be distinguished. In fact, the switching vectors chosen for large errors are the same as those chosen for small errors. In this paper, in order to overcome this problem, after considering the primary ideas of the DSVM-DTC technique, a new approach for the realization of the DSVM-DTC methodology of the induction machine is proposed. The proposed method, along with its simplicity, has an improved performance in terms of the torque and the current ripple and can be easily extended. In addition, it minimizes the steady state torque error. By using the proposed DSVM-DTC methodology,...
Customer Journey Analytics using Process Mining Based on the Markov Model
,
M.Sc. Thesis
Sharif University of Technology
;
Hassan Nayebi, Erfan
(Supervisor)
Abstract
The analysis of customer journeys has gained significant attention due to the critical role of customer behavior data in enhancing business decision-making and formulating strategies for customer acquisition and retention. By segmenting customers based on their journey patterns, businesses can offer personalized recommendations, thereby improving customer engagement and loyalty. Additionally, predicting the next steps in a customer’s journey based on historical data allows for timely and appropriate interventions at various touchpoints. By understanding where customers are in their journey, businesses can provide targeted recommendations that increase the likelihood of converting potential...
A System Dynamic Simulation Approach to Investigate Economic And Environment Factors Based on VUCA framework: A Case Study in Petrochemical Industry
, M.Sc. Thesis Sharif University of Technology ; Hassannayebi, Erfan (Supervisor)
Abstract
To maintain adaptability, businesses should anticipate changes in their environment. The commonly employed forecasting method within corporate circles is the bottom-up approach, which relies on historical data for projecting future trends. However, research suggests that this approach often falls short of accurately reflecting real-world events. This has led to the adoption of dynamic systems modeling, a technique grounded in the assumption of stable conditions. This method effectively replicates the system's current state, thereby assisting in predicting future behaviors over a longer timeframe. The dynamic systems modeling approach was employed in this study, underscoring the imperative...
Discovering and Improving the Processes of an Iranian Psychiatric Hospital Using Process Mining
, M.Sc. Thesis Sharif University of Technology ; Hassan Nayebi, Erfan (Supervisor)
Abstract
Providing quality hospital services depends on the efficient and correct implementation of processes. Therapeutic care processes are a set of activities that are carried out with the aim of diagnosing, treating and preventing any disease in order to improve and promote the patient's health. The purpose of this study is to use process mining techniques to discover and improve healthcare processes. The case study of this research is a psychiatric hospital in Shiraz. The approach implemented in this research consists of three main stages including data pre-processing, model discovery phase, and analysis phase. Three algorithms including Heuristic Miner, Inductive Miner, and ILP Miner were used...
Optimization of Foreign Exchange (Forex) Trading Using Machine Learning Methods
, M.Sc. Thesis Sharif University of Technology ; Hassan Nayebi, Erfan (Supervisor)
Abstract
The foreign exchange market, commonly known as Forex, is one of the largest and most significant financial markets in the world, attracting the attention of numerous investors on a daily basis. One of the main challenges faced by traders in this market is the accurate prediction of currency prices. Although Forex market forecasting is highly popular, the inherent complexity of this market continues to make accurate prediction a persistent concern. In recent decades, remarkable advancements have occurred in the field of machine learning, particularly in deep learning. These developments have also influenced the Forex market, resulting in the publication of numerous research articles aimed at...
The investigation of natural super-cavitation flow behind three-dimensional cavitators: Full cavitation model
, Article Applied Mathematical Modelling ; Volume 45 , 2016 , Pages 165-178 ; 0307904X (ISSN) ; Kadivar, Erfan ; Javadi, K ; Javadpour, S. M ; Sharif University of Technology
Elsevier Inc
2016
Abstract
In this study, natural super-cavitating flow around three different conical cavitators with wedge angles of 30°, 45° and 60° is investigated. We apply the k−ϵ turbulence model and the volume of fluid (VOF) technique to numerically study the three-dimensional cavitating flow around the cavitators. The turbulence approach is coupled with a mass transfer model which is implemented into the finite-volume package. Simulations are performed for different cavitation numbers. Finally, the effects of some important parameters such as the cavitation index, inlet velocity, Froude number and wedge angle of cavitators on the geometrical characteristics of the super-cavities are discussed. Our numerical...
Analysis and Improvement of Agile Software Development Process Using Process Mining and Machine Learning Algorithms
, M.Sc. Thesis Sharif University of Technology ; Hassan Nayebi, Erfan (Supervisor)
Abstract
In the competitive world of software development, IT product development teams face numerous challenges and issues within business processes. In recent years, the combination of process mining and machine learning algorithms to optimize software development processes has gained attention. However, there is still a lack of a comprehensive model for identifying and conducting root-cause analysis of problems and providing solutions based on them in agile software development systems. The aim of this research is to find a solution for identifying and addressing issues in the software development process by modifying the change request workflow and examining various aspects of incidents. To...
Improve Performance of Process Mining Algorithms in Low-Level Event Log with Machine Learning Methods
, M.Sc. Thesis Sharif University of Technology ; Hassan Nayebi, Erfan (Supervisor)
Abstract
This thesis abstract addresses the use of process mining techniques when event data is stored at varying levels of granularity. While most techniques assume that events have the same level of granularity, real data is often stored differently. Pre-processing techniques allow for appropriate summarization of the data, which simplifies the output while retaining important process details. The goal is to ensure an interpretable output for stakeholders and different business teams without losing critical process points. However, adding new data as a feature to the dataset can be expensive, and at times, infeasible. Therefore, existing data is the only solution. To overcome this challenge, this...
A new correlation on the MEXICO experiment using a 3D enhanced blade element momentum technique
, Article International Journal of Sustainable Energy ; Vol. 33, issue. 2 , 2014 , pp. 448-460 ; ISSN: 14786451 ; Jafari, A ; Schaffarczyk, A. P ; Keyhani, A ; Mahmoudi, J ; Sharif University of Technology
2014
Abstract
The blade element momentum (BEM) theory is based on the actuator disc (AD) model, which is probably the oldest analytical tool for analysing rotor performance. The BEM codes have very short processing times and high reliability. The problems of the analytical codes are well known to the researchers: the impossibility of describing inside the one-dimensional code the three-dimensional (3D) radial flows along the span-wise direction. In this work, the authors show how the 3D centrifugal pumping affects the BEM calculations of a wind turbine rotor. Actually to ascertain the accuracy of the analytical codes, the results are compared with rotor performance, blade loads and particle image...