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mohit--mohammad-erfan
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Control of Nonlinear Systems With Full State Constraints
, M.Sc. Thesis Sharif University of Technology ; Shahrokhi, Mohammad (Supervisor)
Abstract
Consideration of constraints on process variables is an essential part in controller design. In this project, controller design methods for systems with full state constraints were studied and advantages and disadvantages of these methods were described. A controller has been designed for a nonlinear strict-feedback system with unknown dynamics, unavailable states, time-varying asymmetric state constraints, input saturation and unknown control direction. The backsteppping method has been used to design the controller. With the aim of the surface error transformation technique, the problem of full state constraints has been solved. Dynamic surface control has been used to reduce the...
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...
Adaptive fixed-time consensus control for a class of non-strict feedback multi-agent systems subject to input nonlinearities, state constraints, unknown control directions, and actuator faults
, Article European Journal of Control ; Volume 66 , 2022 ; 09473580 (ISSN) ; Shahrokhi, M ; Sharif University of Technology
Elsevier Ltd
2022
Abstract
In this work, an adaptive fixed-time controller has been designed for a class of uncertain non-strict feedback multi-agent systems (MASs) subject to different types of input nonlinearities, time-varying asymmetric state constraints, unknown control directions, infinite number of actuator faults and external disturbances. Compared to the existing consensus control schemes, the proposed controller can handle input nonlinearities, actuator faults and unknown control directions simultaneously, while guaranteeing fixed-time convergence of the consensus tracking error and satisfying state constraints for non-strict feedback MASs. By employing a nonlinear mapping, the constrained MAS has been...
Analysis of Effective Factors of Second Job Selection in Iranian Labor Market
, M.Sc. Thesis Sharif University of Technology ; Keshavarz Haddad, Ghloalmreza (Supervisor)
Abstract
Working in second job is one the fact in labor market. based on the data of Statistical center of Iran. In Iran approximately 18 % of worker have second job. This trend fluctuate around 20%. That increase from 18% in 1372 into 19% in 1382. This research examines effective factor on secondary job market panel data from statistical surveys conducted by Statistics Centre of Iran from 1380 to 1382 .We apply three step Multiple selection method. Because of existence of censoring data & sample selection problem We use of probit method for panel data for modeling of existence in labor market and second job. Then we use of Tunali (1985) Method for estimate hours in second job. Result of research...
Adaptive finite-time neural control of non-strict feedback systems subject to output constraint, unknown control direction, and input nonlinearities
, Article Information Sciences ; Volume 520 , 2020 , Pages 271-291 ; Shahrokhi, M ; Mohit, M ; Sharif University of Technology
Elsevier Inc
2020
Abstract
This paper addresses the finite-time controller design for a class of nonlinear systems in the non-strict feedback form subject to unknown system dynamics and disturbances, arbitrary asymmetric time-varying output constraints, four types of input nonlinearities, and unknown control direction. Utilizing the barrier Lyapunov function (BLF) and backstepping technique, an adaptive finite-time controller has been proposed. The difficulties associating with non-strict feedback systems have been handled using the variable separation approach. Furthermore, the unknown control direction problem has been tackled by using the Nussbaum gain function. A unified framework has been utilized for handling...
Observer-based controller for nonaffine time-delayed systems subject to input nonlinearities, state constraints, and unknown control direction
, Article International Journal of Adaptive Control and Signal Processing ; Volume 36, Issue 8 , 2022 , Pages 2122-2149 ; 08906327 (ISSN) ; Shahrokhi, M ; Kamalamiri, A ; Sharif University of Technology
John Wiley and Sons Ltd
2022
Abstract
In this work, an adaptive observer-based control scheme has been designed for uncertain nonaffine nonstrict feedback systems subject to state time delay, various types of input nonlinearities, time-varying asymmetric state constraints, and unknown control direction. Compared to the existing controllers for systems with state constraints, the designed control scheme in this work can be applied to state-constrained systems with nonaffine structure subject to state delays, unknown control direction, and different types of input nonlinearities, while full-states measurement is not required. Moreover, by introducing a novel saturated Nussbaum function in the present work, not only has the problem...
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...
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...
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...
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...
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...
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...
Robust Markov Decision Processes and Applications in Mathematical Finance
, M.Sc. Thesis Sharif University of Technology ; Fotouhi Firouzabadi, Morteza (Supervisor) ; Salavati, Erfan (Supervisor)
Abstract
Dynamic portfolio optimization is one of the prominent problems in financial mathematics, for which numerous theories have been proposed to solve it. One of the solutions to this problem is the use of reinforcement learning. The main challenge with this method is that most reinforcement learning algorithms require a large amount of data, and therefore, the necessary data is often obtained not from the real world, but through simulations by estimating the parameters of a model. However, the approximation error of the parameters can propagate through the final solution, leading to inaccurate results. One approach to addressing this issue is the use of robust Markov processes and robust...
Pemphigus vulgaris and infections: A retrospective study on 155 patients
, Article Autoimmune Diseases ; Volume 2013 , 2013 ; 20900430 (ISSN) ; Mortazavi, H ; Noormohammadpour, P ; Boreiri, M ; Soori, T ; Vasheghani Farahani, I ; Mohit, M ; Sharif University of Technology
2013
Abstract
Background. Autoimmune process and immunosuppressive therapy of pemphigus vulgaris would predispose the patients to infections. Aim. We aimed to study the prevalence of infection and pathogenic agents in pemphigus vulgaris patients admitted to dermatology service. Material and methods. This retrospective study was conducted on 155 pemphigus vulgaris patients (68 males, 87 females) admitted to dermatology service between 2009 and 2011. In this study, the diagnosis of pemphigus vulgaris was confirmed by light microscopic and direct immunofluorescence findings. Data were collected through a questionnaire. Results. Of 155 pemphigus vulgaris patients, 33 had infection at admission and 9 acquired...
Estimating Evaporation from Non-Agricultural Areas (Bare Soil and Range Land) in the Lake Urmia Basin
,
M.Sc. Thesis
Sharif University of Technology
;
Tajrishi, Masood
(Supervisor)
;
Jalilvand, Ehsan
(Co-Supervisor)
;
Haghighi, Erfan
(Co-Supervisor)
Abstract
Evaporation is one of the main parameters of the mass transfer from earth to the atmosphere, which annually transfers more than 65 billion cubic meters of water. Worldwide, evaporation consumes 25% of the energy input and plays a key role in restoring 60% of the precipitation to the atmosphere. Small changes in the water budget and evapotranspiration (ET) in arid and semi-arid areas can cause a large change in ecosystem health. Lake Urmia Basin has been taken into huge consideration due to steepest decline in lake level in the last three decades. Estimating evapotranspiration of this basin is important for the study of agricultural water consumption, hydrological modeling, water resources...
Geomechanical Analysis of Wellbore Instability in Kupal Oil Field
, M.Sc. Thesis Sharif University of Technology ; Khoei, Amir Reza (Co-Advisor) ; Erfan Nia, Ali (Co-Advisor) ; Shad, Saeed (Supervisor)
Abstract
The wellbore instability is one of the challenging problems in the oil industry, which entails huge costs for the industry every year. This phenomenon not only causes numerous problems in drilling and completion of wells, but also reduces production and loss of wells. In recent years, this problem has become much more serious in the Kupal oilfield. As a result, a large number of wells drilled in the field shortly after completion face with the problem of instability, integrity and casing collapse. According to the studies, one of the main causes of such a problem is the Gachsaran high pressure formation. Despite the complexity and importance of this issue, there is not a comprehensive study...
Synthesis and characterization of N- diethyl methyl chitosan
, Article Iranian Polymer Journal (English Edition) ; Volume 13, Issue 5 , 2004 , Pages 431-436+437 ; 10261265 (ISSN) ; Mahdavinia, G ; Sadeghi, A. M ; Erfan, M ; Amini, M ; Tehrani, M. R ; Shafiee, A ; Sharif University of Technology
2004
Abstract
Biodegradable polymers such as chitosan have been used extensively in biomedical fields in the form of sutures; wound dressing and as artificial skin. Colonic drug delivery for either local or systemic effects has been the subject of much research over the last decade. Chitosan exhibits poor solubility at pH values above 6 that prevent enhancing effects at sites of absorption of drugs. In the present work, N-diethyl methyl chitosan (DEMC) was prepared based on a modified two-step process via a 22 factorial design to optimize the preparative conditions. DEMC Polymer with different degrees of quaternization for pharmacological and pharmaceutical experiments was achieved. The reaction was...