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hassanzadeh-yazdi--nafiseh
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Research and Development Project Portfolio Selection
, Ph.D. Dissertation Sharif University of Technology ; Modarres Yazdi, Mohammad (Supervisor)
Abstract
Today, Research and Development (R&D) plays an underlying role in all technology-based companies. It is the R&D that creates competitive advantage and determines survival or growth of a company in the fierce market place. R&D, On the other hand, consumes invaluable resources such as capital, human resource, and laboratories which are generally very scarce. This implies that R&D decisions must be treated as huge investment decisions which are made within the strategic framework of a business. The purpose of R&D portfolio selection is to select a set of projects from a pool of candidate projects in order to maximize some financial measures subject to resource availability and technical...
Synthesis of Electrode Materials for Rechargeable Batteries using Nanostructured Composites
, Ph.D. Dissertation Sharif University of Technology ; Sadrnezhad, Khatiboleslam (Supervisor)
Abstract
Sodium-ion batteries are cost-effective rechargeable batteries which have attracted considerable interest in recent years due to the low cost and abundance of sodium resources on the earth. Na3MnCO3PO4 (NMCP) has been identified as a potential cathode material with a high theoretical capacity of 191 mAh g-1. In order to improve the conductivity and electrochemical properties of NMCP, fabrication of NMCP/reduced graphene oxide (rGO) composite is a novel and interesting research goal. Therefore, in the current study, rGO was produced by using modified Hummers method. Then, the kinetics of NMCP formation through hydrothermal process was investigated. Results indicate that the optimum...
Robust Optimization of Portfolio with Stock Options
, M.Sc. Thesis Sharif University of Technology ; Modarres Yazdi, Mohammad (Supervisor)
Abstract
In this thesis, we apply robust optimization to analyze the uncertainty of model parameters of a portfolio optimization which contains stock options. We also develop two robust counterpart models for single period and multiperiod problems. By assuming that the probability distribution of parameters is not known, their uncertainty is considered to lie within known linear intervals. Due to the existence of nonlinear relations (piecewise linear) between uncertain data (stock and option price), we present an over-conservative robust model to make the solution feasible for all parameters. However in the second model by adopting a different approach we develop a robust counterpart model with...
A Promotion Optimization Model in Retail Markets using Machine Learning Approach
, M.Sc. Thesis Sharif University of Technology ; Sedghi, Nafiseh (Supervisor)
Abstract
Determining a promotion planning is a critical decision for retail managers. This plan should decide on the amount and duration of promotions for each product in a way that maximizes profit compared to a non-promotion scenario. In this study, the promotion optimization problem in a retail environment is formulated as a non-linear integer programming problem. The objective function is to maximize profit from product sales during the sales period. The problem also includes several business-related constraints that limit the number of promotions. In this study, a reinforcement learning approach, specifically Deep Q-Network, has been used to solve the mathematical model. The implementation...
Two-Period Pricing and Sales Channels Selection with Fairness Concern
, M.Sc. Thesis Sharif University of Technology ; Sedghi, Nafiseh (Supervisor)
Abstract
Pricing and revenue management are among the most important decisions for any economic enterprise. Several factors can influence decisions in this area and change the company’s pricing strategy, including uncertainties in product demand and customer preferences. This factor becomes particularly significant when the product is newly launched. Therefore, over time, customer preferences and willingness to pay may increase through various advertisements such as customer reviews and word-of-mouth. With rising demand, the seller has the opportunity to raise prices in the next periods. However, price increases can lead to unfair pricing perceptions by customers, hence reducing their purchasing...
Multi-tariff Pricing of Internet Plans Considering Customer Choice Models
, M.Sc. Thesis Sharif University of Technology ; Sedghi, Nafiseh (Supervisor)
Abstract
One of the important factors that are effective in the continuation of businesses is their profitability. Pricing, as an important component of the business process, greatly impacts profitability. Therefore, by using a suitable pricing method, retailers and service providers can increase their profits and avoid issues such as inventory congestion, imposed discounts, or lost sales opportunities. In this research, the two-tariff pricing system in internet services is investigated and determined by taking into account the randomness of customer consumption. The problem includes a set of Internet sales plans, each plan has a fixed price for a certain amount of data and a variable price for...
A multi-dimensional fairness combinatorial double-sided auction model in cloud environment
, Article 2016 8th International Symposium on Telecommunications, IST 2016, 27 September 2016 through 29 September 2016 ; 2017 , Pages 672-677 ; 9781509034345 (ISBN) ; Movaghar, A ; Hassanzadeh, H. R ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2017
Abstract
In cloud investment markets, consumers are looking for the lowest cost and a desirable fairness while providers are looking for strategies to achieve the highest possible profit and return. Most existing models for auction-based resource allocation in cloud environments only consider the overall profit increase and ignore the profit of each participant individually or the difference between the rich and the poor participants. This paper proposes a multi-dimensional fairness combinatorial double auction (MDFCDA) model which strikes a balance between the revenue and the fairness among participants. We solve a winner determination problem (WDP) through integer programming which incorporates the...
Hydrogen desorption properties of MgH 2–TiCr 1.2 Fe 0.6 nanocomposite prepared by high-energy mechanical alloying [electronic resource]
, Article Journal of Power Sources ; 2011, Vol. 196, No.10, P.4604-4608 ; Kaflou, A ; Simchi, A. (Abdolreza) ; Sharif University of Technology
Abstract
In the present work, high-energy mechanical alloying (MA) was employed to synthesize a nanostructured magnesium-based composite for hydrogen storage. The preparation of the composite material with composition of MgH2–5at% (TiCr1.2Fe0.6) was performed by co-milling of commercial available MgH2 powder with the body-centered cubic (bcc) alloy either in the form of Ti–Cr–Fe powder mixture with the proper mass fraction (sample A) or prealloyed TiCr1.2Fe0.6 powder (sample B). The prealloyed powder with an average crystallite size of 14nm and particle size of 384nm was prepared by the mechanical alloying process. It is shown that the addition of the Ti-based bcc alloy to magnesium hydride yields a...
Pricing of Infrastructure as a Service in Cloud Computing
, M.Sc. Thesis Sharif University of Technology ; Sedghi, Nafiseh (Supervisor)
Abstract
The growing demand for scalable and cost-effective computing resources has led to the widespread adoption of the Infrastructure as a Service (IaaS) model in cloud computing. One of the pricing models for resources, or virtual machines, in this service is the Spot model, which allows customers to access unused cloud server capacity at significantly lower costs compared to other models. However, despite their affordability, these virtual machines do not come with a Service Level Agreement (SLA) and may experience interruptions during use. Such interruptions increase the time required for customers to complete their tasks. In this study, we utilize discrete-event system simulations to examine...
Data-Driven Pricing Based on Demand Prediction Using Machine Learning Methods
, M.Sc. Thesis Sharif University of Technology ; Sedghi, Nafiseh (Supervisor)
Abstract
Pricing plays an important and essential role in the profit and income of companies. The importance of pricing is not only related to its role in the company's profitability, but it also changes the customer's understanding and loyalty towards the company and can create the company's reputation or destroy it. Determining the right price will increase product sales and increase customer loyalty and create a competitive advantage for the company. One of the most important and influential variables in product pricing is the amount of demand. The main challenge of companies for product pricing is the uncertainty in their demand. In order to deal with this problem, data-driven pricing is used....
Using Machine Learning Approaches for Persian Pronoun Resolution
, M.Sc. Thesis Sharif University of Technology ; Ghasem Sani, Gholamreza (Supervisor)
Abstract
Coreference resolution is an essential step toward understanding discourses, and it is needed by many NLP tasks such as summarization, machine translation, question answering, etc. Pronoun resolution is a major and challenging subpart of coreference resolution, in which only the resolution of pronouns is considered. The existing coreference resolution approaches can be classified into two broad categories: linguistic and machine learning approaches. Linguistic approaches need a lot of linguistic information for the resolution process. Acquisition of such information is an error- prone and time-consuming process. In contrast, learning approaches need less linguistic information and provide...
Link Prediction using Dynamic Graph Neural Network with Application to Call Data
, M.Sc. Thesis Sharif University of Technology ; Jafari Siavoshani, Mahdi (Supervisor)
Abstract
In network science, link prediction is one of the essential tasks that has been neglected. One important application of link prediction in telecommunication networks is analyzing the user's consumption pattern to provide better service. This project aims to predict future links with applications to call data using the users' call history. In previous research, there are two main approaches: 1) heuristic-based approach, and 2) deep-learning-based approach, such as graph neural networks. These methods are mainly used for processing static graphs, and therefore, we cannot generalize them to dynamic graphs. But there are many graphs which are dynamic in nature. For instance, call data records...
Synthesis, Characterization and Application of Porous Bioactive Glasses-Based Nanostructures in Bone Tissue Engineering
, Ph.D. Dissertation Sharif University of Technology ; Bagherzadeh, Mojtaba (Supervisor) ; Baheiraei, Nafiseh (Co-Supervisor)
Abstract
In the upcoming research, with the aim of bone tissue engineering and achieving a new structure, a scaffold based on polyhema (PHEMA) and gelatin (Gel), which are biocompatible polymers for bone tissue, was made and evaluated. Also, in order to improve the bioactivity and mechanical properties, bioactive glass alone (BG45S5) or together with strontium (BG-Sr) was used in the scaffold structure. and chemical by conducting FTIR, XRD, SEM, mechanical strength, bioactivity measurement, contact angle, water absorption and degradation tests. Biological investigations were done using mesenchymal stem cells derived from human bone marrow and with the help of MTT evaluations and SEM photography. The...
Magnetic stirring assisted hydrothermal synthesis of Na3MnCO3PO4 cathode material for sodium-ion battery
, Article Ceramics International ; Volume 47, Issue 19 , 2021 , Pages 26929-26934 ; 02728842 (ISSN) ; Sadrnezhaad, S.K ; Sharif University of Technology
Elsevier Ltd
2021
Abstract
Na3MnCO3PO4 (NMCP) is considered one of the promising cathode materials for sodium-ion batteries due to its high theoretical capacity. The hydrothermal method is an efficient, environmental-friendly, and simple route with low instrument cost to prepare active cathode materials such as NMCP. In this research, magnetic stirring was applied to promote the hydrothermal synthesis, and NMCP was produced by controlling different stirring times. This method results in the formation of pure NMCP upon only 45 min processing time. According to the ICP results, the Na to Mn ratio in the NMCP approached the stoichiometric value of 3 by prolonging the stirring time. By analyzing the charge-discharge...
Implementing an automated feedback program for a foreign language writing course: A learner-centric study
, Article Journal of Computer Assisted Learning ; Volume 37, Issue 5 , 2021 , Pages 1494-1507 ; 02664909 (ISSN) ; Fotoohnejad, S ; Sharif University of Technology
John Wiley and Sons Inc
2021
Abstract
Considering the prominence attached to written corrective feedback (WCF) within the domain of second/foreign language (L2) acquisition, automated writing evaluation (AWE) tools have steadily gained ground over the last two decades. The current study was an attempt to investigate the extent incorporating an AWE program, known as Criterion®, within a process writing framework would affect learners' writing quality in an English as a foreign language context. Moreover, we drew a comparison between the overall effects of computer- versus teacher-generated WCF. Participants consisted of 53 tertiary level students from two intact essay-writing classes. The within-group findings revealed that the...
A mixed methods approach to exploring grammar learning strategies in self-regulation task phases: Evidence from grounded theory and regression analysis
, Article Language Teaching Research ; 2022 ; 13621688 (ISSN) ; Ranjbar, M ; Sharif University of Technology
SAGE Publications Ltd
2022
Abstract
While research into various dimensions of language learning strategies has been thriving over the recent years, grammar learning strategies (GLS) have largely remained under-explored. The present mixed methods research aimed to explore GLS in the three stages of classroom grammar tasks, while striving to determine the sequence of GLS and their contribution to grammar proficiency. In the qualitative phase, 13 participants partook in stimulated recall and semi-structured interviews after completing consciousness-raising (CR) tasks. Then, the grounded theory (GT) methodology was applied to conceptualize a theoretical model. For the quantitative phase, a modified version of Pawlak’s Grammar...
A Thesis Submitted in Partial Fulfilment of the Requirements for the Degree of Master of Arts in Teaching English as a Foreign Language
, M.Sc. Thesis Sharif University of Technology ; Alemi, Minoo (Supervisor) ; Meghdari, Ali (Co-Advisor)
Abstract
Although Robot Assisted Language Learning (RALL) has recently received attention as a tool for language learning, its role in pragmatic development has gone unnoticed. Hence, this study sought to explore the effect of RALL on pragmatic learning of greeting, thanking, and request speech acts by young Persian-speaking EFL learners. To this end, 38 preschool female and male kids (3-6 years old) were assigned to the RALL (19 students) and game-based (19 students) groups. The humanoid robot for the RALL group was used as an assistant to the teacher while for the game-based group the instruction was based on gaming methods such as command, mystery bag and pass the ball games. The instructional...
Analytical Nonlinear Solution of a Structurally Integrated Piezoelectric Trapizoidal Tapered Beam for Energy Harvesting
, M.Sc. Thesis Sharif University of Technology ; Hosseini Kordkheili, Ali (Supervisor)
Abstract
Tapering the beam along its length may lead to an increase in the voltage density of piezoelectric energy harvester. In this study, the energy harvester voltage with linear variable cross section is studied by developing an analytical method in both linear and nonlinear states. In linear mode, the results are compared with the experimental results. For the development of linear and nonlinear analytic relations, the Euler–Bernoulli beam and linear voltage variations in the thickness direction are used, and for the separation of variables, the mass normalized mode shapes has been used. The results of the linear analytical method are compared with the results of past research and experimental...
Coupling of ANISN & MCNP Computer Codes for Neutron Importance Calculation
, M.Sc. Thesis Sharif University of Technology ; Vosoughi, Naser (Supervisor)
Abstract
For many reasons the Montecarlo method is chosen for investigation of problems like shielding. Nowadays, superiority of utilizing the codes based upon Montecarlo methods such as using cross sections with continuous energy or using exact models of complex geometries, is obvious for everyone. But obtaining results with least possible variance is extremely important. variance reduction methods usedfor achieving exact results with less calculating time. Up to now in the MCNP codes, many methods have been utilized for reducing the variance. One of the methods which have recently attracted attentions is using the importance function. For obtaining importance function we need to solve the...
Improving the Stability of an Urban Traffic Network with Limited Data by Using Percolation Theory and Dynamic Clustering
, M.Sc. Thesis Sharif University of Technology ; Amini, Zahra (Supervisor)
Abstract
One of the most vital aspects of understanding the traffic phenomenon is scrutinizing the traffic transition status, such as the transition from free flow to congestion. The Percolation Theory is a renowned theory focusing on analyzing various network types to detect the critical zones, which are the zones including links that are important to control to improve stability. By calculating the quality indices of network links, the Percolation Theory can simulate the traffic percolation propagation in the network and determine possible critical zones for further analysis. Most studies in this field assume access to data of several traffic parameters for the entire transportation network, such...