Loading...
Search for: delfani--erfan
0.15 seconds

    Version age-optimal cached status updates in a gossiping network with energy harvesting sensor

    , Article Proceedings of the International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, WiOpt ; 2023 , Pages 143-150 ; 26903334 (ISSN); 978-390317655-3 (ISBN) Delfani, E ; Pappas, N ; Sharif University of Technology
    Institute of Electrical and Electronics Engineers Inc  2023
    Abstract
    In this work, we consider a real-time IoT monitoring system in which an energy harvesting sensor with a finite-size battery measures a physical process and transmits the status updates to an aggregator. The aggregator, equipped with caching capabilities, can serve the external requests of a destination network with either a stored update or a fresh update from the sensor. We assume that the destination network act as a gossiping network in which the update packets are forwarded among the nodes in a randomized setting. We utilize the Markov Decision Process framework to model and optimize the network’s average Version Age of Information (AoI) and obtain the optimal policy at the aggregator.... 

    Automatic Music Signal Classification Through Hierarchical Clustering

    , M.Sc. Thesis Sharif University of Technology Delfani, Erfan (Author) ; Ghaemmaghami, Shahrokh (Supervisor)
    Abstract
    The rapid increase in the size of digital multimedia data collections has resulted in wide availability of multimedia contents to the general users. Effective and efficient management of these collections is an important task that has become a focus in the research of multimedia signal processing and pattern recognition. In this thesis, we address the problem of automatic classification of music, as one of the main multimedia signals. In this context, music genres are crucial descriptors that are widely used to organize the large music collections. The two main components of automatic music genre classification systems are feature extraction and classification. While features are a compact... 

    An enhanced continuum modeling of the ideal strength and the angle of twist in tensile behavior of single-walled carbon nanotubes

    , Article Journal of Applied Physics ; Volume 114, Issue 5 , 2013 ; 00218979 (ISSN) Delfani, M. R ; Shodja, H. M ; Sharif University of Technology
    2013
    Abstract
    By utilizing the fourth-, sixth-, eighth-, and tenth-order elastic moduli tensors of graphene a highly nonlinear constitutive model for it is proposed. Subsequently, an accurate analytical formulation, describing the entire tensile behavior of single-walled carbon nanotubes (SWCNTs) from their initial unloaded states through their ideal strengths, is made possible. The angle of twist which is a critical parameter that varies with the tensile loading is also calculated within the current framework. The estimated value of the theoretical strength of SWCNTs with different chiralities and radii as well as that of graphene ranges from 0.39 to 0.44 TPa. Some peculiarities associated with chirality... 

    An exact analysis for the hoop elasticity and pressure-induced twist of CNT-nanovessels and CNT-nanopipes

    , Article Mechanics of Materials ; Volume 82 , 2015 , Pages 47-62A ; 01676636 (ISSN) Delfani, M. R ; Shodja, H. M ; Sharif University of Technology
    Elsevier  2015
    Abstract
    Carbon nanotubes (CNTs) with and without end caps may be used for fluid storage and transport, respectively, referred to as CNT-nanovessel and CNT-nanopipe. The determination of the stiffness in the hoop (circumferential) and radial directions, ideal hoop strength, and hoop stress-strain curve of such nanostructures is of particular interest. Due to the proposed viewpoint, a chiral free-standing single-walled CNT (SWCNT) has a natural angle of twist and natural extension along the axis of the tube. For example, for the SWCNT (9,3) with diameter of 0.85 nm and chirality angle of 13.9°, the natural angle of twist per unit length is 1.45×10-3 rad/nm. Previously, only Vercosa et al. (2010) who... 

    A large-deformation thin plate theory with application to one-atom-thick layers

    , Article Journal of the Mechanics and Physics of Solids ; Volume 87 , 2016 , Pages 65-85 ; 00225096 (ISSN) Delfani, M. R ; Shodja, H. M ; Sharif University of Technology
    Elsevier Ltd  2016
    Abstract
    Nowadays, two-dimensional materials due to their vast engineering and biomedical applications have been the focus of many researches. The present paper proposes a large-deformation theory for thin plates with application to one-atom-thick layers (OATLs). The deformation is formulated exactly in the mathematical framework of Lagrangian description. In particular, an exact finite strain analysis is given - in addition to the usual strain tensor associated to the middle surface, the second and third fundamental forms of the middle surface of the deformed thin plate are also maintained in the analysis. Exact closed-form solutions for a uniaxially curved thin plate due to pure bending in one case... 

    Dual ideal shear strengths for chiral single-walled carbon nanotubes

    , Article International Journal of Non-Linear Mechanics ; Volume 120 , 2020 Delfani, M. R ; mohamadi Shodja, H ; Sharif University of Technology
    Elsevier Ltd  2020
    Abstract
    By considering a single-walled carbon nanotube (SWCNT) as a two-dimensional elastica obtained from the roll-up of a graphene sheet into a circular tube, the present paper develops a precise well-posed continuum theory for describing the entire torsional behavior of SWCNTs from an initial unloaded state through their ultimate levels of loading. In addition, the proposed approach can capture the dual ideal shear strengths as well as the asymmetrical behavior of chiral tubes with respect to the direction of the applied torsional loading. The theory incorporates a highly nonlinear constitutive equation which provides information about the nanoscopic morphological parameters of the tubes. As it... 

    A Process Mining Approach to Analyze Customer Journeys to Improve Customer Experience

    , M.Sc. Thesis Sharif University of Technology Akhavan, Fatemeh (Author) ; 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 Feiz, Roya (Author) ; 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 Taheriyan, Zahra (Author) ; 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... 

    Green Supplier Selection under Supply Risks with Respect to Supplier’s Financial Performance using Integrated Fuzzy MCDM Methods

    , M.Sc. Thesis Sharif University of Technology Fathi, Mahdi (Author) ; Hassannayebi, Erfan (Supervisor)
    Abstract
    The supplier selection problem is considered as one of the most strategic and critical issues for any organization. This issue is mainly relevant to traditional and manufacturing businesses. However, if we examine its relationship with the emerging concept of Vendor Acquisition, which has become increasingly significant in modern businesses and startups, the importance of supplier selection becomes even greater. Today, choosing the right supplier or vendor determines the level of success organizations achieve in any new project, and the performance of vendors plays a crucial role in shaping and directing these projects. This study aims to present a comprehensive framework for supplier... 

    Operations Optimization in Supply Chain Systems using Simulation and Reinforcement Learning

    , M.Sc. Thesis Sharif University of Technology Mahmoudi, Farzaneh (Author) ; 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 Alibakhshi, Alireza (Author) ; 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... 

    Mechanics and morphology of single-walled carbon nanotubes: From graphene to the elastica

    , Article Philosophical Magazine ; Volume 93, Issue 17 , 2013 , Pages 2057-2088 ; 14786435 (ISSN) Delfani, M. R ; Shodja, H. M ; Ojaghnezhad, F ; Sharif University of Technology
    2013
    Abstract
    The elastica is referred to the shape of the curve into which the centreline of a flexible lamina is bent. Hence, single-walled carbon nanotubes (SWCNTs) are treated as the elastica obtained from bending of graphene. The corresponding large deformation accompanies both the material and geometrical non-linearities. The morphology of the free-standing SWCNTs such as the natural angle of twist, bond lengths, tube radius and wall thickness are determined. Moreover, it is shown that the induced self-equilibriated strain field has a remarkable impact on the mechanical behaviour of the nanotube. Utilization of an appropriate non-linear continuum constitutive relation for graphene leads to exact... 

    Mechanics and Morphology of Single-Walled Carbon Nanotubes

    , Ph.D. Dissertation Sharif University of Technology Delfani, Mohammad Rasoul (Author) ; Mohammadi Shoja, Hossein (Supervisor)
    Abstract
    Vibration is one of the most important factors in design, operation and lifetime of drill strings. There for, investigation of vibrations in drill string, like every other rotary machine, is very important. The main goal of this research is developing a nonlinear model for a drill string system dynamics in an inclined well. Effects of drilling mud flow rate, weight on bit, angular velocity along with viscous damping, on the stability and vibration of a drill string are studied. Dynamic equation of the model is developed considering axial displacement and lateral bending geometric nonlinear coupling. The effect of drilling mud flow is modeled using Paidoussis formulations. Equation of motion... 

    Customer Journey Analytics using Process Mining Based on the Markov Model

    , M.Sc. Thesis Sharif University of Technology Torabi Ardekani, Saba (Author) ; 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 Monfaredi Jafarbagi, Aoun (Author) ; 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... 

    Determination of the scattered fields of an SH-wave by an eccentric coating-fiber ensemble using DEIM

    , Article International Journal of Engineering Science ; Volume 46, Issue 11 , 2008 , Pages 1136-1146 ; 00207225 (ISSN) Sarvestani, A. S ; Mohammadi Shodja, H ; Delfani, M. R ; Sharif University of Technology
    2008
    Abstract
    To date, the existing theories pertinent to the determination of the scattered fields of an inhomogeneity have been limited to certain topological symmetries for which the method of wave-function expansion is widely used. In the literature the wave-function expansion method has also been employed to the case involving concentric coated fiber. An alternative approach is the dynamic equivalent inclusion method (DEIM) proposed by Fu and Mura [L.S. Fu, T. Mura, The determination of elastodynamic fields of an ellipsoidal inhomogeneity. ASME J. Appl. Mech. 50 (1983) 390-396.] who found the scattered field of a single spheroidal inhomogeneity. The pioneering work of Eshelby [J.D. Eshelby, The... 

    Discovering and Improving the Processes of an Iranian Psychiatric Hospital Using Process Mining

    , M.Sc. Thesis Sharif University of Technology Roshan, Mohammad Amin (Author) ; 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 Fakoor, Mohammad Mahdi (Author) ; 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... 

    Integrating Customer Behavior Analysis into Demand Forecasting for Fast-Moving Consumer Goods in Retail Chains

    , M.Sc. Thesis Sharif University of Technology Ghaed Rahmati, Elahe (Author) ; Hassan Nayebi, Erfan (Supervisor)
    Abstract
    Forecasting demand for fast-moving consumer goods (FMCG) is a fundamental yet challenging issue in retail management due to highly volatile demand, short product life cycles, low profit margins, and limited customer loyalty. Customer purchase behavior reflects their response to a set of concurrent product attributes in the retail environment; price, discounts, product placement, and other stimuli influence the final purchase decision not independently, but in combination and in interaction with related products. Therefore, modeling this behavior realistically requires considering the dynamic interactions among products, and relying solely on univariate time series analysis is insufficient....