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khalilzadeh--fatemeh
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Interpenetrating Polymer Networks as New Sorbent for Microextraction Techniques
, M.Sc. Thesis Sharif University of Technology ; Bagheri, Habib (Supervisor)
Abstract
In this project, silica and polystyrene based interpenetrating polymer networks (IPNs) were used as a sorbent for microextraction in packed sorbent for having both of the polymer’s properties at the same time. Interpenetrating polymer networks were synthesized with the simultaneous method and three different kind of interpenetrating polymer networks were prepared including full-interpenetrating polymer networks, covalent semi-interpenetrating polymer networks and non-covalent semi-interpenetrating polymer networks. To investigate extraction efficiency of prepared sorbents, 41 compounds including environmental pollutants and biomolecules were chosen. Studies showed that interpenetrating...
ChemInform abstract: microwave-assisted rapid ketalization/acetalization of aromatic aldehydes and ketones in aqueous media [electronic resource]
, Article Journal of Chemical Research ; September 1999, Volume -, Number 9; Page(s) 562 to 563 ; Mirjalili, Bibi Fatemeh ; Sharif University of Technology
Abstract
Aromatic aldehydes and ketones are readily acetalized or ketalized under microwave irradiation in the presence of water as a solvent
Synthesis and characterization of poly(methacrylates) containing spiroacetal and norbornene moieties in side chain [electronic resource]
, Article Journal of Applied Polymer Science ; Volume 77, Issue 1, pages 30–38, 5 July 2000 ; Mirjalili, Bibi Fatemeh ; Sharif University of Technology
Abstract
A four-step synthetic strategy was applied to achieve novel methacrylic monomers. 5-Norbornene-2,2-dimethanol was prepared from a Diels–Alder reaction of cyclopentadiene and acrolein, followed by the treatment of the adduct with an HCHO/KOH/MeOH solution. The resulting 1,3-diol (1) was then acetalized with different aromatic aldehydes having OH groups on the ring to produce four spiroacetal derivatives. The reaction of methacryloyl chloride with the phenolic derivatives led to four new methacrylic monomers that were identified spectrochemically (mass, FTIR, 1H-NMR, and 13C-NMR spectroscopy). Free radical solution polymerization was used to prepare novel spiroacetal–norbornene containing...
Prediction of DNA/RNA Sequence Binding Site to Protein with the Ability to Implement on GPU
, M.Sc. Thesis Sharif University of Technology ; Koohi, Sommaye (Supervisor)
Abstract
Based on the importance of DNA/RNA binding proteins in different cellular processes, finding binding sites of them play crucial role in many applications, like designing drug/vaccine, designing protein, and cancer control. Many studies target this issue and try to improve the prediction accuracy with three strategies: complex neural-network structures, various types of inputs, and ML methods to extract input features. But due to the growing volume of sequences, these methods face serious processing challenges. So, this paper presents KDeep, based on CNN-LSTM and the primary form of DNA/RNA sequences as input. As the key feature improving the prediction accuracy, we propose a new encoding...
A scatter search algorithm for RCPSP with discounted weighted earliness-tardiness costs
, Article Life Science Journal ; Volume 8, Issue 2 , 2011 , Pages 634-640 ; 10978135 (ISSN) ; Kianfar, F ; Ranjbar, M ; Sharif University of Technology
2011
Abstract
In this paper, we study a resource-constrained project scheduling problem in which a set of project activities have due dates. If the finish time of each one of these activities is not equal to its due date, an earliness or a tardiness cost exists for each tardy or early period. The objective is to minimize the sum of discounted weighted earliness-tardiness penalty costs of these activities. Scatter Search algorithm is used to deal with this extended form of resource-constrained project scheduling problem. Our implementation of Scatter Search integrates the advanced methods such as dynamic updating of the reference set and the use of frequency-based memory within the diversification...
The multi-objective supplier selection problem with fuzzy parameters and solving the order allocation problem with coverage
, Article Journal of Modelling in Management ; Volume 15, Issue 3 , 2020 , Pages 705-725 ; Karami, A ; Hajikhani, A ; Sharif University of Technology
Emerald Group Publishing Ltd
2020
Abstract
Purpose: This study aims to deal with supplier selection problem. The supplier selection problem has significantly become attractive to researchers and practitioners in recent years. Many real-world supply chain problems are assumed as multiple objectives combinatorial optimization problems. Design/methodology/approach: In this paper, the authors propose a multi-objective model with fuzzy parameters to select suppliers and allocate orders considering multiple periods, multiple resources, multiple products and two-echelon supply chain. The objective functions consist of total purchase costs, transportation, order and on-time delivery, coverage and the weights of suppliers. Distance-based...
Automatic segmentation of brain MRI in high-dimensional local and non-local feature space based on sparse representation
, Article Magnetic Resonance Imaging ; Volume 31, Issue 5 , 2013 , Pages 733-741 ; 0730725X (ISSN) ; Fatemizadeh, E ; Behnam, H ; Sharif University of Technology
2013
Abstract
Automatic extraction of the varying regions of magnetic resonance images is required as a prior step in a diagnostic intelligent system. The sparsest representation and high-dimensional feature are provided based on learned dictionary. The classification is done by employing the technique that computes the reconstruction error locally and non-locally of each pixel. The acquired results from the real and simulated images are superior to the best MRI segmentation method with regard to the stability advantages. In addition, it is segmented exactly through a formula taken from the distance and sparse factors. Also, it is done automatically taking sparse factor in unsupervised clustering methods...
Adaptive sparse representation for MRI noise removal
, Article Biomedical Engineering - Applications, Basis and Communications ; Volume 24, Issue 5 , October , 2012 , Pages 383-394 ; 10162372 (ISSN) ; Fatemizadeh, E ; Behnam, H ; Sharif University of Technology
World Scientific
2012
Abstract
Sparse representation is a powerful tool for image processing, including noise removal. It is an effective method for Gaussian noise removal by taking advantage of a fixed and learned dictionary. In this study, the variable distribution of Rician noise is reduced in magnetic resonance (MR) images by sparse representation based on reconstruction error sets. Standard deviation of Gaussian noise is used to find these errors locally. The proposed method represents two formulas for local error calculation using standard deviation of noise. The acquired results from the real and simulated images are comparable, and in some cases, better than the best Rician noise removal method due to the...
Cross-Lingual Speaker Adaptation for Statistical Parametric Speech Synthesis
, M.Sc. Thesis Sharif University of Technology ; Sameti, Hossein (Supervisor)
Abstract
Speech synthesis and its applications have been very attractive recently. The main purpose of this technique is to produce a speech signal with natural characteristics of human speech like prosody and emotion. Among all existing methods for speech synthesis, statistical parametric speech synthesis methods are more promising because ofhigher flexibility in comparison to other methods. One of the applications of speech synthesis is speech to speech translation. In these systems, the generated voice in target language should have the same characteristics as the input voice in source language. The main purpose of this research is to review and evaluate the cross lingual speaker adaptation...
Hydroelastic Analysis of Surface Piercing Propeller
, M.Sc. Thesis Sharif University of Technology ; Seif, Mohamad Saeed (Supervisor)
Abstract
Surface piercing propellers are particular type of supercavitating propellers that are commonly used for High-speed vessels. Most studies on this type of propellers has been investigating the hydrodynamic forces. But in recent years with increase in SPPs diameter used in vessels, structural analysis of this type of propellers is considered. For this purpose, studies on the stresses exerted on the propeller structures under load is done with the help of Hydro elastic methods. In this type of analysis, structura of propeller is intended to be flexible and Displacements under pressure checked and Tensions resulting from it are studied.
The present Thesis using ANSYS software to analyze a...
The present Thesis using ANSYS software to analyze a...
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....
Design of Low-Power Zero Temperature Coefficient (ZTC) CMOS Oscillators
, M.Sc. Thesis Sharif University of Technology ; Akbar, Fatemeh (Supervisor)
Abstract
The increasing demand for autonomous vehicles and reliable communication protocols and hardware interfaces, such as CAN bus and USB, underscores the necessity for stable clock sources that maintain a low temperature coefficient (TC) over wide temperature ranges. This demand is particularly emphasized in applications such as wearables, network sensors, downhole devices, WSNs, and IoT, where long-lasting battery life and frequency-stable clock sources over a broad temperature range (e.g. -20 °C to 100 °C) are crucial. Traditionally, variations in frequency caused by temperature have been mitigated by employing off-chip components like crystals or ceramic based oscillators, but this approach...
Design of Low Power Harmonic Rejection Mixer for Wideband Application
, M.Sc. Thesis Sharif University of Technology ; Akbar, Fatemeh (Supervisor)
Abstract
The increasing demand for communication bandwidth and limited spectrum availability have heightened the complexity of radio front-end circuits in IoT applications. Achieving spectral efficiency is a key challenge, particularly for IoT devices operating at specific frequency bands such as 315 MHz, 433 MHz, 868 MHz, and 915 MHz.Due to the limited linearity of the transmit path, harmonic distortion components, known as counter intermodulation (CIM) products, are generated. These CIM products can directly fall into the receiver (RX) band or enter it via cross-modulation, thereby degrading the frequency division performance. Additionally, CIM products can interfere with protected bands, violating...
Silica chloride/wet SiO2 as a novel heterogeneous system for the deprotection of acetals under mild conditions [electronic resource]
, Article Phosphorus, Sulfur, and Silicon and the Related Elements ; Volume 178:2667-2670, Issue 12, 2003 ; Pourjavadi, Ali ; Zolfigol, Mohammad Ali ; Bamoniri, Abdolhamid
Abstract
A combination of silica chloride and wet SiO2 was used as an effective deacetalizating agent for the conversion of acetals to their corresponding carbonyl derivatives under mild and heterogeneous condition
Reliability modeling of run-of-the-river power plants in power system adequacy studies
, Article IEEE Transactions on Sustainable Energy ; Vol. 5, issue. 4 , 2014 , p. 1278-1286 ; ISSN: 19493029 ; Fotuhi-Firuzabad, M ; Aminifar, F ; Ghaedi, A ; Sharif University of Technology
2014
Abstract
Deployment of renewable energies for the electricity generation is on the rise around the world, among which is the run-of-the-river (ROR) power plant whose output power is variable throughout the year depending on the water flow of the respective river. The inherent uncertainty associated with renewable energy resources calls for new stochastic modeling approaches to measure the impacts of using these energies on the power system performance. This paper develops an analytical reliability model for ROR power plants. The model is based on the state-space analysis and is devised with the intention of being used in adequacy studies of power systems. Failure of related components and the...
The Impact of AV and CAV Vehicles on Capacity and Traffic Flow with Cooperative Lane changing in Mixed Traffic Environment
, M.Sc. Thesis Sharif University of Technology ; Nassiri, Habibollah (Supervisor)
Abstract
Autonomous vehicles, as an integral part of intelligent transportation systems, will play a significant role in the future of transportation services. These vehicles have a high potential to improve road traffic capacity and the efficiency of transportation systems. One type of autonomous vehicle is the connected and autonomous vehicle (CAV), which can communicate with each other, roadside units, traffic control signals, and other infrastructures or devices. This study investigates the impact of autonomous vehicles and connected and autonomous vehicles on the traffic flow of the Tehran-Karaj freeway and vice versa, under various penetration rates and in a mixed traffic environment. In this...
The Impact of Integrated Prediction and Optimization on the the Bullwhip Effect in supply chains
, M.Sc. Thesis Sharif University of Technology ; Sedghi, Nafiseh (Supervisor)
Abstract
The Bullwhip effect is a phenomenon that refers to the amplification of demand variance as one moves upstream in a supply chain. This effect imposes additional costs on the supply chain and complicates inventory planning. Several factors contribute to the emergence of this phenomenon, one of which is demand forecasting. Since the demand faced by each level of the supply chain is uncertain, every level must first forecast demand in order to plan its inventory and meet customer requirements. However, this very process of forecasting contributes to the bullwhip effect. In this study, we investigate the impact of machine learning and deep learning forecasting methods, along with their...
Dynamic mutual manufacturing and transportation routing service selection for cloud manufacturing with multi-period service-demand matching
, Article PeerJ Computer Science ; Volume 7 , 2021 , Pages 1-30 ; 23765992 (ISSN) ; Valilai, O.F ; Haji, A ; Khalilzadeh, M ; Sharif University of Technology
PeerJ Inc
2021
Abstract
Recently, manufacturing firms and logistics service providers have been encouraged to deploy the most recent features of Information Technology (IT) to prevail in the competitive circumstances of manufacturing industries. Industry 4.0 and Cloud manufacturing (CMfg), accompanied by a service-oriented architecture model, have been regarded as renowned approaches to enable and facilitate the transition of conventional manufacturing business models into more efficient and productive ones. Furthermore, there is an aptness among the manufacturing and logistics businesses as service providers to synergize and cut down the investment and operational costs via sharing logistics fleet and production...
A new epileptic EEG spike detection based on mathematical morphology
, Article Proceedings of the IASTED International Conference on Biomedical Engineering, Innsbruck, 16 February 2004 through 18 February 2004 ; 2004 , Pages 301-305 ; 0889863792 (ISBN); 9780889863798 (ISBN) ; Shamsollahi, M. B ; Khalilzadeh, M. A ; Senhadji, L ; Sharif University of Technology
2004
Abstract
The best usual way in order to diagnosis, control and therapy different kind of Epilepsy is to refer to patient's EEG signals. Usually, in normal conditions of a patient, Epilepsy shows itself through EEG signals in the shape of transient waves. Identification of this waves using human eyes is so difficult that automatic detection methods based on mathematics and signal processing, should have been applied as an auxiliary tool to help physician identify this waves. The most significant transient epileptic waves in EEG are spikes. Up to now, various methods are presented for detection of spikes, but a quantitative and comparative evaluation hasn't been performed. In this work, we suggested a...
A fuzzy project buffer management algorithm: a case study in the construction of a renewable project
, Article International Journal of Construction Management ; 2022 ; 15623599 (ISSN) ; Vanhoucke, M ; Khalilzadeh, M ; Amiri, M ; Shadrokh, S ; Sharif University of Technology
Taylor and Francis Ltd
2022
Abstract
One of the major problems with projects is that they are not completed according to schedule. Uncertainty always exists at the heart of real-world project scheduling problems. This paper introduces a fuzzy project buffer management (FPBM) algorithm which is a combination of the adaptive procedure with resource tightness (APRT) and fuzzy failure mode and effects analysis (FFMEA) methods. This paper aims to present an efficient model for project buffer sizing by taking FFMEA into account to reach a more realistic schedule. In this research, for increasing the efficiency of the APRT method, the FFMEA technique is simultaneously applied with them. This research was carried out as a case study in...