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Drug-Target Interaction Prediction with Deep Learning and Recommender Systems
, M.Sc. Thesis Sharif University of Technology ; Ghafourian Ghahramani, Amir Ali (Supervisor) ; Kavousi, Kaveh (Supervisor)
Abstract
A drug can be defined as a substance made to prevent disease, cure a specific symptom, relieve pain, and reduce anomalies in the body. The process of drug designing is so laborious, complex, costly, and time-consuming that chance of failure during the lab experiment stages is high. These challenges have persuaded researchers to find new usage for existing drugs, referred to as drug repurposing, with the main advantage of reducing cost, risk, and time. To this aim, computational methods have been applied to discover hidden pharmaceutical capabilities of drugs in terms of predicting whether a particular drug can interact with a particular protein.Graph Neural Networks (GNNs) have recently...
Brain Tumor Detection with Vision Transformers and Faster R-CNN
, M.Sc. Thesis Sharif University of Technology ; Hemmatyar, Ali Mohammad Afshin (Supervisor) ; Ghahramani Ghahramani, Amir Ali (Co-Supervisor)
Abstract
In the field of cancer diagnosis, particularly brain tumors, the priority is to achieve highly accurate tumor detection. Deep learning has shown remarkable potential in object detection tasks, making it a valuable tool for identifying brain tumors. We have proposed a new method for combining the strength of Faster R-CNN in detecting objects and the ability of Vision Transformer’s (Faster-VIT) ability to extract essential features. The proposed method significantly improves the accuracy and efficiency of brain tumor detection in MRI images. We have called the proposed combination Faster-VIT. To assess the effectiveness of the proposed method, we have utilized the Br35H dataset, comprising...
Mutation Prediction of Infectious Viruses Based on Different Machine Learning Approaches
, M.Sc. Thesis Sharif University of Technology ; Ghafourian Ghahramani, Amir Ali (Supervisor) ; Kavousi, Kaveh (Supervisor)
Abstract
Predicting the evolution of viruses is vital in controlling, preventing, and treating diseases. Mutations that evade the host immune system can propagate and persist through generations, making it crucial to anticipate and combat them effectively. The 1918 H1N1 pandemic serves as an example of the devastating impact of pandemics caused by viral mutations. By predicting mutations in advance, we can identify potential future pandemics and take effective preventative measures to mitigate their impact. Proteins play a vital role in the functioning of viruses. They are involved in various processes, such as replication, transcription, and host cell invasion. Any changes in the protein sequence...
Analysis and Performance Enhancement of MAC Layer Protocols in Vehicular Ad Hoc Networks
, Ph.D. Dissertation Sharif University of Technology ; Afshin Hemmatyar, Ali Mohammad (Supervisor)
Abstract
The Intelligent Transportation Systems (ITS) are aimed to provide innovative services to improve safety of the traffic and make the use of the transport networks more coordinated. Such services are implemented by establishing wireless communications among the vehicles. The resulting mobile ad hoc network formed among the moving vehicles is called the Vehicular Ad Hoc Network (VANET). The IEEE 802.11p has been emerged as the first standardized contention-based MAC protocol for VANETs. The overall performance of the contention-based MAC protocols is directly dependent on the number of the contending nodes . To analyze the performance of the 802.11p protocol, most of the existing approaches...
Buildings Construction Cost Prediction Using Hybrid Machine Learning Models
, M.Sc. Thesis Sharif University of Technology ; Haj Kazem, Kashani (Supervisor) ; Ghahramani, Amir Ali (Co-Supervisor)
Abstract
Since the awareness of project costs is a prerequisite for resource allocation and budget planning in construction projects, it is crucial to forecast project costs. In addition, as a part of the decision-making process, managers use predicted construction costs to assess and reduce project time risks. This study aims to estimate and predict residential building construction costs using hybrid machine learning models. In this research, to estimate the construction costs, in addition to considering the general characteristics of buildings, economic parameters are also considered. These physical and economic features are determined using experts' opinions and the results of previous studies....
Extractive Text Summarization with Domain Adaptation in Persian
, M.Sc. Thesis Sharif University of Technology ; Hemmatyar, Ali Mohammad Afshin (Supervisor) ; Ghafourian Ghahramani, Amir Ali (Supervisor)
Abstract
Text summarization and classification are two important tasks in natural language processing. Text summarization involves condensing a piece of text into its main points, making it easier to understand. On the other hand, text classification involves categorizing a text into predefined categories based on its content. Text summarization can be achieved through various methods, such as extractive summarization, where key sentences or phrases are extracted from the original text. The present research aims to classify and summarize news texts in the Persian Daily News dataset. This objective is carried out in two stages. First, the texts in this dataset are classified using the ParsBERT...
Text summarization and classification are two important tasks in natural language processing. Text summarization involves condensing a piece of text into its main points, making it easier to understand. On the other hand, text classification involves categorizing a text into predefined categories based on its content. Text summarization can be achieved through various methods, such as extractive summarization, where key sentences or phrases are extracted from the original text. The present research aims to classify and summarize news texts in the Persian Daily News dataset. This objective is carried out in two stages. First, the texts in this dataset are classified using the ParsBERT...
Scene Interaction Aware Perception for Autonomous Driving Tasks
, M.Sc. Thesis Sharif University of Technology ; Ghafourian Ghahramani, Amir Ali (Supervisor) ; Shirmohammadi, Zahra (Co-Supervisor)
Abstract
Safely navigating complex urban environments presents a critical challenge in autonomous driving perception tasks. This challenge necessitates the ability to consider interaction with traffic scene agents while accurately predicting the behavior of vulnerable road users (VRUs) like pedestrians. This thesis aims to enhance AV perception by focusing on scene interaction awareness from two key perspectives: vehicle-vehicle and vehicle-pedestrian interactions. For vehicle-vehicle interactions, monocular depth estimation, a low-cost, data-driven approach, is employed to approximate inter-vehicle distance from an RGB image. First, vehicles and their lights are detected using the YOLOv7 algorithm...
An AI Based Cryptocurrency Trading System
, M.Sc. Thesis Sharif University of Technology ; Khayyat, Amir Ali Akbar (Supervisor)
Abstract
Cryptocurrencies are not only regarded as a trustworthy method of financial transaction validated by a decentralized cryptographic system as opposed to a centralized authority, but also as one of the most popular and lucrative forms of trade and investing. Predicting the price of a cryptocurrency is a challenging topic in time-series research. Its intricacy is due to the volatility and large swings of cryptocurrencies' price. The emergence of brand-new cryptocurrencies, which might present a profitable trading opportunity but lack sufficient historical data for technical analysis, prompted us to develop a trading strategy that could be applied universally. The forecast of the next timestep's...
Numerical Investigation of Dewetting of Evaporating thin Films over Nanometric Topography
, M.Sc. Thesis Sharif University of Technology ; Moosavi, Ali (Supervisor)
Abstract
Evaporation and condensation of thin films can rupture or stabilize thin film .We show that evaporation hastens dewetting of a thin film. Dewetting over nanometric downward step causes pinning of the contact line near the step. This phenomena is not permanent and after certain time that contact angle reaches to its critical value depinnnig happens. We also study the effect of the step size, contact angle, film thickness, slip and evaporation on the depinning time of the contact line. We show that depinnig time has a reverse relation with the rate of evaporation
Study of the Current Status and Future Perspective of E-Commerce in IRAN
, M.Sc. Thesis Sharif University of Technology ; Moayedi, Vafa (Supervisor)
Abstract
The main purpose of my research is to present a predictive E-Commerce plan for Iran. For many people the term "electronic commerce" means shopping on the part of the Internet called the World Wide Web, but other technologies such as wireless transmissions on mobile telephone and personal digital assistant devices are also included. In our thesis the term Electronic Commerce or (E-Commerce) is used in its broadest sense, and includes all business activities conducted using electronic data transmission technologies. In Iran e-commerce has achieved an important role and is facing remarkable acceptance in trade operations, therefore my study focuses on the development of E-Commerce model in...
Design and Implementation of Tunable Microwave Gain Equalizer
,
M.Sc. Thesis
Sharif University of Technology
;
Banai, Ali
(Supervisor)
Abstract
Modern broadband microwave and millimeter-wave systems often struggle with excessive pass band ripple and negative gain slopes due to the loss of transmission lines such as coaxial cables, or ripples in the gain characteristic of broadband amplifiers. The common solution for this problem is using a gain equalizer to compensate for the intrinsic pass band variation with some extra loss in the band of interest in return.Designed equalizers often have a constant slope in their bandwidth. However, having ripples in pass band or in other words slope changing in some parts of the band is one of the issues that designers should deal with. In this thesis, after reviewing the previous works on the...
Design and Fabrication of a 1GHz Low phase Noise SAW Oscillator
, M.Sc. Thesis Sharif University of Technology ; Banai, Ali (Supervisor)
Abstract
For decades Crystal Oscillators (XO) have been the unequaled references for stable and low noise frequency sources. This leadership is due to their high Q-factor. The resonant frequency of such crystal resonator is inversely proportional to the thickness of the quartz disk (the resonant cavity) and is today limited , by physical manufacturing constraints , to about 150 MHz . in order to avoid such limitation , the solution is to start with an oscillator at higher fundamental frequency. SAW technology on quartz offers this opportunity . with SAW the resonant cavity size is not linked to the thickness of the substrate and resonant frequencies up to the GHz range are achievable. In this thesis...
On Efficiency and Bandwidth Enhancement of Integrated Class-J Power Amplifiers
, Ph.D. Dissertation Sharif University of Technology ; Medi, Ali (Supervisor)
Abstract
Power amplifiers (PAs) are one of the key components in radio-frequency (RF) and microwave systems. In these systems, PAs must be highly efficient to simplify the thermal management and to enhance dc power requirements. Future systems, including WiMax, 4G, 5G, and beyond, will likely require larger bandwidths due to their wider spectral allocations caused by the extended bandwidth of baseband signals. Therefore, highly-efficient and broadband PAs are needed to be employed in these systems. To realize high-efficiencies over wide frequency ranges, class-J mode of operation was introduced by Cripps in 2009. Class-J mode of operation is capable of maintaining a high efficiency (78% in theory)...
Effect of Subsequent Drying and Wetting on Small Strain Shear Modulus of Unsaturated Silty Soils Using Bender Element
, M.Sc. Thesis Sharif University of Technology ; Khosravi, Ali (Supervisor)
Abstract
Evaluation of the seismic-induced settlement of an unsaturated soil layer depends on several variables, among which the small strain shear modulus, Gmax, and soil’s state of stress have been demonstrated to be of particular significance. Recent interpretation of trends in Gmax revealed considerable effects of the degree of saturation and hydraulic hysteresis on the shear stiffness of soils in unsaturated states. Accordingly, the soil layer is expected to experience different settlement behaviors depending on the soil saturation and seasonal weathering conditions. In this study, a semi-empirical formulation was adapted to extend an existing Gmax model to infer hysteretic effects along...
Analyzing Narrative Policy Framework of Innovation Policy in Development of Iran’s Innovation Ecosystem
, M.Sc. Thesis Sharif University of Technology ; Maleki, Ali (Supervisor)
Abstract
The development of innovation ecosystems has become a global trend. These ecosystems have proven their importance to governments by having a significant impact on the creation of technology companies and the economic growth of the country. In Iran, too, for many years, efforts have been made under various headings to develop the innovation ecosystems. In this dissertation, based on the narrative policy framework, the existing policy narratives of innovation ecosystems development policy in iran between 2013-20 years in the case of startup ecosystem have been analyzed. After analyzing these data, it was found that the three main narratives of catch-up, wealth creation and infiltration, have...
Design and Implementation of a Voltage Controlled Oscillator For 77GHz Automotive Radar
, M.Sc. Thesis Sharif University of Technology ; Medi, Ali (Supervisor)
Abstract
Wideband mm-wave radars are gaining popularity in automotive applications due to their superiority in harsh weather conditions, high distance resolution, precise velocity measurement, and superior spatial resolution. The primary purpose of this thesis is to design and implement a voltage-controlled oscillator for 77GHz automotive radar applications.Phase noise -as one of the most crucial specifications in VCO design- Phase noise improvement techniques as well as harmonic engineering methods are delineated. Also, an Ocean-based code for ISF simulation is introduced and developed to obviate the need for additional signal processing software so that simulation speed increases...
Emergence of molecular chirality by vibrational Raman scattering
, Article Physical Review A - Atomic, Molecular, and Optical Physics ; Volume 88, Issue 3 , 2013 ; 10502947 (ISSN) ; Shafiee, A ; Sharif University of Technology
2013
Abstract
In this study, we apply the monitoring master equation describing decoherence of internal states to an optically active molecule prepared in a coherent superposition of nondegenerate internal states interacting with thermal photons at low temperatures. We use vibrational Raman scattering theory up to the first chiral-sensitive contribution, i.e., the mixed electric-magnetic interaction, to obtain scattering amplitudes in terms of molecular polarizability tensors. The resulting density matrix is used to obtain elastic decoherence rates
Fabrication of Oleophobic Coating
, M.Sc. Thesis Sharif University of Technology ; Mousavi, Ali (Supervisor) ; Nouri Borujerdi, Ali (Supervisor)
Abstract
Wettability is the cause of many interactions today and is definitely effective in almost all processes where liquid and solid phases are in contact. Wetting controls by surface engineering can accelerate the process in the industry or improve the quality of daily life. Therefore, the fabrication of complex surfaces with a specific purpose and different wettability has attracted the attention of researchers. In this thesis, silica nanoparticles were synthesized to create roughness and reduce contact between surfaces and liquids at first. Then, using chemical compounds to reduce the surface energy, a transparent (94.20%) superhydrophobic and oleophobic coating was created on the glass. The...
Prediction and Optimization of Desalination System Performance using Artificial Neural Network Approach
, M.Sc. Thesis Sharif University of Technology ; Mousavi, Ali (Supervisor) ; Nouri Borujerdi, Ali (Supervisor)
Abstract
Due to the global crisis of water and energy scarcity, the design and optimization of water treatment systems with the aim of reducing energy consumption and increasing efficiency have gained significant importance. An electrodialysis system was simulated and validated using advanced lumped model, considering all critical effects in the process, such as Donnan resistance, boundary layer resistance, and osmotic and electroosmotic flows, across salinity ranges from 0.35 to 200 parts per thousand. Additionally, a reverse osmosis desalination system was simulated and validated using the solution-diffusion model, with the concentration polarization coefficient calculated via the thin-film theory....
Entropy Analysis and its Application in Interconnection
, M.Sc. Thesis Sharif University of Technology ; Baniasadi, Amir Ali (Supervisor)
Abstract
Reducing interconnection costs on chip and power consumption are important issues in designing processors. In a processor, a significant amount of total chip power is consumed in the interconnection. The goal of this research is to find a way to reduce power consumption in the interconnection. In this project we propose a new data sending method in which an LZW-like compression algorithm is exploited to compress data before sending it over the interconnection. Then, the codes of the compressed data are sent through the interconnection in order to reduce the number of dynamic cycles. The simulation results show that using this method can reduce 52% of dynamic power consumption