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FWD Data Collection Protocols and Optimum Pavement Maintenance and Rehabilitation Strategies at Network Level
, M.Sc. Thesis Sharif University of Technology ; Tabatabaee, Nader (Supervisor)
Abstract
The objective of this study was to develop an approach for incorporating techniques used to interpret and evaluate deflection data for network-level pavement management system applications. Because it disrupts traffic flow, is a potential safety problem and because of the expense of data collection and analysis, structural capacity is not currently evaluated at the network level by many agencies. A national pavement management system is being developed in Iran and the use of falling weight deflectometers (FWDs) at the network level was deemed necessary to compensate for the lack of vital construction history data in the pavement inventory. It was imperative to increase the interval between...
Protocol for FWD data collection at network-level pavement management in Iran
, Article Transportation Research Record ; 2018 ; 03611981 (ISSN) ; Tabatabaee, N ; Abbasghorbani, M ; Sharif University of Technology
SAGE Publications Ltd
2018
Abstract
The objective of this study was to develop an approach for incorporating techniques used to interpret and evaluate deflection data for network-level pavement management system applications. A national pavement management system is being developed in Iran and the use of falling weight deflectometers (FWDs) at the network level was deemed necessary to compensate for the lack of vital construction history data in the pavement inventory. Because FWD measurements disrupt traffic flow and are a potential safety hazard, it is imperative to increase the interval between FWD testing points as much as possible to allow scanning of the entire 51,000 km network of freeways, highways, and major roads in...
Synthesis and Characterization of Vanadium (IV)-SNO & ONO Tridentate Schiff-Base Complexes and Their Applications in Sulfide and Alcohol Oxidation in Ionic Liquid Media
, M.Sc. Thesis Sharif University of Technology ; Bagherzadeh, Mojtaba (Supervisor)
Abstract
In recent years, application of transition metal biphasic catalytic systems for different reactions is an area of intense research activity. Among these reactions, oxidation of sulfides to sulfoxides and sulfones due to their importance as an intermediate in synthesis of organic compounds is a center of interest. Also, the catalytic conversion of alcohols to the corresponding aldehydes or ketones is a fundamental transformation in both laboratory and industrial synthetic chemistry. From environmental perspectives, the development of new catalytic oxidation systems with molecular oxygen as green oxidant is particularly attractive. In recent years, ionic liquids have been extensively studied...
Agent-based Programming and it's Application Using GOAL
,
M.Sc. Thesis
Sharif University of Technology
;
Ramezanian, Rasoul
(Supervisor)
Abstract
With the significant advances in software engineering and developing complicated systems, it’s important to investigate the interaction between systems. Agentoriented software engineering is a new paradigm for developing distributed intelligent systems. Agent technology currently plays an important role in complex software development. The underlying paradigm offers a large repertoire of original concepts, architectures, interaction protocols, and methodologies for the analysis and the specification of complex systems built as Multi-Agent Systems (MAS). Several efforts, originating from academia, industry, and several standardisation consortium, have been made in order to provide new tools,...
Auto-selection of space-time Interest Points for Action Recognition
Application in Fisherposes Method
,
M.Sc. Thesis
Sharif University of Technology
;
Mohammadzadeh, Narges Hoda
(Supervisor)
Abstract
In this project, a novel action recognition method, named Fisherposes, is proposed, which is improved by several space-time (spatio-temporal) methods afterwards. The proposed method utilizes skeleton data obtained from Kinect sensor. First, pre-processing is performed in which the scales of bodies are canceled and the skeletons become aligned in order to make the method robust to location, orientation, and scale of people. In Fisherposes method, every action is defined as a sequence of body poses. Using the training samples for the poses, a Fisher subspace is created which we name it Fisherposes. Moreover, a novel distance measuring function, named regularized Mahalanobis distance, is...
Temporal Analysis of Functional Brain Connectivity Using EEG Signals
, M.Sc. Thesis Sharif University of Technology ; Mohammadzadeh, Narges Hoda (Supervisor)
Abstract
Human has different emotions such as happiness, sadness, anger, etc. Recognizing these emotions plays an important role in human-machine interface. Emotion recognition can be divided into approaches, physiological and non-physiological signals. Non-physiological signals include facial expressions, body gesture, and voice, and physiological signals include electroencephalograph (EEG), electrocardiograph (ECG), and functional magnetic resonance imaging (fMRI). EEG signal has been absorbed a lot of attention in emotion recognition because recording of EEG signal is easy and it is non-invasive. Analysis of connectivity and interaction between different areas of the brain can provide useful...
Null Controllability and Stabilizability of Compressible Navier-stokes System in One Dimension
, M.Sc. Thesis Sharif University of Technology ; Hesaraki, Mahmoud (Supervisor)
Abstract
In this thesis we study the exponential stabilization of the one dimensional compressible Navier-Stokes system, in a bounded interval locally around a constant steady state by a localized distributed control acting only in the velocity equation. In fact this is an analysis of a paper that published by Shirshendu Chowdhury, Debayan Maity, Mithily Ramaswamy and Jean-Pierre Raymond in Journal of Differential Equations. We determine a linear feedback law able to stabilize a nonlinear transformed system. Coming back to the original nonlinear system, we obtain a nonlinear feedback law able to stabilize locally this nonlinear system. The result is providing feedback control laws stabilizing...
Software Product Line Testing Optimization Based on Regression Test Techniques
, M.Sc. Thesis Sharif University of Technology ; Mirian Hosseinabadi, Hassan (Supervisor)
Abstract
A software product line is a set of products with common features. The design of this set is such that the core assets that are common features between products are implemented only once. All products in the product line use the core assets to reduce development costs. The number of products that can be produced in a software product line is exponential to the number of capabilities in the core assets and the set is very large, so the cost of testing the software product line will be very high. In the software product line testing, various methods have been provided to reduce costs, among which we can mention product prioritization and regression test techniques. In prioritization, the...
Analysis of People Appearance Variation in Multi-Camera Networks
, M.Sc. Thesis Sharif University of Technology ; Behroozi, Hamid (Supervisor) ; Mohammadzadeh, Narges Hoda (Co-Supervisor)
Abstract
Analysis of people appearance variation in multi-camera networks for person re-identification or person retrieval is a very challenging problem due to the many intra-class variations between different cameras. Like any problem in the field of machine vision, it is generally divided into two parts. The first part is feature extraction and the second part is feature matching for person retrieval. So far, various methods have been proposed for the extraction of discriminative features, which are generally divided into three categories: stripe-based, patch-based, and body-based methods. However, methods based on stripes, although simpler, have performed better due to their greater compatibility...
Diverse Video Captioning Using Recurrent Neural Networks and Part of Speech
, M.Sc. Thesis Sharif University of Technology ; Mohammadzadeh, Narges Al Hoda (Supervisor) ; Behroozi, Hamid (Co-Supervisor)
Abstract
In recent years, the simultaneous analysis of image and text by artificial intelligence has gained much attention. Video description is one of the topics used to help the blind, automate video content analysis, and more. This issue is usually examined in the context of supervised learning and is very similar to image description and machine translation.The proposed solutions to this problem are mainly in the framework of encoder-decoder and attention-based neural networks. Selection of various pre-trained networks to extract 2D and 3D visual features (description of objects and actions in the image), various hierarchical structures and different teaching methods (based on reinforcement...
Modeling of Fischer-Tropsch Synthesis Reactor for GTL Process
, M.Sc. Thesis Sharif University of Technology ; Khorasheh, Farhad (Supervisor) ; Taghikhani, Vahid (Supervisor)
Abstract
There is a need from the natural gas and energy industries to seek for an economically attractive way of converting remote gas reserves into transportable products, such as high quality fuels or petrochemicals. A possible way for the conversion of natural gas to middle distillates is based on a three-step process. Firstly, production of syngas from natural gas. Secondly,catalytic conversion of syngas into hydrocarbons, mostly parafins from C5 to C100. (Fischer-Tropsch (F-T) synthesis). Thirdly, hydrocracking of the heavy paraffinic hydrocarbons to middle distillates. The F-T synthesis step is highly exothermic. In order to control the temperature within the reactor, when considering high...
Analyzing Dermatological Data for Disease Detection Using Interpretable Deep Learning
, M.Sc. Thesis Sharif University of Technology ; Rabiee, Hamid Reza (Supervisor) ; Sharifi Zarchi, Ali (Supervisor) ; Ghandi, Narges (Co-Supervisor)
Abstract
We present a deep neural network to classify dermatological disease from patient images. Using self-supervised learning method we have utilized large amount of unlabeled data. We have pre-trained our model on 27000 dermoscopic images gathered from razi hospital, the best dermatological hospital in Iran, along with 33000 images from ISIC 2020 dataset. We have evaluated our model performance in semi-supervised and transfer learning approaches. Our experiments show that using this approach can improve model accuracy and PRC up to 20 percent on semi-supervised setting. The results also show that pretraining can improve classification PRC up to 20 percent on transfer learning task on HAM10000...