Sharif Digital Repository

Chemometrics is an interdisciplinary subject which has many applications among science and industrial process. Environmental chemist, Food chemist, biologist and so on depend on good analytical chemistry measurement and so need chemometrics to interpret their data. In this project, we have developed different chemometrics and machine learning methods for considering the quantitative structure-activity relationship between different drug-like molecules. Also some chemometrics techniques were applied for the pattern recognition of NIR data on human plasma for discriminating between healthy and infected HIV-1 patients. At first, Quantitative structure-activity relationship (QSAR) models for... 

One of the newest methods of rapid prototyping is SLS . In this day, SLS is more common in compare others methods, because it uses little time and man does not nearly interfere in the producing stages of part which is made by SLS method. Also, sophisticated parts, which cannot be built by other methods, can be produced by SLS method. One of the disadvantages of SLS method is low dimensions accuracy of parts produced in this way. This problem has two major reasons: Shrinkage and Warpage. These two phenomena are created because of ununiformed temperature distribution. Others features which have effect on dimensions accuracy are residual stress, porosity and removing space of between powder... 

In parallel to the growing of population in Tehran metropolitan, air pollution in this city has become to a major problem. From which high concentration of pollutants have adverse effects on public health, accurate estimating and forecasting of concentrations for several days ahead, can provide the possibility to implement the management measures to reduce hazard and risks. Among the air pollution models, application of statistic models based on neural network in comparison to the traditional deterministic models are easier and less costly. In most studies, static models use a classical single MLP to predict one step ahead. For this purpose ANN models are required to estimate next value of... 

Before performing any operation on a speech signal, it is necessary to properly remove the environmental noise existing on it. Noise Canceling Operation on Speech Signal is called speech enhancement. Up to now, many studies have been conducted on various ways to enhance the speech signal. Among the existing methods, statistical methods have proven to be superior to others. In all noise removal methods, the main challenge is that most noises are non-stationary. Since most of the noises in the environment are non-stationary, we are still looking for the better ways to remove them. With the advent of deep neural networks and their successful results in areas such as machine learning, a method... 

This thesis provids a Persian End-To-End Speech Recognition system. In this system, the input is low-level features of speech signal. Deep recurrent neural networks (RNNs) and Long Short-Term Memory (LSTM) units as the RNN building blocks are used as the acoustic model. Continuous speech data is labeled by the CTC which is applied as the output layer of a recurrent neural network. By using the CTC objective function, acoustic modeling problem is simplified to just an RNN learning problem over pairs of speech and context-independent (CI) label sequences. A distinctive feature of this system is a generalized decoding approach based on weighted finite-state transducers (WFSTs), which enables... 

Launch vehicle must overcome gravity and place its payload on determined orbit. Multi-staging of launch vehicles causes that the ratio of length to diameter become large and then launch vehicle behave elastically. In this study, the equations of motion using the Lagrangian approach drive at pitch plane. By adding elastic terms to control equations, the launch vehicle modeling is completed. Predictive model controller choose for control system.This controller is based on neural network. In this paper, the main concepts and neural network approach in this controller structure is introduced.Finally implementation of this method in Simulink environment for pitch control of a flexible launch... 

In this study, the high temperature deformation behavior of Al-Cu aluminum alloy and the results of single-stage and multi-stage creep tests have been investigated. To investigate the behavior of alloy fluidity in temperature range 150 ° C to 500 ° C and strain rate 0.0005 s-1 – 0.05 s-1 were subjected to tensile test. The results show that in the temperature range of 200 ° C to 225 ° C, the sensitivity coefficient to the strain rate is negative, which indicates the occurrence of dynamic precipitation during deformation. In the meantime, the reverse processes in the mentioned temperature range were investigated and it was found that 250 ° C was the starting temperature of the dynamic... 

One of the most common nondestructive tests is ultrasonic testing which has been paid great attention from specialists of this field. Apart from being economical and efficient, ultrasonic waves are sensitive to small changes in the structure and thus have a high degree of reliability. The most common method of ultrasonic testing is manual single-element A-scan inspection, carried out offline using longitudinal waves with pulse echo technique which is used in this thesis. The purpose of this thesis is to monitor structural health of thin metal joints and estimate quality of resistance spot welds by simulating ultrasonic testing using a finite element software. Initially, acoustic properties... 

The hourly concentrations of particulate matter in Tehran are modelled in this study. High levels of particles are one of the main air pollution challenges in this metropolis, especially in the colder seasons. A probabilistic neural network is used for modelling. The model uses Bayes' theorem which has a very high ability to tackle the complexities and uncertainties. Traffic, meteorology, land use, baseline concentration (at 5 am), vegetation, along with other data including the location of each station, time of recording each concentration data, area and population of the municipal district of each station are considered. This research introduced a cheap and accurate method for collecting... 

The road authorities of a city have the responsibility of constantly assessing how well their city performs when traffic conditions are taken into account. In many metropolises around the world, if not taken preventive measures, there will be observed a density above the network capacity and a noticeable decrease in the level of service, especially in the morning and evening peak hours. Also, the dynamic congestion pricing of certain areas based on the traffic condition has always been considered significant by urban planning officials. Since this is not possible except by constantly assessing the current traffic state, a variety of methods have been used to predict the future traffic... 

Target recognition is one of the widespread applications of today's radars that requires obtaining target signatures using radar measurements. High-resolution range profile (HRRP) is one of these signatures that provides a one-dimensional radar image of the target. There are several methods for radar target's HRRP synthesis , all of which require a large bandwidth. One of these methods is the use of stepped frequency radar. One of the advantages of this method is providing a wide bandwidth by sending pulses with small bandwidths, thus obviating the need for broadband receivers and transmitters and making implementation easier. In many cases HRRP of target is sparse, because the number of... 

Prediction is an important issue in many areas. Proper planning for the future requires careful forecasting, so providing accurate methods, especially in the financial field, is invaluable. In this study, the main problem is predicting the price of global gold. Factors for gold prices include oil, gas, silver, soybeans, copper, the s & p500 index, the Dow Jones index, the British and Japanese stock market indices, the dollar index, the multi-currency exchange rate (pound-euro-yuan-yen) with the dollar to The title of the influential factors in this research is considered. The time frame of this research is daily, in other words, the data is collected on a daily basis and the goal is to... 

In recent years health monitoring and prognostics of complex systems have been considered more than ever.. In the present researh, data - based approach has been selected among various prognostics and health monitoring approaches. One of the most challenging issues in data-based methods is how to map system sensor information to its health status. In this research, different methods of mapping are discussed. The results show that sensor fusion by principal component analysis (PCA) offers acceptable performance. This pattern produces a single-dimensional signal for health monitoring with high reliability.The second challenge is to predict the status and design of the prognostics module. For... 

In this thesis the hourly concentration of different gaseous air pollutants in Tehran is modeled using Land Use Regression (LUR) and Artificial Neural Network, separately. Both models are provided with the same set of input data; the first step is to find these data. Since traffic affects air pollution, information about traffic conditions is one of the main inputs in air pollution modeling. Therefore, to obtain traffic information, in this thesis, first a novel method is developed to extract and analyze Google Maps traffic data. In this method, image processing is used along with the Geographic Information System (GIS) to count the number of pixels of different traffic colors for each road... 

In this thesis, a model is presented to detect and monitor the rotor bar's condition of large motors. This proposed model uses two diagnostic methods MCSA and ZCT, to extract the fault components. The input of the proposed model is only the motor current at two levels of 80% and 100% of the nominal motor load, which by using the two methods MCSA and ZCT and making changes in how to use them can be the disadvantages of other methods such as incorrect detection of rotor bars in Large motors with variable load, the harmonical stator voltage (or the presence of the drives) and asymmetric conditions. The extracted components are classified using two learnable algorithms, the k-NN algorithm and... 

In recent years, the spread of neurological disorders worldwide has been increasing, especially in developing countries. Due to the unknown function, complexity, and high importance of the brain, such disorders have been pervasive, severe, prolonged, and impose enormous costs on the individual, the family, and the community. Thus, increasing the knowledge about the brain and its areas in various activities is too vital and can facilitate the diagnosis and treatment of many different and unknown neuro- logical disorders. Different kinds of research have been done to automatically process and find the active and vital areas in various states and brain activities. The problem with most of these... 

Action recognition has a lot of applications in everyday human life. In the past, the researchers concentrated on using RGB frames, but since the advent of 3-dimensional sensors such as Kinect, 3D action recognition drew researchers' attention. Kinect can extract the joints of the body in action as time series. One of the main challenges of action recognition is that different individuals perform an action with various styles and speeds. Hence, the conventional methods such as calculating Euclidean distance seem inappropriate for this task. One solution is to use the techniques such as DTW, which aims to temporal aligning of the sequences. The DTW is not a metric distance; hence, in this... 

Today, with the development of technology, cyberattacks are on the rise. Personal and corporate computer systems can be exposed to various threats and dangers of hackers and malware, including information theft, forgery, and denial of service, which can cause great material and moral damage to individuals and organizations. So, it is necessary to take security measures in this regard. Many security mechanisms are available to prevent security vulnerabilities against various threats. In this study, first, after carefully studying network attacks, we identify the criteria for identifying attacks that can be executed in network traffic and explain how to calculate them. The current research... 

During the past 20 years, there has been an ever¬increasing interest in searching for anomalies or features beyond the standard scale¬invariant Gaussian spectrum of the CMB in the hope of finding signals of new physics. In this study, a new type of anomaly on the cosmic microwave background called the Inflationary Cherenkov effect is studied. By first simulating the expected effects and using machine learning methods such as convolutional neural networks, we obtain methods to detect this effect. Afterward, with the help of the detector, we study real data, namely temperature anisotropies of the CMB. Finally, we infer the speed of propagation of scalar field perturbations whose energy runs... 

In this research, the application of composite patch in the repair of pipes damaged by corrosion has been investigated. Numerical modeling, artificial neural network and Taguchi algorithm are used for this purpose. In the numerical modeling section, the accuracy of modeling performance has been verified by experimental results of other researchers. Then, the effect of various parameters such as depth and, angle of corroded area, fiber orientation in the composite patch and angle of composite patch have been investigated. The depth and the angle of the corroded area and the angle of orientation of the fiber have been shown to have a large effect on the growth life of fatigue cracks. For...