Sharif Digital Repository

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... 

Markets are becoming more saturated every day and competition between different businesses is increasing. The importance of managing Customer churn in various businesses has become increasingly important because the cost of attracting a new customer is many times greater than retaining an existing customer. With the development of data mining and its increasing expansion and the other side, the increase of stored information related to various organizations and businesses has accelerated the operations of extracting knowledge from data. Today, businesses are moving towards the use of intelligent knowledge extraction systems, of which Customer churn prediction systems are one of the most... 

Predicting oil prices, especially in exporting countries, will help governments in the policy-making process by obtaining a reliable estimate of oil revenues. The existence of a complex mechanism governing the process of oil price formation has reduced the efficiency of linear models in forecasting and led researchers to use nonlinear intelligent systems to predict oil prices. In this study, after a detailed study of the structure of artificial neural network, two models of neural network GMDH and MLP and ARIMA method have been used to predict oil price. There are important factors in the prediction process with neural networks, and if all these factors are selected correctly; One can expect... 

Access to a reduced and fast mathematical model that can predict the input-output behavior of interconnected systems with acceptable accuracy and in a short time is crucial. The purpose of this project is to provide an object-oriented platform for identifying a model based on input-output data of interconnected systems in real-time. On this basis, in the case of developing fast estimation algorithms and updating the model quickly (in case of extensive changes in the system), good predictions of the model can be used for various applications. In this research, machine learning and data analysis methods are used to extract useful features and relations from data. Then, taken advantage of this... 

Falling is a prevalent event among elderly people, which sometimes leads to their death. Automatic detection of fall can significantly reduce the resulting damages.Fallings can be detected using various modalities, among which we choose RGB videos captured by CCTV cameras because of its advantages. Due to the great advances in deep learning-based image/video classification methods, we focused on using these methods for fall detection. One of the main challenges in using deep learning methods is lack of enough training data. Unlike other activities, there are not enough falling samples available which is due to its unconscious nature. Moreover, simulating falling by actors can endanger their... 

Chaos theory examines complex systems whose output results in large changes by applying small changes to the initial conditions. In other words, some seemingly accidental phenomena for which we have not yet found a reason can be justified with the help of chaos theory. The strong dependence of the response to the initial conditions is one of the most important features of turbulent systems, but their quasi-random behavior will be independent of these conditions after some time. Chaotic systems, as an important branch of nonlinear dynamic systems, behave close to stochastic systems. Perhaps the most important similarity between the two systems is the existence of invariant probability density... 

One of the key subjects in the area of mathematical optimization is a class of problems known as combinatorial optimization. We can find the optimal solution of continuous optimization problems feasible in time. But, in combinatorial optimization, we aim to obtain the optimal solution of the problem over a finite set. These problems are NP-hard and no polynomial-time solution has been proposed for this class of problems so far. Thus, in practical scenarios, we often use heuristic methods for solving NP-hard problems. There are lots of heuristic methods and choosing the best one in different situations might be challenging. In recent years, with the advances in deep neural networks,... 

Ground granulated blast furnace slag (GGBFS) based alkali-activated concrete (GAAC) is one of the eco-friendly alternatives of traditional concrete, which uses industrial byproducts instead of ordinary Portland cement (OPC). Besides environmental benefits, substituting OPC concrete with GAAC has some economic advantages, while it successfully meets the concrete structural requirements in both mechanical and durability characteristics. Despite this fact, employing GAAC in the construction industry has been limited due to a lack of standard mix design code.This study aims to develop an accurate prediction model for the compressive strength of GAAC by employing the most appropriate machine... 

Water shortages resulting from macro-environmental climate changes as well as local inefficient agricultural practices and dam constructions activities have resulted in the gradual reduction of water level in Urmia Lake, located in the northwest of Iran. As such, restoration efforts were initiated to prevent further adverse impacts exacerbating the conditions and creating secondary problems such as regional salt dust generation and dispersion, resulting in health issues for the greater area population in the neighboring vicinities. The utilization of advanced forecast modeling based on deep learning algorithms can assist the authorities to manage better multi-dimensional issues affecting the... 

In this paper, a machine learning-based atomistic-continuum multi-scale scheme is introduced to model the materials' geometrically and materially nonlinear behavior. The kinematic and energetic consistency principles are employed to link the atomistic and continuum scales. In order to establish the kinematic consistency principle, the periodic boundary condition is implemented for the atomistic RVE. The Ni-based superalloy, including 0 to 3% porosity, is considered for the models. Several parameter analysis is done to distinguish the proper atomistic RVE to be used in multi-scale models. The data set, including the stress-strain samples, is generated through molecular dynamics analysis... 

This study proposes a method to predict the remaining useful life (RUL) of the rolling element bearings (REBs) by forecasting the future trend of the peak of the acceleration signal. It is also employed to determine an appropriate time interval between the measurements of REBs vibration to reduce the error of forecasting and avoid collecting too much data in addition to increasing the reliability. In the first step, in order to achieve better results, the history of the acceleration peak is transformed into a stationary space before using the long short-term memory (LSTM) model to make it normally distributed and stationary. Then, LSTM forecasts the future trend of the stationary time series... 

Fiber-reinforced polymer (FRP) composites have been used tremendously to repair and rehabilitate timber structures due to their formability, ease of use, and high specific strength. The quality of the bond between FRP and timber substrate is critical for having complete composite action. In this paper, a comprehensive set of linear and nonlinear ultrasonic methods was performed to investigate the bond between carbon-FRP (CFRP) and timber. For this purpose, one hundred and twenty-six specimens of reinforced timber were prepared. Two techniques were considered to bond CFRP and timber: 1) externally bonded reinforcement (EBR) and 2) externally bonded reinforcement on the groove (EBROG). The... 

DNA methylation in one of the most important epigenetic variations, which causes significant variations in gene expressions of mammalians. Our current knowledge about DNA methylation is based on measurments from samples of bulk data which cause ambiguity in intracellular differences and analysis of rare cell samples. For this reason, the ability to measure DNA methylation in single-cells has the potential to play an important role in understanding many biological processes including embryonic developement, disease progression including cancer, aging, chromosome instability, X chromosome inactivation, cell differentiation and genes regulation. Recent technological advances have enabled... 

Civil structures are on the verge of changing which leads energy dissipation capacity to decline. Structural Health Monitoring (SHM) as a process in order to implement a damage detection strategy and assess the condition of structure plays a key role in structural reliability. Earthquake is a recognized factor in variation of structures condition, inasmuch as inelastic behavior of a building subjected to design level earthquakes is plausible. In this study Hilbert Hunag Transformation (HHT) is superseded by Ensemble Empirical Mode decomposition (EEMD) and Hilbert Transform (HT) together. Albeit this method is closely resemble HHT, EEMD brings more appropriate Intrinsic Mode Functions (IMFs).... 

Rapid visual screening is a way to assess unsafe structures and reduce urban earthquake vulnerability. Although this method is faster than detailed analytical methods(e.g. Incremental dynamic analysis), it still requires a lot of time and financial resources to execute. Due to the widespread use of computer vision in engineering, this study has used this technology to perform rapid visual screening, improve its overall process and provide a standard method for automatic assessment of structures. In the process of rapid visual screening, the screener identifies features from the exterior view of the building, which are finally recorded in a scoring system. According to the score obtained,...