Sharif Digital Repository

The main problem of steel-reinforced concrete structures is corrosion of steel reinforcements which leads to premature failure of the concrete structures. This problem costs a lot annually to rehabilitate and repair these structures. In order to improve the longterm performance of reinforced concrete structures and for preventing this corrosion problem, Fiber Reinforced Polymer (FRP) bars can be substituted of conventional steel bars for reinforcing concrete structures. This study is a numerical study to evaluate structural behavior of the simply supported concrete beams reinforced with FRP bars in comparison with steel-reinforced concrete beams. The commercial Finite Element Modeling... 

The ground experiences various hydraulic conditions under climate and groundwater level changes, and it becomes dry or wet frequently. The states of pore-water within the geomaterial, being signified in terms of suction and saturation degree, change during these variations, and consequently affect the soil behavior. The main objective of this research is investigation the effect of anisotropic loading induced by rotation angel of principal axes parameter under unsaturated conditions . Hence, shear strength of firoozkooh silt, in terms of deviatoric stress at failure under monotonic loading under different values of rotation angel of principal stress axes parameter and confining stress have... 

Although surface water networks play a very important role in transporting runoff, they contain significant amounts of pollutants entered through the point or non-point sources which cannot be neglected. The goal of this research is quantitative modeling of Zargande reach located in Maghsoodbeyg-Sadr area using SWMM model and investigating the effect of variation of permeable surface on the volume of runoff. Analysis of a 7 hour precipitation with the total of 5 mm cumulative precipitation resulted in 1.6 mm per hour loss of watershed. We utilized a FORTRAN code which minimizes the difference between the Espey synthetic hydrograph and the observed hydrograph for the precipitation to obtain... 

The human action recognition is one of the most important concepts of computer vision in recent decades. Most of the two dimensional methods in this field are facing serious challenges such as occlusion and missing the third dimension of data. Development of depth sensors has made easy access to tracking people and 3D positions of human body joints. This Thesis proposes a new method of action recognition that utilizes the position of joints obtained by Kinect sensor. The learning stage uses Fisher Linear Discriminant Analysis (LDA) to construct discriminant feature space. Two types of distances, i.e., Euclidean and Mahalanobis, are used for recognizing the states. Also, Hidden Markov Model... 

The non-stationary nature of brain activity signals and their many inter-subject differences have created many challenges in the practical applications of emotion recognition based on electroencephalogram (EEG) signals, such as brain-computer interfaces. In such a way, the use of traditional classifiers in classifying these signals leads to a significant decrease in accuracy when applying the classifier to a new subject. Domain Adaptation methods seem to be an effective way to solve this problem by minimizing the difference between the EEG signals of different subjects. But in the basic techniques for domain adaptation, looking at all subjects' data in the same look causes the loss of a part... 

As digital content grows rapidly due to the internet, user reviews about different topics such as product quality can be used as a rich source to check and analyze product quality and performance. Automatic methods are being widely used to extract these information because of the massive amount of available resources. Sentiment analysis is one of the important fields in natural language processing, which uses a combination of learning and rule-based methods to extract subjective information out of documents. Aspect based sentiment analysis deals with sentiment analysis based on each aspect of the product. It consists of two main steps: first, aspects should be extracted from the reviews and... 

Metallic multilayer composites provide remarkable mechanical, electrical and magnetic properties. These kinds of composites are recently processed by severe plastic deformation methods. Accumulative roll bonding (ARB) is one of the SPD processes in which accumulation of strain by repeating cycles, leads to the ultra fine grains structures. The goal of this research is manufacturing of Al/AZ31 composite and investigating the relation between the rolling process parameters and the mechanical and physical properties of the final sheet. The initial composite was carried out by cladding of 1mm thick AZ31 sheet in between two commercially pure aluminum sheets with the same thickness (57%... 

Mixed-model production Lines manufacture or assemble more than one product with similar production characteristics or different models of a product on the same line. This level of flexibility in commodities is very important to face diverse customers' expectations. In this article, U-shaped, mixed-model, synchronous lines with stochastic task times are discussed in a cost-oriented perspective. In U-shaped, mixed-model, Simultaneous consideration of line balancing and model sequencing is essential because different models require different tasks with different task times and the sequence of models determine the models which is produced in each station in each cycle. This sequence affects the... 

Making distribution networks smart includes all appropriate hardware and software devices for controlling and making operation of the network optimized. (SCADA system, distribution management, communication equipments, substation automation, monitoring equipments, etc). Monitoring and management of electricity distribution networks enable us to control and record events in the operation. Equipments in the distribution substations, will be under full time monitoring and hence, we would be able to protect them against over loads, over voltages, load unbalances and inefficient usage of transformers capacity and other distribution instruments. It also enables us to manage operation switchings,... 

This thesis addresses design of an adaptive tracking control of input-quantized strict-feedback fractional-order nonlinear systems with unknown control directions. The control design is achieved by using a hysteretic quantizer to avoid chattering. The main advantages of the proposed controller are: the fractional order is available for both commensurate and non-commensurate cases, the¬¬ controller design does not depend on the quantization parameters and some restrictive assumptions are relaxed. Additionally only one adaptive law has been used for the unknown control directions which leads to reduction of computational load. By utilizing the backstepping approach and based on the frequency... 

About 42 percent of annual mortality in all around the world is originated from cardiovascular arrhythmias and diseases. One of these arrhythmias is atrial fibrillation whose onset and persistence can produce clot and consequently cause stroke. The basis of our research are upon this idea that dangerous heart arrhythmias do not happen abruptly and there always are some background signs before occurrence of them. In our approach to predict the onset of atrial fibrillation, by analyzing ECG signal in order to extract distinguishing features, we want to classify signals which will terminate Paroxysmal Atrial Fibrillation (PAF) from signals which won’t end with PAF. In this thesis, we propose... 

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... 

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... 

Continuous Blood Pressure monitoring can provide invaluable information about individuals’ health conditions. However, BP is conventionally measured using inconvenient cuff-based instruments, which prevents continuous BP monitoring. This work presents an efficient algorithm, based on the Pulse Arrival Time (PAT), for the continuous and cuff-less estimation of the Systolic Blood Pressure (SBP), Diastolic Blood Pressure (DBP), and Mean Arterial Pressure (MAP) values. The proposed framework estimates the BP values through processing vital signals and extracting two types of features, which are based on either physiological parameters or whole-based representation of vital signals. Finally, the... 

Brain states analysis during consciousness is emerging research in brain-computer interface(BCI). Emotion recognition can be applied to learn brain states and stages of neural activities. Therefore, emotion recognition is crucial to the analysis of brain functioning. Electrical signals such as electroencephalogram (EEG), electrocardiogram (ECG) and functional magnetic resonance imaging(fMRI) are frequently used in emotion recognition researches. Convenience in recording, non-invasive nature and high temporal resolution are the factors that have made EEG popular in brain researches. EEG can be used to identify brain region activity solely or the connectivity of various regions in time in the...