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Selçuk Üniversitesi FBE tez yazım kılavuzuna uygun tez şablonu. Selcuk University Graduate School of Natural and Applied Sciences thesis template

Created with Xavier Danaux's CV template.

This work is going to analyze the Forced Van Der Pol's Equation which is used to analyze the electric circuit. In 1927, Balthasar Van Der Pol observed the stable oscillation and heard some irregular noise in vacuum tube circuit. He then proposed the Forced Van Der Pol's Equation to analyze the circuit and suggested the concept of limit cycle and Chaos to explain his observation. In this work, We would like to analyze behavior of the model by observing the phase space, time series, bifurcation diagram and power spectrum. Those points in the figures are calculated by Runge-Kutta Method with the aid of MATLAB. For a better understanding, the RLC circuit, which is a electric circuit consisting the a resistor, an inductor and a capacitor, will be used as an example for explaining the properties. Apart from electric circuit, the Forced Van Der Pol's Equation can be applied to dynamic systems in different aspect, such as the artificial heart, economic market and so on. Therefore, we suggest this work to all students since the Forced Van Der Pol's Equation can be applied to many majors, like Mathematics, Physics, Economics, Sociology, Biology, Engineering and so on.

Modelo de Relatório de Sessão PBL com abnTeX2, para Departamento de Tecnologia, Universidade Estadual de Feira de Santana

Principal Components Analysis (PCA) and Canonical Correlation Analysis (CCA) are among the methods used in Multivariate Data Analysis. PCA is concerned with explaining the variance-covariance structure of a set of variables through a few linear combinations of these variables. Its general objectives are data reduction and interpretation. CCA seeks to identify and quantify the associations between two sets of variables i.e Pulp fibres and Paper variables.PCA shows that the first PC already exceeds 90% of the total variability. According to the proportion of variability explained by each canonical variable , the results suggest that the first two canonical correlations seem to be sufficient to explain the structure between Pulp and Paper characteristics with 98.86%. Despite the fact that the first the two canonical variables keep 98% of common variability, 78% was kept in the pulp fiber set and about 94% of the paper set as a whole. In the proportion of opposite canonical variable,there were approximately 64% for the paper set of variables and 78% for the pulp fiber set of variables kept for the two respectively.

This is the partial source code and images of Edible Food Book, a CC-BY-SA-3.0 book. Copyright © 2013 Abdelkrime Aries <kariminfo0@gmail.com> Some fonts and colours have been modified from the original. This template contains only nuts, cereals and pulses (grain legumes), and the images have been resized to save disk space. You can see the complete output PDF here, or get the complete source at the original Github site.

This is the full PDF of Edible Food Book, a CC-BY-SA-3.0 book. Copyright © 2013 Abdelkrime Aries <kariminfo0@gmail.com> Some fonts and colours have been modified from the original. The partial source code of the book (because the complete book contains so many images!) can be found in this example. Or get the complete source at the original Github site.

The Journal of High Energy Physics (JHEP) is an international, peer-reviewed, online-only, scientific journal owned by the International School for Advanced Studies (SISSA - Trieste, Italy) and published by Springer. As of 2014 papers are published according to the gold open access scheme funded by SCOAP3. SISSA is in charge of the peer review and production of submissions, while Springer is in charge of their publication. See the journal website for more information about submission to JHEP.

Gesture recognition and its implementation that support Human Computer systems are becoming very popular mode of interaction now a days. It allows to interfacing the man machine commutative information flow naturally. Vision based gesture recognition has the potential that can provide intuitive and effective interaction between man and machine. However there are not adequate tools and techniques that support for developing, detecting or executing these tasks. In this paper we will implement a prototype that facilitates recording data during building some action based activities captured by the Kinect sensor. We analyze those recorded clips and visualize the user interactions by recognition the gestures objects based on depth, IR and skeletal data. Kinect tools include an analysis feature, a time-line-based approach that manually or automatically can mark the recording sequences of clips. We will implement both discrete and continuous gestures by using AdaBoast machine learning approach to detect hands activities. Our result suggest that the learning mechanism can achieve more than 98% of confidence level of given gestures. Keywords: Gesture recognition, Kinect, HCI, Machine learning, AdaBoost, Computer vision