Articles — Project / Lab Report

We were asked to design our own Electrocardiogram. Obviously, recording heart beats without any noise is a real challenge. Seeing the prices of those kinds of devices, we could already imagine that reaching great performances with our means would be difficult. However, the real goal of this project was to be able to analyze the different problems we encountered and to think about possible improvements we could have provided to overcome them.

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.

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

Propuesta : Amazon

juego de ajedrez

Report on Modern Philosophy

SVD-разложение и его практические приложения с исходным кодом на языке Matlab. (SVD - decomposition and its practical applications with source code in the language Matlab.

Projections are a "prescribed" part of structural analysis and visualizations, with the change in day and age numerous computer applications have been written to aid this. Most of them have taken care in explaining and elaborating the mathematical and programmatic aspects of their implementation. These applications and/or programs all have attained a robust and well accepted status in the field. The previously developed programs have mostly taken a traditional approach in code and design, i.e. the use of programming languages like C/C++, Fortran, Java, Python or packages like Matlab, Mathematica etc. The Open Source Web application discussed here takes up the task of removing system dependencies of the code by the use of JavaScript, the language of the web-browsers, for the entirety of the programming, and improves portability of the output by directly plotting into Scalable Vector Graphics (SVG).

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