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Forces Primer
Forces Primer
Solving the physics problems you are presented with in an introductory course become easier if each time you sit down to solve a problem, you follow a generalized problem-solving strategy that includes sketching pictures.
David DeMuth, Jr.
Si \(AB=I\) entonces \(A\) es invertible y \(A^{-1}=B\)
Si \(AB=I\) entonces \(A\) es invertible y \(A^{-1}=B\)
Vamos a demostrar el notable teorema que dice que, dadas dos matrices cuadradras \(A\) y \(B\) del mismo tamaño, si \(AB=I\), donde \(I\) es la matriz identidad del mismo tamaño que la matrices \(A\) y \(B\), entonces \(A\) es invertible y \(B^{-1}=A\). La prueba será directa y sólo usaremos el hecho de que si \(|A|\ne0\) entonces \(A\) es invertible. La pregunta es si puedes tú, estimado estudiante, ofrecer otra prueba de la que aquí se sugiere. Sirva además este texto como un ejemplo de escritura con LaTeX.
Memo Garro
Solutions to exercises
Solutions to exercises
Geometry topics exercises
liyang
Templates for French Mathematical Society monographs and articles
Templates for French Mathematical Society monographs and articles
The classes smfbook and smfart are intended to help the preparation in LaTeX of the monographs and articles to be published by the French Mathematical Society.
Joseph Vidal-Rosset
Materials 1 Lab Report
Materials 1 Lab Report
The aim of this laboratory work is to design a strut/bracket assembly for aircrafts. Experiments are carried out to determine mechanical properties of certain materials.The material chosen is Mild Steel. Given the possible condition experienced by the material and the safety factor, the dimensions for the designs of the strut/bracket assembly for aircrafts are obtained to avoid failure by yield or fracture. The diameter of the pin, d ,which is subjected to shear stress should be larger than 14.56mm. The diameter of the rod, D, should be larger than 12.74mm. The thickness of the rod would be 10mm.
Chen Zhi Shen
MDA HW2: Principial components analysis and Canonical correlation analysis
MDA HW2: Principial components analysis and Canonical correlation analysis
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.
AGYAPONG ANTHONY ADOMAH
Geometría Analítica
Geometría Analítica
Geometría Analítica
CARLOS RODRÍGUEZ JASO
Why it's good that Soulstealer Vayne is so hard to get - a statistical Analysis
Why it's good that Soulstealer Vayne is so hard to get - a statistical Analysis
I analyzed the Hextech-Crafting in a Stochastic Simulation with 10 Million Players and found that you're going to make more Riot Points than you spend (in value) and thats without counting Champs. I've made some assumptions, which can be found down in the paper itself for those interested. For everyone else: If you're trying to maximize your RP-Net-Worth stack up on Hextech Chests.
WORST BRUISER EU
Compte rendu Thermo
Compte rendu Thermo
TP thermodynamique
Remini Loucif

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