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Dot Products and Cosines
Dot Products and Cosines
A simple derivation of the relationship between dot products and cosines. I wrote this reacquaint myself with LaTeX.
Paul Glezen
Automobile Suspension Design
Automobile Suspension Design
Vibration control is crucially important in ensuring a smooth ride for vehicle passengers. This study sought to design a suspension system for a car such that its mode of vibration would be predominantly bouncing at lower speeds, and primarily pitching at higher speeds. Our study used analytical and numerical methods to choose appropriate springs and dampers for the front and rear suspension. After an initial miscalculation, we succeeded in arriving at appropriate shocks for the vehicle with the desired modes of vibration at the specified frequencies. We then assessed the maximum bouncing and pitching that the vehicle would experience under a specific set of conditions: travel at 40 km/hr over broken, rough terrain. Our testing showed moderate success in our suspension design. We successfully damped the force being transmitted to both the front and rear quarter car somewhat, while ensuring that the modes of vibration fell into the desired shapes at the desired frequency ranges.
Little Ian
Determining the Ratio of Specific Heats of\\ Gases using Adiabatic Oscillations
Determining the Ratio of Specific Heats of\\ Gases using Adiabatic Oscillations
The ratios of specific heats, γ = (CP/CV), for three gases (air, argon and carbon dioxide) were calculated by measuring the oscillations of different masses in various apparatus. The experiments followed Rüchardt's and Rinkel's methods; a 100ml glass gas syringe was additionally used to extend the investigation as well as a technique to elimination of friction. The approaches and results were compared; the most accurate method (Rüchardt's method alongside compensation for friction) yielded: Air, γ = 1.358 ± 0.0038 Argon, γ = 1.6597 ± 0.0009 Carbon dioxide, γ = 1.2996 ± 0.0087 These differ from the literature value by 3.0%, 0.6% and 1.5% respectively. The reasons for these apparent discrepancies are discussed.
Pip Armstrong
Coursework template CO343
Coursework template CO343
Template for LaTeX beginners, designed with students taking the Imperial College London CO343: Operations Research course in mind.
Simon
Cour 1 ere AS
Cour 1 ere AS
Cour 1 ere AS
khaled
MODELO LOGIT
MODELO LOGIT
Es posible diseñar modelos en donde la variable dependiente posea característica cualitativas, ese es el caso que analizaremos en el presente trabajo, enfocándonos únicamente en el modelo LOGIT que nos brinda ciertas ventajas en comparación a un modelo lineal de probabilidad, estimada por mínimos cuadrados ordinarios(MCO) para lo cual resaltaremos dichas diferencias. Los modelos de regresión con respuesta cualitativa son modelos de regresión en los cuales la variable dependiente puede ser de naturaleza cualitativa, mientras que las variables independientes pueden ser cualitativas o cuantitativas, o una mezcla de las dos; por ejemplo, si se está estudiando la relación entre ingresos y el pagar o no impuesto de renta, la respuesta o regresada solo puede tomar dos valores (si paga impuesto de renta o no paga dicho impuesto); otros ejemplos en que la regresada es cualitativa son si la familia posee o no vivienda propia, se aprueba o pierde un curso, padece determinada enfermedad o no la padece. La variable cualitativa en estos tipos de modelos no tiene que restringirse simplemente a respuestas de sí o no, la variable respuesta puede tomar más de dos valores, ser tricotómica o politómica, también se establecen modelos en lo que la variable dependiente es de carácter ordinal o de carácter nominal, en donde no hay preestablecido ningún tipo de orden. En este trabajo se analizara el modelo LOGIT en donde la variable dependiente es de carácter binario o dicotómico (sí o no). (Green 2001) Se trata pues de adoptar una formulación no lineal que obligue a que los valores estimados estén entre 0 y 1 ya que, la regresión con una variable binaria dependiente Y modeliza la probabilidad de que Y = 1. La regresión LOGIT utiliza una función de distribución logística, su función de distribución de probabilidad da lugar a probabilidades ente 0 y 1, y presenta un crecimiento no lineal (con mayores incrementos en la parte central).
cefiro2610
Template for SIAM Online-Only Journals
Template for SIAM Online-Only Journals
Template for SIAM Online-Only Journals (JUQ, SIADS, SIAGA, SIFIN, and SIIMS), downloaded from SIAM homepage on March 14, 2018.
SIAM
Typed Homework Template for MAT434
Typed Homework Template for MAT434
This is a template for students enrolled in MAT434 at DePaul University.
Bridget Tenner
Math 453 HW 1
Math 453 HW 1
Math 453 HW 1 (with solutions)
munh1

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