The history of Automobiles Essay Example for Free

The history of Automobiles Essay Automobiles also known as Cars, Trucks and SUV’s are a very important part of our everyday lives. Automobiles have been around a lot longer than most people think. In Europe, automobiles date back to as early as the late 1700’s. European engineers began thinking of developing the first automobile to make life easier. By the mid 1800’s they began to think over how the automobile would run. Some manufactures tried using stream, combustion, and electrical motors to run their prototypes. The steam engine was invented in the early 18th century and has been applied to a variety of practical uses. But one of the most important ways steam was used was to power an automobile. The first steam powered automobile was built by built by Nicolas Joseph Cugnot. It was used by the French Army to haul artillery at a speed of 2 1/2 mph on only three wheels. The vehicle had to stop every ten to fifteen minutes to build up steam power. The steam engine and boiler were separate from the rest of the vehicle and placed in the front for easier maintenance. The combustion engine was invented in the late 1600’s by Dutch physicist Christian Huygens. He found that using a combustion substance such as kerosene or gasoline. He found that this type method to power a automobile was much more effective than a steam powered because it could go much faster and was able to have enough power to be able to do what was required. Today we still use combustion to power our automobiles, and it is expected that by the year 2020 most automobiles will be electrical powered to save are planet from globe warming and ozone destruction. The electric engine on an automobile was not very popular until recent years ago. But the engine itself was invented back in the early 1900’s and had many advantages over their competitors. They did not have the vibration, smell, and noise associated with gasoline automobiles. Changing gears on gasoline automobile was the most difficult part of driving, while electric automobiles did not require gear changes. While steam-powered automobiles also had no gear shifting, they suffered from long start-up times of up to 45 minutes on cold mornings. The steam automobiles had less range before needing water than an electrics range on a single charge. Now as time progresses the electric automobiles are becoming more popular especially hybrid models which use both combustion and electricity. Now a day almost every family has one or two or even three automobiles and purchases a new one every two years. Automobiles are becoming more and more popular as the years go by, and are becoming more fuel efficient to run and have more options available than the year before, and are a very important part of our everyday lives in order to transport ourselves around more efficiently than ever before.

Goethes Faust - A Man of Un-heroic Proportions Essay -- Faust Essays

Faust: A Man of Un-heroic Proportions In Faust, Goethe builds a dramatic poem around the strengths and weaknesses of a man who under a personalized definition of a hero fails miserably. A hero is someone that humanity models themselves and their actions after, someone who can be revered by the masses as an individual of great morality and strength, a man or woman that never sacrifices his beliefs under adversity. Therefore, through his immoral actions and his unwillingness to respect others rights and privileges, Faust is determined to be a man of un-heroic proportions. It is seen early in the poem, that Faust has very strong beliefs and a tight moral code that is deeply rooted in his quest for knowledge. Sitting in his den, Faust describes his areas of instruction, "I have, alas, studied philosophy, jurisprudence and medicine, too, and, worst of all, theology with keen endeavor, through and through..." It is obvious that through his studies he has valued deep and critical thinking, however with the help of Mephisto, he would disregard his values and pursue the pleasures of the flesh. Faust's impending downward spiral reveals the greed that both Mephisto and Faust share. Mephisto's greed is evident in the hope that he will overcome Faust's morality and thus be victorious in his wager with God; also because he is the devil and that is what he does. For Faust, greed emerges because of his desire to attain physical pleasures and therefore become whole in mind, body and spirit. Faust's goal to become the ÃÅ"berminche is an understandable desire, however, the means at which he strives for those ends are irresponsible and unjust. It is through this greed that Faust with the help of Mephisto exploit others in the pursuit... ... dishonest and greedy to such a wondrous and magical location only because he admits that what he did was wrong. Attaining passage into heaven is the only accomplishment that Faust makes in order to attain hero status. Even this final accomplishment is questionable, because God would not allow a man so unworthy to accompany people who have such a high moral standard and irrefutable grace. Faust then, neither falls under the classical definition of a hero except that he was, "...favored by the gods" and he does not fit into my personal definition of a hero. For Faust is not someone whose actions should be followed, he sacrificed his beliefs under adversity and most importantly; he destroyed anyone's life if it conflicted to any aspect of his plan for superiority. Faust then, may be considered the greatest un hero to have ever attain passage into heaven.

Math Internal Assessment Gold Medal Heights

Gold Medal Heights The heights achieved by gold medalists in the high jump have been recorded starting from the 1932 Olympics to the 1980 Olympics. The table below shows the Year in row 1 and the Height in centimeters in row 2 Year| 1932| 1936| 1948| 1952| 1956| 1960| 1964| 1968| 1972| 1976| 1980| Height (cm)| 197| 203| 198| 204| 212| 216| 218| 224| 223| 225| 236| They were recorded to show a pattern year after year and to reveal a trend. The data graph below plots the height on the y-axis and the year on the x-axis. Data Graph 1 Height (cm) Height (cm) Year YearIn Data Graph 1 the data shown represents the height in cm achieved by gold medalists in accordance to the year in which the Olympic games were held. The Graph shows a gradual increase in height as the years increase. The parameters shown in this are the heights, which can be measured during each year to show the rise. The constraints of this task are finding a function to fit the data point shown in Data Graph 1. Some other constraints would be that there aren’t any outliers in the graph and it has been a pretty steady linear rise. The type of function that models the behavior of the function is linear.This type of function models it because the points resemble a line rather than a curve. To represent the points plotted in Data Graph 1 a function is created. To start deciphering a function I started with the equation – Y = mx + b To show the slope of the line since the function is linear. For the first point the function would have to satisfy 197 = m (1932) + b In order for the line to be steep the b value or y intercept will have to be low to give it a more upward positive slope. Y = mx -1000 197 = m (1932) -1000 1197 = m (1932) m = 0. 619The final linear equation to satisfy some points would be y = 0. 62x – 1000 The graph below shoes the model linear function and the original data points to show their relationship. Graph 2 Year Year Height (cm) Height (cm) The graph above shows t he linear function y = 0. 62x – 1000 in relation to the data points plotted on Data Graph 1. The differences between the function and the points plotted is that the function does not full satisfy all the x and y values. The outliers in this case are from the years 1948, 1952, and 1980 which all of y values that do not meet the function closely.Using regression the following function and graph is found. The function and line found using regression matches the one found by me. The linear function does not cross all points but shows the gradual shape in which the points plotted make. Another function that is used is a quadratic function Quadratic functions are set up as: Y = px2 + tx +b To make this function resemble the points plotted on the Graph 1 the p value will have to be very small to widen the shape of the quadratic The b value also has to be small to resemble the y intercept and to give the graph a more upward slopeI used the function: Y = 0. 0000512Ãâ€"2 + 0. 5171x â €“ 1010 In order for this function to work it must satisfy the point of (1964, 218) Y = 0. 0000512 (1964)2 + 0. 5171 (1964) – 1010 Y = 0. 0000512 (3857296) + 1015. 58 – 1010 Y = 197. 49 + 1015. 58 – 1010 Y = 218 This graph of the function y = 0. 0000512Ãâ€"2 +0. 5171x – 1010 is shown in the following Graph 3 as it is against the points plotted in Data Graph 1 Graph 3 Height (cm) Height (cm) Year Year It is shown in Graph 3 that the quadratic function does resemble the shape of the line plotted by the points in Data Graph 1.In Graph 4 both functions are shown against the original data points plotted in Data Graph 1. Graph 4 Height (cm) Height (cm) Year Year Had the games been held in 1940 and 1944 the winning heights would be estimated as: Y = 0. 62(1940) – 1000 Y = 1202. 8 – 1000 Y = 202. 8 When the x value of 1940 is plugged into the linear equation y = 0. 62x – 1000 the y value, or winning height in the year 1940, would be 202. 8. Y = 0. 0000512(1940)2 + 0. 5171(1940) – 1010 Y = 0. 0000512(3763600) + 1003. 17 – 1010 Y = 192. 69 + 1003. 17 – 1010 Y = 185. 86 When the x value 1940 is plugged into the quadratic equation y = 0. 000512Ãâ€"2 + 0. 5171x – 1010 the y value, or winning height for 1940, is 185. 86. In order to make a more accurate estimate for the winning height in 1940 the average of both terms, 202. 8 and 185. 86, are taken. 202. 8 + 185. 86 / 2 = 194. 33 The estimated winning height in 1940 would be 194. 33 For the estimated winning height in 1944: Y = 0. 62(1944) – 1000 Y = 1205. 28 – 1000 Y = 205. 28 When the x value of 1944 is plugged into the linear equation 0. 62x – 1000 the y value, or winning height in 1944, is 205. 8. Y = 0. 0000512(1944)2 + 0. 5171(1944) – 1010Y = 0. 0000512(3779136) + 1005. 24 – 1010 Y = 193. 49 + 1005. 24 – 1010 Y = 188. 73 When the x value of 1944 is plugged into the quadratic equation of 0. 00005 12Ãâ€"2 + 0. 5171x + 1010 the y value, or winning height in 1944, is 188. 73. To have a more accurate estimate of the winning height the average of the two y values of two functions is taken. 188. 73 + 205. 28 / 2 = 197. 01 The winning height for the 1944 Olympics would be estimated at 197. 01 Graph 5 Year Year Height (cm) Height (cm) Graph 5 shows all the data from the 1896 Olympics to the 2008 Olympics.The red line is the quadratic function f(x) = 0. 0000512Ãâ€"2 + 0. 5171x – 1010 and the blue line represents the linear function f(x) = 0. 62x -1000. The function models that are represented in Graph 5 do not fully resemble the points plotted from the gold medal high jump heights but have an overall shape of the rise in height from year to year. Graph 6 Height (cm) Height (cm) Year Year The graph above shows all data point plotted on a graph. The overall trend or shape resemble that of a cubic. Graph 7 The shape of the cubic resembles more of the shape shown in the data poi nts plotted on Graph 6.The modifications that need to be made on my models are that the quadratic function needs to have a more curve to it than just a straight line. To do that I need to change the variables a, b, and c in the equation f(x) = ax2 + bx + c f(x) = 0. 0000512Ãâ€"2 + 0. 5171x -1010 Graph 8 Height (cm) Height (cm) Year Year In a zoomed out view the graph shows the overall shape of the quadratic shape of the red line and how it goes through the black data points and how the linear equation is completely straight. IB Mathematics SL Year 2 Internal Assessment Gold Medal Heights Date Due: February 11, 2013

The SLOSS Debate in Conservation

One of the most heated controversies in conservation history is known as the SLOSS Debate. SLOSS stands for Single Large or Several Small and refers to two different approaches to land conservation in order to protect biodiversity in a given region. The single large approach favors one sizeable, contiguous land reserve. The several small approach favors multiple smaller reserves of land whose total areas equal that of a large reserve. Area determination of either is based on the type of habitat and species involved. New Concept Spurs Controversy In 1975, an American scientist named Jared Diamond proposed the landmark idea that a single large land reserve would be more beneficial in terms of species richness and diversity than several smaller reserves. His claim was based on his study of a book called The Theory of Island Biogeography by Robert MacArthur and E.O. Wilson. Diamonds assertion was challenged by ecologist Daniel Simberloff, a former student of E.O. Wilson, who noted that if several smaller reserves each contained unique species, then it would be possible for smaller reserves to harbor even more species than a single large reserve. Habitat Debate Heats Up Scientists Bruce A. Wilcox and Dennis L. Murphy responded to an article by Simberloff in The American Naturalist journal by arguing that habitat fragmentation (caused by human activity or environmental changes) poses the most critical threat to global biodiversity. Contiguous areas, the researchers asserted, are not only beneficial to communities of interdependent species, they are also more likely to support populations of species that occur at low population densities, particularly large vertebrates. Harmful Effects of Habitat Fragmentation According to the National Wildlife Federation, terrestrial or aquatic habitat fragmented by roads, logging, dams, and other human developments may not be large or connected enough to support species that need a large territory in which to find mates and food. The loss and fragmentation of habitat make it difficult for migratory species to find places to rest and feed along their migration routes. When habitat is fragmented, mobile species that retreat into smaller reserves of habitat can end up crowded, increasing competition for resources and disease transmission. The Edge Effect In addition to interrupting contiguity and decreasing the total area of available habitat, fragmentation also magnifies the edge effect, resulting from an increase in the edge-to-interior ratio. This effect negatively impacts species that are adapted to interior habitats because they become more vulnerable to predation and disturbance. No Simple Solution The SLOSS Debate spurred aggressive research into the effects of habitat fragmentation, leading to conclusions that the viability of either approach may depend on the circumstances. Several small reserves may, in some cases, be beneficial when indigenous species extinction risk is low. On the other hand, single large reserves may be preferable when extinction risk is high. In general, however, the uncertainty of extinction risk estimates leads scientists to prefer the established habitat integrity and security of a single larger reserve. Reality Check Kent Holsinger, Professor of Ecology and Evolutionary Biology at the University of Connecticut, contends, This whole debate seems to have missed the point. After all, we put reserves where we find species or communities that we want to save. We make them as large as we can, or as large as we need to protect the elements of our concern. We are not usually faced with the optimization choice poised in the [SLOSS] debate. To the extent we have choices, the choices we face are more like †¦ how small an area can we get away with protecting and which are the most critical parcels?