Rising Gas Prices in the United States Essay -- The Oil Industry

Sometime in the distant past Americans jumped into their vehicles on warm spring days and took lengthy drives to respect the magnificence of nature. Adolescents took moonlight trips around town to meet companions and rode starting with one â€Å"hot spot† then onto the next. Those were the days when gas costs were moderate to the normal American. In the course of recent years, gas costs in the United States have been on the ascent. What is causing the expansion in gas costs? To comprehend the expansion in gas costs, one should initially distinguish the dispersion of dollars paid per gallon at the siphon. As indicated by the U.S. Vitality Information Administration (eia) in 2010, the yearly normal paid at the siphon comprised of 68% raw petroleum, 7% refining, 10% conveyance and showcasing, and 15% expenses (see Fig.1). This shows an expansion of raw petroleum over the 2000-2009 normal of 51%. (e. I. Organization) As of now, the most significant factor in the ascent of gas costs is the expanding cost of unrefined petroleum. Shockingly, the United States has three percent of the world’s oil holds. (Horsley) In 2009, the United States was third in raw petroleum creation just as the world’s biggest oil customer. (e. I. Organization) Such utilization required and still requires the United States to import oil/raw petroleum from different nations. Principally, the United States imports oil based goods and unrefined petroleum from Canada 23.3%, Venezuela 10.7%, Saudi Arabia 10.4%, Mexico 9.2%, and Nigeria 8.3%. (e. I. Organization) what's more, around 77 different nations import to the United States. (e. I. Organization) Around the world, there are numerous variables adding to the expansion in cost per barrel. Most as of late, Libyan dissidents, propelled by the accomplishment of their Tunisian and Egyptian neighbors, are up... ... Oil Production.† 10 March 2011. 19 March 2011 . Press, Associated. â€Å"MSNBC Oil Prices Fall as Libya Promises Ceasefire.† 18 March 2011. 19 March 2011 . Press, Associated. â€Å"Oil Hits Highest Levels Since Recession.† 25 March 2011. 25 March 2011 . Press, The Associated. â€Å"IEA Says Libyan Oil Exports Halted.† 15 March 2011. 25 March 2011 . Reuters. â€Å"Factbox: Libyan Oil Production, Exports, Customers.† 11 February 2011. 20 March 2011 .

What is outsourcing Essay -- Globalization essays, research papers

Pornography Research Paper Example | Topics and Well Written Essays - 2000 words

Erotic entertainment - Research Paper Example As per the examination paper Sex entertainment discoveries, it is imperative to comprehend that different gatherings in the network have considered sex entertainment for instance of a substance that advances extramarital perversion. On this premise, there have been endeavors to blue pencil the creation of explicit materials, just as giving lawful limitations against their creation, just as distribution. Notwithstanding, Johansson and Nils (60) discloses that because of the various meanings of erotic entertainment, in view of the national, recorded, just as social settings, this part of sex entertainment has flourished. Besides, in the twentieth century, there was the improvement of social mentalities that are progressively lenient to introduction and conversations of sex and its related elements. This expanded the advancement of sex entertainment, mostly in light of the fact that numerous nations began loosening up laws with respect to the creation and distribution of explicit materi als. Besides, Johansson and Nils (61) clarifies that the advancement of the web and the home video made it workable for a blast in the worldwide obscene industry, and this aides in producing billions of dollars in a year. McKee (36) indicates that in the referenced film, the female character has been utilized as a portrayal of erotic entertainment. In this film, Bettie, a female character is utilized to model for naked pictures, and photos, for explicit magazines, and studios. McKee (38) clarifies that in most explicit materials, ladies are constantly portrayed as sex images and articles. This outcomes in the annihilation of the excellencies of the ladies viable. This is obviously delineated in the film, whereby Bettie Page can't discover companions, due to an awful name.

Emeregency Management (Basic Quantitative Methods) Essay

Emeregency Management (Basic Quantitative Methods) - Essay Example Since wellbeing impacts are remembered for the extent of results, at that point it might be said that according to ASME details, seriousness of wounds would have been incorporated as a major aspect of the evaluation of hazard as right on time as the advantage portrayal stage. Other ASME writing makes further reference to seriousness, this time in direct relationship to casualty or injury, an outlines with a table of â€Å"severity ranking†. In this positioning scale, S5 (â€Å"Very High†) indicates â€Å"offsite fatalities and various on location fatalities†; S4 (â€Å"High†) is the â€Å"severity rank for the chance of on location fatalities just as offsite injuries†; S3 (â€Å"Medium†) is assigned to the nonappearance of â€Å"fatalities or wounds foreseen offsite, yet with the conceivable far reaching nearby genuine injuries.† S2 (â€Å"Low†) is assigned for â€Å"onsite wounds that are not boundless but rather just in the region of the incident†; and S1 (â€Å"Very Low†) is related with â€Å"possible minor injury on location; no fatalities or wounds foreseen offsite† (ASME, 2006:28). Such a positioning would lead one to reason, in this manner, that to be sure RAMCAP would ta ke into account the thought of seriousness of wounds foreseen in a potential occurrence. Smith (2006, April), introducing the case for the U.S. Division of Homeland Securities, is slanted to concur with the ASME. Then again, a progressively cautious perusing of the Cox (2008) article, as of now referenced, explicitly expressed RAMCAP doesn't think about seriousness of wounds (p.1750), in spite of the fact that it allows for the â€Å"severity of conceivable unfavorable consequences† (p.1755). Cox contends that there are not kidding confinements of â€Å"severity† in the RAMCAP model, which basically requires the estimation of all components in quantitative terms. First confinement is that there is â€Å"no target conviction proportionate for dubious

Reaction paper 2 Essay Example | Topics and Well Written Essays - 500 words - 1

Response paper 2 - Essay Example Beam Eddy resorts to direct unlawful business after her better half left with all the family reserve funds. Vortex and her two youngsters no longer can get by on the pitiful wages she gets from her stores. She meets Lila, who recently, has been in the matter of sneaking foreigners. The two motion pictures have amazing differentiations. The exposition delineates key contrasts clear in the two movies. The main distinction between the two movies identifies with their creation. Karate Kid is a Hollywood film. The creation was kindness of Sony Pictures, which makes it a significant studio film (Horn 1). Solidified waterway, despite what might be expected, was a creation of the Cohen Media Group organization. Different organizations credited for the film’s creation are Harwood Hunt Productions and Off Hollywood Pictures. Its run time is 98 minutes. That is in opposition to the Karate Kid that has a runtime of 2 hours 20 minutes. There is an astounding contrast in the way wherein watchers are spoken to in the two movies. That clarifies the distinctions wherein eurocentrism works in the two movies. Eurocentrism identifies with impression of exceptionalism of Europe that created to a perspective after western human advancement. Hollywood, over quite a while, has advanced the idea of Eurocentrism in many motion pictures and movies. Fundamentally, such movies portray the apparent incomparability that Europe holds. Eurocentrism is clear in the Karate Kid delineated through its characters. It suggests that normal thought of prevalence clear in Dre over learn and contend with peers, who were at first prevalent. That stresses eurocentrism being that the two characters, Dre and Wang are from various locales. That contrasts from the delineation of characters in the Frozen River. The film doesn't uncover Eurocentrism and parts of prevalence. There is distinction in the way in which non-White fundamental characters in the two movies

Writing an Abstract For Research Paper

Writing an Abstract For Research PaperIt is difficult to write an abstract for research paper. The ideas can be complex and be relevant in different fields of research but when one talks about the abstract they tend to have a restricted meaning. The ideas in it are generally limited to those that are important to the writer.Abstract for research paper is not that difficult if one has the right ideas. Ideas that are relevant to research often fall under the categories of scientific and technological advances. These ideas can be grouped under the topics of ecology, conservation, nutrition, and human development. These subjects have simple ideas and do not contain complex ideas, which makes them easy to make use of.Abstract for research paper usually deals with questions regarding some new breakthrough in the field of ecology, conservation, or human development. These are answers that usually fall under some new concept. The idea is sometimes conceptualized to make it more simple. When it is done in a simple way, it can help the writer to write the paper faster and easier.A good abstract for research paper will not make use of complex or complicated ideas but rather it should stick to a few ideas. Complex ideas are easily dismissed when writing. Simplicity is usually perceived as more interesting. People are more interested in the ideas of simple concepts than those of complex ones.If the research paper is related to some new concept, then it is best that the researcher makes it simple. The abstract should include a few basic ideas, so that it can easily be understood by the readers. The ideas that are useful to the readers should be included in the abstract for research paper. While the ideas in the abstract are relevant to the research work that the researcher is doing, it should also be convenient to the reader.Abstract for research paper can be of several formats. It can be in essay form or it can be in the form of some research report. This depends on the nee ds of the researcher.Sometimes a writer may be required to meet some deadlines before the deadline of the abstract for research paper. In such situations, the writer may have to rewrite the abstract for research paper. The introduction section is the first section of the research paper. The section is usually in essay form. Some writers may even include a brief summary of the main points and ideas in the essay form.Abstract for research paper is normally an idea of what the researcher is researching. The information contained in the abstract is designed to allow the readers to understand the information of the paper that has been written.

Network Opimisation Problems And Forecasting - Free Essay Example

The Makonsel Company, a fully integrated company that both produces and sells goods at its retail outlets. After production, the goods are stored in companys two warehouses until needed by the retail outlets. Trucks are used to transport the goods from the two plants to the warehouses, and then from the warehouses to the three retail outlets. Using units of full truckloads, the following table shows each plants monthly output, its shipping cost per truckload sent to each warehouse, and the maximum amount that it can ship per month to each warehouse. Unit Shipping Cost For each retail outlet (RO), the next table shows its monthly demand, its shipping cost per truckload from each warehouse, and the maximum amount that can be shipped per month from each warehouse. Unit Shipping Cost The Managements objective is to determine the shipping plan (number of truckloads shipped per month from each plant to each warehouse and from each warehouse to each retail outlet) that will minimise the total shipping cost. In order to achieve the objective, the following issues will be discussed : The distribution network of Makonsel Company, algebraic formulation for the network model, spreadsheet formulation for this problem by using the solver of excel and interpretation and recommendation of the result. The distribution network A network model for the Makonsel Company problem as a minimum-cost flow problem According to the data from the table above we put it into a distribution network. The supply nodes in this network are P1 (plant1) and P2 (plant2), the transshipment nodes are W1 (warehouse1) and W2 (warehouse2) and the demand nodes in this network are RO1, RO2 and RO3. And the shipping cost and the shipping capacity differ considerably among these shipping lanes. The cost per unit shipped and the maximum amount that it can ship per month (given in square brackets of the arc) through each lane is shown above corresponding arrow in the above Figure. Algebraic Formulation Solution: Decision variables Makonsel must determine how much to ship per month from each plant to each warehouse and from each warehouse to each retail outlet. Let Xij = Number of truckloads to ship from i to j (i = P1, P2; j = W1, W2). Let Xjk =Number of truckloads to ship from j to k (j =W1, W2 k=RO1, RO2, RO3). Then Makonsels problem may be formulated as Objective: Subject to: The first five constraints ensure that each retail outlet is meet their monthly demand, and the 2 Sources constraints are ensure that each plants monthly output and the last 10 ensure the maximum amount that can be shipped per month. Spreadsheet Formulation After we finished the algebraic formulation, we can transform them to spreadsheet, and using the solver of Excel to work out the distribution problem. The spreadsheet formulations are all showed in the graph below. A spreadsheet model for the Makonsel Company minimum-cost flow problem, where the changing cells (C4:C13) show the optimal solution obtained by the Solver and the target cell (E15) gives the resulting total cost of the flow through the network. Interpretation and Recommendation The optimal solution for the Makonsel Company problem, where the shipping amounts are shown in parentheses over the arrows By using excel we can calculate the minimum total shipping cost of Makonsel Company is  ¿Ãƒâ€šÃ‚ ¡488.125. In order to make the minimum total monthly shipping cost of  ¿Ãƒâ€šÃ‚ ¡488.125, the Makonsel Company should first transport 125 truckloads per month from plant 1to warehouse 1 and 75 units to warehouse 2. And ship 175 truckloads per month from plant 2 to warehouse 1, ship 125 truckloads per month to warehouse2. After that the retail outlet1, retail outlet 2 and retail outlet 3 should get 100 truckloads, 50 truckloads and 100 truckloads from warehouse 1 respectively. And should separately transport 50 truckloads, 150 truckloads and 50 truckloads from warehouse 2 to retail outlet1, retail outlet 2 and retail outlet 3. As we have known the shipping cost per truckload from each plant and each warehouse from the table. Thus the Minimum Cost= 425*125+560*75+510*125+600*175+470*100+505*50 +490*100+390*50+410*150+440*50 =488,125 Conclusion Determined the shipping plan which can minimise the total shipping cost is the management objective of Makonsel Company. By building the distribution network , formulating the constraints and calculating the result through using the solver of excel , Makonsel Company successfully solve the distribution network problem and construct the shipping plan with the minimum total shipping cost of  ¿Ãƒâ€šÃ‚ ¡488.125. Forecasting Introduction The time-series below relates to the Sales of a company (00s) for the last five years. The objective is to use the information contained in the time-series data above to construct a forecast of the next four quarters sales. In order to achieve the objective, the following issues will be discussed: Analysis this time-series, Detrend a Time-Series and construct the Seasonal Indices by MINITAB, Forecasting the next four quarters sales and use measures to identify the forecast accuracy, Reservations about the appropriateness of the forecasting procedure used. Time-series Analysis Main characteristics of this time-series The first step in any forecasting exercise is to plot a graph of the time-series. We transfer the data from the table to Minitab and use the time series plot-simple of Minitab to make the graph, since the time-series was recorded in quarter, so we choose the quarter of calendar in time scale. The plot of this time-series looks like: Form the graph above We can roughly find out that there is a decreasing trend over time, a clear quarterly seasonal effect and it is a table time series, the pattern is regular with little random noise. With the purpose of confirming the characteristics of the time-series, we use the cantered moving averages (CMA). Since the CMA is the average and smoothed data of the actual figures, which is much easier for us to determine the characteristics of the time-series, we use this plot instead. As the time-series was recorded in quarters and with quarterly seasonal effect so the length of moving average is 4, and chose the moving averages, plot the g raph smoothed vs. actual. Negative Trend Structure, an decreasing trend over time It is a negative trend structure. Look at the smoothed line of this time-series, as at the beginning of the time-series the sales of this company is about 485 ,however , it keeps decreasing and from about 485 down to around 478 to roughly 471 and finally it decrease to around 405. A clear seasonal structure , additive seasonal structure It can be seen from the graph above that there is a clear quarterly seasonal structure, for each quarter 1 the actual observed value is about 13 units below the trend value. For quarters 2, 3 4 estimating from the graph the actual observed values are 30 above, 22 above and 23 below the estimated trend values. Seasonal Structures: Q1 Q2 Q3 Q4 -13 30 22 -23 These are estimates of the seasonal indices; and also in this case, for a given variable the quarter 1 is 13 units below trend, quarter 2, 3 are 30 units and 22 units above trend, quarter 4 is 23 units below trend. And it can be seen from the graph above, seasonal deviation is constant about the trend so this seasonal structure is additive. A table time series, the pattern is regular with little random noise The graph of Moving average plot for sales above shows us that the pattern is regular with little random noise, it decreasing stability of the seasonal pattern, and also from the smoothed line we can find that the series reduce stability, from about 485 down to around 478 to roughly 471, ect. No more than 10units lower. Model the time-series QUADRATIC TREND MODELS There are two trend models ,one is linear trend model (Trend = a + b*t ) and the other is Quadratic trend model (Trend = a + b*t + ct2 ), and as we have been calculated the Cantered Moving Average (CMA)above, which is the average and smoothed line of the actual sales, so by using the CMA, we can use value of these two models to compare with the value of CMA, and then choose the model which the value is much closer to the CMA as our forecasting model. There are three commonly used measures of forecast accuracy: Mean Square Deviation (MSD), Mean Absolute Deviation (MAD) and Mean Absolute Percentage Error (MAPE). And the smaller the data is, the more accurate of the forecast. And it can be seen from the graph above that the Quadratic Trend Model, MAPE=0.43297, MAD=1.91172, MSD = 5.44313, and to the Linear Trend Model, MAPE=0.51281, MAD=2.21232, MSD = 7.74838. The data of the Quadratic Trend Model are all smaller than the Linear Trend Model, which means that the value of quadratic t rend model is much closer than value of the CMA; the quadratic trend model is much more accurate than the linear trend model, so choose the quadratic trend model to forecast. Detrend a Time-Series and construct SI of MINITAB Detrend a Time-Series Detrend a Time-Series, which means Sales-Trend (DIV), the gap between the actual sales and the forecast sales. After we have decided to take the quadratic model to forecast, we can record the data as the trend data, and the plot the graph above to compare with the sales and trend. And use the actual sales data minus the forecast one we can Detrend a Time-Series. As the graph shows us above the DIV1=472-500.367=-28.3673, DIV2=516-493.333=22.6674, DIV3=507-486.459=20.5414, DIV4=462-479.745=-17.7454, etc. By using the Minitab, we can use the calculator to figure the result. Construct the Seasonal Indices by MINITAB As Seasonal Indices is the quarter average of DIV, after we have calculated the DIV, we can use MINITAB to construct the seasonal indices. And in the MINITAB, we use the decomposition to figure out the SI. As we have described before that the sales trend of this company is additive and seasonal and the data were recorded in quarter, so the seasonal indices is four quarters as a unit, the seasonal length is 4 and the model type is additive. And Seasonal Indices is the average of each quarter of DIV, so the seasonal indices can be calculated as below: Quarter1=SI1= (DIV1+DIV5+DIV9+DIV13+DIV17)/5= -24.0937 Quarter2=SI2= (DIV2+DIV6+DIV10+DIV14+DIV18)/5=20.4062 Quarter3=SI3= (DIV3+DIV7+DIV11+DIV15+DIV19)/5=17.2812 Quarter4=SI4= (DIV4+DIV8+DIV12+DIV16+DIV20)/5=-13.5937 Since seasonal indices is the average of each quarter of DIV so SI is quarterly cycle, the value of SI5 will equal to the value of SI1, SI6=SI2, etc. And also it can be seen from graph above that the S I is quarterly cycle. Forecasting and measures of forecast accuracy Future Forecast As the Future Forecast equal Future Trend plus Future Seasonal Indices, so first we should use the CMA to calculate the future trend of the next four quarters. Since the CMA is the average and the smoothed data of the actual data, using the data of CMA can let forecast more accuracy. And the time-series is seasonal structure of quarter, so the number of forecast is 4. And we use trend analysis to calculate the future trend. After we figure out the future trend, copy the first four Seasonal Indices (SI is quarterly cycle) which we have calculated before (-24.0937, 20.4062, 17.2812, -13.5937), as Future Seasonal Indices. And then use the FTrend and FSI to figure out the Future Forecast value (FFC=FTrend+FSI). After figure out the FFC, copy them after the FC to plot a forecast. The plot of time series of sales and forecast looks like: So the next four quarters; Q1, Q2, Q3 Q4 of 2009 are: Q1=366.116, Q2=406.796, Q3=400.011, Q4=365.637 Measures of forecast accuracy After we calculate the forecasts for the next four quarters, we need to know whether the forecast is accurate or not, so we use the three commonly used measures of forecast accuracy: MSD, MPE and MAD to check the forecasts. i. Mean Square Deviation: MSD = S (Xt Ft)2/n ii. Mean Absolute Deviation: MAD = S |Xt Ft| /n iii. Mean Percentage Error: MPE = S |(Xt Ft)/Xt| /n Since all of measures above need the value of Xt Ft (error), so we should calculate the error first. Error = Sales-FC, in the Minitab we use calculator to figure it out. After calculated the error, we can figure out the value of accuracy. MSD = S (Xt Ft)2/n MAD = S |Xt Ft| /n MPE = S |(Xt Ft)/Xt| /n And for this forecast the MSD=29.3526, MAD=4.69560, MPE=1.08963. As we all know for each forecast indicator, the lower value, the higher prediction accuracy. And usually we use the MPE to confirm the accuracy. Lets look at the MPE, the value of MPE is equal to 1.08963%, though the value of M PE is slightly higher than 1%, it close to 1%, the forecast is still accuracy. Reservation In this forecasting procedure we faced two choices, one is determined the seasonal structure of the time-series, determining whether the seasonal structure is additive or multiplicative. And the other one is to confirm the trend model, choosing the linear model or the quadratic model. The choice we make will affect the accuracy of forecasting. Additive or Multiplicative In this forecasting, we analysis the time-series as additive seasonal structure by using method below ¼Ãƒâ€¦Ã‚ ¡ Seasonal Structures: Q1 Q2 Q3 Q4 -13 30 22 -23 In this case ¼Ãƒâ€¦Ã¢â‚¬â„¢for a given variable the quarter 1 is 13 units below trend, quarter 2 is 30 units above trend, etc. This is an Additive Seasonal Index. Alternatively we could have expressed the index as follows: Q1 Q2 Q3 Q4 -13% 30% 22% -23% Here the quarter 1 data is 13% below the trend value, or more conventionally 87% of trend, similarly for the other quarters. It is conventional to express this Seasonal Index as: Q1 Q2 Q3 Q4 87% 130% 122% 77% This is called a Multiplicative Seasonal Index and if the seasonal deviation is proportional to the trend then the seasonal structure is multiplicative. In this case we preferred the additive seasonal structure as the time-series constant about the trend, but in fact it could proportional to the trend and become the multiplicative seasonal structure in the future, so we should make appropriate adjustments base on the future data. Linear or Quadratic model In this case, we modeled the time-series as quadratic model due to the data the company provided closer to the quadratic model now, however, with the future data the model may be transformed into the linear model. Conclusion The objective of the company is to use time-series data to construct a forecast of the next four quarters sales. So as to do the forecast first we analysed the time-series to determine main characteristics of this time-series and modeled it, then found out the difference between the sales and trend to construct the seasonal indices, after that did the forecasting and to identify whether the forecast accurate or not by using the MAD, MSD and MPE. And the next four quarters sales of this company are Q1=366.116, Q2=406.796, Q3=400.011, Q4=365.637. However, during the forecasting procedure we should also consider about the choice we have made whether to choose additive or multiplicative, the linear model or the quadratic model will affect the accuracy of forecasting.