...Accomplishments of Dr. Segrè i The Life, Times and Accomplishments of Dr. Emilio Segrè Zachary Gaston English 1010-02 Dr. Bray November 24, 2008 Accomplishments of Dr. Segrè 1 Emilio Segrè was born in Tivoli, Italy on February 1st, 1905. His parents were Giuseppe Segrè, the manufacturer, and Amelia Treves, his mother. His father ran a papermaking and hydroelectric plant and his uncles were scholars, lawyers, and engineers that were well respected in Italy’s intelligence community. Emilio was born into a prosperous Jewish family making him have a happy, pampered, childhood. Being the youngest of the three brothers he always admired Angelo Marco and Marco Claudio. When he was not attending elementary school, he would always spend his time playing in the famous gardens of Villa d’ Este or as Gale (2005) said, “Reading La Scienza per Tutti, which was a popular science magazine called Science for Everybody” (Document 3). As Gale (2005) said, “In his first years of high school, Segrè lacked any interest in the studies of law or in history and most of it was a waste of time” (Document 3). Specialized subjects, including basic engineering, were also taught and this would become the start of his primary occupation. Professor Monti was one of his favorite teachers during his adolescent days in school. In physics he always made him concentrate on the force equation F = ma until he really understood...
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...Particle Accelerator Since the evolution of advancement and science mankind always wondered about the existence of this universe and how it came into being. To answer these queries great scientists put forward many theories. Two most famous of them are “The Bing Bang Theory” and “The String Theory”. Nevertheless these are just theories. Therefore in order to prove them scientists at present using modern technology such as “The Large Hadron Collider” trying to stimulate what really happened at the beginning of time and space. This technology is also the Particle Accelerator as it accelerates particles such as Atoms at close to the speed of light. A Brief History of Time and Space “Is not He who created the heavens and the earth Able to create the likes of them? Yes; and He is the Knowing Creator. His command is only when He intends a thing that He says to it, ‘Be,’ and it is.” (Quran 36:81-82) The Big Bang theory states that around 12-15 billion years ago the universe came into existence from one single extremely hot and dense point, and that something triggered the explosion of this point that brought about the beginning of the universe. Matter was created along with its opposite antimatter. Time and space began at the moment of Big Bang. The Large Hadron Collider/ the Particle Accelerator The Large Hadron Collider is the largest and most powerful particle accelerator ever built. It was built by the European Organization for Nuclear Research (CERN) from 1998 to 2008, with...
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...When Google chief financial officer Patrick Pichette said the tech giant might bring10 gigabits per second internet connections to American homes, it seemed like science fiction. That’s about 1,000 times faster than today’s home connections. But for NASA, it’s downright slow. While the rest of us send data across the public internet, the space agency uses a shadow network called ESnet, short for Energy Science Network, a set of private pipes that has demonstrated cross-country data transfers of 91 gigabits per second–the fastest of its type ever reported. NASA isn’t going bring these speeds to homes, but it is using this super-fast networking technology to explore the next wave of computing applications. ESnet, which is run by the U.S. Department of Energy, is an important tool for researchers who deal in massive amounts of data generated by projects such as the Large Hadron Collider and the Human Genome Project. Rather sending hard disks back and forth through the mail, they can trade data via the ultra-fast network. “Our vision for the world is that scientific discovery shouldn’t be constrained by geography,” says ESnet director Gregory Bell. In making its network as fast as it can possibly be, ESnet and researchers are organizations like NASA are field testing networking technologies that may eventually find their way into the commercial internet. In short, ESnet a window into what our computing world will eventually look like. The Other Net The first nationwide computer...
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...form of matter that is acting within the galaxy; which could have certain properties that explain the larger amount of gravity e.g. more massive matter. Properties of Dark Matter: Figure 1 Figure 1 Dark matter is hard to “get your head” around as scientists say that you can’t see it; then how can it exist? Dark matter is said to be “non-luminous”, therefore it does not absorb, give off or reflect light, which means we cannot observe the existence of Dark Matter (But we could detect it: See section on “Detection”). Detection: Although we cannot see Dark Matter it supposedly makes up 22% of the universe, compared to 4% of normal matter (See Figure 1). The evidence of how dark matter could exist is from experiments held in particle accelerators, such as the Large Hadron Collider at CERN. As Dark Matter does not interact with electromagnetic forces, the detectors may not be able to detect dark matter in a collision of two or more particles in an experiment. However if the energy of the particles before the collision is not equal the energy of the products after the collision the energy could be lost to Dark matter that we cannot detect. Dark matter often occurs in research and...
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...Session 13 - Homework Problems Miguel Faundez Chapter 13 13.4 Answers a) The scatter plot shows a positive linear relationship. b) For each increase in shelf space of an additional foot, weekly sales are estimated to increase by $7.40. c) Y=145+7.4X=145+7.4(8)=204.2, or $204.20. 13.5 Answers a) From the scatter diagram, we can see that there exists positive relation between reported and audited magazine. b) The slope, B1=26.724 implies that for a unit increment in number of reported magazines, there will be 26.724 increment in the dependent variable, Audited number of magazines. c) The predicted audited newsstand sales for magazine that report newsstand sales of 400,000(X=400) is audited=0.5718+26.724x400=10690.1718. 13.16 Answers a) 20,535/30,025=0.684. 68.4% of the variation in sales can be explained by the variation in shelf space. b) √9,490/10=30.8058. c) Based on a) and b), the model should be useful for predicting the labor hours. 13.17 Answers a) r2 = 130,301.41/144,538.64 = .901498796 This means that 90.15% of the variation in audited sales is explained by the variability in reported sales. b) Formula = SST = SSR + SSE SST-SSR = SSE 144.538.64 – 130,301.41 = 14,237.23 SSE = 14,237.23 SYX = √SSE/ (n – 2) = √14,237.23/ (10 – 2) = √1779.65 SYX = 42.1859 c) This regression model is very helpful in predicting audited sales 13.24 Answers a) A residual analysis of the data indicates a pattern, with sizable clusters of...
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...INTRODUCTION Background Driving Simulators are used for entertainment as well as in training of driver's education courses taught in educational institutions and private businesses. They are also used for research purposes in the area of human factors and medical research, to monitor driver behavior, performance, and attention and in the car industry to design and evaluate new vehicles or new advanced driver assistance systems (ADAS). Training Driving simulators are being increasingly used for training drivers all over the world. Research has shown that driving simulators are proven to be excellent practical and effective educational tools to impart safe driving training techniques for all drivers. Uses • • • • • • • User training Training in critical driving conditions Training for impaired users Analysis of the driver behaviours Analysis of driver responses Analysis of the user performances Evaluating user performances in different conditions (handling of controls) Entertainment Apart from training drivers, driving simulators are also used for entertainment purposes like giving video games a more realistic feel. Steering wheels and seats can be purchased and synchronised with game consoles to be used when playing racing games. 1 Research Driving simulators are used at research facilities for many purposes. Some vehicle manufacturers operate driving simulators. Many universities also operate simulators for research. In addition to studying driver training issues...
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...Unit Four – Case Analysis 1) Describe the primary system described in the story including the parts of the system, the system’s purpose, and the larger system in which it is embedded. The primary system described in The Tip of the Iceberg involved an iceberg, penguins, walruses, and clams. The penguins were living on an iceberg which had a clam bed beneath it. The penguins did not have the tools (sufficient lung capacity or tusks) to crack open the clams, but the walruses did. The walruses were respectful of the penguins’ territory and were not going to access the penguins’ clams without their permission. The penguins had an idea to ask the walruses to harvest the clams for them and in return the walruses could eat clams alongside them as long as they don’t eat the penguins. As more penguins heard of this treaty and made their way to the iceberg more walruses were needed to meet the demand. The system was looped; as more penguins arrived, more clams were needed, and thusly more walruses were also needed. Due to the increase weight of the penguins and walruses, the iceberg began to sink causing the capacity of the iceberg to decrease. The decrease in area resulted in penguins being sat on which lead to fighting amongst the groups. Such fighting makes the appeal of the iceberg decrease which brings the loop back to the number of penguins and walruses wanting clams and iceberg access. Ultimately, the entire penguin, walrus, clam, and iceberg system is part of a larger system...
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...it would mean to a manager (AIU Online). Introduction Regression analysis can help us predict how the needs of a company are changing and where the greatest need will be. That allows companies to hire employees they need before they are needed so they are not caught in a lurch. Our regression analysis looks at comparing two factors only, an independent variable and dependent variable (Murembya, 2013). Benefits and Intrinsic Job Satisfaction Regression output from Excel SUMMARY OUTPUT Regression Statistics Multiple R 0.018314784 R Square 0.000335431 The portion of the relations explained Adjusted R Square -0.009865228 by the line 0.00033% of relation is Standard Error 1.197079687 Linear. Observations 100 ANOVA df SS MS F Significance F Regression 1 0.04712176 0.047122 0.032883 0.856477174 Residual 98 140.4339782 1.433 Total 99 140.4811 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 4.731133588 1.580971255 2.992549 0.003501 1.593747586 7.86852 Intrinsic -slope 0.055997338 0.308801708 0.181338 0.856477 -0.5568096 0.668804 Line equation is benefits =4.73 + 0.0559 (intrinsic) Intercept- t-stat HO: Coefficients is zero. Intrinsic t-stat is zero...
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...Michelle D. Griner MAT540 – Professor Johnson Strayer University Formulate a linear programming model for Julia that will help you to advise her if she should lease the booth. Formulate the model for the first home game. Explain how you derived the profit function and constraints and show any calculations that allow you to arrive at those equations. Let, X1 =No of pizza slices, X2 =No of hot dogs, X3 = No of barbeque sandwiches Objective function co-efficient: The objective is to maximize total profit. Profit is calculated for each variable by subtracting cost from the selling price. For Pizza slice, Cost/slice=$4.5/6=$0.75 | X1 | X2 | X3 | SP | $1.50 | $1.60 | $2.25 | -Cost | $0.75 | $0.50 | $1.00 | Profit | $0.75 | $1.10 | $1.25 | Maximize Total profit Z = $0.75X1 + 1.10X2 +1.25X3 * Constraints: 1. Budget constraint: 0.75X1 + 0.50X2 + 1.00X3 ≤ $1500 2. Space constraint: Total space available = 3*4*16=192 sq feet =192*12*12=27,648 sq. in. The oven will be refilled during half time. Thus, the total space available = 2*27,648 = 55,296 sq. in. Space required for a pizza = 14*14 = 196 sq. in. Space required for a slice of pizza = 196/6 = 32.667 sq. in. approximately. Thus, space constraint can be written as: 33X1 + 16X2 +25X3 ≤ 55,296 (sp. in of oven space) 3. at least as many slices of pizza as hot dogs and barbeque sandwiches combined X1 ≥ X2 + X3 (at least as many slices of pizza as hot dogs and barbeque sandwiches ...
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...Forecasting Methods Genius forecasting - This method is based on a combination of intuition, insight, and luck. Psychics and crystal ball readers are the most extreme case of genius forecasting. Their forecasts are based exclusively on intuition. Science fiction writers have sometimes described new technologies with uncanny accuracy. There are many examples where men and women have been remarkable successful at predicting the future. There are also many examples of wrong forecasts. The weakness in genius forecasting is that its impossible to recognize a good forecast until the forecast has come to pass. Some psychic individuals are capable of producing consistently accurate forecasts. Mainstream science generally ignores this fact because the implications are simply to difficult to accept. Our current understanding of reality is not adequate to explain this phenomena. Trend extrapolation - These methods examine trends and cycles in historical data, and then use mathematical techniques to extrapolate to the future. The assumption of all these techniques is that the forces responsible for creating the past, will continue to operate in the future. This is often a valid assumption when forecasting short term horizons, but it falls short when creating medium and long term forecasts. The further out we attempt to forecast, the less certain we become of the forecast. The stability of the environment is the key factor in determining whether trend extrapolation is an appropriate forecasting...
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...MODELS FOR ESTIMATION OF ISOMETRIC WRIST JOINT TORQUES USING SURFACE ELECTROMYOGRAPHY by Amirreza Ziai B.Eng., Sharif University of Technology, Tehran, 2008 THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF APPLIED SCIENCE In the School of Engineering Science Faculty of Applied Science © Amirreza Ziai 2011 SIMON FRASER UNIVERSITY Summer 2011 All rights reserved. However, in accordance with the Copyright Act of Canada, this work may be reproduced, without authorization, under the conditions for Fair Dealing. Therefore, limited reproduction of this work for the purposes of private study, research, criticism, review and news reporting is likely to be in accordance with the law, particularly if cited appropriately. APPROVAL Name: Degree: Title of Thesis: Amirreza Ziai M.A.Sc Models for estimation of isometric wrist joint torques using surface electromyography Examining Committee: Chair: Parvaneh Saeedi, P.Eng Assistant Professor – School of Engineering Science ______________________________________ Dr. Carlo Menon, P.Eng Senior Supervisor Assistant Professor – School of Engineering Science ______________________________________ Dr. Shahram Payandeh, P.Eng Supervisor Professor – School of Engineering Science ______________________________________ Dr. Bozena Kaminska, P.Eng Examiner Professor – School of Engineering Science Date Defended/Approved: _________September 2, 2011 ______________ ii ABSTRACT With an aging...
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...coordinates of the image are (8, -1). Example 2: A rectangle has coordinates (1, 1), (4, 1), (4, 3) and (1, 3). Find the coordinates of the image of the rectangle under the transformation represented by the matrix . Solution: You could find the image of each vertex in turn by finding , etc. However, it is more efficient to multiply the transformation matrix by a rectangular matrix containing the coordinates of each vertex: . So the image has coordinates (2, 0), (11, -3), (9, -1) and (0, 2). The diagram below shows the object and the image: Any transformation that can be represented by a 2 by 2 matrix, , is called a linear transformation. 1.1 Transforming the unit square The square with coordinates O(0, 0), I(1, 0), J(0, 1) and K(1, 1) is called the unit square. Suppose we consider the image of this square under a general linear transformation as represented by the matrix : . We therefore can notice the following things: * The origin O(0, 0) is mapped to itself; * The image of the point I(1, 0) is (a, c), i.e. the first column of the transformation matrix; * The image of the point J(0, 1) is (b, d), i.e. the second column of the transformation matrix; * The image of the point K(1, 1) is (a + b, c+ d), i.e. the result of finding the sum of the entries in each row of the matrix. Example: Find the image of the...
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...Churn Prediction Vladislav Lazarov vladislav.lazarov@in.tum.de Technische Universität München Marius Capota Technische Universität München mariuscapota@yahoo.com ABSTRACT The rapid growth of the market in every sector is leading to a bigger subscriber base for service providers. More competitors, new and innovative business models and better services are increasing the cost of customer acquisition. In this environment service providers have realized the importance of the retention of existing customers. Therefore, providers are forced to put more efforts for prediction and prevention of churn. This paper aims to present commonly used data mining techniques for the identification of churn. Based on historical data these methods try to find patterns which can point out possible churners. Well-known techniques used for this are Regression analysis, Decision Trees, Neural Networks and Rule based learning. In section 1 we give a short introduction describing the current state of the market, then in section 2 a definition of customer churn, its’ types and the imporance of identification of churners is being discussed. Section 3 reviews different techniques used, pointing out advantages and disadvantages. Finally, current state of research and new emerging algorithms are being presented. given a huge choice of offers and different service providers to decide upon, winning new customers is a costly and hard process. Therefore, putting more effort in keeping churn low has become...
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...which can be described by a probability distribution. Regression analysis is widely used for prediction and forecasting, where its use has substantial overlap with the field of machine learning. Regression analysis is also used to understand which among the independent variables are related to the dependent variable, and to explore the forms of these relationships. In restricted circumstances, regression analysis can be used to infer causal relationships between the independent and dependent variables. However this can lead to illusions or false relationships, so caution is advisable:[1] see correlation does not imply causation. A large body of techniques for carrying out regression analysis has been developed. Familiar methods such as linear regression and ordinary least...
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...Section 9-1 1. Identify each type of filter response in Figure 9-32. A)Band-pass B)High-pass C)Low-pass D)Band-stop 2. A certain low-pass filter has a critical frequency of 800 Hz. What is its bandwidth? For this low-pass filter with fc of 800 Hz, the bandwidth is 800Hz. 3. A single-pole high-pass filter has a frequency-selective network with R=2.2 kΩ and C=0.0015µF. What is the critical frequency? fc=1/2πRC=1/(2π(2200Ω)(.0000000015F))= 48.2kHz Can you determine the bandwidth from the available information? No. 4. What is the roll-off rate of the filter described in Problem 3? As a single-pole filter it has a roll-off rate of -20 dB\decade. 5. What is the bandwidth of a band-pass filter whose critical frequencies are 3.2 kHz and 3.9 kHz? BW=fc2-fc1=3.9kHz-3.2kHz=700Hz What is the Q of this filter? Q=fo/BW= √fc1fc2/700Hz= √(3.2×3.9)/700=5.05 6. What is the center frequency of a filter with a Q of 15 and a bandwidth of 1 kHz? Q=fo/BW 15= fo/1kHz=15kHz Section 9-2 7. What is the damping factor in each active filter shown in Figure 9-33? DF=2-R1/R2 a)2- 1.2/1.2=1 b)2- 560/1000=1.44 c)both stage 1&2: 2- 330/1000=1.67 Which filters are approximately optimized for a Butterworth response characteristic? b)2- 560/1000=1.44 8. For the filters in Figure 9-33 that do not have a Butterworth response, specify the changes necessary to convert them to Butterworth responses...
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