While I was in school, I acquired substantial information regarding how computers can be programmed and also used with the growth in technology. Since this period, my desire and fascination in computers and programming grew rapidly. When I joined secondary school, I learned various programming languages including C++ and HTML. This enabled me to conduct a presentation concerning these languages during the career day in the school. My fellow students were extremely amazed based on my understanding
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Involved in developing suitable algorithm for Sequential Linear Programming (SLP) in order to obtain the topology optimization for compliant mechanism. Jul 1994- May 1997 Diploma in Manufacturing Engineering specialized in Automation system design in NANYANG POLYTECHNIC, GERMAN SINGAPORE INSTITUTE. Final Year Project: Involved in Bosch Robot Programming, retrofitting electrical component and re-wiring for 3-pin plug
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Congram@paconsulting.com • C.N.Potts@maths.soton.ac.uk • S.Velde@fac.fbk.eur.nl Richard K. Congram • Chris N. Potts • Steef L. van de Velde T his paper introduces a new neighborhood search technique, called dynasearch, that uses dynamic programming to search an exponential size neighborhood in polynomial time. While traditional local search algorithms make a single move at each iteration, dynasearch allows a series of moves to be performed. The aim is for the lookahead capabilities of dynasearch
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1. Factorial program in cFactorial program in c: c code to find and print factorial of a number, three methods are given, first one uses for loop, second uses a function to find factorial and third using recursion. Factorial is represented using '!', so five factorial will be written as (5!), n factorial as (n!). Alson! = n*(n-1)*(n-2)*(n-3)...3.2.1 and zero factorial is defined as one i.e. 0! = 1. #include <stdio.h> int main() { int c, n, fact = 1; printf("Enter a number to
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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
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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
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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
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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
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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
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