B.Tech. (Computer Science and Engineering) S E M E S T E R C O U R S E FIRST CHM101 PHY101 PHY102 MTH101 HSS-I-1/ ENG112N ESC101 PE101 SECOND TA101 PHY103 MTH102 ESC102 CS100 PE102 THIRD MTH203 CHM201 CS220 ESO-1 ESO211 FOURTH HSS-I-2 TA201 CS201 CS355 OE-1 FIFTH CS330 CS340 ONE OUT OF CS350‚ CS425‚ CS455 SIXTH CS335 CS345 ONE OUT OF CS315‚ CS365‚ CS422 SEVENTH CS498 EIGHTH CS499 In addition to above‚ the student must complete
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eigenvalue is 1 (one). Eigenvalues are introduced in the context of linear algebra or matrix theory. The introduction and development of the notation of matrix and system of linear algebra followed the development of determinant‚ which rose from the study of coefficient system of linear equations. Leibnitz‚ one of the founders of calculus used determinant in 1693 an Cramer presented his determinant - based formula system of solving linear equations (known as Cramer’s’ rule) in 1750. In 1848‚ James J
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Dimensional analysis of models and data sets James F. Pricea) Woods Hole Oceanographic Institution‚ Woods Hole‚ Massachusetts 02543 Received 22 May 2002; accepted 4 November 2002 Dimensional analysis is a widely applicable and sometimes very powerful technique that is demonstrated here in a study of the simple‚ viscous pendulum. The first and crucial step of dimensional analysis is to define a suitably idealized representation of a phenomenon by listing the relevant variables‚ called the physical
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voltage that is typically hundreds of thousands of times larger than the voltage difference between its input terminals.[2] Operational amplifiers had their origins in analog computers where they were used to do mathematical operations in many linear‚ non-linear and frequencydependent circuits. Characteristics of a circuit using an op-amp are set by external components with little dependence on temperature changes or manufacturing variations in the op-amp itself‚ which makes op-amps popular building
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money to the government.| _A___ 6. Linear programming problems have a.|linear objective functions‚ non-linear constraints.| b.|non-linear objective functions‚ non-linear constraints.| c.|non-linear objective functions‚ linear constraints.| d.|linear objective functions‚ linear constraints.| ____C 7. The first step in formulating a linear programming problem is a.|Identify any upper or lower bounds on the decision variables.| b.|State the constraints as linear combinations of the decision variables
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by making use of important geometric and econometric concepts such as a ‘linear manifold’‚ a ‘plane of support’‚ a ‘projection matrix’‚ ‘linearly estimable parametric functions’‚ ‘minimum variance estimators’ and ‘linear transformations’‚ seeks to explore the role of a Concentration Ellipsoid as a geometric tool in the interpretation of certain key econometric results connected with the efficiency of estimators of the linear regression model and thereby present these econometric results in a whole
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years of the Olympic Games‚ and y axis is the dependent variables which represents the heights that are achieved by the gold medalists. Also it shows that it is not constant. Linear Regression To create a certain equation‚ you draw the best fit line on the graph. The difference between the red graph and the linear function is that the red does not have a predictable pattern. When the best fit is drawn it is possible to find the equation of this graph. Though the equation that is made by the
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Linear Function :(Module): Sharmaine N. Sayao Mathematics IV-A Mrs. Imelda Sayao 1.1 Definition of a Linear Function A linear function is a function whose graph is a straight line. The equation of a linear function of x can be written in the form f(x) = mx + b or a linear equation y = mx + b where m is the slope and b is the y-intercept. The equation in the form Ax + By = C where A‚ B and C are real numbers is referred to as the general form of a linear equation. We
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copyright; see http://www.siam.org/journals/ojsa.php Vol. 4‚ No. 1‚ pp. 208-227‚ February 1994 1994 Society for Industrial and Applied Mathematics 012 ON THE CONVERGENCE OF A CLASS OF INFEASIBLE INTERIOR-POINT METHODS FOR THE HORIZONTAL LINEAR COMPLEMENTARITY PROBLEM* YIN ZHANGt Abstract. Interior-point methods require strictly feasible points as starting points. In theory‚ this requirement does not seem to be particularly restrictive‚ but it can be costly in computation. To overcome
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Mechanics: Work‚ Energy‚ Momentum‚ Kinematics of Rotational Motion Jacque Lynn F Gabayno‚ Ph.D. Lecture Notes 1 Work as defined in Physics r r W =F s Force× Displacement = Force × Displacement *SI Units: 1 N.m = 1 Joules (i.e. same as the unit of energy) 2 Recall “Dot Product” The dot product allows us to multiply two vectors to get something that is SCALAR. r A r A For a constant force: r r r B = A B cos ! r B = Ax Bx + Ay By + Az Bz Only those along the direction of
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