Analysis of Algorithms 07/29/13 CS202 - Fundamentals of Computer Science II 1 Algorithm • An algorithm is a set of instructions to be followed to solve a problem. – There can be more than one solution (more than one algorithm) to solve a given problem. – An algorithm can be implemented using different prog. languages on different platforms. • Once we have a correct algorithm for the problem‚ we have to determine the efficiency of that algorithm. – – How much time that algorithm
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independently from learning programming. For this purpose we use problems that are not easy to solve but have an easily understandable problem definition. A proper visualization of these problems can help to understand the basic concepts connected with algorithms: correctness‚ termination‚ efficiency‚ determinism‚ parallelism‚ etc. The presented examples were used by the author in a pre-university course‚ they may also be used in secondary schools to help understanding some concepts of computer science.
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D $350 E $425 Problem-Solving 1. Develop an algorithm or write pseudocode that accepts as input the names of no more than twelve masqueraders who each have paid the full cost of their costume and the amount each has paid. A masquerader may have paid for a costume in any of the five sections in the band. The algorithm should determine the section in which a masquerader plays based on the amount he/she has paid for the costume. The algorithm should also determine the number of masqueraders who
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SUDOKU GAME IN ANDROID INTRODUCTION The main objective of this project is to create a game through which the user will be able to play a Sudoku puzzle. Our project deals with the task of designing a game of Sudoku using various algorithms. These are algorithms‚ both for generating games of various difficulties for the user and also for solving the puzzles provided by the user. A user will be able to ask for a random puzzle or the user will be able to manually input a puzzle. In either case‚ the software
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Nondegenerate Solution‚ Convex set and explanation with examples. [5L] Solution of LPP by Simplex Method; Charnes’ Big-M Method; Duality Theory. Transportation Problems and Assignment Problems. [12L] Module II Network Analysis: Shortest Path: Floyd Algorithm; Maximal Flow Problem (Ford-Fulkerson); PERT-CPM (Cost Analysis‚ Crashing‚ Resource Allocation excluded). [6L] Inventory Control: Introduction to EOQ Models of Deterministic and Probabilistic ; Safety Stock; Buffer Stock. [3L] Module III Game Theory:
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Function blocks. Contents IntroductionChannel Matrix GenerationPerformance Optimization TechniquesData Control TechniquesBit Error RateReference Introduction The decoding algorithm used in this demo applies the Schnorr-Euchner method as the search strategy in the lattice decoder. For details on this algorithm‚ see the paper listed in the Reference section below. Channel Matrix Generation The MIMO decoder implemented in this demo models a 4 transmit and 4 receive wireless system with
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of one or more algorithms (pseudocodeor flowcharts); truth tables Determination of most efficient solution –comparison of algorithms to test for numbers of steps‚ no of variables dry ‚ runs‚ etc Develop and represent algorithm–using a programming language ( PASCAL ) Test and validate solution –debugging Problem Definition –a statement (a paragraph or series of paragraphs) outlining the nature of the problem E.g. of some problem definitions: 1.Write an algorithm to find the average
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alisaad@aucegypt.edu Course Description Introduction to the discipline of computing. Computer history and Evolution. Internal Information representation and operations. Professional ethics for computer programmers and users. Problem solving concepts‚ algorithms‚ pseudo-code‚ and Flow Charts. Control structures‚ functions‚ procedures‚ parameters‚ one-dimensional arrays. Programming laboratory provides hands-on using C++ language in problem solving . Course Outcomes: After completing the CSCE 106‚ students
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TCO 2—Given a simple problem‚ design a solution algorithm that uses arithmetic expressions and built-in functions. Assignment Your goal is to solve the following simple programming exercise. You have been contracted by a local stadium to design an algorithm determining the total seating charges for any game held at the stadium. Lower level seats cost $25 per seat‚ midlevel seats cost $15 per seat‚ and upper level seats cost $10 per seat. The algorithm should ask the user for the number of seats being
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How to solve a Rubik’s cube The purpose of this report is to inform the audience on how to solve a Rubik’s cube in three simple steps. Solving a Rubik’s cube can be difficult; however by solving one layer at a time‚ and knowing the correct algorithm to use for each desired move‚ makes solving a Rubik’s cube easier than it looks. Introduction Invented by mechanics in 1974. There are over 43 quintillion possible combinations for solving a Rubik’s cube. That is 43‚252‚003‚274‚489‚856‚000. (information-facts)
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