DATA STRUCTURES ANALYSIS OF ALGORITHMS Definition:- The method of solving a problem is known as an algorithm.It is a sequence of instructions that act on some input data to produce some output in a finite number of steps. Properties:- a) Input:An algorithm must receive some input data supplied externally. b)Output:An algorithm must produce atleast one output as the result. c)Finiteness:The algorithm must terminate after a finite number of steps. d)Definiteness:The steps to be performed
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finite number of steps Efficiency – easily understandable 3. Define Space Complexity The Space complexity of an algorithm is the amount of memory it needs to run to completion 4. Define Time Complexity Time complexity of an algorithm is the amount of computer time it needs to run to completion 5. What are asymptotic notations? The notations that enables us to make meaningful statements about the time and space complexity of a program is called asymptotic notations. 6. What are the various asymptotic
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efficient 2. A long, long time ago, when I was in graduate school, I wrote a program to solve a difficult problem. The program had a time complexity of 2n(yeah, no kidding!). On input of size 50, my program finished in about an hour. How long would it have taken me to run my program on input of size 100? If input of 50 takes 1hr in a time complexity of 2n It also takes 1 hour to execute and input of 100 3. Write an All-Pairs algorithm that is given a list of numbers and a target and
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• “class A” building • was built in 2006 • Location: the Mokotow district in Warsaw, adjacent to Galeria Mokotow . • 14,007 sqm gross lease area (GLA) including 13,049 sqm of office • space, 958 sqm of retail area, and 192 sqm of storage. • Parking space with a ratio of 1/45. • Highly accessible: 6 bus and 3 tram lines; 500 meters to train station and 5 minute drive to metro stations. The Cirrus building typical floor plan The Cirrus building excusive interior The current tenants
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International Journal of Computer Applications (0975 – 8887) Volume 4– No.8, August 2010 Invisible Digital Watermarking Through Encryption Samir Kumar Bandyopadhyay Dept. of Computer Sc. & Engg, University of Calcutta 92 A.P.C. Road, Kolkata – 700009, India Tuhin Utsab Paul Dept. of Computer Sc. & Engg, University of Calcutta, 92 A.P.C. Road, Kolkata-700009, India Avishek Raychoudhury Dept. of Computer Sc. & Engg, University of Calcutta 92 A.P.C. Road, Kolkata-700009, India ABSTRACT
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THE PRESENCE of multiple objectives in a problem, in principle, gives rise to a set of optimal solutions (largely known as Pareto-optimal solutions), instead of a single optimal solution. In the absence of any further information, one of these Pareto-optimal solutions cannot be said to be better than the other. This demands a user to find as many Pareto-optimal solutions as possible. Classical optimization methods (including the multicriterion decision-making methods) suggest converting the
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Dynamic Resource Provisioning in Cloud Computing: A Randomized Auction Approach ∗ Department Linquan Zhang∗ , Zongpeng Li∗ , Chuan Wu† of Computer Science, University of Calgary, {linqzhan,zongpeng}@ucalgary.ca of Computer Science, The University of Hong Kong, cwu@cs.hku.hk † Department Abstract—This work studies resource allocation in a cloud market through the auction of Virtual Machine (VM) instances. It generalizes the existing literature by introducing combinatorial auctions
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Application of Supply Chain Methods Problem/Opportunity Description: High level of complexity of a vehicle line, with too many possible configurations that can be ordered (approximately 2,000) Background: Our product began with >10,000 configurations. With high level support, we successfully lowered the number of configurations to 800 for 2014 Model Year, but then increased it to 2,000 for 2015 Model Year with newly introduced features. While our Supply Chain team is eager to reduce
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A Comparison of Solution Procedures for the Flow Shop Scheduling Problem with Late Work Criterion Jacek Błażewicz *) Erwin Pesch 1) Małgorzata Sterna 2) Frank Werner 3) *) Institute of Computing Science, Poznań University of Technology Piotrowo 3A, 60-965 Poznań, Poland phone: +48 (61) 8790 790 fax: +48 (61) 8771 525 blazewic@sol.put.poznan.pl Institute of Information Systems, FB 5 - Faculty of Economics, University of Siegen Hölderlinstrasse 3, 57068 Siegen, Germany pesch@fb5.uni-siegen
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Interdisciplinary Description of Complex Systems 8(1), 34-48, 2010 COMPLEXITY IN ORGANIZATIONS AND ENVIRONMENT - ADAPTIVE CHANGES AND ADAPTIVE DECISION-MAKING Robert Fabac* Faculty of Organization and Informatics, University of Zagreb Varaždin, Croatia Regular article Received: 14. May 2010. Accepted: 30. June 2010. ABSTRACT The features of complexity are ever more present in modern organizations and in environments in which they operate, trying to survive and be as competitive as possible
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