0 0 0 2 2 2 2 0 0 0 0 0 2 2 2 6 0 0 8 2 C 8 6 8 5 6 2 3 0 0 38 8 8 8 8 6 2 0 0 40 8 8 6 6 6 2 2 2 40 6 6 8 2 Course No EC-1101 CS-1101 MA-1102 ME-1101 PH-1101/ CH-1101 CS-1111 EE-1111 PH-1111/ CH-1111 Course Name Semester-2 Basic Electronics Introduction to Computing Mathematics-II Engineering Mechanics Physics/Chemistry Computing Laboratory Electrical Science Laboratory Physics/Chemistry Laboratory Physical Training –II NCC/NSO/NSS Semester-4 Structural Analysis-I Hydraulics Environmental Engg-I
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Jim Albert and Ruud H. Koning (eds.) Statistical Thinking in Sports CRC PRESS Boca Raton Ann Arbor London Tokyo Contents 1 Introduction Jim Albert and Ruud H. Koning 1.1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.1.1 Patterns of world records in sports (2 articles) . . . . . . . 1.1.2 Competition, rankings and betting in soccer (3 articles) . . 1.1.3 An investigation into some popular baseball myths (3 articles) . . . . . . . . . . . . . . . .
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fields,[2] including mathematics (foundations of mathematics, functional analysis, ergodic theory, geometry, topology, and numerical analysis), physics (quantum mechanics, hydrodynamics, and fluid dynamics), economics (game theory), computing (Von Neumann architecture, linear programming, self-replicating machines, stochastic computing), and statistics.[3] He was a pioneer of the application of operator theory to quantum mechanics, in the development of functional analysis, a principal member of the
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customers that businesses have to get on board to succeed—there is a “chicken-and-egg” problem that needs to be solved. These industries range from dating clubs (men and women), to video game consoles (game developers and users), to credit cards (cardholders and merchants), and to operating system software (application developers and users). They include some of the most important industries in the economy. Two-sided firms behave in ways that seem surprising from the vantage point of traditional
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Long Range Planning 41 (2008) 378e394 http://www.elsevier.com/locate/lrp Innovation Games: A New Approach to the Competitive Challenge ´ Roger Miller, Xavier Olleros and Luis Molinie Innovation is often perceived as an unmanageable phenomenon. Bets are placed on new products with the hope that a few winners will compensate for the many losers. At best, sophisticated selection procedures impose a certain discipline and provide guidance for containing costly errors. The research that we have
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their use within the organization’s decision-making structure. In addition, the difference in the tools and techniques of the two fields is addressed. The question is raised as to how distinct the two academic fields have become in light of the application of their models to the service industry. Suggestions are made regarding the possibility of incorporating OM/OR models and their output into the decision making structure of the organization towards the goal of “system optimization”. ORIGINS OF
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Chapter-1 INTRODUCTION TO GRAPH THEORY A graph G = (V, E) is a set of objects, V = {v1, v2, . . .} called vertices, and a set E = {e1, e2, . . .} called edges, such that an edge ek is determined with an unordered pair (vi, vj) of vertices. The vertices vi, vj that belong to an edge ek are called the end vertices of ek. A graph is generally represented by a diagram, with points representing vertices and line segments joining these vertices representing edges. This diagram is generally referred
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Index 1.1 Introduction …………………………………………………………………… 3-5 1.2 Research Questions …………………………………………………………… 5 1.3 Methodology Selected ………………………………………………………… 5-6 1.4 Data Analysis / Findings ……………………………………………………... 6-13 1.5 Final Discussion of Insights ………………………………………………… 13-15 1.6 Conclusion …………………………………………………………………...15-16 1.7 References …………………………………………………………………... 16-17 1.8 Appendices ………………………………………………………………… 18-29 1.1 Introduction Today, children
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E-Learning: Emergence of the Profession Jason Drysdale, Jackie Flynt, and Shauna Hannon-Johnson 24 July 2011 The e-learning profession has grown leaps and bounds over the past two decades. Despite being slow to take hold, e-learning is now rapidly increasing in universities: “Today, almost all institutions of higher education offer some form of distance teaching and learning in the U.S.” (Saba, 2008). The historical timelines of instructional design and technology (ID&T) and distance education inform
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provide some form of elasticity, the ability to expand and contract capacity on-demand. The implication is that at some point additional instances of an application will be needed in order for the architecture to scale and meet demand. That means there needs to be some mechanism in place to balance requests between two or more instances of that application. The mechanism most likely to be successful in performing such a task is a load balancer. The aim of this paper is to discuss the existing techniques
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