Set Theory, branch of mathematics, first given formal treatment by the German mathematician Georg Cantor in the 19th century. The set concept is one of the most basic in mathematics, even more primitive than the process of counting, and is found, explicitly or implicitly, in every area of pure and applied mathematics. Explicitly, the principles and terminology of sets are used to make mathematical statements more clear and precise and to clarify concepts such as the finite and the infinite. A set
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DECISION MAKING THEORY AND TOOLS PROBLEM 1: The following information is for below questions: *PV for profits ($000) i. The maximax strategy would be: Answer: buy with value = RM80,000 ii. The maximin strategy would be: Answer: lease with value = RM50,000 iii. The minimax regret strategy would be: Answer: lease iv. If P(high) is 0.60, the choice for maximum expected value would be: Answer: rent (EMV => RM70,000 x 0.6 + RM30,000 x 0.4 = RM54,000) PROBLEM 2 A manager
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between trigonometric functions and complex exponential functions. According to the formula, for any real number x, In the above formula, e is the base of the natural logarithm, i the imaginary unit. Cos and Sin are trigonometric functions (the arguments are to be taken in radians and not degrees.). The formula applies even if x is a complex number. Particularly with x = π, or half a turn around the circle, e^iπ = cos π + i sin π Since cos π = -1 and sin π = 0, It can be deduced
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1.Introduction Relational database design theory is mainly based on a class of constraints called Functional Dependencies (FDs).FDs are a generalization of keys. This theory defines when a relation is in normal form (e.g., in Third Normal Form or 3NF) for a given set of FDs. It is usually a sign of bad DB design if a schema contains relations that violate the normal form requirements. If a normal form is violated, data is stored redundantly, and information about different concepts is intermixed
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determine why its study is important. 2. Summarize early studies that laid the groundwork for understanding employee motivation. 3. Compare and contrast the human-relations theories of Abraham Maslow and Frederick Herzberg. 4. Investigate various theories of motivation, including Theories X, Y, and Z; equity theory; and expectancy theory. 5. Describe some of the strategies that managers use to motivate employees. 6. Critique a business’s program for motivating its sales force. Key Terms and Definitions
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This is page i Printer: Opaque this A Mathematical Introduction to Fluid Mechanics Alexandre Chorin Department of Mathematics University of California, Berkeley Berkeley, California 94720-3840, USA Jerrold E. Marsden Control and Dynamical Systems, 107-81 California Institute of Technology Pasadena, California 91125, USA ii iii A Mathematical Introduction to Fluid Mechanics iv Library of Congress Cataloging in Publication Data Chorin, Alexandre A Mathematical Introduction
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functions f (z) = u + iv, with particular regard to analytic functions. Of course, one way to think of integration is as antidifferentiation. But there is also the definite integral. For a function f (x) of a real variable x, we have the integral b f (x) dx. In case f (x) = u(x) + iv(x) is a complex-valued function of a a real variable x, the definite integral is the complex number obtained by b integrating the real and imaginary parts of f (x) separately, i.e. b b u(x) dx + i a f (x) dx = a v(x) dx.
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Figures Figure 1: Equity Theory (Al-Zawahreh & Al-Madi 2012) 12 Figure 2: Predicted job satisfaction levels for equity sensitivity orientations (Huseman et al 1987) 15 Figure 3: Representation of the Preference Groups in Company X 17 Figure 4: Representation of the Preference Groups within the Total Sample 18 Figure 5: Motivation Level of company X 18 Figure 6: Total Motivation Level of three companies 19 Figure 7: Preference Groups vs Motivation Level in company X 19 Figure 8: Preference
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complexity theory has developed rapidly in the past three decades. The list of surprising and fundamental results proved since 1990 alone could fill a book: these include new probabilistic definitions of classical complexity classes (IP = PSPACE and the PCP Theorems) and their implications for the field of approximation algorithms; Shor’s algorithm to factor integers using a quantum computer; an understanding of why current approaches to the famous P versus NP will not be successful; a theory of derandomization
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regions, related in the same way? If an object x is a proper part of some other object y, does it follow that the location, lx, of the former object is a proper part of the location of the latter object, ly (and conversely)? Likewise, if some spatial region, lx, is a proper extension of some smaller spatial region, ly, does it follow that the object located at the former region, x, is a proper extension of the object located at the latter region, y (and conversely)? Let mirror realism be the view
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