...Homework 2 System optimization and scheduling | Name : | 杜彪 | Class ID : | 3034 | Student ID : | 3113033039 | Department : | CS | Email: | 1012298204@qq.com | | | Solution 2 Solution of problem 1.6.4 : It suffices to show that the subspace spanned by is the same as the subspace spanned by, for .We will prove this by induction. Clearly, when k = 1 the statement is true. Assume it is true for k-1 < n-1, i.e. Where denotes the subspace spanned by the vectors. Assume. Since and minimize f over the manifold, from our assumption we have that . The fact that yields . (1) If, then from formulation (1) and the inductive hypothesis it follows that (2) We know that is orthogonal to . Therefore formulation (2) is possible only if which contradicts our assumption. Hence.If , then formulation (1) and our inductive hypothesis again imply formulation (2) which is not possible. So the vectorsare linearly independent. Combined with formulation (1) and linear independence of the vectors we can get that . Solution of problem 2.1.12 : (a) Assume that z is a fixed vector in. Then the problem is equal to find a vector of the simplex X, which is at a minimum distance from z; that is Minimize f(x) = ||z-x||2 Subject to x ∈X, that is subject to = r Suppose, H = In = and A = , we can write the problem as Minimize f(x) = Subject to Ax = r We can easily get...
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...0 1 Integer Linear Programs: Using INT Command in LINDO restricts a variable to being either 0 or 1. These variables are often referred to as binary variables. In many applications, binary variables can be very useful in modeling all or nothing situations. Examples might include such things as taking on a fixed cost, building a new plant, or buying a minimum level of some resource to receive a quantity discount. Example: Consider the following Knapsack Problem Maximize 11X1 + 9X2 + 8X3 + 15X4 Subject to: 4X1 + 3X2 + 2X3 + 5X4 8, and Xi either o or 1. Using LINDO, the problem statement is Max 11X1 + 9X2 + 8X3 + 15X4 S.T. 4X1 + 3X2 + 2X3 + 5X4 8 END INT X1 INT X2 INT X3 INT X4 The click on SOLVE. The output shows the optimal solution and the optimal value after 8 Branch and Bound Iterations Note that instead of repeating INT four times one can use INT 4. The first four variables appeared in the objective function. OBJECTIVE FUNCTION VALUE 1) 24.00000 VARIABLE VALUE REDUCED COST X1 0.000000 11.000000 X2 1.000000 9.000000 X3 0.000000 8.000000 X4 1.000000 15.000000 ROW SLACK OR SURPLUS DUAL PRICES 2) 0.000000 0.000000 NO. ITERATIONS= 8 ...
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...Instructor information Wyatt C. Christian-Carpenter Office: Evans 111D Office Number: 870-230-5043 Google Number: 828-539-0402 Email: CARPENW@hsu.edu Office Hours MWF: 9 – 10 a.m. & 11 a.m. – 12 p.m.; TR: 12:30 – 1:30 p.m. & 2:45 – 3:45 p.m. Meeting Times and Location MWF: 10 – 10:50 a.m., EV205 MWF: 1 – 1:50 p.m., EV 205 TR: 11 a.m. – 12:15 p.m., EV 205 TR 1:30 – 2:45 p.m., EV 207 Text and Required Supplies A Graphical Approach to College Algebra, 6th Edition by John Hornsby, Margaret Lial, Gary Rockswold ©2014 Prentice Hall. Description | | ISBN-10 | ISBN-13 | Approximate Cost | MyMathLab access code | Required | 032119991X | 9780321199911 | $75–100 | Hardcopy or Kindle | Optional | 0321920309 | 9780321920300 | $145–196 | Hardcopy bundled with MML | Optional | 978-0321909817 | 032190981X | $200–290 | The MyMathLab code can be purchased from the Arkadelphia bookstores or online. MWF MyMathLab CourseID: carpenter58666 TR MyMathLab CourseID: carpenter61414 A graphing calculator is required. Any TI newer than a TI-83 is highly recommended, for example, the TI-83+, TI-84+, or TI-nspire. The mathematics department strongly recommends the TI-Nspire CAS if you will take Calculus 1 or above. Course Prerequisite(s) A score of 20 on the ACT Mathematics Section, or equivalent score, or a grade of “C” or better in Intermediate Algebra from an accredited institution is required. However, it is recommended that your ACT score be at least 22. If...
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...Richard M. Murray∗ Electronics Research Laboratory University of California Berkeley, CA 94720 murray@united.berkeley.edu John Hauser† Department of EE-Systems University of Southern California Los Angeles, CA 90089–0781 hauser@nyquist.usc.edu 29 April 1991 Abstract The acrobot is a simple mechanical system patterned after a gymnast performing on a single parallel bar. By swinging her legs, a gymnast is able to bring herself into an inverted position with her center of mass above the part and is able to perform manuevers about this configuration. This report studies the use of nonlinear control techniques for designing a controller to operate in a neighborhood of the manifold of inverted equilibrium points. The techniques described here are of particular interest because the dynamic model of the acrobot violates many of the necessary conditions required to apply current methods in linear and nonlinear control theory. The approach used in this report is to approximate the system in such a way that the behavior of the system about the manifold of equilibrium points is correctly captured. In particular, we construct an approximating system which agrees with the linearization of the original system on the equilibrium manifold and is full state linearizable. For this class of approximations, controllers can be constructed using recent techniques from differential geometric control theory. We show that...
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...Optical Modulators. In solid state modulators 3 types are there. They are Bulk, Integrated Optical and All-Fiber Modulators. 1. Bulk In these modulators the signal propagates through a uniform block of material. They lack wave guiding. They require high electrical drive power and external optics to couple in of optical fibers. They require high electrical drive power and external optics to couple out of optical fibers. 2. Integrated Optical How IO materials are formed? : By fabricating waveguides directly into modular material. For this modulators Low external power is needed. No external optics needed. 3. All-fiber The optical signal never leaves the fiber. In All-Fiber Modulators low external power is necessary. There is no need of external optics or precision alignment. Modulation capabilities of the glass are very poor. Electro-optic Effect Electro optic effect is the base for most of the optical modulators. In linear electro- optic Effect, The refractive indices of crystals are linked to external electric field. In this Modulator the light propagating in an anisotropic medium can be decomposed into its normal modes, or Eigen waves. It can be determined by the index ellipsoid In certain crystals the application of an external electric field will redistribute the charges in the molecules. It results in a size change and orientation change of the index ellipsoid. This is the electro-optic effect. This effect relates the dimensions of the index...
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...Year 2 Project Build and Study electronic circuits that have chaotic behavior Name Di Peng (ID 200907437) Name Yifan Liu (ID 200780972) Group 41 Supervised by Pro. Steve Hall March 22, 2013 Abstract This project aims to investigating the chaotic behavior of the electronic circuit. The chaotic is an aperiodic behavior appears in deterministic nonlinear system that is extremely sensitive to initial status. Chaotic circuit is the circuit with nonlinear components, which is diode in this project. The objective of this project is to build chaotic circuit and analyze chaotic behavior in the circuit. RLD is used as the chaotic circuit in the experiment. The experiment is carried out basically successful, important results and conclusions has acquired from the experiment and looking up the papers of predecessors online. In addition, PSpice is used to get simulation results to compare with experimental results. To analyze the chaotic behavior, the relative knowledge such as resonance frequency, diode capacitance, bifurcation phenomenon and Fiegenbaum constant are included. This report will show the method, results, analysis and conclusion in details. Contents 1 Introduction 1.1 Background information . . . . . . . . 1.2 Theory . . . . . . . . . . . . . . . . . . 1.2.1 RLD circuit . . . . . . . . . . . 1.2.2 Resonance frequency . . . . . . 1.2.3 Diode Capacitance . . . . . . . 1.2.4 Chaotic behavior: bifurcation, harmonic . . . . . . . . . . . . 1.3 Objective . . ....
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...Physics, Cornell University, Ithaca, NY 14853 of Electrical and Computer Engineering, Cornell University, Ithaca, NY 14853 alg3@cornell.edu Abstract: We demonstrate highly broad-band frequency conversion via four-wave mixing in silicon nanowaveguides. Through appropriate engineering of the waveguide dimensions, conversion bandwidths greater than 150 nm are achieved and peak conversion efficiencies of -9.6 dB are demonstrated. Furthermore, utilizing fourth-order dispersion, wavelength conversion across four telecommunication bands from 1477 nm (S-band) to 1672 nm (U-band) is demonstrated with an efficiency of -12 dB. © 2007 Optical Society of America OCIS codes: (190.4380) Four-wave mixing; (130.5990) Semiconductors; (130.4310) Nonlinear; (130.3060) Infrared References and links 1. H. K. Tsang, C. S. Wong, T. K. Liang, I. E. Day, S. W. Roberts, A. Harpin, J. Drake, M. Asghari, “Optical dispersion, two-photon absorption and self-phase modulation in silicon waveguides at 1.5 µ m wavelength,” Appl. Phys. Lett. 80, 416 (2002). 2. M. Dinu, F. Quochi, H. Garcia, “Third-order nonlinearities in silicon at telecom waveguides,” Appl. Phys. Lett. 82, 2954 (2003). 3. T. Liang, L. Nunes, T. Sakamoto, K. Sasagawa, T. Kawanishi, M. Tsuchiya, G. Priem, D. Van Thourhout, P. Dumon, R. Baets, H. Tsang, “Ultrafast all-optical switching by cross-absorption modulation in silicon wire waveguides,” Opt. Express 13, 7298 (2005), http://www.opticsinfobase.org/abstract.cfm?URI=oe-13-19-7298...
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...EXECUTIVE SUMMARY You may ask yourself what is needed for a new building and what are the codes that must be followed in order to have a building nice and free of hazards. Well to start here are the new building requirements for the following materials: patch cables, cat 6 cables, fiber optic multi-mode, cable trays, Cisco- WS-C3750 G24PS-S 24 Ports, laser printer, vertical runs, computers, Cisco border router, server run a and server run b. The following codes must be in play to ensure the building or work space is safe for everyone. 1. American National Standards Institute (ANSI). 2. Electronic Industries Alliance (EIA) 3. Telecommunications Industry Association (TIA) 4. Insulated Cable Engineers Association (ICEA) 5. National Fire Protection Association (NFPA) 6. National Electrical Manufacturers Association (NEMA) 7. Federal Communication Commission (FCC) 8. Underwriters Laboratories (UL) 9. International Organization for Standardization (ISO) 10. International Electrotechnical Commission (IEC) 11. Institute of Electrical and Electronic Engineers (IEEE) 12. National Institute of Standards and Technology (NIST) 13. International Telecommunications Union (ITU) 14. CSA International (CSA) 15. IP/MPLS Forum (ATM Forum) 16. European Telecommunications Standards Institute (ETSI) 17. Building Industry Consulting Services International (BICSI) 18. Occupational Safety and Health Administration (OSHA) 19. ANSI/TIA-568-C Cabling Standard The following...
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...Research and Development of Freeform Gameplay in Computer Games Contextual Report Contents Section 1: Introduction………………………………………………………… | 1 | 1.1 The Project……………………………………………………………... | 1 | 1.1.1 Project Key Words…………………………………………… | 1 | 1.1.2 What is Freeform Gameplay?.............................. | 1 | 1.1.3 Project Goal…………………………………………………….. | 1 | 1.1.4 Project Context……………………………………………….. | 2 | 1.1.5 Project Objectives…………………………………………… | 3 | 1.1.6 Techniques for Realisation………………………………. | 3 | 1.1.7 Structure of This Report………………………………….. | 4 | Section 2: The Contextual Review……………………………………….. | 6 | 2.1 Market Research…………………………………………………….. | 6 | 2.1.1 Categorisation of Gameplay Elements…………….. | 6 | 2.1.2 Game Comparisons…………………………………………. | 8 | 2.1.3 Comparison Analysis………………………………………. | 9 | 2.2 Market Surveys……………………………………………………….. | 11 | 2.2.1 Target Audience……………………………………………… | 11 | 2.2.2 Survey Approach…………………………………………….. | 11 | 2.2.3 Questionnaire…………………………………………………. | 12 | 2.2.4 Survey Results………………………………………………… | 12 | Section 3: Project Planning………………………………………………….. | 17 | 3.1 Design Blueprints……………………………………………………. | 17 | 3.1.1 Design Approach……………………………………………...
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...Chaos: A short Introduction Scientists have been coming up with theories for thousands of years now. The theories have been tried and tested have been altered and improved to better understand why certain things happen in and out of this world. Many of these theories are still in the works and our not fully comprehendible and scientists have been working hard to achieve breakthroughs in these areas. One such theory has achieved several breakthroughs within the past couple of years and that theory is called Chaos Theory. This theory first started out mainly as a sort of fictitious happening only read about in novels until lately when scientist have discovered that this theory may have more effect than previously deliberated. In Leonard Smith’s book, “Chaos: A Very Short Introduction” he gives an understandable account of what the Chaos Theory is and how it affects the environment around us. Leonard explains to the reader how the Chaos Theory works through mathematical diagrams, models, and simulations to show the possible results the theory could claim on the environment around us. The book is for the most part easy to understand and gives the reader a sufficient understanding even if the reader does not have a background in mathematics or science. Chaos theory first came about when scientist decided they wanted to be able to predict the future more accurately of certain events happening. The theory takes a look at the initial beginning of a system and tries to determine...
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...Karachi Campus . Nonlinear Control Systems Fall 2013 Lecture 1 Nonlinear Control Systems – Fall 2013 Attaullah Y. Memon, PhD BUKC - Nonlinear Control Systems – Fall 2013 Slide 2 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 3 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 4 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 5 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 6 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 7 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 8 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 9 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 10 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 11 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 12 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 13 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 14 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 15 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 16 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 17 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 18 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 19 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 20 Lecture 1 BUKC - Nonlinear Control Systems – Fall 2013 Slide 21 Lecture 1 BUKC - Nonlinear Control Systems...
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...21. Describe how or why integer programming OR goal programming OR nonlinear programming (choose ONE) might be used in a real-world business situation. Be as specific as you can and use examples as appropriate. Goal programming is an aid for decision-making problems with multiple, possibly conflicting goals. Typically, linear goal programming attempts to minimize a weighted sum of deviations from goals. This program is used in real-world business in an attempt to eliminate or, at the least, mitigate this disquieting disconnect. Goal programming is the most widely applied tool of multiple-objective optimization/multicriteria decision making. However, today’s goal programming models, methods, and algorithms differ significantly from those employed even in the early 1990s. Goal programming, may be combined with various tools from the artificial intelligence sector (most notably genetic algorithms and neural networks) so as to provide an exceptionally robust and powerful means to model, solve, and analyze a host of real-world problems. In other words, today’s goal programming while maintaining its role as the “workhorse” of multiple-objective decision analysis—is a much different tool than that described in most textbooks. Goal programming’s label as the “workhorse” of multiple-objective optimization has been achieved by its successful solutions of important real-world problems over a period of more than 50 years. Some examples among these applications are: • The analysis of...
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...Different Change Detection Techniques Table of Contents Introduction...................................................3 Digital Change Detection Process...............................4 Description of the most commonly used change detection methods.5 I. Post-Classification Comparison..........................5 II. Direct Classification...................................6 III. Principal Component Analysis (PCA)......................6 IV. Image Differencing......................................8 V. Change Vector Analysis (CVA)............................9 Relative accuracy of the most commonly used change detection methods........................................................9 I. Post-Classification Comparison.........................10 II. Direct Classification..................................11 III. Principal Component Analysis (PCA).....................11 IV. Image Differencing.....................................12 V. Change Vector Analysis (CVA) Conclusion....................................................14 References....................................................15 Introduction Remote sensing change detection has been defined as the process of identifying change in the state of an object or phenomena through the detection of differences between two or more sets of images taken of the same area on different dates (Wang, 1993). The underlying assumption is that changes on the ground cause significant changes...
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...1 Mathematical Programming The Mathematical Programming Add-in constructs models that can be solved using the Solver Add-in or one of the solution add-ins provided in the collection. When the Math Programming add-in is installed, several new command lines are added to the OR_MM menu. The menu items under the title Math Programming create models of the different types. Selecting an item from this list causes a dialog box to be presented which constructs a mathematical programming model. The models created by the add-in are solved with the Excel Solver, the Jensen Network Solver or the Jensen LP/IP Solver. All are Excel add-ins. Documentation for these programs can be reached by clicking the links on the lower left. The Solver add-in comes with Excel, and it can solve linear programming, integer programming and nonlinear programming models. The Math Programming add-in automatically builds Solver models and calls the computational procedures that solve the problems. All four model types can be can be solved in this way. The Jensen LP/IP Solver solves linear or integer programming problems. It is available for the Linear/Integer Programming and Network Flow Programming model types. The Jensen Network Solver can solve pure or generalized network flow models. Both linear and integer problems can be solved. It is available for the Network Flow Programming or Transportation model types. Parametric analysis can be applied to any of the math programming models. Here one parameter...
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...Department of Management Information Systems Assignment on: Application of Management Science in Business [Type the document subtitle] Course Title: Management Science Course Code: EMIS 517 Submitted to: Professor Dr. Abdul Hannan Mia Honorable Course Teacher, Dept. of MIS Submitted by: Name | ID | Batch | Md. Al-Mamun Riyadh | 61427-20-079 | 20th | Abdullah-Al-Kashem | 61427-20-006 | 20th | Submission date: 31st August, 2014 Management Science Management Science is concerned with developing and applying models and concepts that help to clarify management issues and solve managerial problems. The models used can often be represented mathematically, but sometimes computer-based, visual or verbal representations are used. The range of problems and issues to which management science has contributed insights and solutions is vast. It includes scheduling airlines, both planes and crew, deciding the appropriate place to site new facilities such as a warehouse or factory, managing the flow of water from reservoirs, identifying possible future development paths for parts of the telecommunications industry, establishing the information needs and appropriate systems to supply them within the health service, and identifying and understanding the strategies adopted by companies for their information systems. Scientific Planning Successful management relies on careful coordination, often using scientific methods in project planning...
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