inverse of a matrix and saves it ## to the cache such that the next time the user attempts to calculate the ## matrix inverse‚ the previously saved value is returned instead of ## repeating the calculation. ## This function creates a special "matrix" object‚ which is really a list ## containing a function to ## 1. set the value of the matrix ## 2. get the value of the matrix ## 3. set the value of the inverse ## 4. get the value of the inverse makeCacheMatrix <- function(x = matrix()) {
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This phase consists of different subphases‚ which can last up to 4 weeks in the clean and uncontaminated wound. These sub phases do not happen in discrete time frames but constitute an overall and ongoing process. The sub phases are "fibroplasia‚ matrix deposition‚ angiogenesis and re-epithelialization" (Cho & Lo‚ 1998). The first sub phase of granulation process is fibroplasia. In days 5-7‚ fibroblasts have migrated into the wound‚ laying down new collagen of the subtypes I and III. In normal
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Fault-Tolerant Observers Supervisor: Dr Imad M. Jaimoukha Designing of a robust fault-tolerant observer that guarantees a certain level of performance for real-time applications. By: YEO Zhi-Wei‚ Laurence 00566245 Overview For any system such as a factory plant‚ an aircraft jet engine system or a water pumping system‚ it can be replicatedi by a mathematical model which includes the affecting dynamics based on observations and assumptions. However‚ it would be practically challenging
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How to Use the Short Listing Matrix General principles: The short-listing process is confidential and the panel should be at least two members. Any member of the Appointment/Short-listing Panel‚ who knows any candidate‚ must declare this to the Panel Chair. The short-listing matrix should be used to record the process and will form part of the Recruitment and Selection documents kept by HR for legal reasons. DO NOT introduce any new criteria at the short-listing stage. Reasons for success and
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Transform. But a direct proof of orthogonality‚ by calculating inner products‚ does not reveal how natural these cosine vectors are. We prove orthogonality in a different way. Each DCT basis contains the eigenvectors of a symmetric “second difference” matrix. By varying the boundary conditions we get the established transforms DCT-1 through DCT-4. Other combinations lead to four additional cosine transforms. The type of boundary condition (Dirichlet or Neumann‚ centered at a meshpoint or a midpoint) determines
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Even though the Peoplehood Matrix is not a perfect and exact model‚ it can still be used as a tool to start somewhere when it comes to characterizing indigenous people. The Peoplehood matrix based of the Holm‚ et al. Peoplehood: A Model for the Extension of Sovereignty in American Indian Studies can be applied to tribes that are presented in the Paths of Life exhibit at the Arizona State Museum. The deer dance of the Yaqui can be used for language‚ the mix of Christian and ancient beliefs of the
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Ansoff’s Product/Market Matrix This well known marketing tool was first published in the Harvard Business Review (1957) in an article called ’Strategies for Diversification’. It is used by marketers who have objectives for growth. Ansoff’s matrix offers strategic choices to achieve the objectives. There are four main categories for selection. Introduction: The Ansoff matrix presents the product and market choices available to an organization. Herein markets may be defined as customers‚ and products
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Ansoff’s Matrix Igor Ansoff in 1957 created the Matrix. It is a marketing planning tool‚ used for identifying and categorising growth opportunities. The matrix considers on two dimensions: markets and products. |Existing Products|New Products|Risk| Existing Markets|||| New Markets|||| Risk|| Market Penetration| Involves:|Methods:|Use when:| • Increasing market share in current markets with current products.• Securing dominace in growth markets‚ but saturated markets are hard to
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SUFFICIENT DIMENSION REDUCTION BASED ON NORMAL AND WISHART INVERSE MODELS A THESIS SUBMITTED TO THE FACULTY OF THE GRADUATE SCHOOL OF THE UNIVERSITY OF MINNESOTA BY LILIANA FORZANI IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY R. DENNIS COOK‚ Advisor December‚ 2007 c Liliana Forzani 2007 UNIVERSITY OF MINNESOTA This is to certify that I have examined this copy of a doctoral thesis by Liliana Forzani and have found that it is complete
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Institute Of Engineering Studies (IES‚Bangalore) Formulae Sheet in ECE/TCE Department Communication Systems Amplitude Modulation : DSB-SC : u (t) = m(t) cos 2π t Power P = Conventioanal AM : u (t) = [1 + m(t)] Cos 2π t . as long as |m(t)| ≤ 1 demodulation is simple . Practically m(t) = a m (t) . () () Modulation index a = ( ) ‚ m (t) = | ( )| Power = + SSB-AM : → Square law Detector SNR = () Square law modulator ↓ = 2a / a → amplitude Sensitivity Envelope Detector R C (i/p) < < 1 / ≥ Frequency
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