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Matrix E Services, Pune, Maharashtra. 91 likes. We at Matrix E Services take immense pride in the Tally's 'Power of Simplicity' .

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Detailed Amazon BCG Matrix Analysis 1. Introduction The Boston Consulting Group (BCG) growth-share matrix is a graphical planning tool for a company's products, services and stand alone business units to assess their standing and growth chances in the market. The basic purpose of a BCG matrix is to determine which units require investment for further expansion and growth and which units are self sufficient or not worthy of investments. The BCG matrix has market growth rate at the y-axis and market share at the x-axis. Let us analyze the BCG matrix of Amazon to understand the scenario better. 2. Background of Amazon Amazon was founded in 1994 by Jeff Bezos based in Seattle. Amazon was first launched as an online bookstore but the business model was so appreciated that gradually it moved on to become the world’s largest e-commerce store with a huge variety of products. It deals in books, music, films, household products, furniture, digital products, gadgets, garments and what not. Amazon has another business unit that deals with Amazon's digital service like Cloud and AWS etc. 3. Amazon BCG Matrix The BCG matrix of Amazon com helps us understand the current position of different products and services in the Amazon business model and we can also see the business level strategies for its business units. A BCG matrix is categorized into four types of products based on the market share and growth potential. These four types are dogs, stars, cash cows and question marks. Source: EdrawMax Online 3.1. 2j )+ . . . +(H iN ⁇ D Nj ) for 1 ⁇ i ⁇ M and 1 ⁇ j ⁇ L. Such an encoding matrix E is also referred to as an information dispersal matrix (IDM). IDM information dispersal matrix matrices such as check drive encoding matrix H and identity matrix I N also represent encoding matrices, in that they represent matrices of factors to produce linear combinations over GF arithmetic of the original data. the identity matrix I N is trivial and may not need to be constructed as part of the IDM E. Only the encoding matrix E, however, will be referred to as the IDM. Methods of building an encoding matrix such as IDM E or check drive encoding matrix H are discussed below. the original data in turn, can be represented by an N ⁇ L matrix D of bytes, each of the N rows representing the L bytes of a block of the corresponding one of the N data drives. If C represents the corresponding (N+M) ⁇ L matrix of encoded bytes (where each of the N+M rows corresponds to one of the N+M data and check drives), then C can be represented as the first row of the check drive encoding matrix H (or the (N+1) th row of the IDM E) can be all 1's, representing the parity drive. the GF multiplication can be bypassed and replaced with a GF sum of the corresponding bytes since the products are all trivial

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Powers of a Matrix A^{n}, is defined as n copies of matrix A. Example A = \left(\begin{matrix} 5 & 2 \\ 3 & 1 \end{matrix}\right) A^{2} = \left(\begin{matrix} 5 & 2 \\ 3 & 1 \end{matrix}\right) \left(\begin{matrix} 5 & 2 \\ 3 & 1 \end{matrix}\right) A^{3} = \left(\begin{matrix} 5 & 2 \\ 3 & 1 \end{matrix}\right) \left(\begin{matrix} 5 & 2 \\ 3 & 1 \end{matrix}\right) \left(\begin{matrix} 5 & 2 \\ 3 & 1 \end{matrix}\right) A^{4} = \left(\begin{matrix} 5 & 2 \\ 3 & 1 \end{matrix}\right) \left(\begin{matrix} 5 & 2 \\ 3 & 1 \end{matrix}\right) \left(\begin{matrix} 5 & 2 \\ 3 & 1 \end{matrix}\right) \left(\begin{matrix} 5 & 2 \\ 3 & 1 \end{matrix}\right) Determinant of a Matrix |A| is a used to symbolize the determinant of matrix A. Only a square matrix can have a determinant. Finding the determinant 2×2 Matrix A = \left(\begin{matrix} a & b \\ c & d \end{matrix}\right) |A| = ad-bc Example A = \left(\begin{matrix} 5 & 3 \\ 2 & 8 \end{matrix}\right) |A| = (5)(8)-(3)(2) = 34 3×3 Matrix A = \left(\begin{matrix} a & b & c \\ d & e & f \\ g & h & i \end{matrix}\right) |A| = a(ei - fh) - b(di-fg) + c(dh-eg) The image below shows how this formula is calculated. Example A = \left(\begin{matrix} 5 & 3 & 4 \\ 7 & 2 & 6 \\ 2 & 1 & 9 \end{matrix}\right) |A| = 5((2)(9)-(6)(1)) - 3((7)(9)-(6)(2)) + 4((7)(1)-(2)(2)) = -81 4×4 Matrix A = \left(\begin{matrix} a & b & c & d \\ e & f & g & h \\ i & j & k & l \\ m & n & o & p \end{matrix}\right) |A| = a \left|\begin{matrix} f & g & h \\ j & k & l \\ n & o & p \end{matrix}\right| - b \left|\begin{matrix} e & g & h \\ i & k & l \\ m & o & p \end{matrix}\right| + c \left|\begin{matrix} e & f & h \\ i & j & l \\ m & n & p \end{matrix}\right| - d \left|\begin{matrix} e & f & g \\ i & j & k \\ m & n & o \end{matrix}\right| Inverse of a Matrix The inverse of a matrix A is a matrix A^{-1} such that AA^{-1}=I . I is the identity matrix. Please Note 1. Only square matrices can have an inverse. 2. If the determinant of a matrix is 0, that matrix has no inverse. Finding the Inverse of a Matrix One method of finding the inverse is to use Gauss-Jordan elimination to transform [A|I] to [I|A^{-1}] Example A = \left(\begin{matrix} 8 & 5 \\ 6 & 4 \end{matrix}\right) Find inverse of A. \left[ \begin{array}{cc|cc} 8 & 5 & 1 & 0 \\ 6 & 4 & 0 & 1 \end{array} \right] R_{1} \rightarrow \frac{1}{8}R_{1} \left[ \begin{array}{cc|cc} 1 & \frac{5}{8} & \frac{1}{8} & 0 \\ 6 & 4 & 0 & 1 \end{array} \right] R_{2} \rightarrow R_{2}- 6R_{1} \left[ \begin{array}{cc|cc} 1 & \frac{5}{8}. Matrix E Services, Pune, Maharashtra. 91 likes. We at Matrix E Services take immense pride in the Tally's 'Power of Simplicity' . User Termination: Client User shall notify Matrix Absence Management, Inc. (Matrix) immediately in the event a User is no longer authorized to have access to E-Services, or in the event that the User ID and/or password of an Authorized User become compromised. Matrix reserves the right to deny access to E-Services to any User at our discretion.

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Skip to content Description What are Dot Matrix Marking Services? A Dot Matrix is a simple grid pattern of dots used to create a number or letter as one would see on an old score board or an old computer screen. The key to legibility and definition is the density of dots. However, density can present problems in Low Stress Marking applications. The key to maintaining Low Stress while sustaining legibility is by balancing dot frequency with character size. Advantages Pros of Dot Matrix Marking Services Very legible marks in clear fonts to eliminate confusion in marked textVery little pressure is applied on the part. Too much pressure on a metal part could result in a “stress riser” or a concentration of stress that could lead to cracking. Dot Matrix Marking reduces this risk Features Features of Dot Matrix Marking Services Capability to produce a Dot Matrix Mark via multiple marking methods: Laser Etching, Rotary Engraving, Vibro Peening, or Electrochemical EtchingAbility to mark flats, rounds and irregular shaped partsShallow Marking Depths (under 0.003” deep)Can mark parts up to 24” x 48”Typical marks include: Serial Numbers, Part Numbers, Cage Codes, Manufacturing Numbers, and Date Codesi. Common Part Marking Specifications for Dot Matrix Marking include Spec SAE AS478, Spec MIL-STD-130, Boeing Spec BAC5307, Parker Aerospace Spec BPS 4106, General Electric Spec P23TF3, & Sikorsky Spec SS8798 Dot Matrix Marking Services Dot Matrix Marking Need to discuss your custom part marking job? Complete our simple Request For Quotation form and a Sales Professional Matrix: A L A D I N 1 5 2 3 4 6 ----------- W E C O N F I R M T H E D E L I V E R Y O F T H E D O C U M E N T S X Next, we create a second matrix with the second keyword. Again, we assign digits according to the order of the letters in the alphabet. We then read off the letters from the first transposition matrix column by column according to the key order sequence and put them row by row into the second matrix. The second transposition matrix: C O N S P I R A C Y 2 6 5 9 7 4 8 1 3 10 -------------------- W I D R E E C M L O O T O T I F C S N H V T U X E R E Y D N F E E H M The final ciphertext is again read off column by column according to the key order sequence of the second keyword. The final ciphertext in groups: MSYWO VFLND EFRDO UEITT EEIEM CCERT XHOHN To decipher the double transposition, we work in exactly the opposite direction. First, we create a matrix with the second keyword and determine the long and short columns (free places at the end) according to the message length. The ciphertext is written into the matrix, column by column, according to the keyword sequence. Next, we

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11 D 12 … D 1 ⁢ L D 21 D 22 … D 2 ⁢ L ⋮ ⋮ ⋱ ⋮ D N ⁢ ⁢ 1 D N ⁢ ⁢ 2 … D NL ] , where J11=(H11×D11)+(H12×D21)+ . . . +(H1N×DN1), J12=(H11×D12)+(H12×D22)+ . . . +(H1N×DN2), J21=(H21×D11)+(H22×D21)+ . . . +(H2N×DN1), and in general, Jij=(Hi1×D1j)+(Hi2×D2j)+ . . . +(HiN×DNj) for 1≦i≦M and 1≦j≦L. Such an encoding matrix E is also referred to as an information dispersal matrix (IDM). It should be noted that matrices such as check drive encoding matrix H and identity matrix IN also represent encoding matrices, in that they represent matrices of factors to produce linear combinations over GF arithmetic of the original data. In practice, the identity matrix IN is trivial and may not need to be constructed as part of the IDM E. Only the encoding matrix E, however, will be referred to as the IDM. Methods of building an encoding matrix such as IDM E or check drive encoding matrix H are discussed below. In further embodiments of the present invention (as discussed further in Appendix A), such (N+M)×N (or M×N) matrices can be trivially constructed (or simply indexed) from a master encoding matrix S, which is composed of (Nmax+Mmax)×Nmax (or Mmax×Nmax) bytes or elements, where Nmax+Mmax=256 (or some other power of two) and N≦Nmax and M≦Mmax. For example, one such master encoding matrix S can include a 127×127 element identity matrix on top (for up to Nmax=127 data drives), a row of

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To calling ECCGenerate, ECCSolve is called to compute the appropriate constants for the particular configuration of data drives and check drives, as well as the solution matrix B ⁇ 1 . ECCRegenerate is used to regenerate data vectors and check code vectors for a particular configuration of data drives and check drives (that is, reconstructing the original data matrix D from the surviving data matrix X and the surviving check matrix W, as well as regenerating the lost check data from the restored original data), this time using Sequencer 2 and the Parallel Lookup Multiplier as described above. ECCSolve is called to compute the appropriate constants for the particular configuration of data drives, check drives, and failed drives, as well as the solution matrix B ⁇ 1 . erasure code processing such as an erasure coding system used in RAID processing the computation of the solution matrix B ⁇ 1 for a given failure scenario the computation of the solution matrix B ⁇ 1 for a given failure scenario the byte-level processing of encoding the check data J and reconstructing the lost data after a lost packet e.g., data drive failure the master encoding matrix S permits further data drives and/or check drives can be added without requiring the recomputing of the IDM E (unlike other proposed solutions, which recompute E for every change of N or M). Rather, additional indexing of rows and/or columns of the master encoding matrix S will suffice. the use of the parity drive can