Cloud Computing INFS3208 Background – Big Data Era • “Big Data” has been in use since 1990s. • Data sets with sizes beyond the ability of commonly used software tools to capture, curate, manage, and process data within a tolerable elapsed time. • Reasons of Big Data: – – – Hardware development: Storage (more cheaper), […]
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Recap – Course Structure This course includes 13 lectures and 10 tutorial/practical sessions Lecture 1 Introduction Lecture 2 Adv. topics&appl Lecture 3 Networks & Load Balancing Concepts Orchestration Storage Computation Others Programming and Linux experiences required! Lecture 4 VT: Docker I Lecture 5 VT: Docker II Lecture 6 VT: Docker III Lecture 7 DBs in
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COMP90007 Internet Technologies Week 12 Workshop Semester 2, 2021 1 Question 1 Given the RSA algorithm we studied last week, if p = 3, q = 11 and if d = 3 and e = 7 instead of the version we saw in class, using the same character mapping we saw in class though, where
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COMP90007 Internet Technologies Week 8 Workshop Semester 2, 2021 Suggested solutions * © University of Melbourne 2021 1 Question 1 A router has just received the following IP addresses: 57.6.96.0/21, 57.6.104.0/21, 57.6.112.0/21 and 57.6.120.0/21. If all of them use the same outgoing line, can they be aggregated? If so, to what? If not, why not?
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Fundamentals of Image Processing Book of Exercises Part 1: Basics Master 1 Computer Science – IMAge & VCC Sorbonne Universit ́e Year 2020-2021 Fundamentals of Image Processing – Exercises IMAge & VCC Contents 1. Basic Operations 2. Fourier Transform 3. Digitization 4. Image Filtering 5. Filtering and Edge Detection Appendix 1: Dirac delta function Appendix
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Bases de l’imagerie Parcours IMA BIMA – Exam 2 January 12, 2021 – 2pm The grading of each exercise may be modified. The total is 20 points. No document allowed. Your mobile phone should be off and put away. Calculator allowed. Please respect sanitary rules. Duration: 1 hour Exercise 1 Questions on the lectures (5
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Fundamentals of Image Processing Book of Exercises Part 2 Master 1 Computer Science – IMAge & VCC Sorbonne Universit ́e Year 2020-2021 Fundamentals of Image Processing – Exercises IMAge & VCC Contents 6. Keypoint Detection 7. Image descriptors 8. Segmentation: split and merge 9. Principal component analysis (PCA) 10. Linear Discriminant Analysis (LDA) 1 Appendix:
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PCA Algorithm – Data Let’s say this is our data matrix (say our houses), where each data point is an d-dimensional row vector. ̈ ̨ T ̊ x1 ‹ ̊‹ ̊‹ ̊ xT ‹ ̊‹ X“2 ̊ . ‹ ̊ . ‹ ̊‹ ̋‚ xTn The dimensions are n ˆ d ⃝c -Trenn, King’s College
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Consensus Mechanisms This week, we are going to look at some different mechanisms by which a collection of agents can reach consensus on some question. There are three parts to the lecture: – Part A is an Introduction given by me – Part B is Voter Models (aka Flag Colouring) given by Dr
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Goal: Points in the same cluster are ‘close’ and points of different clusters are ’far’ ⃝c -Trenn, King’s College London 2 Application: Biological Networks Protein-Protein Interaction Networks (PPINs). See e.g., Rual et al Nature ’05 (+2500 citations) ⃝c -Trenn, King’s College London 3 Application: Recommendation Systems Similar users will buy similar items High dimensional data,