This Lab Sheet contains material based on the lectures up to and including the material on concurrency. The deadline for Moodle submission of this lab exercise is 4:30pm on Thursday 19 November 2020. Aims and objectives • Using enumerated types • Writing immutable classes • Using the Streams API

This assignment will teach you to build a minimal bootable code that boots on real hardware into C. Technically, you can do this assignment on a operating system that supports the Unix API and can run Qemu (Linux Openlab machines, your laptop that runs Linux or Linux VM, and even MacO etc.). You don't need to set up xv6 for this assignment, but if you're running on Openlab you'll have to install QEMU, see QEMU setup instruction Submit your programs and the shell through Gradescope (see instructions at the bottom of this page).

1) You must submit the answers to all the questions below. However, only one or more questions, possibly chosen at random, will be corrected and will be evaluated to the full 50 marks. 2) TAs will not be able to answer Theory Assignment related queries. Please get in touch with Professor for any queries related to Theory Assignment. 3) Theory assignment to be completed individually.

There is a maximum file size cap of 5MB, so make sure your submission files do not in total exceed this size. You are allowed to use any Python library used in the tutorial notebooks or given in the example code. No other library will be accepted, particularly libraries for graph and Bayesian network representation and operation. Also, you can reuse any piece of source code developed in the tutorials. Submit your files using give. On a CSE Linux machine, type the following on the command-line: $ give cs9418 ass2 solution.py report.pdf *.csv *.py *.pickle Zero or more csv or pickle files can be submitted to store the parameters of your model, to be loaded by solution.py during testing. Nov 12th: You may submit data.csv as one of your files, if your program needs it. Zero or more python helper files may be included in the submission, if you want to organise your code using multiple files. Alternatively, you can submit your solution via WebCMS. Recall the guidance regarding plagiarism in the course introduction: this applies to this assignment, and if evidence of plagiarism is detected, it will result in penalties ranging from loss of marks to suspension.

In this part of the assignment, you will revisit a dataset on Australian Schools, which you encountered before in ‘R Questions on Week 4’. This dataset is available on Moodle under the name school data2019.csv. On Moodle there is also a file ‘Decription of Variables’, which briefly describes what each variable represents.

In this assignment, we will study a simple case of a SNN receiving time-dependent inputs.

Problem 5.10 #12 in Chihara/Hesterberg. The data set FishMercury contains mercury levels (parts per million) for 30 fish caught in lakes in Minnesota. (a) Create a histogram or boxplot of the data. What do you observe? (b) Find the Bootstrap sampling mean and record the bootstrap standard error and the 95% bootstrap percentile interval. (c) Remove the outlier and find bootstrap sampling mean of the remaining data. Record the bootstrap standard error and the 95% bootstrap percentile interval. Comment on your results. (d) What effect did removing the outlier have on the bootstrap distribution, in particular, the standard error?

Consider the problem of determining whether the following system of equations is consistent for all b1, b2, b3

you will implement the semantic analysis phase of the WLP4 compiler for which you wrote a scanner in Assignment 5 and a parser in Assignment 6. In particular, it is the job of this assignment to catch all remaining compile-time errors in the source program; a program that makes it through this phase of compilation is guaranteed to be free of compile-time errors.

This exercise focuses on DH parameters and the forward (position and orientation) kinematics transformation for the planar 3-DOF, 3R robot shown below. The following fixed-length parameters are given: 𝐿1 = 4, 𝐿2 = 3, 𝐿3 = 2 (𝑚)