Web-based applications are becoming the most common way to build a digital capability accessible to a mass audience. While there are modern tools that help us build these rapidly, it's important to understand the fundamental Javascript-based technology and architectures that exist, both to gain a deeper understanding for when these skills may be needed, but also to simply understand the mechanics of fundamental JS. Even when working with a high level framework like React, understanding (in-concept) the code that is transpiled-to will ensure you're a more well rounded web-based engineer.

There are two tasks in this project: Task I aims to develop your skills in applying unsupervised machine learning techniques for anomaly detection; and Task II helps you better understand how to use gradient descent-based method to generate adversarial samples against supervised learning models beyond the computer vision domain. Specifically, two network traffic (NetFlow) datasets are provided, one for each task. Both datasets contain botnet traffic and normal traffic. You need to identify botnet IP addresses from both two datasets. In addition, for Task II you also need to choose a botnet IP address, and explain how to manipulate its network traffic in order to bypass detection.

虽然现在学习CS和IT专业的人非常多，但是由于学习能力或者其他的因素，很多朋友如果需要做好代写作业，往往都会遇到较多的问题，甚至不能在规定due时间内完成作业，这个时候应该怎么做呢？如果是FYP的话，所带来的困扰自然就会更大了，实际上只要与专业的程序代写团队合作，都会有不错的效果，接着来了解选择什么样团队会更好。

A life at age 50 is subject to an extra hazard during the year of age 50 to 51. If the standard probability of death from age 50 to 51 is 0.006, and if the extra risk may be expressed by an addition to the standard force of mortality that decreases uniformly from 0.03 at the beginning of the year to 0 at the end of the year, calculate the probability that the life will survive to age 51.

needs to be able to play a valid game; manage a "memory" string with a parsercombinator; and, leverage concepts from the course. You will also need to write a twopage-report describing your submission.

A new lab device is planned to be installed in an office on the same floor slab that a reciprocating engine works. The lab device is very sensitive to vibration and could generate wrong outputs if displacement at the device sensor reaches to a threshold. You are assigned to study effect of vibration produced by the engine on the new device.

The assignment will be marked with an automatic testing system on Ed as well as manual inspection by a tutor. An automatic mark will be given based on the number of tests passed (10%) and a manual mark will be given for overall style, quality, readability, etc (5%). You are expected to write your own tests and submit them with your code, and a mark will be given based on coverage and manual inspection of your tests (5%). There will be public test cases made available for you to test against, but there will also be extra non-public tests used for marking. Success with the public tests doesn't guarantee your program will pass the private tests.

This assignment includes the tasks related to database normalization, indexing of relational tables, and using cursors to search a database. The outcomes of the laboratory work are due by Saturday 17 October, 2020, 7.00 pm (sharp). Please read very carefully information listed below

• This assignment has two questions comprising 10 parts and will be marked out of 50 (all question parts—(a), (b), (c) etc.—are worth five marks each). • Up to five marks in total can be deducted for not doing the following:  for parts marked (*), providing neatly tabulated regression output (e.g., from texreg or stargazer); raw R-Studio output from the console is not sufficient;  providing your R code.

In this individual assignment you will extend your group work by drawing up a Design Class Diagrams. These Design Class Diagrams will start to look very much like computer software. They will need to reflect the “real world” of your Domain Model but they will include extra classes, linkages and details to fully explain how the Domain Layer of your system might look.