For this discussion: 

1. Share what your project research entails and your decision criteria. 
2. Address the potential risk in your project, both for performing the work and the potential impacts of not completing the work.

Note: 300 words with intext citation and references

Project Name: Dominos Pizza Group PLC

Also attached the project document

Description and Instructions:

The deliverables of the project should include A report with the following sections: 

o Abstract: summary of chosen problem. (2 Marks)

o Introduction: a brief introduction about the chosen topic. These should be demonstrated using text and diagrams. (2 Marks) 

o Background: a brief of the chosen topic (provide any terms or theories the reader should know about). (3 Marks) 

o Discussion: discuss the chosen topic thoroughly. ( 4 Marks)

o Conclusion: summarize the findings of the discussion. (2 Marks)

o References: The citation should follow the APA style. (1 Marks)

Your paper must be 4-6 pages, including references.

Topic:  Comparative survey between Desktop OS and Mobile OS in terms of various features like Storage, Memory requirement, boot time etc. 

Learning Outcome(s):

– Describe the OS mechanism for process management, threads, memory, storage management, I/O, file and concurrency management.

it is a priority that students are provided with strong educational programs and courses that allow them to be servant-leaders in their disciplines and communities, linking research with practice and knowledge with ethical decision-making. This assignment is a written assignment where you will demonstrate how this course research has connected and put into practice within your own career.

Assignment:   
Provide a reflection of at least 500 words (or 2 pages double spaced) of how the knowledge, skills, or theories of this course have been applied, or could be applied, in a practical manner to your current work environment. If you are not currently working, share times when you have or could observe these theories and knowledge could be applied to an employment opportunity in your field of study. 

Requirements:   
Provide a 500 word (or 2 pages double spaced) minimum reflection.   
Use of proper APA formatting and citations. If supporting evidence from outside resources is used those must be properly cited.   
Share a personal connection that identifies specific knowledge and theories from this course.   
Demonstrate a connection to your current work environment. If you are not employed, demonstrate a connection to your desired work environment.    
You should NOT, provide an overview of the assignments assigned in the course. The assignment asks that you reflect how the knowledge and skills obtained through meeting course objectives were applied or could be applied in the workplace.

 You are the web master of a college website. You share a server with other school departments such as accounting and HR.

Based on this chapter, create at least five security-related rules for staff members who are adding web pages being added to your site. Include a justification and explanation for each rule. Rules should relate to college, staff and student, and system information security.

Question: As Customers, Students, Patients, Taxpayers, And Citizens, We Are Surrounded By Information Systems That Support Customer Interactions. Respond To The Following In A Minimum Of 175 Words: Identify And Describe Two Such Systems That You Have Used. Briefly Discuss The Types Of Customer Interactions You Have Experienced With These Systems. Compare What You what you found to be important features of each one. Are there features or functions that you would change or add to either systems.

Discuss some of the “Software Engineering ” constraints that must be overcome in order to build a successful system.

Please view uploaded Assignment Instructions. The excel file uploaded already has everything required, all you need to do is follow the instructions and input the information. No need to create a new excel file from scratch. 

k

Back Propagation

Neural Network

For the multi

–

layer neural network that you will be implementing in the following problems, you may use 

either the hyperbolic tangent or the sigmoid for the activation function.  Obviously you will be implementing 

the back propagation method to train the n

etwork.  Your code should include an arbitrary method that allows 

you to code it for any number of input dimensions, hidden layers, neurons and output neurons, (i.e. you need 

it to be able to allow you to change a variable and it changes the number of laye

rs, or the number of neurons 

at a given layer, or the number of dimensions, or the number of output layers…in other words this cannot be 

hard coded

for a specific data set

).   

1.

(25pts) 

Develop a multi

–

layer neural network to solve the 

regression problem: f

(x) = 1/x

, (for only the 

positive values of x)

.  Be sure to create a testing and training set.  

I am 

NOT

providing you with data. 

The 

number of hidden layers and neurons 

is your discretion, however, you must provide an explanation as to why 

the number of l

ayers and nodes you used was a good choice.  You will need to create multiple different 

structures that you train and p

lot this error for the different models to show why you chose the final model 

that you did for this problem.

Report your network configu

ration, and comment on your observations 

regarding the performance of your network as you try to determine the number of hidden layers and hidden 

nodes of your final network, once you determine the correct model

:

a.

(10pts) 

T

rack 

your training and testing history.  

This means that you 

check your training performance 

and your testing performance at multiples of some fixed number of 

iterations

(and over many Epochs 

also)

, implement 

the online learning method.

Be 

sure to label plots appropriately.

(Remember to scale the data in the range that provides the best 

results for your activation function

… normalization is a must)

b.

(5pts) 

What did you observe regarding the value of the learni

ng parameter and how the network 

performed given

: 

(do one of each)  

i.

(2.5pts)

a fixed value, 

ii.

(2.5pts) 

and a time decreasing value 

c.

(2.5pts) 

Choose a couple of points beyond your training set (i.e., if your max training input 

is 

x=10, 

try testing your netw

ork with, say, x=10.5, x=

12

, and x=

30

).  What do you observe regarding the 

networks ability to generalize for data that is beyond its training set (note, you may have to increase 

the v

alue of x 

to a large number 

to get a good idea

to answer this

)

.

d.

(2.5pts)

Briefly comment on 

the extrapolation capability 

compared 

to the interpolation capability

of 

the network.

e.

(5pts) 

Plot the final results

showing the capability of your network to determine the function f(x) = 

1/x versus the function f(x) = 1/x.

2.

(25pts)

Develop a multi

–

layer neural network to

classif

y

the 

IRIS 

data set.  

Use K

–

Fold Cross Validation for 

this problem.

The code you use for thi

s problem will be an extension of the code you created for problem 1.

a.

(12pts) Implement the NN and r

eport your network configuration: number of hidden layers, number 

of nodes per hidden layer, learning rate/learning schedule, encoding of the output

, etc.

b.

(

5pts) 

Plot 

the 

error metric versus the number of training steps (similar to problem 

1

).

c.

(8pts) 

Comment on how well your network learned the data.  Things to think about: did the network 

classify the data well (or not), and why (or why not); how well did it

classify each class independently 

(you might consider contingency

table

s for this

); and what observation do you have regarding number 

of training samples

: was the normalization technique I used adequat

Retrospective

1. What things do you think to make up the Web?
2. When arriving at a crime scene, is it better to shut down the computer immediately or insure it stays on? What are the tradeoffs?