This week we focus on the productivity paradox.  Please define the productivity paradox and explain current thinking on this topic

14 

Using the Web or other resources, research an example of Cyber Terrorism.

Write a brief Discussion describing the terrorism attack and it’s aftermath. Comment on ways the attack could have been prevented.

 *I need an expert who can work on this and turn it back in 24hrs**
**I will also require some progress every 6hrs, just to be sure of the progress**
ANything you need for the job let me know

In this assignment, you will gain experience working with OpenAI Gym, which is a set of problems that can be explored with different reinforcement learning algorithms. This assignment is designed to help you apply the concepts you have been learning about Q-learning algorithms to the “cartpole” problem, a common reinforcement learning problem.

Note: The original code referenced in this assignment was written in Python 2.x. You have been given a zipped folder containing an updated Python 3 version of the code that will work in the Apporto environment. To make this code work, some lines have been commented out. Please leave these as comments.

Reference: Surma, G. (2018). Cartpole. Github repository. Retrieved from https://github.com/gsurma/cartpole.

Prompt

Access the Virtual Lab (Apporto) by using the link in the Virtual Lab Access module. It is recommended that you use the Chrome browser to access the Virtual Lab. If prompted to allow the Virtual Lab access to your clipboard, click “Yes”, as this will allow you to copy text from your desktop into applications in the Virtual Lab environment.

1. Review the following reading: Cartpole: Introduction to Reinforcement Learning. In order to run the code, upload the Cartpole.zip folder into the Virtual Lab (Apporto). Unzip the folder, then upload the unzipped folder into your Documents folder in Apporto. Refer to the Jupyter Notebook in Apporto (Virtual Lab) Tutorial to help with these tasks.

   Note: The Cartpole folder contains the Cartpole.ipynb file (Jupyter Notebook) and a scores folder containing score_logger.py (Python file). It is very important to keep the score_logger.py file in the scores folder (directory).

2. Open Jupyter Notebook and open up the Cartpole.ipynb and score_logger.py files. Be sure to review the code in both of these files. Rename the Cartpole.ipynb file using the following naming convention:

   __Assignment5.ipynb

   Thus, if your name is Jane Doe, please name the submission file “Doe_Jane_Assignment5.ipynb”.

3. Next, run the code in Cartpole.ipynb. The code will take several minutes to run and you should see a stream of output while the file runs. When you see the following output, the program is complete:

   Solved in _ runs, _ total runs.

   Note: If you receive the error “NameError: name ‘exit’ is not defined” after the above line, you can ignore it.

4. Modify the values for the exploration factor, discount factor, and learning rates in the code to understand how those values affect the performance of the algorithm. Be sure to place each experiment in a different code block so that your instructor can view all of your changes.

   Note: Discount factor = GAMMA, learning rate = LEARNING_RATE, exploration factor = combination of EXPLORATION_MAX, EXPLORATION_MIN, and EXPLORATION_DECAY.

5. Create a Markdown cell in your Jupyter Notebook after the code and its outputs. In this cell, you will be asked to analyze the code and relate it to the concepts from your readings. You are expected to include resources to support your answers, and must include citations for those resources.

   Specifically, you must address the following rubric criteria:

   • Explain how reinforcement learning concepts apply to the cartpole problem.
     • What is the goal of the agent in this case?
     • What are the various state values?
     • What are the possible actions that can be performed?
     • What reinforcement algorithm is used for this problem?
   • Analyze how experience replay is applied to the cartpole problem.
     • How does experience replay work in this algorithm?
     • What is the effect of introducing a discount factor for calculating the future rewards?
   • Analyze how neural networks are used in deep Q-learning.
     • Explain the neural network architecture that is used in the cartpole problem.
     • How does the neural network make the Q-learning algorithm more efficient?
     • What difference do you see in the algorithm performance when you increase or decrease the learning rate?

Guidelines for Submission

Please submit your completed IPYNB file. Make sure that your file is named as specified above, and that you have addressed all rubric criteria in your response. Sources should be cited in APA style.

Week 3 assignment 

This program shows how to use an extra tool, which is a button in the window.  When you click on the button the program jumps to the ‘terminate’ section. You can create a jump section by giving it any name and place that section somewhere for the program to go to just like the terminate section.

Program 3:

nomainwin

UpperLeftX  = 1

UpperLeftY = 1

WindowWidth = DisplayWidth – 800

WindowHeight = DisplayHeight – 80

BackgroundColor$ = “red”

ForegroundColor$ = “yellow”

statictext #main.static, ” How is my window looking?” , 20,20, 600, 100

button #main.button1, “Exit”,[terminate], UR, 130, 150, 60, 40

open “Sample Window” for window as #main

print #main, “font Arial 16 bold”

wait

notice ” See you later”

close #main

‘notice ” See you later”

end

Use Justbasic software 

Read chapter 3. Review all the documents in the weekly module before doing the assignment.  

Modify program 3 above to create your own program with the following modifications:

a) Choose different background and foreground colors. Make sure thee text is visible.

b) Create two buttons in the window instead of one.

c) Each button should give a different message when clicked.

1. Conduct graduate-level, academic research on the following topics and draft a five- to 10-page, APA paper summarizing your research results. The paper counts for 300 points of the 1,000 total course points.

   What is the state of cybersecurity viz. digital forensics as its function to mitigate risk and solve incidents?

   What are some of the prominent, open-course digital forensics tools that the field deploys to help conduct forensics investigations? What are some missed opportunities that the industry reflects?

   What are some recent (within last five years) DF successes? Describe two to five incidents that were solved, or partially solved, by digital forensics practitioners. These could be criminal cases or civil cases, such as contract disputes, intellectual property theft, divorces, even. You should be thinking about this part of the research as demonstrating case studies that highlight the importance of forensics to cybersecurity.

Project Topic: Cloud Computing

Follow this link how to write the abstract

https://www.scribbr.com/apa-style/apa-abstract/

This week our topic shifts to the classification concepts in chapter four.  Therefore, answer the following questions:

1. What are the various types of classifiers?
2. What is a rule-based classifier?
3. What is the difference between nearest neighbor and naïve bayes classifiers?
4. What is logistic regression?

Text Books-

 ch. 4 in textbook: Classification: Alternative Technique

Read: Hemmatian, H. (2019). A survey on classification techniques for opinion mining and sentiment analysis. Artificial Intelligence Review, 52(3), 1495–1545.

BIT 595: Professional Consulting in IS

** Minimum 1-2 page with details about Project Idea which include a brief description of your idea and project timeline. **

Mostly it will be complete design. 

Project Idea and Approval

1. Discuss your preliminary ideas with course professor.

Your project idea is your responsibility. Ideas may come from coursework; class or team discussions; your workplace; past experiences; needs identified; or prototypes developed to solve remembered problems.

2. Submit your project idea by end of second week of the semester. This must include a brief description of your idea and project timeline. The project timeline includes the processes involved in meeting the course objectives. Project approval will come from your professor.

The final Project Requirements is as below

In the Professional Consulting in IS course you must:

1. design, plan and/or implement an IS project demonstrating the skills and knowledge learned in the MSIS coursework,

2. prepare a structured written report describing that project and deliverables,

3. make a formal presentation to the MSIS faculty, and

4. submit the approved report to the course professor.

 Write a Java program as follows:
1. Prompt the user on which action they want to take:
a. Convert cubic feet to U.S. bushels
b. Convert miles to kilometers
c. Determine graduation with honors title
d. Exit program
2. Programs at a minimum must have the following methods:
a. Convert cubic feet method that gets cubic feet and returns U.S. bushels.
b. Convert to kilometers method that gets miles and returns kilometers
c. Determine graduation with honors title method that gets GPA and returns
honors title value (category) 

What is AI’s Natural Language processing. What does it involved and provide some examples of it.
Provide examples and present your written findings. 

Requirement 

APA format. You must include 3 scholarly reviewed references that are DIRECTLY related to the subject. 

Pages : 3 ( 1000 words)