In the transformational leadership model, we learn how important it is for a leader to articulate his or her vision to others.

  

In the transformational leadership model, we learn how important it is for a leader to articulate his or her vision to others. One way of doing that is through personal stories. The stories should involve lessons you have learned about YOURSELF, about other people, about leadership, or about life in general. Some questions to prompt reflection and recognition:

· What people have had a significant impact on your life and why?

· What hardships have you faced and overcome?

· What are the greatest blessings in your life?

· What do you really, really believe?

· What ideas make your heart skip a beat?

· What do you know about life now that you wish you had known in high school?

· What is the one best piece of advice you could give to a person?

· What life lesson would you like to pass on to your children some day?

· If you only had one year left to live, how would you spend it?

Think beyond clichés (e.g., Love makes the world go round) to insights that are unique to you. How might others benefit from hearing your stories? How do the stories point to your vision as a leader? 

5G Support for autonomous vehicles

  

The term paper it should be of professional quality and be in the format of an IEEE transaction style. Figures must be clear and drawn by you. Proper citation of references must be embedded in the term paper. All term report should be printed in 8.5x11in format, 10 size, time new roman font, two-column, about 8 pages, left, right, top, bottom margin 1 inch, and contain the following:

1. Title page.

2. Abstract (summary of the paper).

3. Introduction (problem motivation, background materials, related work, summary of objectives and methods).

4. (i) Description of existing algorithms/protocols for survey papers; (ii) system model, assumptions, and/or formal problem formulation for research-oriented papers.

5. (i) Comparison among existing algorithms/protocols and discussion on possible

improvements/enhancements; (ii) project results (derivation, proof, justification, or detailed

design/simulation) in one or more numbered sections for research-oriented papers.

6. Conclusions (evaluation of results, suggestions for improvements, or future work).

7. References must follow IEEE Transactions format (at least 10 references). Proper citation of

references must be embedded in the term paper.

Note: Please, follow the above-mentioned guidelines and prepare my term paper report accordingly. Also, I’m attaching my mid-term report document 

Application security – Malware Protection Procedure Guide

  

Project Part 3: Malware Protection Procedure Guide

Scenario

Always Fresh allows external users, such as vendors and business partners, to access the Always Fresh Windows environment. You have noticed a marked increase in malware activity in the test environment that seems to originate from external users. After researching the likely source of new malware, you conclude that allowing external users to connect to your environment using compromised computers exposes Always Fresh to malware vulnerabilities.

After consulting with your manager, you are asked to create a policy that will ensure all external computers that connect to Always Fresh environment are malware free. You create the following policy:

“To protect the Always Fresh computing environment from the introduction of malware of any type from external sources, all external computers and devices must demonstrate that they are malware free prior to establishing a connection to any Always Fresh resource.”

Consider the following questions:

1. What does “malware free” mean?

2. How can a user demonstrate that their computer or device is malware free?

3. What are the steps necessary to establish a malware-free computer or device?

4. How should Always Fresh verify that a client computer or device is compliant?

Tasks

Create a malware protection procedure guide that includes steps for installing and running anti-malware software. Fill in the following details to develop your procedure guide:

1. Provide a list of approved anti-malware software solutions—include at least three leading antivirus and two anti-spyware products. You may include Microsoft products and third-party products. Instruct users to select one antivirus and one anti-spyware product and install them on their computer.

2. Describe the process of:

a. Ensuring anti-malware software and data is up to date. Mandate daily updates.

b. Running regular malware scans. Mandate that automatic scans occur whenever the computer is idle. If that setting is unavailable, mandate daily fast scans and biweekly complete scans.

3. Provide steps to follow any time malware is detected.

a. Immediate reaction—what to do with current work, leave the computer on or turn it off

b. Who to contact

c. What information to collect

The procedure guide may be used by company security professionals in the future. Hence, all steps listed should be clear and self-explanatory.

Required Resources

§ Internet access

§ Course textbook

Submission Requirements

§ Format: Microsoft Word (or compatible)

§ Font: Times New Roman, size 12, double-space

§ Citation Style: APA

§ Length: 2 pages

Self-Assessment Checklist

§ I created a procedure guide that provides clear instructions that anyone with a basic technical knowledge base can follow.

§ I created a well-developed and formatted procedure guide with proper grammar, spelling, and punctuation.

§ I followed the submission guidelines.

DONT BID ON THIS QUESTION IF YOU ARE NOT A PYTHON EXPERT!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

 DONT BID ON THIS QUESTION IF YOU ARE NOT A PYTHON EXPERT!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

DONT BID ON THIS QUESTION IF YOU ARE NOT A PYTHON EXPERT!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

DONT BID ON THIS QUESTION IF YOU ARE NOT A PYTHON EXPERT!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

DONT BID ON THIS QUESTION IF YOU ARE NOT A PYTHON EXPERT!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

DONT BID ON THIS QUESTION IF YOU ARE NOT A PYTHON EXPERT!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!

 

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.

Assignment

Labs 2240…..8

  

  • Module 8 – EC Lab 1
    • Visit the following site:
    • Module 4:Problem Statement:  4.3.1.15 LAB: Character frequency histogram==============================================================================================Submit your Python solution through Blackboard (as explained below).
      Your lab will be graded on whether it’s been set up as a complete and workable solution.

      For your solution to be complete, your program must be able to

    • Set up your script based on the given specifications
    • compile (ie, no syntax error(s))
    • run (ie, no run-time error(s))
    • For your solution to be workable,
    • Your solution should be free of any type of errors (syntax, run-time, logic)
    • you may want to develop an algorithm first, using pseudocode
    • you do NOT need to turn in any algorithm
    • ==========================================================================================================================Grading rubric:
      • You’ll receive full credit, if 
        • your program
          • compiles and runs with no problems 
          • produces the expected output
      • You’ll receive partial credit, if 
        • your program
          • compiles and runs with no problems 
          • produces partial output (that is, incomplete output)
    • You’ll receive 25% of the points, if your program will not compile
    • You’ll receive 30% of the points, if your program compiles but has a run-time problem
    • You’ll receive 40% of the points, if your program produces logic error(s)
    • ==========================================================================================================================What to submit:
      • Your Python solution as a text file
      • A screenshot of a run of your program, showing the output
    • How to submit:
    1. Save your Python program (Module 8 – EC Lab 1) as a text file to your computer
    2. Save a screenshot of a run of your program, showing the output
    3. Click on the above link: Module 8 – EC Lab 1
    4. Locate your Python program (Module 8 – EC Lab 1 file) on your computer
    5. Locate your screenshot of the run of your program
    6. upload (that is, attach) BOTH files, under #4 and #5, to Blackboard
    7. Click on SUBMIT
    8. NOTE: You can make your submission just ONCE.  So, before making your submission, ensure that it does not need any additional editing/revisions.=====================================================================================================
  • AssignmentModule 8 – EC Lab 2
    • Visit the following site:
    • Module 4:Problem Statement:  4.3.1.16 LAB: Sorted character frequency hist===============================================================================================Submit your Python solution through Blackboard (as explained below).
      Your lab will be graded on whether it’s been set up as a complete and workable solution.

      For your solution to be complete, your program must be able to

    • Set up your script based on the given specifications
    • compile (ie, no syntax error(s))
    • run (ie, no run-time error(s))
    • For your solution to be workable,
    • Your solution should be free of any type of errors (syntax, run-time, logic)
    • you may want to develop an algorithm first, using pseudocode
    • you do NOT need to turn in any algorithm
    • ==========================================================================================================================Grading rubric:
      • You’ll receive full credit, if 
        • your program
          • compiles and runs with no problems 
          • produces the expected output
      • You’ll receive partial credit, if 
        • your program
          • compiles and runs with no problems 
          • produces partial output (that is, incomplete output)
    • You’ll receive 25% of the points, if your program will not compile
    • You’ll receive 30% of the points, if your program compiles but has a run-time problem
    • You’ll receive 40% of the points, if your program produces logic error(s)
    • ==========================================================================================================================What to submit:
      • Your Python solution as a text file
      • A screenshot of a run of your program, showing the output
    • How to submit:
    1. Save your Python program (Module 8 – EC Lab 2) as a text file to your computer
    2. Save a screenshot of a run of your program, showing the output
    3. Click on the above link: Module 8 – EC Lab 2
    4. Locate your Python program (Module 8 – EC Lab 2 file) on your computer
    5. Locate your screenshot of the run of your program
    6. upload (that is, attach) BOTH files, under #4 and #5, to Blackboard
    7. Click on SUBMIT
    8. NOTE: You can make your submission just ONCE.  So, before making your submission, ensure that it does not need any additional editing/revisions.

Module 8 – EC Lab 3

Module 4:Problem Statement:  4.3.1.17 LAB: Evaluating students’ results ================================================================================================Submit your Python solution through Blackboard (as explained below).
Your lab will be graded on whether it’s been set up as a complete and workable solution.

For your solution to be complete, your program must be able to

  • Set up your script based on the given specifications
  • compile (ie, no syntax error(s))
  • run (ie, no run-time error(s))

For your solution to be workable,

  • Your solution should be free of any type of errors (syntax, run-time, logic)
  • you may want to develop an algorithm first, using pseudocode
  • you do NOT need to turn in any algorithm

==========================================================================================================================Grading rubric:

  • You’ll receive full credit, if 
    • your program
      • compiles and runs with no problems 
      • produces the expected output
  • You’ll receive partial credit, if 
    • your program
      • compiles and runs with no problems 
      • produces partial output (that is, incomplete output)
  • You’ll receive 25% of the points, if your program will not compile
  • You’ll receive 30% of the points, if your program compiles but has a run-time problem
  • You’ll receive 40% of the points, if your program produces logic error(s)

==========================================================================================================================What to submit:

  • Your Python solution as a text file
  • A screenshot of a run of your program, showing the output

How to submit:

  1. Save your Python program (Module 8 – EC Lab 3) as a text file to your computer
  2. Save a screenshot of a run of your program, showing the output
  3. Click on the above link: Module 8 – EC Lab 3
  4. Locate your Python program (Module 8 – EC Lab 3 file) on your computer
  5. Locate your screenshot of the run of your program
  6. upload (that is, attach) BOTH files, under #4 and #5, to Blackboard
  7. Click on SUBMIT

NOTE: You can make your submission just ONCE.  So, before making your submission, ensure that it does not need any additional editing/revisions. 

OLAP and CRM

 

Primary Task Response: Within the Discussion Board area, write 400–600 words that respond to the following questions with your thoughts, ideas, and comments. This will be the foundation for future discussions by your classmates. Be substantive and clear, and use examples to reinforce your ideas.

Discuss the following for this assignment:

  • Explain the relationship and the difference between online analytical processing (OLAP) systems and customer relationship management (CRM) systems within a business intelligence (BI) program.
  • How can this relationship bolster an organization’s marketing efforts?

Provide sources and examples to support your assessment.

Rope model

 Question

What is the ROPE Model and how is it used? 

Instructions

Length:250 words

Format: MS word

Citations Required