Comparison Outline

 Software engineering tools for soft computing: MATLAB, R Tool and DTREG.  Comparison should focus on how they are able to model neural networks.  Also, pick criteria that compares things they all have in common. 

PS: The outline should look like the sample attached

Response

Your responses to other students must be more than a simple “Good job” or “I agree with your post”. They must also not just be “Let me add to your post…” Instead, your responses to each other should do three things:

1. Acknowledge the other student’s post with some form of recognition about what they posted
2. Relate their posting to something you have learned or are familiar with
3. Add to the conversation by asking additional questions about their post, or discussing their topic further

Remember, this is a discussion forum. Your engagement with each other should be similar to how you would speak with each other if you were seated at the same table talking. Plagiarism in the discussion will not be tolerated.

Ethical Hacking

Select one network scanning software tool (there is a list in your required reading slides) and explain in detail how it works and how detects network vulnerabilities. Provide the site where you obtained your information and include that in your assignment write-up.

Homework

Answer the following question:

SQL is a pervasive querying language. While there is one primary SQL dialect that all SQL RDBMS implementations must support, and that’s ANSI SQL, each database platform comes out with its own context. Each of these dialects has its own  DDL (Data Definition Language). DML (Data Manipulation Language). and DQL (Data Query Language). Other than for marketing purposes (to sell the product as unique), what is the value of creating a new variation of a SQL dialect. 

Provide an example of one SQL dialect as part of your write-up. 

Instructions:

This is a required assignment, worth 15 points. The assignment must be submitted by the due date. Late assignment are not allowed. 

You are required to submit a minimum of two postings. Points will be deducted for not fulfilling this minimum requirement.

Apply and use the basic citation styles of APA is required. Points are deducted per the rubric for this behavior.

Do not claim credit for the words, ideas, and concepts of others. Use in-text citation and list the reference of your supporting source following APA’s style and formatting. Points are deducted per the rubric for this behavior.

Do not copy and paste information or concepts from the Internet and claim that is your work. It will be considered Plagiarism and you will receive zero for your work. A second offense results in a zero for the course. A third is termination from the university.

Discussion: Activities Encapsulated by Working With Data

According to Kirk (2016), most of your time will be spent working with your data.  The four following group actions were mentioned by Kirk (2016):

  • Data acquisition: Gathering the raw material
  • Data examination: Identifying physical properties and meaning
  • Data transformation: Enhancing your data through modification and consolidation
  • Data exploration: Using exploratory analysis and research techniques to learn

Select 1 data action and elaborate on the actions performed in that action group.

Remember your initial post on the main topic should be posted by Wednesday 11:59 PM (EST). Your 2 following posts should be commenting on your classmates’ post on different days by Sunday 11:59 PM (EST). You should end the week with 3 total discussion posts.

A quality post is more than stating, “I agree with you.” Maybe you should state why you agree with your classmate’s post. Additionally, post some examples or find a related topic on the internet or University library and comment on it in the discussion post.

 Reference: Kirk, A. (2016). Data Visualisation: A Handbook for Data-Driven Design (p. 50). SAGE Publications.