Louis Vuitton Malletier S.A. v. Haute Diggity Dog, LLC

In 2007, the high-end signature handbag and luggage maker, Louis Vuitton Malletier, lost an outrageous copyright infringement case against comedy fashion company Haute Diggity Dog.

  1. What was the principle issue in the legal dispute? This should surround the legal issue at the heart of the lawsuit and may include the essential facts of the matter.
  2. What was the rule or set of rules that the court analyzed to frame the legal dispute? Maybe they are federal laws or regulations, or it could be at the state level, or a combination.?
  3. How did the court apply the rules to the set of facts posed by each side? Here, we want your summary of the logic, the critical thinking, and the rationale that the court built its conclusion upon.
  4. What did the court conclude? Who won, who lost, what’s left unanswered for the next phase of litigation if there is one to follow?

· No Plagiarism 

· Should be 400 words without References.

· APA Format Required

  

References: 

https://www.casebriefs.com/blog/law/intellectual-property-law/intellectual-property-keyed-to-merges/trademark-law/louis-vuitton-malletier-s-a-v-haute-diggity-dog-llc/

Louis Vuitton’s Other Lawsuit Was a Winner, but Loses to a Parody Defense – Again.

https://www.law.berkeley.edu/files/louisvuitton.pdf

Python project

Objective: Web scraping with Python

Due: December 7 (11:59pm). 10 pts will be deduced for each late day (24hr). No submission will be accepted after Dec 10 (11:59pm). Total grade for the project is 100.

Grading Procedures: All submission will be checked with a plagiarism software. Submission having more than 70% similarity to any other student submission and/or internet resources will share total points the assignment. For example, 4 submissions having more than 70% similarity will be graded as 100/4 = 25pts, assuming that the program is worth of 100 pts.

Description: The university maintains course schedules at http://appsprod.tamuc.edu/Schedule/Schedule.aspx for different semesters (spring, fall, winter, etc ). You will develop a Python program to dynamically complete certain tasks, such as list, find, sort, and save, in course listings from schedule portal. You will mainly use “request” and “BeautifulSoup” libraries (or similar, see exercise 12.1). The program will operate at different level: Semester and Department.  Your program will be a menu based application. Assume that you project file is myproject.py. Once you run, it will show last 5 semester (fall, spring, summer only, (not winter, may mini))

> python myproject.py
Choose a semester: 1) Sprint 2021   2)Fall 2020  3)Summer II  4)Summer I 5)Spring 2020 
Selection: 2

Here, your program will parse the data from website and show only last (most recent) 5 semesters. User will make selection, then, you will show departments for the selected semester (Fall 2020). Note that selected semester is visible before a “>” sign.

Fall 2020> Select a department:
1) Undeclared
2) Accounting and Finance
3) Art
4) Ag Science & Natural Resources


30) Social Work
31) Theatre
Q)Go back

Selection: 3

Fall 2020> Art > Select an option:
1) List courses by instruction name
2) List courses by capacity
3) List courses by enrollment size
4) List courses by course prefix
5) Save courses in a csv file
6) Search course by instruction name
7) Search courses by course prefix
Q)Go back
Selection: ??

Here, your program will parse the data from website and show all available department then list of tasks. Q (go back) option will take user to previous level. 

Course listing output should show the following fields. For instance for course listing for “Fall 2020> Computer Science & Info Sys> List the course by prefix ” should show

PrefixIDSecNameInstructorHoursSeatsEnroll.COSC130101WIntro to CompuLee, Kwang33510COSC143601EIntro to Comp Sci & ProgBrown, Thomas44036COSC143601LIntro to Comp Sci & ProgBrown, Thomas4036COSC143601WIntro to Comp Sci & ProgHu, Kaoning44543COSC143602EIntro to Comp Sci & ProgHu, Kaoning43532

as first 5 rows.

You will follow above headers and order (prefix (col. width 6), ID (5), Sec (5) ,Name (25), Inst (20), Hours (5), Seats (5), Enroll. (7) ) for other listing selections too. Data cell should be aligned with column header and left justified. A course name should not have a word more than 5 chars. For instance Algorithms should be abbreviated as “Algor”. The length of course name will not exceed 25 chars. In option 5, the above format should be used to save a listing to a file as .csv format. User will be able to provide a filename for csv file.

For this program you need to develop at least one class (chapter 10) with (possible) many methods.

Data Security Principles

Do a bit  if research into File Inclusion Vulnerability.

  • What is it?
  • Why is is dangerous?
  • What is the difference of low and remote inclusion?
  • What methods can me employed to prevent a security breach?
  • What programming languages are vulnerable to this type of attack.

Post between 100-300. Use your own words. Do not copy the work of another students.

Data Science

 Classification: Basic Concepts

Decision Tree Induction

Bayes Classification Methods

Rule-Based Classification   

Assignment 4

1- Consider the data in the following table: 

  

TID 

Home Owner

Marital Status

Annual Income

Defaulted   Borrower

 

1

Yes

Single

[120 – < 150K]

No

 

2

No

Married

[90 – < 120K]

No

 

3

No

Single

[60 – < 90K]

No

 

4

Yes

Married

[120 – < 150K]

No

 

5

No

Divorced

[90 – < 120K]

Yes

 

6

No

Married

[60 – < 90K]

No

 

7

Yes

Divorced

[120 – < 150K]

No

 

8

No

Single

[90 – < 120K]

Yes

 

9

No

Married

[60 – < 90K]

No

 

10

No

Single

[90 – < 120K]

Yes

Let Defaulted Borrower be the class label attribute. 

a) Given a data tuple X = (Home Owner= No, Marital Status= Married, Income= $120K). What would a naive Bayesian classification of the Defaulted Borrower for the tuple be?

2- Consider the training example in the following table for a binary classification problem.

  

Customer ID

Gender

Car Type

Shirt Size

Class

 

1

M

Family

S

C0

 

2

M

Sports

M

C0

 

3

M

Sports

M

C0

 

4

M

Sports

L

C0

 

5

M

Sports

XL

C0

 

6

M

Sports

XL

C0

 

7

F

Sports

S

C0

 

8

F

Sports

S

C0

 

9

F

Sports

M

C0

 

10

F

Luxury

L

C0

 

11

M

Family

L

C1

 

12

M

Family

XL

C1

 

13

M

Family

M

C1

 

14

M

Luxury

XL

C1

 

15

F

Luxury

S

C1

 

16

F

Luxury

S

C1

 

17

F

Luxury

M

C1

 

18

F

Luxury

M

C1

 

19

F

Luxury

M

C1

 

20

F

Luxury

L

C1

a) Find the gain for Gender, Car Type, and Shirt Size.

b) Which attribute will be selected as the splitting attribute? 

CLA2 – CLO 1, CLO 2, CLO 3, CLO 4, CLO 5

 Summary:

CLA2 – CLO 1, CLO 2, CLO 3, CLO 4, CLO 5

In a 4 – 6 page paper based on your internship course experience and the learning objectives achieved during the course, review your internship experience successes and challenges leading to growth. You should demonstrate in your paper a description of your professional portfolio and include any evidence of accomplishment and skill development or recognition that you have acquired this session and how it will contribute to your portfolio.

Provide at least two (2) peer-reviewed sources. If you have completed this CLA2 assignment in an internship course prior to this class, select new examples and sources to support your response. For questions, contact your instructor.

numerical computation project

 This is simple project about numerical computation of Computer Science. It is going to be not heavy work. Read the Project.pdf and do the work and fill the Word Template and Lab report files what I attached.  

week 12 Discussion – Cyberlaw

Please describe the reasons for having a totally anonymous means of accessing the internet. Please also discuss the dangers of that same internet. Minimum 450 words. Please add references in APA format.