IMSC 500 TERM PAPER FUZZY LOGIC How can a logic which is "fuzzy" be useful? As humans‚ we often rely on imprecise expressions like "usually"‚ "expensive"‚ or "far". But the comprehension of a computer is limited to a black-white‚ everything-or-nothing‚ or true-false mode of thinking. Within conventional logic‚ terms can be only "true" or "false" i.e. either 0 or 1. Fuzzy logic allows a generalization of conventional logic. It provides for terms between "true" and "false" like "almost true"
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The fallacy that I have chosen is Scare Tactic Define: Using fear or a threat against another person in the attempts to get them to conform to your way of thinking or desired action. Design: Scenario 1: As a car salesman I would invoke a sense of fear or urgency in the couple by stating that this car has just come in on the lot and will not last the day. I would tell them that this specific used car and the way and which it was cared for is rare. I would go on to say that this car was just posted
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4 7-1-1952 An Introduction to Legal Logic Lee Lovevinger Member of Supreme Court Bar; Member‚ Minnesota Bar Follow this and additional works at: http://www.repository.law.indiana.edu/ilj Part of the Legal Education Commons Recommended Citation Lovevinger‚ Lee (1952) "An Introduction to Legal Logic‚" Indiana Law Journal: Vol. 27: Iss. 4‚ Article 1. Available at: http://www.repository.law.indiana.edu/ilj/vol27/iss4/1 This Article is brought to you for free and open access by the Law School Journals
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Logic & Critical Thinking - PHIL-C115-002: MIDTERM- — P A G E 1 — 1. "Critical Thinking" is another name for logic. | True | x | False | 2. In the broadest sense‚ _______________‚ is just any matter that is in dispute‚ in doubt‚ or simply "up for review." | logic | | critical thinking | x | an issue | | a premise | 3. Learning how to distinguish between good and bad arguments makes one a better global citizen. x | True | | False | 4. Premises and conclusions are
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LOGIC DESIGN ASSIGNMENT 1. A. B. To convert 85.85 from its decimal form to binary. 2|85 0.85 × 2 = (1). 70 2|42 r 1 0.70 × 2 = (1).40 2|21 r 0 0.40 × 2 = (0).80 2|10 r 1 0.80 × 2 = (1).60 2|5 r 0 0.85₁₀ = .1101₂ 2|2 r 1 2|1 r 0 =1010101₂ THEREFORE 85.85₁₀ = 1010101.1101₂ 2|0 r 1 To convert 85.85₁₀ to Octal 8|85 0.85 x 8 = (6).80 8|10 r 5 0.80 x 8 = (6).40 8|01 r 2
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Programming Logic and Design‚ 6th Edition Chapter 5 Exercises 1. What is output by each of the pseudocode segments in Figure 5-22? Answer: |a. |5‚ 22‚ 5 | |b. |4‚ 6‚ 7 | |c. |5‚ 6 | |d. |Goodbye | | |Goodbye
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3.3 QUIZ In the appeal to force‚ the arguer physically attacks the listener. F In the fallacy of accident‚ a general rule is applied to a specific case where it does not fit. T If an arguer attempts to discredit court room testimony or a promise by pointing out that the witness or the person making the promise is a liar‚ then the arguer commits an argumentum ad hominem (argument against the person) fallacy. T (calling someone a liar without evidence is abusive) In the argumentum ad hominem circumstantial
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Logical Fallacies Handlist and it states that fallacies are statements that might sound reasonable or superficially true but are actually flawed or dishonest. It is important to avoid logical fallacies as they undermine your argument. There are several types of logical fallacies and to keep track of all of them you can separate them into different categories. There are four different main categories that the certain types can go into; they are fallacies of relevance‚ component fallacies‚ fallacies of
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discussing some of the major logical fallacies. A fallacy is a mistaken belief that is used to try and win an argument such as: Elephants are animals. You’re an animal. That makes you an elephant. The mistake here is the belief that since elephants are animals‚ anything considered an animal is an elephant. To detect a fallacy‚ look out for a bad proof‚ the wrong number of choices‚ or a disconnect between the proof and the conclusion. To detect the all natural fallacy by breaking it in half. Some of the
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subqueries up to 32 levels. There are several ways you can categorize subqueries—by the number of results they returns‚ whether they’re correlated (linked to the outer query)‚ or where they’re used within a DML statement. For the purposes of this article‚ I take the last approach and explain how subqueries can be implemented in the SELECT‚ FROM‚ and WHERE clauses of a SELECT statement. Although you can implement subqueries in other clauses and other statement types‚ the examples I provide should demonstrate
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