2023.03.29 00:56 *smolway7* **Could anyone help me in sketching a hydraulic circuit diagram with electrical push buttons for this crane?**

Not sure if this is the right place to post this but, I have to do this for a course which I’m required to take and I’ve been having difficulty with this, any help is appreciated! submitted by smolway7 to Hydraulics [link] [comments] |

2023.03.28 21:47 *werewolves779* **87 f150 5.0 v8 mechanical fan**

Im trying to put a mechanical fan on that bolts to water pump instead of electric. No smog pump, serpentine belt with smooth side running over water pump pulley like the pink diagram. How do i know if i need clockwise or counterclockwise fan? submitted by werewolves779 to MechanicAdvice [link] [comments] |

2023.03.28 21:06 *blockyworld9926* **Anyone have experience with requesting transfer credit evaluations?**

I am currently trying to request for an evaluation for one of my classes that I have taken at my current school which is not yet on the Transfer Equivalency Table. I sent in the syllabus as they requested and they wrote back saying,

"The Dept requires a more detailed Syllabus. Please provide one that lists weekly topics/chapters covered over the course of the semester. Remember to select "Send Back to Registrar" to return the evaluation."

The syllabus for the class already has a OK amount of detail about the topics covered but it wasn't split into the weekly timeframe. I made a new syllabus by reading the old lecture notes and took it to my professor for approval, but he rejected it since he thought that I went way too in depth (something which he thinks isn't needed since he has experience with this type of stuff).

Does anyone know the "correct" amount of detail that they want for the syllabus? I feel like if I just rewrite my professors syllabus again but with a weekly split they will reject it again. I have included both of the syllabuses below. Let me know which one is closer to the one they want:

**Professor's original syllabus:**

**An updated version I made with more detail:**

**Week 1:**

· The importance of the CS 350 course

· Applications of the course in areas such as natural language, bioinformatics, AI state-based machines, and L-systems

· The difference between formal language and natural language, including ambiguity as the main distinction.

· The need for models for hardware and software, and the development of models for computation

· The key elements of a model, including precision, formalization, and abstraction.

· Discrete mathematics review and set theory

· Proof techniques: contradiction, construction, induction

· Two preliminary examples of a DFA (to accept a language)

· Definition of the deterministic finite automaton (DFA)

· DFA as a hardware model and other DFA examples

**Week 2:**

· Review of Deterministic Finite Automata (DFA)

· Two important questions related to DFA: DFA to language and language to DFA

· Definition of alphabet, string, and language

· Examples of DFA for identifying syntactically legal code and legal if statements in C++ code

· DFA file format for encoding Q, Σ, 𝛅, q0, F

· Examples of DFA with state diagrams for identifying even parity and strings containing "aab"

· Kleene star of a function and the extended transition function

· Closure of regular languages under complement.

· Definition of Kleene star of a set and its use to express the language accepted by a DFA as a set

**Week 3:**

· Closure properties of regular languages under union, intersection, and difference

· Using the Cartesian product to simulate two machines together

· Example of DFAs for the intersection and union of two regular languages

· Proof of closure under difference using de Morgan's laws

· Regular operators for regular languages - union, concatenation, and Kleene star

· Introduction to non-deterministic finite automata (NFA) and their examples

· Two interpretations of nondeterminism: oracle and cloning

· A combined parity problem with nondeterminism

· Definition of Nondeterministic Finite Automaton (NFA)

· Examples of NFAs accepting different languages

· Building an NFA that accepts a string with a certain pattern

· Translation of an NFA to a Deterministic Finite Automaton (DFA) using the set of clones construction

· Simulation of an NFA

**Week 4:**

· Review of definitions of DFA, NFA, closure

· Formal construction of simulating DFA

· Why nondeterminism in the FA model then?

· Regular languages are closed under union, concatenation, and Kleene star

· Exercises to build an equivalent DFA for given NFAs

· Corollaries of equivalent power between DFA and NFA

· Regular expressions and their definition

· Building NFA for given languages using regular operations

· Constructively showing regular languages are closed under union, concatenation, and Kleene star

· Abstraction of FA by black box

· Informal ideas and examples to prove closure properties under different regular operations

· Closure constructions for regular operations

· Closure constructions for regular operations (union, concatenation, Kleene star) using NFA

· Translation of regular expression to NFA

· Translation of NFA to regular expression.

**Week 5:**

· Monday & Wednesday: Review of all the above material (Weeks 1-4)

· Friday: MIDTERM 1 (Covers materials from weeks 1-4)

**Week 6:**

· Go over midterm exam 1 results.

· Translation of NFA to regular expressions

· Formal proof of translation of FA to regular expressions

· Removing a state from a GNFA without changing the language

· Examples of translating DFAs to regular expressions.

· Decision algorithms for regular languages

· Testing infiniteness of a language

· Testing equality of two DFAs

· The pumping lemma for regular languages

· Using the pumping lemma to prove a language is not regular.

· Two grammars: Koch snowflake and a sentence grammar

· Context-free grammars for {anbn: n ≥ 0} and {wwR: w∈{a,b}*}

· Definition of the context-free grammar

· Derivations of context-free grammars

**Week 7:**

· Ken Thompson and regular expressions

· Definition of context-free grammar

· Examples of context-free grammars, including one for Boolean expressions in Python

· Extending the grammar for {anbn} to handle Lisp-style expressions

· Examples of grammars for programming languages, compilers, and data formats

· Goals of context-free languages, including unique and efficient parsing

· Different types of grammars, including those for nested parentheses, palindromes, and even length palindromes

· Ambiguity in natural language versus formal language

· Ambiguity in a string, a grammar, and a language

· Two approaches to removing ambiguity in grammar: brute-force and elegant

· Examples of ambiguity in Shakespeare's sonnets, programming languages, and arithmetic expressions

· The definition of an ambiguous string, grammar, and language

**Week 8:**

· Normal forms and their use in various structures

· Definitions of context-free grammars, languages, and leftmost derivations

· Parsing and its goals, including efficient and unique parsing

· Removing epsilon and unit rules from grammars

· Introducing Chomsky normal form and its benefits

· Greibach normal form

· Closure operators for CFL

· Pumping lemma for CFL

· Definitions related to CFGs

· How to build a CFG composed of two parts

· Review examples of translations (DFA to regular expression and NFA to DFA)

**Week 9:**

· Monday & Wednesday: Review of weeks 6-8

· Friday: MIDTERM 2 (Covers materials from weeks 6-8)

**Week 10:**

· Introduction to PDA model

· A hardware model for CFL

· Adding a stack to FA to handle context-free languages

· Typical steps of a PDA

· General form of the PDA transition function

· Oracle Corporation and its early success in using the C programming language

· Definition and interpretation of pushdown automaton (PDA)

· PDA for {an bn : n ≥ 1}

· Accepting by empty stack and translation between accepting with final state and accepting by empty stack

· Deterministic PDA and its limitations

· Translating between CFG and PDA

· Building a PDA from a CFG

· Simulating a CFG using a PDA

· Theorem: A pushdown automaton can be simulated by a context-free grammar

· The search for a universal computer

· The Turing machine in context

**Week 11:**

· The Turing machine model and its fundamental differences from previous models

· Formal definition of the Turing machine

· Examples of the Turing machine and their implementation in a table

· Transition function and strategies to accept certain languages using the Turing machine.

submitted by blockyworld9926 to gatech [link] [comments]
"The Dept requires a more detailed Syllabus. Please provide one that lists weekly topics/chapters covered over the course of the semester. Remember to select "Send Back to Registrar" to return the evaluation."

The syllabus for the class already has a OK amount of detail about the topics covered but it wasn't split into the weekly timeframe. I made a new syllabus by reading the old lecture notes and took it to my professor for approval, but he rejected it since he thought that I went way too in depth (something which he thinks isn't needed since he has experience with this type of stuff).

Does anyone know the "correct" amount of detail that they want for the syllabus? I feel like if I just rewrite my professors syllabus again but with a weekly split they will reject it again. I have included both of the syllabuses below. Let me know which one is closer to the one they want:

- Review of set theory, functions, and proof techniques (Sipser Chapter 0)

- Regular languages (Chapter 1) (a) deterministic and nondeterministic finite automata (hardware models) (b) regular expressions and regular grammars (software models) (c) properties of regular languages (pumping lemma, closure and decision properties)
- Context-free languages (Chapter 2) (a) context-free grammars (software model) (b) pushdown automata (hardware model) (c) parsing and ambiguity; simplification and normal forms for context-free grammars (d) properties of context-free languages (pumping lemma, closure and decision properties)

- Recursively enumerable languages, computability (Chapters 3 and 7) (a) Turing machines (hardware model) (b) Church’s thesis; undecidable and intractable problems; P vs. NP; NP-completeness (c) Chomsky hierarchy.

· The importance of the CS 350 course

· Applications of the course in areas such as natural language, bioinformatics, AI state-based machines, and L-systems

· The difference between formal language and natural language, including ambiguity as the main distinction.

· The need for models for hardware and software, and the development of models for computation

· The key elements of a model, including precision, formalization, and abstraction.

· Discrete mathematics review and set theory

· Proof techniques: contradiction, construction, induction

· Two preliminary examples of a DFA (to accept a language)

· Definition of the deterministic finite automaton (DFA)

· DFA as a hardware model and other DFA examples

· Review of Deterministic Finite Automata (DFA)

· Two important questions related to DFA: DFA to language and language to DFA

· Definition of alphabet, string, and language

· Examples of DFA for identifying syntactically legal code and legal if statements in C++ code

· DFA file format for encoding Q, Σ, 𝛅, q0, F

· Examples of DFA with state diagrams for identifying even parity and strings containing "aab"

· Kleene star of a function and the extended transition function

· Closure of regular languages under complement.

· Definition of Kleene star of a set and its use to express the language accepted by a DFA as a set

· Closure properties of regular languages under union, intersection, and difference

· Using the Cartesian product to simulate two machines together

· Example of DFAs for the intersection and union of two regular languages

· Proof of closure under difference using de Morgan's laws

· Regular operators for regular languages - union, concatenation, and Kleene star

· Introduction to non-deterministic finite automata (NFA) and their examples

· Two interpretations of nondeterminism: oracle and cloning

· A combined parity problem with nondeterminism

· Definition of Nondeterministic Finite Automaton (NFA)

· Examples of NFAs accepting different languages

· Building an NFA that accepts a string with a certain pattern

· Translation of an NFA to a Deterministic Finite Automaton (DFA) using the set of clones construction

· Simulation of an NFA

· Review of definitions of DFA, NFA, closure

· Formal construction of simulating DFA

· Why nondeterminism in the FA model then?

· Regular languages are closed under union, concatenation, and Kleene star

· Exercises to build an equivalent DFA for given NFAs

· Corollaries of equivalent power between DFA and NFA

· Regular expressions and their definition

· Building NFA for given languages using regular operations

· Constructively showing regular languages are closed under union, concatenation, and Kleene star

· Abstraction of FA by black box

· Informal ideas and examples to prove closure properties under different regular operations

· Closure constructions for regular operations

· Closure constructions for regular operations (union, concatenation, Kleene star) using NFA

· Translation of regular expression to NFA

· Translation of NFA to regular expression.

· Monday & Wednesday: Review of all the above material (Weeks 1-4)

· Friday: MIDTERM 1 (Covers materials from weeks 1-4)

· Go over midterm exam 1 results.

· Translation of NFA to regular expressions

· Formal proof of translation of FA to regular expressions

· Removing a state from a GNFA without changing the language

· Examples of translating DFAs to regular expressions.

· Decision algorithms for regular languages

· Testing infiniteness of a language

· Testing equality of two DFAs

· The pumping lemma for regular languages

· Using the pumping lemma to prove a language is not regular.

· Two grammars: Koch snowflake and a sentence grammar

· Context-free grammars for {anbn: n ≥ 0} and {wwR: w∈{a,b}*}

· Definition of the context-free grammar

· Derivations of context-free grammars

· Ken Thompson and regular expressions

· Definition of context-free grammar

· Examples of context-free grammars, including one for Boolean expressions in Python

· Extending the grammar for {anbn} to handle Lisp-style expressions

· Examples of grammars for programming languages, compilers, and data formats

· Goals of context-free languages, including unique and efficient parsing

· Different types of grammars, including those for nested parentheses, palindromes, and even length palindromes

· Ambiguity in natural language versus formal language

· Ambiguity in a string, a grammar, and a language

· Two approaches to removing ambiguity in grammar: brute-force and elegant

· Examples of ambiguity in Shakespeare's sonnets, programming languages, and arithmetic expressions

· The definition of an ambiguous string, grammar, and language

· Normal forms and their use in various structures

· Definitions of context-free grammars, languages, and leftmost derivations

· Parsing and its goals, including efficient and unique parsing

· Removing epsilon and unit rules from grammars

· Introducing Chomsky normal form and its benefits

· Greibach normal form

· Closure operators for CFL

· Pumping lemma for CFL

· Definitions related to CFGs

· How to build a CFG composed of two parts

· Review examples of translations (DFA to regular expression and NFA to DFA)

· Monday & Wednesday: Review of weeks 6-8

· Friday: MIDTERM 2 (Covers materials from weeks 6-8)

· Introduction to PDA model

· A hardware model for CFL

· Adding a stack to FA to handle context-free languages

· Typical steps of a PDA

· General form of the PDA transition function

· Oracle Corporation and its early success in using the C programming language

· Definition and interpretation of pushdown automaton (PDA)

· PDA for {an bn : n ≥ 1}

· Accepting by empty stack and translation between accepting with final state and accepting by empty stack

· Deterministic PDA and its limitations

· Translating between CFG and PDA

· Building a PDA from a CFG

· Simulating a CFG using a PDA

· Theorem: A pushdown automaton can be simulated by a context-free grammar

· The search for a universal computer

· The Turing machine in context

· The Turing machine model and its fundamental differences from previous models

· Formal definition of the Turing machine

· Examples of the Turing machine and their implementation in a table

· Transition function and strategies to accept certain languages using the Turing machine.

2023.03.28 17:34 *SierraLover1819* **Flanges on pumps..**

Good Morning! I am 37+4 and I pulled out my pump and was checking the parts ( Elivie Stride Pump) and the diagram vs nipple size and my question is when did you make the jump to buy a different flange size. My boobs have not grown since early pregnancy. So should I hold out until after baby is born to measure my nipple in the flange?

submitted by SierraLover1819 to breastfeeding [link] [comments]