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Pumping Lemma, Table Filling, DFA Minimization, Parse Trees, Ambiguous Grammars & Context-Free Grammars

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Pumping Lemma and Non-Regular Languages

9) Define Pumping Lemma. Prove that the language L = { ai bj | i > j } is not a regular language:

Let L be a regular language. There exists a constant k such that for every string ω in L, where the length of string ω i.e |ω| ≥ k, we can break ω into 3 strings i.e ω = xyz following conditions:

  • (i) |xy| ≤ k
  • (ii) y ≠ ε i.e |y| > 0
  • (iii) for each q ≥ 0, xyqz ∈ L

Let L be a regular language. w = a(k+1) bk is a long string (given k > 0). |w| = 2k + 1, w = xyz should satisfy:

  • (i) |xy| ≤ k
  • (ii) y ≠ 0
  • (iii) for each q ≥ 0, xyq z ∈ L

Let k = 3, w = a4 b3, which is aaaaabbb.

  • (i) |xy| ≤ k, 3 ≤ 3
  • (ii) y ≠ 0, y = a

H9FBuxZIeVj9wAAAABJRU5ErkJggg==


QTJxPHYAAAAASUVORK5CYII=

Minimization of DFA's

11) Minimization of DFA’s A=(Q, Σ, δ, q0, F):

Use... Continue reading "Pumping Lemma, Table Filling, DFA Minimization, Parse Trees, Ambiguous Grammars & Context-Free Grammars" »

English Vocabulary Acquisition and Teaching Stages

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English Vocabulary Acquisition

How Children Learn Word Meaning

Children are always acquiring and building up their L1. They must find out which things can be packaged together under a label.

Knowing a Word: Types of Knowledge

Knowing a word involves different types of knowledge. The importance is how it is pronounced.

Factors Affecting Vocabulary Learning

  • Demonstrability: Can the meaning be easily shown? (e.g., car = transport)
  • Similarity: Is it similar to known words? (e.g., equal)
  • Brevity: Is it a short or long word?
  • Regularity of Form / Learning Load: Does it follow typical patterns? (e.g., bedroom)
  • Opportunism: Is the word relevant to the child's immediate situation?
  • Centres of Interest: Are words likely to be of relevance to the child's interests?
... Continue reading "English Vocabulary Acquisition and Teaching Stages" »

Language Acquisition & Child Development

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Key Concepts in Language Acquisition and Child Development

Questions & Answers

  1. According to Chomsky, language is... A (We possess an innate capacity for language.)
  2. Which of the following statements is true? C (Learners need a supportive environment.)
  3. Behaviorism relies on... A (Skinner's theory of operant conditioning.)
  4. According to Krashen... C (Comprehensible input is important.)
  5. According to constructivism... A (Children of a similar age think similarly.)
  6. The term "concentration span" refers to... A (The time and capacity for focused attention.)
  7. Comprehensible input means... B (The teacher uses facial expressions and gestures.)
  8. Language acquisition does not require... D (All of the above.)
  9. What is the zone of proximal development? A (The zone
... Continue reading "Language Acquisition & Child Development" »

Power control.

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To control by PWM requires 2 factors:

1-crossing detection signal by 0.

2-? determine the time, every time you walk by 0.

to detect the zero crossing can be performed
through an operational amplifier connected
comparator.

gYQAAAAASUVORK5CYII =

TCA = 785
Pin Symbol Function
1 GND Earth
2 Q2 *Output 2 Inverted
3 Output U QU
4 Q1 * Output 1 Inverted
5 5Synchronizing voltage Vsync (to detect
zero crossing)
6 Inhibitor
7 QZ Z Output
8 8 Vref voltage stabilized (continuous signal for the
integrator)
9 9 ramp resistor R9 (for the integrator)
10 C10 ramp Capacitance (for the integrator)
11 11 V11 Control Voltage (for comparator)
12 12 C12 pulse Extension
13 LLong pulse
14 Q1 Output 1
15 Q2 Output 2
16 l sSupply voltage.
2Q ==

NLP Techniques: Text Generation, Semantic Search & More

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Preprocessing the Dataset

a. Normalize the Text

Python

import re
from nltk.tokenize import word_tokenize
import nltk
nltk.download('punkt')

# Preprocessing Function
def preprocess(text):
    text = re.sub(r'[^a-z\s]', '', text.lower())
    return word_tokenize(text)

# Apply Preprocessing
df['Processed'] = df['Sentence'].apply(preprocess)
print(df)


GPT-2 Text Generation

Python

from transformers import pipeline

# Load GPT-2 Model for Text Generation
generator = pipeline('text-generation', model='gpt2')

# Generate Text for a Given Prompt
prompt = "Once upon a time"
result = generator(prompt, max_length=50,
    num_return_sequences=1)
print(result[0]['generated_text'])


GPT-2 for AI Prompts

a. Prompt 1 - Future of AI

Python

prompt = "What is the future
... Continue reading "NLP Techniques: Text Generation, Semantic Search & More" »

English Grammar: Past Simple vs. Past Continuous, Used to, Modals, Reported Speech

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When past simple and while past continuous. Used to: affirmative - S+used to+v.ing, negative - S+didn't use to+inf, interrogative - Did+S+use to+inf? Yes, I did. No, I didn't. Active Voice: Subject+verb+D.C.+Complement

Passive Voice: Subject+verb+D.C. (by)+Complement

Modals

  • can/can't -> puede/no puede
  • could/couldn't -> podía/no podía
  • should/shouldn't -> debería/no debería -> consejo
  • must -> deber -> obligación
  • mustn't -> no deber -> prohibición
  • have to -> tener que
  • don't have to -> no tener que -> no obligación
  • may -> puedo que
  • might -> podía ser que -> posibilidad

Reported Speech

  • now -> then
  • today -> that day
  • tomorrow -> the next day/the following day
  • yesterday -> the previous day/the day before
  • next
... Continue reading "English Grammar: Past Simple vs. Past Continuous, Used to, Modals, Reported Speech" »

Understanding Hardware and Software in Computing Systems

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[Ch-1] Hardware = [Physical](iPhone) - vs - Software -- (iOS) = [Programs with instructions] -- [Layers of a Computing System] - (C.A.O.P.H.I) Communications -> Applications -> Operating Systems -> Programming -> Hardware

Information -- Abstraction - [a mental model that removes complex details] - Applies to (Miller's Law) [the average person can hold in working memory about seven items] Internal View = car engine, while Abstract View = driving -- Stonehenge, Wiltshire, England 3000 BC to 2000 BC -- Abacus - [early device to record numerical values] - Blaise Pascal - [Mechanical device for addition, subtraction, multiplication, and division] -- Joseph Jacquard - [Loom, punched card], Charles Babbage - [Analytical engine] -- Ada Lovelace... Continue reading "Understanding Hardware and Software in Computing Systems" »

English Grammar: Verb Tenses and Adjectives

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INGREDIENTES:

  • Present Simple: pronoun + present form of verb.
  • Present Continuous: pronoun + am/is/are + verb + -ing.
  • Past Simple: pronoun + second column.
  • Past Continuous: pronoun + was/were + verb + -ing.
  • Past Perfect: pronoun + had + third column.
  • Present Perfect Simple: pronoun + have/has + third column.
  • Present Perfect Continuous: pronoun + have/has + been + verb + -ing.

MODO DE USO:

  • Extreme Adjectives: totally, completely, and absolutely.
  • Normal Adjectives: very, extremely, rather, and quite.
  • Both: really.
  • Vocabulary: u1 arrogant, bossy, calm, cheerful, clever, confident, friendly, funny, hard-working, impatient, lazy, nervous, nice, patient, quite, reliable, selfish, serious, shy, talkative, tidy, unfriendly, untidy. u2 break down, check in, get
... Continue reading "English Grammar: Verb Tenses and Adjectives" »

English Verb Tenses: Simple, Continuous, Perfect, and Future

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Presente simple

Afirmativa: persona + verbo (3a sg -s)(He, She, It) I play Yo juego

Negativa: persona + don't/doesn't(3a sg) + verbo You don't play

Interrogación: do/does(3a sg) + persona + verbo Does she play?

Presente continuo

Afirmativa: persona + to be (am, is, are) + verbo (-ing)I am playing Yo estoy juego

Negativa: persona + am not/ isn't/ aren't + verbo (-ing) You aren't playing

Interrogación: to be + persona + verbo (-ing) Is he playing?

Pasado simple

Afirmativa: persona+ verbo (-ed/ 2ª columna irregulares) I played Yo jugué

Negativa: persona + didn't + verbo He didn't play

Interrogación: did + persona + verbo Did you play?

Pasado continuo

Afirmativa: persona + to be en pasado (was/were) + verbo (-ing) I was playing Yo estaba jugando

Negativa:... Continue reading "English Verb Tenses: Simple, Continuous, Perfect, and Future" »

Wind and Solar Power: The Future of Energy?

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The Energy of Tomorrow

Wind Power: A Solution?

It is generally accepted that we will not be able to use oil and gas to power our homes forever. These energy forms contribute to pollution, and as a result, alternative, clean energy sources will be relied on more in the future. One of the most common alternative sources is wind power, but does this solve our energy problems?

It is well known that wind energy is a clean energy source. Not only is it sustainable, but it is also cheap. Furthermore, wind turbines perform reliably and are adaptable; they are perfect for both the city and the countryside. In countries such as Spain, more than 20% of the electricity used is already generated by wind turbines.

Disadvantages of Wind Power

However, there are... Continue reading "Wind and Solar Power: The Future of Energy?" »