ASKiIMAN™ DOOR 03 / THE DIGITAL MACHINE / REALM 02
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Ontological Layer: Data Representation

Number Systems

The Languages of Mathematical Truth

The Universal Value

A number is an abstract concept; a numeral is merely the symbol we use to express it. The Digital Machine understands only binary (0 and 1), while humans understand decimal (0-9). This realm maps the positional mathematics that allows us to translate absolute mathematical values across different linguistic bases—Binary, Octal, Decimal, and Hexadecimal—without losing their fundamental truth.

NUMBER → REPRESENTATION → BASE / RADIX → POS WEIGHTS → DIGITS → CONVERSION → CAPACITY LIMITS → OVERFLOW → MACHINE INTERPRETATION

The 12 Conversional Nodes

Vertical Ontology: From Abstract Value to Machine Bits

NODE 01

Value vs Representation

  • 01 Number vs Numeral
  • 03 Base / Radix Definition
  • 17 General Positional Rep.
  • 70 Numerical Interpretation
NODE 02

Positional Notation

2³2²2¹2⁰
1011
8021
  • 06 Place Value & 07 Weight
  • 08 MSD vs 09 LSD
  • 12 The Radix Point
  • Integer vs Fractional Parts
NODE 03

The Four Major Bases

  • 13 Decimal (Base 10)
  • 14 Binary (Base 2)
  • 15 Octal (Base 8)
  • 16 Hexadecimal (Base 16)
NODE 04

Integer Conversion

25 ÷ 2 = 12 R 1
12 ÷ 2 = 6 R 0
6 ÷ 2 = 3 R 0
  • 19 General Base Conversion
  • 33 Repeated-Division Method
  • Read Remainders Bottom-Up
  • 34 Positional-Expansion (To Dec)
NODE 05

Fractional Conversion

1.375 × 2 = 1.375
0.375 × 2 = 0.75
1.75 × 2 = 1.5
  • 37 Fractional Number Systems
  • 42 Repeated-Multiplication Method
  • Read Integers Top-Down
  • 44 Terminating vs Repeating
NODE 06

Binary ↔ Octal Shortcut

101
010
111
  • 35 Grouping Method Concept
  • 36 3-bit groups = 1 Octal Digit
  • 53 Binary–Octal Mathematical Rel.
  • 26 Bin→Oct and 27 Oct→Bin
NODE 07

Binary ↔ Hex Shortcut

1010
1111
  • 36 4-bit groups = 1 Hex Digit
  • 54 Binary–Hexadecimal Relation
  • Why Hex is used in Computing
  • 28 Bin→Hex and 29 Hex→Bin
NODE 08

Representation Limits

  • 56 Representation Limits Concept
  • 59 n-Bit Representation Constraints
  • 57 Range (0 to 2ⁿ - 1)
  • Hardware Size Constraints
NODE 09

Overflow & Underflow

  • 68 Overflow (Exceeding Max Value)
  • Loss of Most Significant Bit
  • 69 Underflow (Fractions/Negative)
  • Critical Engineering Concept
NODE 10

Size Terminology

  • 60 Bit (Binary Digit)
  • 61 Nibble (4 bits)
  • 62 Byte (8 bits)
  • 63 Word (Architecture Dependent)
NODE 11

Machine Interpretation

  • 71 Rep vs Mathematical Value
  • Raw Bits Have No Inherent Meaning
  • Context Defines Interpretation
  • 77 Number-System Applications
FINAL PROTOCOL

12 — Conversion & Verification Laboratory

[72] SHORTCUTS [73] VERIFICATION [74] CROSS-BASE CHECK [76] COMMON TRAPS [80] PROBLEM SOLVING

A number converted incorrectly corrupts all subsequent operations. This final stage focuses on rapid conversion techniques, identifying common computational traps, and utilizing cross-base verification to guarantee absolute mathematical fidelity.

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