Study Notes / MCQ

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MCQ

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How I have been studying and future plans

  • I have reviewed three mcqs on collegeboard
  • I watched over collegeboard videos
  • I am going to solve more mcqs to be prepared for the exam.
  • It is good to finish the final drafts for video, program code, and ppr this week so that I don’t have to worry about it later.
  • I will review my notes and lessons to grab all the informations and concepts that I missed.

Study Guide

Beneficial and Harmful Effects of Computing Innovations

Beneficial Effects

  • Medical Advancements: Improved surgeries, diagnostics, and data-driven patient care.
  • Business Efficiency: Data analytics and automation streamline operations.
  • Artistic Expansion: Digital platforms foster creativity and global collaboration.
  • Convenience (Drones): Faster deliveries and innovative aerial photography.

Harmful Effects

  • Cyberbullying: Causes psychological stress and social isolation.
  • Privacy Loss: Data exploitation and excessive surveillance.
  • Technology Dependence: Reduces critical thinking and research skills.
  • Economic Impact: Job displacement due to automation.
  • Drone Risks: Privacy violations and safety hazards.

Self-Driving Cars: Benefits and Risks

Benefits

  • Safety: Reduces accidents from human error.
  • Traffic Efficiency: Optimized flow and reduced congestion.
  • Accessibility: Empowers the elderly and disabled.
  • Environmental Benefits: Lower emissions from optimized routes.

Risks

  • Job Displacement: Loss of driving-related jobs.
  • Security Risks: Vulnerable to hacking and privacy concerns.
  • Ethical Challenges: Controversies in accident responsibility.
  • Infrastructure Costs: High initial investment for adoption.

Dopamine and Social Media

  • Beneficial Effects: Improves motivation and learning through rewards.
  • Harmful Effects: Addiction and mental health issues from overuse.
  • Solutions: Limit screen time, practice mindfulness, and seek alternatives.

Intellectual Property (IP)

  • Key Protections:
    • Copyright: Protects artistic and literary works.
    • Patents: Safeguards inventions for ~20 years.
    • Trademarks: Covers unique symbols and branding.
    • Trade Secrets: Protects confidential business information.
  • Preventing Violations:
    • Use watermarks and digital rights management (DRM).
    • Register IP and enforce rights.
    • Educate about ethical practices.

Creative Commons Licenses

  • Types: CC BY, CC BY-SA, CC BY-NC, etc.
  • Uses: Share work with permissions; facilitate collaboration.
  • Examples: Open educational resources and shared creative content.

Graphs & Heuristics

Graphs

  • Components: Nodes (entities) and edges (relationships).
  • Types: Directed/undirected, weighted/unweighted.
  • Applications: Social networks (e.g., Facebook), navigation, and recommendations.

Heuristics

  • Definition: Rule of thumb for problem-solving.
  • Examples: Greedy algorithms and A* search.
  • Applications: Google Maps and optimization problems like TSP (Traveling Salesman Problem).

Plagiarism in Computing

  • Definition: Copying code or algorithms without credit.
  • Risks: Legal actions, loss of credibility, and academic penalties.
  • Prevention: Attribute sources, avoid unauthorized collaboration, and use original work.

Licensing Overview

  • MIT License: Flexible and widely used for open-source.
  • GPL License: Requires modified versions to remain open-source.
  • Creative Commons: Best for non-software content like art or media.
  • Apache 2.0: Grants explicit patent rights along with software use.

Social Network Analysis

  • Nodes & Edges: Users are nodes; relationships (e.g., follows, likes) are edges.
  • Example: Facebook uses graphs to model friendships and suggest friends.
  • Key Insight: Graph theory identifies influential nodes and clusters.

Undecidable vs. Decidable Problems

  • Undecidable: No algorithm solves all cases (e.g., Halting Problem).
  • Decidable: Algorithm always provides a correct answer (e.g., divisibility checks).
  • Real-World Handling: Browsers use timeouts and error handling for infinite loops.

Random Algorithms

  • Definition: Use randomness for fairness, efficiency, or modeling uncertainty.
  • Applications: Cryptography, simulations, gaming, AI, and load balancing.
  • Python Example: random.choice() selects random items from a list.

Simulations

  • Definition: Model real-world processes (e.g., epidemics, climate).
  • Applications: Healthcare (drug trials), engineering (stress tests), games (AI).
  • Why Use?: Saves cost, reduces risk, and improves prediction accuracy.

Base64 Encoding

  • Purpose: Converts binary data to text for safe transmission.
  • Use Cases: Email attachments, APIs, embedded images.
  • Drawbacks: Increases data size (~33%) and is not secure.
  • Definition: Efficiently searches sorted lists by dividing the search space.
  • Time Complexity: O(log n) (faster than linear search).
  • Applications: Databases, routing, spell checkers, and AI decisions.

Logic Gates

  • Types: AND, OR, NOT, NAND, NOR, XOR, XNOR.
  • Applications: Authorization, alarms, traffic lights, and pattern recognition.
  • Key Insight: Boolean algebra simplifies circuits.

Lists & Filtering Algorithms

  • Lists: Ordered, mutable collections of elements.
  • Filtering: Extracts elements based on conditions (e.g., even numbers).
  • Efficiency: Linear time complexity (O(n)) for filtering.

Binary (Base-2)

  • Basics: Uses 0 and 1 to represent data.
  • Applications: Arithmetic, circuits, and AI decision-making.
  • Operations: Addition, subtraction, and conversion to/from decimal.

Color Codes

  • Hex: Six-character code (e.g., #FF0000 for red).
  • RGB/RGBA: Red, Green, Blue (+ Alpha for transparency).
  • Applications: Web design, gaming, printing, and video editing.