Lecture 3: Computer Organization Flashcards
Week 3
What was covered in the ICT lecture conducted in Week 3.
The lecture’s overarching topic was computer organization.
The professor explained the fetch, decode, and execute cycle, as well as how different registers are read from and written to by the CPU.
Suggested Revision
Detailed notes about this topic can be found in the ‘Programming Fundamentals’ class, within the ‘Chapter 1’ section.
Week 4
How is mathematics relevant to computer science?
Mathematics finds various uses throughout the field of Computer Science, such as:
- It is used in the ALU to compute different results.
- It is used to calculate memory sizes
- Binary
- Algorithms and Complexity Analysis
Week 4
How is data about a character encoded in hardware?
A lexical character (such as the letter ‘A’) contains the following information about itself in a 16-bit (two word) code:
- 8 bit ASCII code.
- 1 bit blink check boolean value.
- 3 bit background RGB code.
- 3 bit foreground RGB code.
- 1 bit boolean intensity value.
Week 4
How do image recognition algorithms work?
An image recognition algorithm works by analyzing the patterns and features within an image. It typically involves a neural network, which is trained on a dataset of labeled images.
During training, the network learns to recognize specific patterns and features that distinguish different objects or classes. When given a new image, the algorithm processes it through the neural network, which identifies patterns and predicts the object or class it corresponds to based on its learned knowledge.
Image recognition algorithms extract relevant features, filtering out irrelevant information during processing, using techniques like convolutional layers in deep learning.
Week 4
What is a cipher?
A cipher is a piece of information that has been scrambled using a different set of instructions. For example, the cipher in the example below will shift the value of each letter forward by five values.
Input ALI HOW ARE YOU
Output EPM LSA EVI CSY
Week 4
What are shortest path algorithms?
Algorithms that find the shortest path determine the most efficient route between two points in a graph or network, minimizing distance, cost, or other criteria.
Well known examples include the A* algorithm and Dijkstra’s Algorithm.
In a conventional each node is connected to at least one other node. The path between them has two pieces of information stored in it.
- The weight (distance) of the path/
- The direction of the path (optional)
We can also arrange the different paths in a matrix configuration. An example can be found here.
If the paths in the algorithm are directional, we must assign them a positive magnitude while traveling along them, and a negative magnitude while traveling against them.