Notes, summaries, assignments, exams, and exercises for Computer science for Vocational training

Essential Number Properties and Divisibility Rules

Computer science4.22 KB

Fundamental Number Concepts

Prime Numbers Up to 97

Here is a list of prime numbers up to 97:

  • 2
  • 3
  • 5
  • 7
  • 11
  • 13
  • 17
  • 19
  • 23
  • 29
  • 31
  • 37
  • 41
  • 43
  • 47
  • 53
  • 59
  • 61
  • 67
  • 71
  • 73
  • 79
  • 83
  • 89
  • 97

Rules for Exponents

Understanding how exponents work is crucial for various mathematical operations:

  • Positive Base: If the base (m) is positive, the result (b) of mn = b is always positive.
  • Negative Base, Even Exponent: If the base (-M) is negative and the exponent (n) is an even number, the result (+b) of (-M)n = +b is positive.
  • Negative Base, Odd Exponent: If the base (-M) is negative and the exponent (n) is an odd number, the result (-b) of (-M)n = -b is negative.

Powers of Decimal Numbers

Here are examples of squaring and cubing decimal numbers:

  • 1.12 = 1.21
  • 0.42 = 0.16
  • 0.032 = 0.0009
  • 0.23 = 0.008

Divisibility Criteria

Divisibility...

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Mastering Page Layout: Essential Elements and Formats

Computer science4.81 KB

Elements of Page Layout

Clean layout: Visual elements in good order.

Layout elements are three essential elements:

Format: The size or area of the paper on which our design will be printed.

Many formats are according to user needs, such as books, magazines, etc.

Margins: The surrounding areas that respect each box and the edge of the paper.

May be varied according to design. (Head, Spine, Foot, and Fore-edge).

The Box: This is the real space and limiting area where we diagram and fit the elements of the page.

In Microsoft Publisher, the document box appears delineated by a blue box on the page.

Chaotic layout: Items at random, without aesthetic consideration.

What is Page Layout?

It is the attempt to balance the elements across pages, organizing the masses...

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Understanding Computer Systems: Hardware, Software, and Key Concepts

Computer science3.17 KB

1. Computer System

The set of physical elements (Hardware) and software (Software) that allow information processing.

2. Physical Subsystem

Commonly known as hardware.

3. Logical Subsystem

Referred to as software.

4. Computer

An electronic device capable of processing data, performing load, arithmetic, and logic operations without human intervention.

5. Informatics

The science that studies the automatic and rational treatment of information.

6. Automatic and Rational

  • Automatic: Tasks are performed by machines.
  • Rational: Processes follow human reasoning.

7. Central Processing Unit (CPU)

Responsible for implementing programs and comprises the main memory, control unit, and arithmetic-logic unit.

8. Supercomputer

A specialized machine designed for tasks requiring...

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Workshop Workload and Production Capacity Management

Computer science3.82 KB

Workshop Planning and Control

Planning

Planning aims to coordinate workload with available resources and equipment to perform the required services in production, or the quantity and quality required, at the lowest cost and meeting the deadline.

Organization

Methods, order, time > budget OR > acceptance > delivery term.

Workload

The workload is the amount of work available for the workshop, consisting of the OR already issued and accepted by clients.

Production Capacity

Production capacity is the amount of work that the workshop can perform based on available operators, equipment, and facilities.

The workload can be defined in a working or time to implement and scale, or are uncertain about working with an open OR work involving a diagnostic...

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Shared Memory in IPC: Features and Creation

Computer science2.8 KB

Common Features of IPC Light Mechanisms

These mechanisms are implemented as a unit and share common features, including:

  • All mechanisms have a table whose entries describe their usage. Each table entry has a numerical key chosen by the user.
  • Each mechanism has a 'get' call to create a new entry or retrieve an existing one. The parameters of this call include a key and a mask of flags. The kernel searches the table for an entry that matches the provided key.
  • If the key is set to IPC_PRIVATE, the kernel occupies the first free entry. Subsequent calls will return this entry until it is released.
  • If the IPC_CREAT flag is active in the mask, the kernel creates a new entry if there is no match for the provided key. If both IPC_CREAT and IPC_EXCL flags
...
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SPC Control Systems: Centralized vs. Distributed

Computer science2.3 KB

SPC Control System

SPC Control System refers to the method of controlling a switching system.

  • Centralized SPC Control: If a given processor has direct access to all resources of the node and performs all system functions. This usually means the node has a single central computer (doubled for security).
  • Distributed SPC Control: If a processor is in a given state but does not have access to some of the resources and/or is not able to run only some of the functions of the system. In practice, this leads to an existing digital system with a high number of microprocessors that perform the control node as a whole.

Functions of Switching Systems

Switching systems provide power and signaling with user terminals. The user, via the wire pair of the switching...

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MS-DOS Memory Management: Conventional, Upper, Expanded

Computer science3.53 KB

MS-DOS Memory Management

The memory management depends on the version of MS-DOS we use and the CPU that we have.

Processor Memory Limits

Processors have different address limits:

  • 8088 / 8086 (XT): handle up to 1 MB
  • 286 (AT): handle up to 16 MB
  • 386: handle up to 4096 MB

Conventional Memory

Conventional memory is where programs run; you must manage it properly and release memory when possible.

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S.O.

Contains the interrupt table, computer specification, etc.

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Core MS-DOS Files

The core files include (examples by version):

  • IO.SYS (depending on the version)
  • MSDOS.SYS (system)
  • Other variable core components

Order File (CONFIG.SYS)

Configuration directives and settings found in CONFIG.SYS:

  • BUFFERS
  • FCBS
  • FILES
  • LASTDRIVE
  • STACKS

Device Drivers

Device drivers loaded via

...

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Computer Architecture Fundamentals: CPU, Memory, Buses, and Addressing

Computer science3.52 KB

Core Computer Architecture Components

CPU Registers Explained

CPU registers are small, high-speed storage locations within the central processing unit (CPU) that hold data and instructions for immediate processing.

Accumulator Register

The Accumulator Register stores the results of executed operations. It connects to input registers for feedback in chained operations and also connects to the data bus for sending results to main memory or the control unit.

Program Counter (PC)

The Program Counter (PC) stores the memory address of the next instruction to be executed.

Instruction Register (IR)

The Instruction Register (IR) contains the instruction currently being executed.

Understanding Computer Buses

A bus is a channel or set of parallel connections that...

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Operating Systems: Types, Processes, and Architectures

Computer science2.77 KB

Batch Processing Systems

5) For + d l sistma oprativo exploit. Two types are distinguished:

  • Processes by Lots: The following processes are followed:
  1. Load the data in a device (e.g., punched cards).
  2. Receive the magnetic tape CPU and processes, leaving the results on another magnetic tape.
  3. Other devices manage the processed data, leaving it for printing or visualization.

In this way, the CPU processes data only in intervals. This system is very slow because it takes time to load and remove the data. This is the oldest system used and the first structure supposed to be of the IT department, according to these functions. The operators entered and exited the CPU managers.

  • Real-Time:

The process is very different from the processes by lots, more prone to...

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Tensors and Variables in PyTorch and TensorFlow

Computer science2.4 KB

Tensors and Variables in PyTorch and TensorFlow

Here's a brief explanation of tensors and variables in the context of deep learning frameworks like PyTorch and TensorFlow:

Tensors

  • Definition: A tensor is a multi-dimensional array used to represent data (such as scalars, vectors, matrices, or higher-dimensional data).
  • Common Operations: Tensors can be manipulated with mathematical operations (addition, multiplication, etc.), reshaped, sliced, etc.

In PyTorch, tensors are the core data structure:

import torch
# Create a tensor
a = torch.tensor([[1, 2], [3, 4]])
# Basic operations
b = a + 2         # Adds 2 to each element
c = a * a         # Element-wise multiplication
d = a @ a         # Matrix multiplication

Output:

Tensor `b`: [[3, 4], [5, 6]]
Tensor
...
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