Static RAM and Dynamic RAM

 Your computer probably uses both static RAM (SRAM) and dynamic RAM (DRAM) at the same time, but it uses them for different reasons because of the cost difference between the two types. Once you understand how dynamic and static RAM chips work inside your computer, it's easy to see why there's a cost difference between the two and how the two types of RAM got their names.

Dynamic RAM is the most common type of memory in use today. Inside a DRAM chip, each memory cell holds one bit of information and is made up of two parts: a transistor and a capacitor. These are, of course, extremely small transistors and capacitors so that millions of them can fit on a single memory chip

The capacitor holds the bit of information — a 0 or a 1 (see How Bits and Bytes Work for information on bits). The transistor acts as a switch that lets the control circuitry on the memory chip read the capacitor or change its state.

Byte Prefixes and Binary Math

When you start talking about lots of bytes, you get into prefixes like kilo, mega and giga, as in kilobyte, megabyte and gigabyte (also shortened to K, M and G, as in Kbytes, Mbytes and Gbytes or KB, MB and GB). The following table shows the binary multipliers:

Kilo (K)

2^10 = 1,024

Mega (M)

2^20 = 1,048,576

Giga (G)

2^30 = 1,073,741,824

Tera (T)

2^40 = 1,099,511,627,776

Peta (P)

2^50 = 1,125,899,906,842,624

Exa (E)

2^60 = 1,152,921,504,606,846,976

Zetta (Z)

2^70 = 1,180,591,620,717,411,303,424

Yotta (Y)

2^80 = 1,208,925,819,614,629,174,706,176

Modem

 

The Origin of Modems

The word "modem" is a contraction of the words modulator-demodulator. A modem is typically used to send digital data over a phone line.

The sending modem modulates the data into a signal that is compatible with the phone line, and the receiving modem demodulates the signal back into digital data. Wireless modems convert digital data into radio signals and back.

In a configuration like this, a dumb terminal at an off-site office or store could "dial in" to a large, central computer. The 1960s were the age of time-shared computers, so a business would often buy computer time from a time-share facility and connect to it via a 300-bit-per-second (bps) modem.

• 300 bps - 1960s through 1983 or so
• 1200 bps - Gained popularity in 1984 and 1985
• 2400 bps
• 9600 bps - First appeared in late 1990 and early 1991
• 19.2 kilobits per second (Kbps)
• 28.8 Kbps
• 33.6 Kbps
• 56 Kbps - Became the standard in 1998
• ADSL, with theoretical maximum of up to 8 megabits per second (Mbps) - Gained popularity in 1999

What is Modem?

A modem and router are two of the most frequent components in a home network configuration. A router establishes a local area network (LAN), whereas a modem connects to an internet service provider (ISP). For a home network to work, both devices are necessary.

Modem stands for Modulator/Demodulator. The modem is defined as a networking device that is used to connect devices connected in the network to the internet. The main function of a modem is to convert the analog signals that come from telephone wire into a digital form. In digital form, these converted signals are stored in the form of 0s and 1s. The modem can perform both the task of modulation and demodulation simultaneously.

Working of Modem

The two main components of a modem are modulation and demodulation. Where the modem can perform both tasks simultaneously. The step-by-step working of the modem is given below:

Step 1: Data Generation: When data needs to be transmitted it is first generated. Therefore computer system generated the data which is in digital form of 0s and 1s.

Step 2: Modulation: Modulation is defined as a process of converting digital data signals of the computer into analog data signals so that these signals can travel on the internet. The digital data is encoded onto a carrier wave.

Step 3: Transmission: The resultant of modulation that is modulated data is transmitted over the communication line to the modem that is receiving it.

Step 4: Demodulation: Demodulation is defined as a process in which analog data signals from the internet are converted into digital data signals so they can be understood by computer systems. In the process of demodulation the digital data from the carrier wave is decoded.

Step 5: Decoding: The resultant of demodulation that is demodulated data is being sent to the computer systems for their further use.

Types of Modem

There are different types of modems available. Each modem has different features and provides with different benefits. Below are the different types of modems:

1. Optical Modem 

An optical modem, commonly called an ONT (Optical Network Terminal) or ONU (Optical Network Unit), is a device that changes light signals from a fiber-optic cable into digital electrical signals for your router.

In modem, different type of media is used to transfer the signals. Optical Modem is the type of modem that makes use of optical cables instead of using another metallic type of media. The digital data is converted into the pulse of light that is transmitted on the optical fiber used in the optical Modem.

2. Digital Modem

A modem is a device that connects your computer or home network to the internet by translating signals. The main jobs of a modem are modulation and demodulation

Digital Modem is defined as a type of modem that is used to convert digital data into digital signals. Digital data is in form of 0s and 1s. For this, it performs the process of modulation. Digital Modem modulates the digital data on digital carrier signals for transmission.

3. Cable Modem

Cable modems are defined as a type of modem used to establish a communication between computer systems and the Internet Service Providers. A cable modem helps to access high-speed data through cable TV networks. Such modems are usually connected to desktops or systems and work like external devices.

4. Satellite Modem

Satellite Modems are defined as a type of modem that provides with the internet connection through satellite dishes. This type of modem works by sending the input bits into output radio signals and vice versa. The internet network that is provided by such types of modems is more reliable and efficient as compared to other types of modems.

5. Dial Modem

A Dial Modem is a type of modem that converts data used in telephone and data used on computers. In short dial modem converts between analog form and digital form. The networking devices connected to the computer are all at one end and the telephone line is at another end. This type of modem transmits the data at a speed of 56000 per/sec.

Advantages of Modem

• A modem converts digital signals into an analog signal.
• The cost of a modem increases according to the features it has.
• The modem helps to connect the LAN to the internet.
• Modem performs both modulation and demodulation processes simultaneously

ALL LINKS / BDU MSC CS SYLLABUS 26-27

M.SC CS 26-27 SYLLABUS 

BDU M.Sc CS SYLLABUS

ONE NATION ONE SUBSCRIPTION

HOW TO PREPARE WEBINAR

ONOS REG LINK

RESEARCH / IIP SERIES BOOK CHAPTER

 

PYTHON - Data Cleaning and Pre -processing Data

1. Basic Quality Inspection & Summary

Before altering data, ask ChatGPT to write code that analyzes the overall health of your dataset 

Prompt:

“Act as a Senior Data Scientist. I have a DataFrame called df containing global sales data with columns: order_id, product_name, price, quantity, order_date, and customer_email. Write Python code using Pandas to check for missing values, identify total duplicate records, and output the exact data types of each column. Keep the code clean and well-commented.”

2. Handling Missing Data and Type Standardization

Standardizing irregular data formats and resolving blank fields ensures model stability

Prompt:
*“You are a data cleaning assistant. I have a dataset with hidden anomalies. Write a Python script to do the following:

1. Impute missing numerical values in the price column using the column median.
2. Convert strings representing missing values like 'N/A' or 'null' into true NumPy NaN values.
3. Standardize the order_date column into a proper datetime64[ns] format.
   Output only optimized Python code without verbose explanations.”*

3. Handling Outliers Using Statistical Methods

Automatically strip extreme visual anomalies that skew downstream machine learning models

Prompt:
“Write a Python function using Pandas and NumPy that takes a DataFrame df and removes rows containing outliers in the numeric column quantity. Use the Interquartile Range (IQR) method where outliers are defined as values 1.5 × IQR outside the first and third quartiles. Return the cleaned DataFrame.”

4. Categorical Feature Encoding

Transforming non-numeric labels into structured matrices is essential for Scikit-learn pipelines. 

Prompt:
“I am preparing data for a machine learning model. Write Python code to encode a categorical column named shipping_region which has values like 'North', 'South', and 'West'. Use One-Hot Encoding via pd.get_dummies() and ensure it avoids the dummy variable trap by dropping the first category.” 

PYTHON

import pandas as pd

from openai import OpenAI

# Initialize client (Ensure your API key is configured correctly)

client = OpenAI(api_key="your_openai_api_key")

def clean_text_with_gpt(dirty_text_list):

    # Convert text chunks into a structured prompt

    prompt_content = f"Standardize and clean this list of company names. Remove trailing characters, fix typos, and return a clean, comma-separated list:\n{dirty_text_list}"

    

    response = client.chat.completions.create(

        model="gpt-4o",  # Use a stable, current model

        messages=[

            {"role": "system", "content": "You are a precise data cleaning utility. Output only the requested list without chat."},

            {"role": "user", "content": prompt_content}

        ],

        temperature=0.1  # Low temperature keeps output deterministic

    )

    return response.choices[0].message.content

# Example integration into a Pandas pipeline

df = pd.DataFrame({"company": ["Apple Inc.", "apple", "Aple!!", "Google LLC", "Gooogle"]})

cleaned_output = clean_text_with_gpt(df["company"].tolist())

print(cleaned_output)

```

If you want to fine-tune this workflow for your projects, tell me:

* What does a **sample row** of your dataset look like?

* What **specific data issues** are you trying to fix (e.g., typos, broken zip codes, messy text)?

* Do you want the AI to **write the code for you** or **process the data directly** via the API?