7, జులై 2025, సోమవారం

professor.<......... it is appearing to me as a railway station. oh............. if it so you can travel to your place.......... Mr ram..............Eidetic memory, often called photographic memory, refers to the ability to recall an image with high precision and detail after only a brief exposure. It's like having a temporary "afterimage" in your mind's eye that you can access for a short time. While often used interchangeably, it's distinct from hyperthymesia, which involves detailed recall of personal autobiographical events

 Professor Robert Langdon is a fictional character created by author Dan BrownHe is a Harvard University professor specializing in religious iconology and symbology. Langdon is the protagonist of a series of novels, including Angels & Demons, The Da Vinci Code, The Lost Symbol, Inferno, and Origin. He is known for his eidetic memory, problem-solving skills, and expertise in deciphering symbols and codes. 

Here's a more detailed look at Professor Langdon:
  • Fictional Field:
    Langdon's area of expertise is religious iconology and symbology, a fictional field that explores the study of historical symbols. While not directly connected to the actual discipline of semiotics, it is a central element in the novels. 
  • Physical Description:
    He is often depicted as having blue eyes, a pale complexion, thick black hair with hints of gray, and a dimpled chin. He is lean and toned, with a strong, carefree smile. 
  • Key Characteristics:
    Langdon possesses a brilliant mind, capable of solving complex puzzles and deciphering hidden messages. His eidetic memory allows him to recall vast amounts of information, which proves crucial in his adventures. 
  • Morning Ritual:
    He is known for his morning ritual of swimming laps in the Harvard pool. 
  • Novel Adaptations:
    Several of the Robert Langdon novels have been adapted into successful films, with Tom Hanks portraying the character. 
  • Recurring Themes:
    The novels often involve Langdon being drawn into international conspiracies and historical mysteries, forcing him to use his knowledge and skills to solve puzzles and prevent disasters. 

print("Hello, World!")...........output hellow, world! for final B.TECH .............import sys print(sys.version).................if 5 > 2: print("Five is greater than two!")

class Person:

  def __init__(self, fname, lname):

    self.firstname = fname

    self.lastname = lname


  def printname(self):

    print(self.firstname, self.lastname)


#Use the Person class to create an object, and then execute the printname method:


x = Person("Ram", "Dayinaboyina python calsses and objects")

x.printname() 

output:-   ram, python calsses and objects.........

Python is a popular programming language. It was created by Guido van Rossum, and released in 1991.

It is used for:

  • web development (server-side),
  • software development,
  • mathematics,
  • system scripting.

What can Python do?

  • Python can be used on a server to create web applications.
  • Python can be used alongside software to create workflows.
  • Python can connect to database systems. It can also read and modify files.
  • Python can be used to handle big data and perform complex mathematics.
  • Python can be used for rapid prototyping, or for production-ready software development.

6, జులై 2025, ఆదివారం

now offering ruby , ADV RUBY , perl. ADV PERL, tcl SL's.............Write a function to calculate the roots of a Quadratic equation, where you give the coefficients a,b,c to the function, and it returns both the values of x

 PERL :Data Types, Variables, Scalars, Operators, Conditional statements , Loops, Arrays ,Strings ,Hashes, Lists,Built-inFunctions,Patternmatchingandregularexpressionoperators.

ADV PERL......

Ruby:Datatypes,Variables,Operators,Conditionalstatements,Loops,Methods,Blocks,Modules,Arrays,Strings,Hashes,FileI/O,RubyForm handling.

ADV RUBY........

TOOL COMMAND LANGUAGE..................


print "Hello world";
exit();
my $divisionResult = 4000/7;
print "Result of 4000 divided by 7 is $divisionResult";
sub evaluate_delta_and_answer {
        my($x,$y,$z) = @_;
        if ($x != 0) {
                $delta = ($y**2 - (4 * $x * $z));
                if ($delta < 0) {
                        print "b^2-4ac is less than zero. Both roots undefined.\n\n";
                        print "Program Terminated. Goodbye, Dave.\n\n"
                        }
                elsif ($delta == 0) {
                        $root = (0 - $y) /(2 * $x );
                        print "b^2-4ac = 0. There will be only one root: " . $root . "\n\n";
                        print "Goodbye, Dave.\n\n";
                        }
                elsif ($delta > 0) {
                        print "b^2-4ac > 0. There will be two roots.\n\n";
                        $root1 = ((0 - $y) - ($delta)**(0.5)) / (2 * $x);
                        $root2 = ((0 - $y) + ($delta)**(0.5)) / (2 * $x);
                        print "The first root, x1 = " . $root1 . "\n\n";
                        print "The second root, x2 = " . $root2 . "\n\n";
                        print "Goodbye, Dave.\n\n";
                        }
        }
        else {
                print "a = 0. This is not a quadratic function.\n";
                print "Goodbye, Dave.\n";
        }
}

The rest of the program:

print "This program takes three numbers (a, b and c) as coefficients\n";
print "of a quadratic equation, calculates its roots, and displays them\n";
print "on the screen for you.\n\n";
print "Please enter the value of a and press <ENTER>: ";
$a = <STDIN>;
print "\n";
print "Please enter the value of b and press <ENTER>: ";
$b = <STDIN>;
print "\n";
print "Please enter the value of c and press <ENTER>: ";
$c = <STDIN>;
print "\n";

evaluate_delta_and_answer($a,$b,$c);
offering for B.TECH 4TH Yr ......Mr.RAM.A.DAYINABOYINA FOR C.S.CYBERSECURITY..........
CS742PE: CYBER SECURITY (Professional Elective – IV)
B.Tech. IV Year I Sem. L T P C
3 0 0 3
Course objectives:
 To understand various types of cyber-attacks and cyber-crimes.
 To learn threats and risks within the context of cyber security.
 To have an overview of the cyber laws & concepts of cyber forensics.
 To study the defensive techniques against these attacks.
Course Outcomes:
1. Analyze and evaluate the cyber security needs of an organization.
2. Understand Cyber Security Regulations and Roles of International Law.
3. Design and develop security architecture for an organization.
4. Understand fundamental concepts of data privacy attacks.
UNIT- I
Introduction to Cyber Security: Basic Cyber Security Concepts, layers of security, Vulnerability,
threat, Harmful acts, Internet Governance – Challenges and Constraints, Computer Criminals, CIA
Triad, Assets and Threat, motive of attackers, active attacks, passive attacks, Software
attacks, hardware attacks, Cyber Threats-Cyber Warfare, Cyber Crime, Cyber terrorism, Cyber
Espionage, etc., Comprehensive Cyber Security Policy.
UNIT - II
Cyberspace and the Law & Cyber Forensics: Introduction, Cyber Security Regulations, Roles of
International Law. The INDIAN Cyberspace, National Cyber Security Policy.
Introduction, Historical background of Cyber forensics, Digital Forensics Science, The Need for
Computer Forensics, Cyber Forensics and Digital evidence, Forensics Analysis of Email, Digital
Forensics Lifecycle, Forensics Investigation, Challenges in Computer Forensics.
UNIT - III
Cybercrime: Mobile and Wireless Devices: Introduction, Proliferation of Mobile and Wireless
Devices, Trends in Mobility, Credit card Frauds in Mobile and Wireless Computing Era, Security
Challenges Posed by Mobile Devices, Registry Settings for Mobile Devices, Authentication service
Security, Attacks on Mobile/Cell Phones, Organizational security Policies and Measures in Mobile
Computing Era, Laptops.
UNIT- IV
Cyber Security: Organizational Implications: Introduction, cost of cybercrimes and IPR issues, web
threats for organizations, security and privacy implications, social media marketing: security risks and
perils for organizations, social computing and the associated challenges for organizations.
UNIT - V
Privacy Issues: Basic Data Privacy Concepts: Fundamental Concepts, Data Privacy Attacks, Data
linking and profiling, privacy policies and their specifications, privacy policy languages, privacy in
different domains- medical, financial, etc.
Cybercrime: Examples and Mini-Cases
Examples: Official Website of Maharashtra Government Hacked, Indian Banks Lose Millions of
Rupees, Parliament Attack, Pune City Police Bust Nigerian Racket, e-mail spoofing instances.
Mini-Cases: The Indian Case of online Gambling, An Indian Case of Intellectual Property Crime,
Financial Frauds in Cyber Domain.

4, జులై 2025, శుక్రవారం

DS..........

 Distributed systems are used in a wide range of applications, including internet and web services, cloud computing, e-commerce platforms, and moreThey enable scalability, reliability, and performance for applications that need to handle large amounts of data and traffic. 

Here's a more detailed look at specific applications:
1. Internet and Web Services:
  • The Internet:
    The internet itself is a massive distributed system, connecting countless devices and enabling communication and data exchange globally. 
  • Websites and Web Applications:
    Many websites and web applications, especially those with high traffic or complex functionalities, are built on distributed architectures. 
  • E-commerce Platforms:
    E-commerce sites like Amazon and eBay rely on distributed systems to handle transactions, manage product catalogs, and serve users across different locations. 
2. Cloud Computing:
  • Cloud Platforms:
    Cloud computing platforms like AWS, Azure, and Google Cloud are built on distributed systems, providing scalable computing resources and storage. 
  • Virtualization and Containerization:
    Distributed systems enable virtualization and containerization technologies, allowing for efficient resource allocation and management. 
3. Financial Systems:
  • Banking and Payment Systems:
    Distributed systems are crucial for handling transactions, managing accounts, and ensuring the reliability of financial services. 
  • High-Frequency Trading:
    Financial institutions use distributed systems for high-frequency trading, requiring speed and low latency. 
4. Telecommunications:
  • Cellular Networks:
    Distributed systems manage the complex infrastructure of cellular networks, enabling communication between mobile devices. 
  • Internet Backbone:
    The internet's core infrastructure relies on distributed systems to route data and manage network traffic
5. Scientific Computing:
  • Large-Scale Simulations:
    Distributed systems are used to run complex simulations in fields like climate modeling, drug discovery, and astrophysics.
  • Data Analysis:
    They enable the processing and analysis of massive datasets generated in scientific research. 6. Other Applications:

Examples and Applications of Distributed Systems in Real-Life

 



Distributed systems are the key technological component of modern information and communications technology. These are such that different computers work on specific tasks simultaneously but as if they functioned as a single entity. It enables effective parallel processing, upgrade of system capacity, and performance redundancy, which are currently in practice.

Examples-and-Applications-of-Distributed-Systems-in-Real-Life

What is a Distributed System?

Also known as distributed computing and distributed databases, a distributed system consists of clusters of independent components situated on different machines intended to communicate messages with each other to work as a whole. Therefore, the user will have the impression that the distributed system is a single entity or a computer located at the farthest end of the world.

  • This is the optimum point where the system is always evolving and getting taller to be able to maximize resources and prevent failures, even if one system fails, as one system won't affect the availability of the service.
  • Now, the storage of data is more dispersed, parallel to the spread of modern applications that do not run in isolation. The majority of apps and products leverage distributed systems, which stand as their foundation.

Real-world Applications and Use Cases of Distributed Systems

The most common applications of distributed systems would include distributed computing, file sharing, smart grids, and online gaming.

1. Internet and Web Services

The internet itself is a distributed system, allowing for seamless communication and data exchange across the globe. Web servers, content delivery networks (CDNs), and peer-to-peer networks all rely on distributed systems architecture to handle vast amounts of data and user requests efficiently.

Example:

Consider a website like Wikipedia. It is hosted on servers distributed across the globe. When a user requests a page, the request may be routed to the nearest server using a content delivery network (CDN), which reduces latency and improves performance.

2. Cloud Computing

Cloud computing platforms like Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) are built on distributed systems. They provide scalable and reliable infrastructure services, such as storage, computing power, and networking, to businesses and individuals worldwide.

Example:

Amazon Web Services (AWS) offers a wide range of cloud computing services. One example is Amazon S3 (Simple Storage Service), which provides scalable object storage for storing and retrieving data. AWS uses distributed systems architecture to replicate data across multiple servers and data centers for redundancy and fault tolerance.

3. Social Media Platforms

Platforms like Facebook, Twitter, and Instagram use distributed systems to handle millions of users, posts, and interactions every second. Distributed databases, caching systems, and content delivery networks are essential components in ensuring fast and reliable service.

Example:

Facebook uses distributed systems to handle billions of users and their interactions. When a user posts a status update, it is replicated and stored across multiple servers for redundancy. When another user likes or comments on the post, the interaction is propagated to other servers using a distributed messaging system.

4. Financial Systems

Stock exchanges, banking systems, and payment processors rely on distributed systems to handle transactions securely and efficiently. Distributed databases and messaging systems are crucial for maintaining data consistency and handling high transaction volumes.

Example:

NASDAQ is one of the largest stock exchanges globally and relies on distributed systems to handle high-frequency trading. Distributed databases ensure that trade data is replicated and synchronized across multiple servers in real-time, enabling fast and reliable transaction processing.

5. Online Marketplaces

E-commerce platforms like Amazon and eBay use distributed systems to manage product catalogs, process orders, and handle inventory across multiple locations. Distributed databases and caching systems help ensure fast and accurate product searches and transactions.

Example:

Amazon is a prime example of an online marketplace that utilizes distributed systems. When a user searches for a product, Amazon's distributed database indexes millions of products across multiple categories and returns search results quickly and accurately.

Benefits of Distributed Systems

Distributed systems offer several benefits compared to centralized systems. Here are some key advantages:

  • Scalability: Distributed systems can scale horizontally by adding more machines to the network, allowing them to handle increasing workloads and accommodate growing numbers of users or data. This scalability is essential for applications experiencing rapid growth or fluctuating demand.
  • Fault Tolerance: Distributed systems are inherently resilient to failures because they distribute data and processing across multiple nodes. If one node fails, the system can continue to operate without significant disruption by rerouting requests to other healthy nodes. This fault tolerance improves system reliability and availability.
  • Performance: By distributing data and computation closer to users, distributed systems can reduce latency and improve performance. This is particularly important for applications that require real-time responsiveness, such as online gaming, streaming media, and financial trading.
  • High Availability: Distributed systems can achieve high availability by replicating data and services across multiple nodes. Even if some nodes become unavailable due to hardware failures or network issues, the system remains accessible and continues to provide services to users.
  • Flexibility: Distributed systems offer greater flexibility in terms of deployment and resource allocation. They can run on heterogeneous hardware and operating systems, allowing organizations to leverage existing infrastructure and adopt a mix of on-premises and cloud-based solutions.
  • Geographic Distribution: Distributed systems enable data and services to be replicated across multiple geographic locations, improving performance for users in different regions and providing disaster recovery capabilities. This geographic distribution also helps comply with data sovereignty requirements and regulatory constraints.

Challenges of Distributed Systems

Here are some of the key challenges:

  • Network Complexity: Distributed systems rely on network communication between nodes, which introduces complexity and overhead. Managing network latency, bandwidth limitations, and packet loss can be challenging, particularly in large-scale deployments spanning multiple geographic locations.
  • Consistency and Coordination: Maintaining data consistency across distributed nodes is challenging due to the possibility of concurrent updates and network partitions. Achieving strong consistency requires coordination mechanisms like distributed transactions and consensus protocols, which can introduce latency and overhead.
  • Fault Tolerance: Distributed systems must be resilient to hardware failures, software bugs, and network issues. Implementing fault tolerance mechanisms, such as replication, redundancy, and failure detection, adds complexity and overhead to the system architecture.
  • Concurrency Control: Coordinating concurrent access to shared resources in a distributed environment is challenging. Distributed systems must implement efficient concurrency control mechanisms to prevent data corruption, race conditions, and deadlocks while maximizing throughput and performance.
  • Security: Distributed systems face various security threats, including unauthorized access, data breaches, and denial-of-service attacks. Securing communication channels, authenticating users and nodes, and implementing access control policies are critical to protecting sensitive data and ensuring system integrity.

Conclusion

Distributed systems are those invisible resources that run background missions and keep many technologies going every hour of each day. From web stores to social media and so on, they help to ensure that the connectivity in today's web universe is not disrupted by the need for scalability and enhanced reliability. With technology growing day in and day out in the future, distributed systems will continue to be the main determinant of how the world will achieve development.