Hand written notes for java, I tried the best to explain best,if you found any mistake in this, or anything written in is incorrect then most welcome to suggestions and advise
The document discusses the longest common subsequence (LCS) problem and how to solve it using dynamic programming. It begins by defining LCS as the longest sequence of characters that appear left-to-right in two given strings. It then describes solving LCS using a brute force method with exponential time complexity and using dynamic programming with polynomial time complexity. Finally, it provides an example of finding the LCS of two strings and discusses applications and references.
Este documento presenta 12 ejercicios de álgebra. Los ejercicios cubren temas como calcular expresiones algebraicas, verificar igualdades, resolver ecuaciones, ordenar números, calcular fracciones, y representar puntos y conjuntos en el plano. El objetivo es que los estudiantes repasen estos conceptos básicos antes de comenzar el curso.
The document appears to be a scanned copy of a legal contract for the sale of a residential property located in California. The contract details the purchase price of the property, the down payment, terms for the remaining balance, contingencies for inspections and appraisal, and closing date. The contract is signed by both the buyer and seller agreeing to the terms of the sale.
Longest common subsequence(dynamic programming).munawerzareef
The document discusses the longest common subsequence (LCS) problem. It defines key terms like subsequence and common subsequence. It presents the dynamic programming solution to find the longest common subsequence of two input sequences in O(nm) time using two nested for loops over the sequences' lengths, storing results in a 2D table and using pointers to recover the subsequence. It also provides pseudocode for the algorithm and discusses applications in biology.
String matching with finite state automataAnmol Hamid
The document discusses the string matching algorithm that builds a finite automaton to scan a text string for occurrences of a pattern string. It explains the suffix function and transition function that are used to specify the string matching automaton corresponding to a given pattern. It then provides an example of computing the transition function for a given text and pattern string through multiple iterations.
This document contains questions related to Internet and Web Technology. It asks about CGI scripts versus programs, JavaScript exception handling, form submission handling, JavaScript types, block level versus inline elements, the <img> tag and its attributes, JavaScript variable typing, viewing applet output, the DOM, and scalar variables in JavaScript. It also asks about hyperlinks, creating arrays in JavaScript, DOCTYPE declarations and DTDs, creating a form, framing pages, creating tables, class selectors, DOM node manipulation, using InnerHTML, and applet lifecycles. The questions cover a wide range of topics including scripting languages, HTML elements, forms, tables, styling, and applets.
MindMap that summarize fundamental drilling process; the used machine, drill bits, tool and workpiece fixation, and other operations related to drilling like reaming.
Application of matrices to system of linear equation consistency & inconsistency & Theory of equation.
Class - B.Sc. I Mathematics
Paper Name - Algebra & Trigonometry
Paper - No . - I
Unit - II
SSmv Junwani Bhilai.
This document summarizes lecture material on automata theory and formal languages. It provides examples of languages defined over the alphabet {a,b} that can be expressed using regular expressions and accepted by generalized transition graphs. Kleene's theorem is also discussed, which states that a language can be expressed using finite automata, transition graphs, or regular expressions if and only if it can be expressed using the other two as well. The proof of Kleene's theorem is outlined in three parts: 1) A language accepted by a finite automaton can be accepted by a transition graph; 2) A language accepted by a transition graph can be expressed with a regular expression; and 3) A language expressed by a regular expression can be accepted by
This document outlines the terms and conditions for a rental agreement between John Doe and Jane Smith for the property located at 123 Main St. It specifies the monthly rental rate of $1,000 due on the 1st of each month, the security deposit of $500, and responsibilities of landlord and tenant for repairs and maintenance. The initial lease term is one year beginning January 1st.
Introduction to Computer theory (Automata Theory) 2nd Edition By Denial I.A. ...Farwa Ansari
This document contains solutions to problems from Chapter 2 on languages in automata theory. It discusses languages where the alphabet S consists of various combinations of the letters a and b. For problems 1-3, it explicitly lists out all words of a given length in the languages and determines properties like whether certain substrings can occur. For problems 4-5, it analyzes whether given strings are in the languages and how a string of a certain length can be factorized into shorter strings from the alphabet.
Mohammad Kaif Anwar has fulfilled the requirements for a Bachelor of Science degree in Textile Engineering from Daffodil International University in Dhaka, Bangladesh. He maintained a cumulative grade point average of 3.53 out of 4.0. This provisional certificate recognizes his achievement pending approval from the university's Academic Council, and must be surrendered when obtaining the original certificate.
Lecture Notes
Module-1, Chapter-1
An Overview of Java
Programme: B E (CSE)
Semester: 3
Course Code: BCS306A
Course Instructor: Demian Antony Dmello
2022 Scheme of VTU
An Overview of Java: Object-Oriented Programming (Two Paradigms, Abstraction, The Three OOP Principles), Using Blocks of Code, Lexical Issues (Whitespace, Identifiers, Literals, Comments, Separators, The Java Keywords).
Data Types, Variables, and Arrays: The Primitive Types (Integers, Floating-Point Types, Characters, Booleans), Variables, Type Conversion and Casting, Automatic Type Promotion in Expressions, Arrays, Introducing Type Inference with Local Variables.
Operators: Arithmetic Operators, Relational Operators, Boolean Logical Operators, The Assignment Operator, The ? Operator, Operator Precedence, Using Parentheses.
Control Statements: Java’s Selection Statements (if, The Traditional switch), Iteration Statements (while, do-while, for, The For-Each Version of the for Loop, Local Variable Type Inference in a for Loop, Nested Loops), Jump Statements (Using break, Using continue, return).
An Overview of Java; Data Types, Variables and Arrays; Operators; Control Statements.
Introducing Classes; Methods and Classes.
Inheritance; Interfaces.
Packages; Exceptions.
Multithreaded Programming; Enumerations, Type Wrappers and Autoboxing.
Textbook
Java: The Complete Reference, Twelfth Edition, by Herbert Schildt, November 2021, McGraw-Hill, ISBN: 9781260463422
References:
Programming with Java, 6th Edition, by E Balagurusamy, Mar-2019, McGraw Hill Education, ISBN: 9789353162337
Thinking in Java, Fourth Edition, by Bruce Eckel, Prentice Hall, 2006 (https://sd.blackball.lv/library/thinking_in_java_4th_edition.pdf)
Kerala Land reforms Act - kaanam order go rt 756/18 RD dated 05-03-2018 uploaded y T james Joseph Adhikarathil Definition of Mutation/Pokkuvaravu
When a property is sold or transferred from one person to another, there needs to be a change in the title ownership as well. This process of transferring the ownership is called mutation. The property is recorded in the land revenue department under the new owner’s name, and from then on this person will be responsible to pay the property tax charged by the government.
The documentation procedure for mutation, and the applicable fee may vary from state to state. The process of mutation is called “Pokkuvaravu” in Kerala.
How to Do Pokkuvaravu or Mutation of Your Property in Kerala
Here’s the step by step process on how to do Pokkuvaravu or mutation of property in Kerala.
1. Complete Property Purchase
The process of purchasing the property from the seller needs to be fully completed. This include identification, negotiation, payment and getting the property registered in the name of the buyer.
2. Collect Sale Deed
Once the property sale is registered with the respective sub-register office, they will process it. The sale deed can be collected from them within a few weeks.
3. Pokkuvaravu Application
After receiving the sale deed, an application need to be given to the respective village office, requesting the pokkuvaravu/mutation to be done in favour of the buyer.
4. Pay Fees
Village offices charge a nominal fee for getting the pokkuvaravu/mutation done. The current rates applicable are as follows:
Rs. 25 for up to five acres of property
Rs. 50 for over five and up to 20 acres
Rs. 100 for over 20 and up to 40 acres
Rs. 200 for over 40 acres and up to two hectares
Rs. 500 for over two hectares
This fees need to be paid at the respective village office for the application to be processed. The above mentioned rates will be revised by the government from time to time.
5. Submit Copy of the Deeds
A copy of the current and previous registration deeds need to be submitted at the village office.
6. Verification of Original Deed
The respective authorities in the village office may need to verify the original deed. In that case, the original deed needs to be produced to them for verification at the village office.
7. Issue Date of Property Verification
A village officer (surveyor) will then visit the property in order to physically measure and verify it. The surveyor will fix a date for the site visit in agreement with the applicant .
8. Physical Survey
The surveyor from the village office will visit the property on the agreed date, measure the property and also verify its boundaries.
9. Disputes with the Neighbours
The surveyor will also check if there any unresolved disputes with any of the neighbours in terms of borders, area or any other disputes with respect to the said property.
The document discusses graph algorithms breadth-first search (BFS) and depth-first search (DFS). It provides pseudocode for BFS and DFS algorithms and explains key aspects of each. BFS uses a queue to explore all neighbors of a node before moving to the next level, building a breadth-first tree. DFS uses recursion to explore as deep as possible along each branch before backtracking, resulting in a depth-first tree structure. Both algorithms run in O(V+E) time on a graph with V vertices and E edges.
This document discusses supervised learning and decision trees. It introduces supervised learning and how examples are split into training and test sets. It presents an example dataset and features for classification. It shows a decision tree for this data and discusses scoring functions for trees, overfitting, and using cross-validation for pruning trees. It covers PAC learning theory, naive Bayes classification, and what was covered - decision tree representation, memorization problems, and finding small accurate trees greedily. Homework involves using WordNet to check word synonyms and drawing decision trees.
String matching with finite state automataAnmol Hamid
The document discusses the string matching algorithm that builds a finite automaton to scan a text string for occurrences of a pattern string. It explains the suffix function and transition function that are used to specify the string matching automaton corresponding to a given pattern. It then provides an example of computing the transition function for a given text and pattern string through multiple iterations.
This document contains questions related to Internet and Web Technology. It asks about CGI scripts versus programs, JavaScript exception handling, form submission handling, JavaScript types, block level versus inline elements, the <img> tag and its attributes, JavaScript variable typing, viewing applet output, the DOM, and scalar variables in JavaScript. It also asks about hyperlinks, creating arrays in JavaScript, DOCTYPE declarations and DTDs, creating a form, framing pages, creating tables, class selectors, DOM node manipulation, using InnerHTML, and applet lifecycles. The questions cover a wide range of topics including scripting languages, HTML elements, forms, tables, styling, and applets.
MindMap that summarize fundamental drilling process; the used machine, drill bits, tool and workpiece fixation, and other operations related to drilling like reaming.
Application of matrices to system of linear equation consistency & inconsistency & Theory of equation.
Class - B.Sc. I Mathematics
Paper Name - Algebra & Trigonometry
Paper - No . - I
Unit - II
SSmv Junwani Bhilai.
This document summarizes lecture material on automata theory and formal languages. It provides examples of languages defined over the alphabet {a,b} that can be expressed using regular expressions and accepted by generalized transition graphs. Kleene's theorem is also discussed, which states that a language can be expressed using finite automata, transition graphs, or regular expressions if and only if it can be expressed using the other two as well. The proof of Kleene's theorem is outlined in three parts: 1) A language accepted by a finite automaton can be accepted by a transition graph; 2) A language accepted by a transition graph can be expressed with a regular expression; and 3) A language expressed by a regular expression can be accepted by
This document outlines the terms and conditions for a rental agreement between John Doe and Jane Smith for the property located at 123 Main St. It specifies the monthly rental rate of $1,000 due on the 1st of each month, the security deposit of $500, and responsibilities of landlord and tenant for repairs and maintenance. The initial lease term is one year beginning January 1st.
Introduction to Computer theory (Automata Theory) 2nd Edition By Denial I.A. ...Farwa Ansari
This document contains solutions to problems from Chapter 2 on languages in automata theory. It discusses languages where the alphabet S consists of various combinations of the letters a and b. For problems 1-3, it explicitly lists out all words of a given length in the languages and determines properties like whether certain substrings can occur. For problems 4-5, it analyzes whether given strings are in the languages and how a string of a certain length can be factorized into shorter strings from the alphabet.
Mohammad Kaif Anwar has fulfilled the requirements for a Bachelor of Science degree in Textile Engineering from Daffodil International University in Dhaka, Bangladesh. He maintained a cumulative grade point average of 3.53 out of 4.0. This provisional certificate recognizes his achievement pending approval from the university's Academic Council, and must be surrendered when obtaining the original certificate.
Lecture Notes
Module-1, Chapter-1
An Overview of Java
Programme: B E (CSE)
Semester: 3
Course Code: BCS306A
Course Instructor: Demian Antony Dmello
2022 Scheme of VTU
An Overview of Java: Object-Oriented Programming (Two Paradigms, Abstraction, The Three OOP Principles), Using Blocks of Code, Lexical Issues (Whitespace, Identifiers, Literals, Comments, Separators, The Java Keywords).
Data Types, Variables, and Arrays: The Primitive Types (Integers, Floating-Point Types, Characters, Booleans), Variables, Type Conversion and Casting, Automatic Type Promotion in Expressions, Arrays, Introducing Type Inference with Local Variables.
Operators: Arithmetic Operators, Relational Operators, Boolean Logical Operators, The Assignment Operator, The ? Operator, Operator Precedence, Using Parentheses.
Control Statements: Java’s Selection Statements (if, The Traditional switch), Iteration Statements (while, do-while, for, The For-Each Version of the for Loop, Local Variable Type Inference in a for Loop, Nested Loops), Jump Statements (Using break, Using continue, return).
An Overview of Java; Data Types, Variables and Arrays; Operators; Control Statements.
Introducing Classes; Methods and Classes.
Inheritance; Interfaces.
Packages; Exceptions.
Multithreaded Programming; Enumerations, Type Wrappers and Autoboxing.
Textbook
Java: The Complete Reference, Twelfth Edition, by Herbert Schildt, November 2021, McGraw-Hill, ISBN: 9781260463422
References:
Programming with Java, 6th Edition, by E Balagurusamy, Mar-2019, McGraw Hill Education, ISBN: 9789353162337
Thinking in Java, Fourth Edition, by Bruce Eckel, Prentice Hall, 2006 (https://sd.blackball.lv/library/thinking_in_java_4th_edition.pdf)
Kerala Land reforms Act - kaanam order go rt 756/18 RD dated 05-03-2018 uploaded y T james Joseph Adhikarathil Definition of Mutation/Pokkuvaravu
When a property is sold or transferred from one person to another, there needs to be a change in the title ownership as well. This process of transferring the ownership is called mutation. The property is recorded in the land revenue department under the new owner’s name, and from then on this person will be responsible to pay the property tax charged by the government.
The documentation procedure for mutation, and the applicable fee may vary from state to state. The process of mutation is called “Pokkuvaravu” in Kerala.
How to Do Pokkuvaravu or Mutation of Your Property in Kerala
Here’s the step by step process on how to do Pokkuvaravu or mutation of property in Kerala.
1. Complete Property Purchase
The process of purchasing the property from the seller needs to be fully completed. This include identification, negotiation, payment and getting the property registered in the name of the buyer.
2. Collect Sale Deed
Once the property sale is registered with the respective sub-register office, they will process it. The sale deed can be collected from them within a few weeks.
3. Pokkuvaravu Application
After receiving the sale deed, an application need to be given to the respective village office, requesting the pokkuvaravu/mutation to be done in favour of the buyer.
4. Pay Fees
Village offices charge a nominal fee for getting the pokkuvaravu/mutation done. The current rates applicable are as follows:
Rs. 25 for up to five acres of property
Rs. 50 for over five and up to 20 acres
Rs. 100 for over 20 and up to 40 acres
Rs. 200 for over 40 acres and up to two hectares
Rs. 500 for over two hectares
This fees need to be paid at the respective village office for the application to be processed. The above mentioned rates will be revised by the government from time to time.
5. Submit Copy of the Deeds
A copy of the current and previous registration deeds need to be submitted at the village office.
6. Verification of Original Deed
The respective authorities in the village office may need to verify the original deed. In that case, the original deed needs to be produced to them for verification at the village office.
7. Issue Date of Property Verification
A village officer (surveyor) will then visit the property in order to physically measure and verify it. The surveyor will fix a date for the site visit in agreement with the applicant .
8. Physical Survey
The surveyor from the village office will visit the property on the agreed date, measure the property and also verify its boundaries.
9. Disputes with the Neighbours
The surveyor will also check if there any unresolved disputes with any of the neighbours in terms of borders, area or any other disputes with respect to the said property.
The document discusses graph algorithms breadth-first search (BFS) and depth-first search (DFS). It provides pseudocode for BFS and DFS algorithms and explains key aspects of each. BFS uses a queue to explore all neighbors of a node before moving to the next level, building a breadth-first tree. DFS uses recursion to explore as deep as possible along each branch before backtracking, resulting in a depth-first tree structure. Both algorithms run in O(V+E) time on a graph with V vertices and E edges.
This document discusses supervised learning and decision trees. It introduces supervised learning and how examples are split into training and test sets. It presents an example dataset and features for classification. It shows a decision tree for this data and discusses scoring functions for trees, overfitting, and using cross-validation for pruning trees. It covers PAC learning theory, naive Bayes classification, and what was covered - decision tree representation, memorization problems, and finding small accurate trees greedily. Homework involves using WordNet to check word synonyms and drawing decision trees.
The document discusses different search methods for problem solving, including uninformed search, heuristic search, and informed search using heuristic functions. It provides examples of heuristic functions that estimate the cost to reach the goal state and explores greedy best-first search and A* search algorithms. A* combines the cost to reach a node and a heuristic estimate of remaining cost to ensure optimal, efficient search.
Directed graphs and topological sorting can be used to determine a feasible ordering of courses based on prerequisites. Topological sorting algorithms perform a depth-first search on a directed acyclic graph (DAG) of course prerequisites to output a linear ordering of courses with no edges between earlier and later courses. For example, a topological sorting of computer science courses outputs an order allowing each course to be taken only after completing its prerequisites.
•Common Problems Needs Computers
•The Search Problem
•Basic Search Algorithms
–Algorithms used for searching the contents of an array
•Linear or Sequential Search
•Binary Search
•Comparison Between Linear and Binary Search
•Algorithms for solving shortest path problems
–Sequential Search Algorithms
•Depth-First Search
•Breadth First Search
–Parallel or distributed Search Algorithms
•Parallel Depth-First Search
•Parallel Breadth First Search
The document discusses graph traversal algorithms breadth-first search (BFS) and depth-first search (DFS). It provides examples of how BFS and DFS work, including pseudocode for algorithms. It also discusses applications of BFS such as finding shortest paths and detecting bipartitions. Applications of DFS include finding connected components and topological sorting.
Linear and Binary Search Algorithms.(Discrete Mathematics)Shanawaz Ahamed
This Power point slides were prepared for small project named "Linear and Binary Search Algorithms.".
Its totally based on the project report.
Q1. Why i am sharing this here???
Ans. a) This is Simple but perfect slide in my view.
b) One can take inspiration to make slides based on this
topic.
c) I wanna Help Jr, Students of EWU. I am putting this
here so that they can see this and be benefited from this.
d) Course Code: CSE 205. Instructor: Md. Wasilul Sadid..
Thank You :)
The document defines and explains several key graph concepts and algorithms, including:
- Graph representations like adjacency matrix and adjacency list.
- Graph traversal algorithms like breadth-first search (BFS) and depth-first search (DFS).
- Minimum spanning tree algorithms like Prim's algorithm.
- Single-source shortest path algorithms like Dijkstra's algorithm and Floyd's algorithm.
Pseudocode and examples are provided to illustrate how BFS, DFS, Prim's, Dijkstra's and Floyd's algorithms work on graphs. Key properties of minimum spanning trees and shortest path problems are also defined.
1. An algorithm is a sequence of unambiguous instructions to solve a problem within a finite amount of time. It takes an input, processes it, and produces an output.
2. Designing an algorithm involves understanding the problem, choosing a computational model and problem-solving approach, designing and proving the algorithm's correctness, analyzing its efficiency, coding it, and testing it.
3. Important algorithm design techniques include brute force, divide and conquer, decrease and conquer, transform and conquer, dynamic programming, and greedy algorithms.
Hill climbing is a heuristic search algorithm that starts with an initial solution and iteratively improves it by incrementally changing a single element of the solution. It selects the change that results in the greatest improvement to the solution based on an evaluation function. However, hill climbing is prone to getting stuck at local optima rather than finding the global optimum. Solutions include backtracking, making larger jumps, or applying multiple changes before evaluating.
This document discusses and provides examples of depth-first search (DFS) and breadth-first search (BFS) algorithms for traversing graphs. It explains that DFS involves recursively exploring all branches of the graph as deep as possible before backtracking, while BFS involves searching the neighbors of the starting node first before moving to the next level. Examples are given showing the step-by-step process of applying DFS and BFS to traverse graphs and mark visited vertices.
This document summarizes a lecture on algorithms and graph traversal techniques. It discusses:
1) Breadth-first search (BFS) and depth-first search (DFS) algorithms for traversing graphs. BFS uses a queue while DFS uses a stack.
2) Applications of BFS and DFS, including finding connected components, minimum spanning trees, and bi-connected components.
3) Identifying articulation points to determine biconnected components in a graph.
4) The 0/1 knapsack problem and approaches for solving it using greedy algorithms, backtracking, and branch and bound search.
This document discusses various heuristic search algorithms including generate-and-test, hill climbing, best-first search, problem reduction, and constraint satisfaction. Generate-and-test involves generating possible solutions and testing if they are correct. Hill climbing involves moving in the direction that improves the state based on a heuristic evaluation function. Best-first search evaluates nodes and expands the most promising node first. Problem reduction breaks problems into subproblems. Constraint satisfaction views problems as sets of constraints and aims to constrain the problem space as much as possible.
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Trees. Defining, Creating and Traversing Trees. Traversing the File System
Binary Search Trees. Balanced Trees
Graphs and Graphs Traversal Algorithms
Exercises: Working with Trees and Graphs
Analysis of reinforced concrete deep beam is based on simplified approximate method due to the complexity of the exact analysis. The complexity is due to a number of parameters affecting its response. To evaluate some of this parameters, finite element study of the structural behavior of the reinforced self-compacting concrete deep beam was carried out using Abaqus finite element modeling tool. The model was validated against experimental data from the literature. The parametric effects of varied concrete compressive strength, vertical web reinforcement ratio and horizontal web reinforcement ratio on the beam were tested on eight (8) different specimens under four points loads. The results of the validation work showed good agreement with the experimental studies. The parametric study revealed that the concrete compressive strength most significantly influenced the specimens’ response with the average of 41.1% and 49 % increment in the diagonal cracking and ultimate load respectively due to doubling of concrete compressive strength. Although the increase in horizontal web reinforcement ratio from 0.31 % to 0.63 % lead to average of 6.24 % increment on the diagonal cracking load, it does not influence the ultimate strength and the load-deflection response of the beams. Similar variation in vertical web reinforcement ratio leads to an average of 2.4 % and 15 % increment in cracking and ultimate load respectively with no appreciable effect on the load-deflection response.
We introduce the Gaussian process (GP) modeling module developed within the UQLab software framework. The novel design of the GP-module aims at providing seamless integration of GP modeling into any uncertainty quantification workflow, as well as a standalone surrogate modeling tool. We first briefly present the key mathematical tools on the basis of GP modeling (a.k.a. Kriging), as well as the associated theoretical and computational framework. We then provide an extensive overview of the available features of the software and demonstrate its flexibility and user-friendliness. Finally, we showcase the usage and the performance of the software on several applications borrowed from different fields of engineering. These include a basic surrogate of a well-known analytical benchmark function; a hierarchical Kriging example applied to wind turbine aero-servo-elastic simulations and a more complex geotechnical example that requires a non-stationary, user-defined correlation function. The GP-module, like the rest of the scientific code that is shipped with UQLab, is open source (BSD license).
ADVXAI IN MALWARE ANALYSIS FRAMEWORK: BALANCING EXPLAINABILITY WITH SECURITYijscai
With the increased use of Artificial Intelligence (AI) in malware analysis there is also an increased need to
understand the decisions models make when identifying malicious artifacts. Explainable AI (XAI) becomes
the answer to interpreting the decision-making process that AI malware analysis models use to determine
malicious benign samples to gain trust that in a production environment, the system is able to catch
malware. With any cyber innovation brings a new set of challenges and literature soon came out about XAI
as a new attack vector. Adversarial XAI (AdvXAI) is a relatively new concept but with AI applications in
many sectors, it is crucial to quickly respond to the attack surface that it creates. This paper seeks to
conceptualize a theoretical framework focused on addressing AdvXAI in malware analysis in an effort to
balance explainability with security. Following this framework, designing a machine with an AI malware
detection and analysis model will ensure that it can effectively analyze malware, explain how it came to its
decision, and be built securely to avoid adversarial attacks and manipulations. The framework focuses on
choosing malware datasets to train the model, choosing the AI model, choosing an XAI technique,
implementing AdvXAI defensive measures, and continually evaluating the model. This framework will
significantly contribute to automated malware detection and XAI efforts allowing for secure systems that
are resilient to adversarial attacks.
☁️ GDG Cloud Munich: Build With AI Workshop - Introduction to Vertex AI! ☁️
Join us for an exciting #BuildWithAi workshop on the 28th of April, 2025 at the Google Office in Munich!
Dive into the world of AI with our "Introduction to Vertex AI" session, presented by Google Cloud expert Randy Gupta.
Concept of Problem Solving, Introduction to Algorithms, Characteristics of Algorithms, Introduction to Data Structure, Data Structure Classification (Linear and Non-linear, Static and Dynamic, Persistent and Ephemeral data structures), Time complexity and Space complexity, Asymptotic Notation - The Big-O, Omega and Theta notation, Algorithmic upper bounds, lower bounds, Best, Worst and Average case analysis of an Algorithm, Abstract Data Types (ADT)
"Boiler Feed Pump (BFP): Working, Applications, Advantages, and Limitations E...Infopitaara
A Boiler Feed Pump (BFP) is a critical component in thermal power plants. It supplies high-pressure water (feedwater) to the boiler, ensuring continuous steam generation.
⚙️ How a Boiler Feed Pump Works
Water Collection:
Feedwater is collected from the deaerator or feedwater tank.
Pressurization:
The pump increases water pressure using multiple impellers/stages in centrifugal types.
Discharge to Boiler:
Pressurized water is then supplied to the boiler drum or economizer section, depending on design.
🌀 Types of Boiler Feed Pumps
Centrifugal Pumps (most common):
Multistage for higher pressure.
Used in large thermal power stations.
Positive Displacement Pumps (less common):
For smaller or specific applications.
Precise flow control but less efficient for large volumes.
🛠️ Key Operations and Controls
Recirculation Line: Protects the pump from overheating at low flow.
Throttle Valve: Regulates flow based on boiler demand.
Control System: Often automated via DCS/PLC for variable load conditions.
Sealing & Cooling Systems: Prevent leakage and maintain pump health.
⚠️ Common BFP Issues
Cavitation due to low NPSH (Net Positive Suction Head).
Seal or bearing failure.
Overheating from improper flow or recirculation.