The von Neumann principle for the design and operation of computers requires that a
program has to be primary memory resident to execute. Also, a user requires to revisit his
programs often during its evolution
The document discusses how operating systems manage files and memory allocation. It explains that from the computer's perspective, there are no actual files, only blocks of allocated and unallocated memory. The file manager in the operating system creates the illusion of files and folders by tracking memory locations and implementing file allocation policies. Files can be stored contiguously, non-contiguously, or through indexed allocation with pointers. Access controls determine which users can access which files.
The document discusses different techniques for improving the efficiency of union-find algorithms, including union-by-size, path compression, and union-by-height. Union-by-size works by making the root of the smaller tree the child of the larger tree during a union operation, keeping tree heights small. Path compression further optimizes find operations by updating the parent pointers along the search path. Together these optimizations allow union-find algorithms to run in almost linear time for practical purposes.
The document discusses divide and conquer algorithms for sorting, specifically mergesort and quicksort. It explains that mergesort works by recursively splitting a list in half, sorting the halves, and then merging the sorted halves together. Quicksort works by picking a pivot value and partitioning the list into elements less than and greater than the pivot, before recursively sorting the sublists. Both algorithms run in O(n log n) time.
The document discusses different types of tree data structures, focusing on binary trees. It defines a binary tree recursively as a finite set of elements that is either empty or partitioned into three disjoint subsets containing a single root element and left and right subtrees. The document outlines common binary tree terminology like nodes, parents, descendants, and levels. It also describes complete binary trees where all levels are fully filled except the lowest, which has nodes filled from left to right.
The document discusses AVL trees and balanced binary search trees. It provides the following key points:
1) An AVL tree is a self-balancing binary search tree where the height of the two child subtrees of every node differ by at most one.
2) A balanced binary search tree is one where the height of the left and right subtrees of each node differ by no more than one.
3) Inserting new nodes can cause the tree to become unbalanced if the insertion breaks the height balance property. Rotations may be needed to rebalance the tree.
The document discusses level-order traversal of binary trees. Level-order traversal visits all nodes at each level from left to right before moving to the next level. This can be implemented by using a queue, where the left and right children of each dequeued node are enqueued. The code provided traverses a binary tree using this level-order technique.
The document discusses how operating systems manage files and memory allocation. It explains that from the computer's perspective, there are no actual files, only blocks of allocated and unallocated memory. The file manager in the operating system creates the illusion of files and folders by tracking memory locations and implementing file allocation policies. Files can be stored contiguously, non-contiguously, or through indexed allocation with pointers. Access controls determine which users can access which files.
The document discusses different techniques for improving the efficiency of union-find algorithms, including union-by-size, path compression, and union-by-height. Union-by-size works by making the root of the smaller tree the child of the larger tree during a union operation, keeping tree heights small. Path compression further optimizes find operations by updating the parent pointers along the search path. Together these optimizations allow union-find algorithms to run in almost linear time for practical purposes.
The document discusses divide and conquer algorithms for sorting, specifically mergesort and quicksort. It explains that mergesort works by recursively splitting a list in half, sorting the halves, and then merging the sorted halves together. Quicksort works by picking a pivot value and partitioning the list into elements less than and greater than the pivot, before recursively sorting the sublists. Both algorithms run in O(n log n) time.
The document discusses different types of tree data structures, focusing on binary trees. It defines a binary tree recursively as a finite set of elements that is either empty or partitioned into three disjoint subsets containing a single root element and left and right subtrees. The document outlines common binary tree terminology like nodes, parents, descendants, and levels. It also describes complete binary trees where all levels are fully filled except the lowest, which has nodes filled from left to right.
The document discusses AVL trees and balanced binary search trees. It provides the following key points:
1) An AVL tree is a self-balancing binary search tree where the height of the two child subtrees of every node differ by at most one.
2) A balanced binary search tree is one where the height of the left and right subtrees of each node differ by no more than one.
3) Inserting new nodes can cause the tree to become unbalanced if the insertion breaks the height balance property. Rotations may be needed to rebalance the tree.
The document discusses level-order traversal of binary trees. Level-order traversal visits all nodes at each level from left to right before moving to the next level. This can be implemented by using a queue, where the left and right children of each dequeued node are enqueued. The code provided traverses a binary tree using this level-order technique.
The document discusses equivalence relations and the union-find algorithm. It defines what makes a binary relation an equivalence relation by having the properties of reflexivity, symmetry, and transitivity. It gives examples like electrical connectivity being an equivalence relation. The union-find algorithm can be used to dynamically determine if elements are in the same equivalence class based on the given relations, by performing find and union operations in time proportional to m+n for m finds and n-1 unions.
The document discusses various aspects of balanced binary search trees, including:
1) Const keyword can be used to mark parameters and return values as constant to prevent unintended modification.
2) AVL trees are binary search trees where the heights of left and right subtrees differ by at most 1.
3) For a binary search tree to be balanced, the heights of left and right subtrees should be close to equal to avoid a skewed or degenerate tree structure.
Union-find data structures can be used to efficiently generate random mazes. A maze can be represented as a grid of cells where each cell is initially isolated by walls. Removing walls corresponds to union operations, joining the cells' sets. A maze is generated by randomly performing unions until the entrance and exit cells are in the same set, connected by a path through the maze.
The document discusses different types of linked lists, including singly linked lists, doubly linked lists, and circularly linked lists. It provides code examples for implementing linked lists in C++ and compares the time complexity of different linked list operations. It also describes how a circularly linked list can be used to solve the Josephus problem of eliminating people seated in a circle.
The document discusses binary search trees and different ways to traverse them. It explains that traversing a binary search tree can be done in preorder, inorder, or postorder fashion by recursively visiting the left child, then the node, then the right child in different orders. Searching for a value in a balanced binary search tree takes O(log n) time, while searching an unsorted linked list takes O(n) time.
The document discusses deleting nodes from a binary search tree (BST). There are three cases to consider when deleting a node: 1) if the node is a leaf, it can be deleted immediately, 2) if the node has one child, its parent pointer is redirected to the child node, 3) if the node has two children, it is replaced with its inorder successor. The algorithm and C++ code for deleting nodes from a BST is presented.
The document discusses deletion in AVL trees and outlines 5 cases to consider when deleting nodes from an AVL tree. It also discusses expression trees and parse trees, providing examples of an expression tree for a mathematical expression and a parse tree for an SQL query. Other uses of binary trees mentioned include their use in compilers for expression trees, parse trees, and abstract syntax trees.
The document discusses various data structures including skip lists, AVL trees, and hashing. It explains that skip lists allow for logarithmic-time operations and are simple to implement. Hashing provides constant-time operations by mapping keys to array indices via a hash function, but collisions must be handled. Common hash functions discussed include summing character codes or converting to a number in a prime base.
The document discusses different methods for handling collisions in hash tables, which occur when two keys hash to the same slot. It describes linear probing, where the next empty slot is used to store the colliding key; quadratic probing which uses a quadratic function to determine subsequent slots; and chaining, where each slot contains a linked list of colliding keys. It notes the advantages and disadvantages of each approach.
The document discusses recursion and different traversal methods for binary trees. It explains how the call stack is used during recursive function calls and shows examples of preorder and inorder recursive tree traversals. It then describes how to perform non-recursive inorder traversal using an explicit stack. Finally, it introduces level-order traversal, which visits all nodes at each level from left to right before proceeding to the next level.
The document describes a simulation of customer transactions at a bank with 4 tellers. It discusses how customers arrive at certain times, are assigned to the shortest teller queue if a teller is available, or must wait in line if all tellers are busy. The simulation proceeds by maintaining a priority queue of upcoming arrival and departure events and processing customers from the queue. Statistics like total wait time are tracked to calculate the average time customers spend at the bank. Code for implementing the simulation with data structures like queues and priority queues is also presented.
The document discusses implementing a stack data structure using both an array and linked list. A stack is a last-in, first-out data structure where elements can only be inserted or removed from one end, called the top. The key stack operations of push, pop, top, isEmpty and isFull are described. Implementing a stack with an array allows for constant time operations but has size limitations, while a linked list avoids size limits but has slower insertion and removal.
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
The document discusses equivalence relations and the union-find algorithm. It defines what makes a binary relation an equivalence relation by having the properties of reflexivity, symmetry, and transitivity. It gives examples like electrical connectivity being an equivalence relation. The union-find algorithm can be used to dynamically determine if elements are in the same equivalence class based on the given relations, by performing find and union operations in time proportional to m+n for m finds and n-1 unions.
The document discusses various aspects of balanced binary search trees, including:
1) Const keyword can be used to mark parameters and return values as constant to prevent unintended modification.
2) AVL trees are binary search trees where the heights of left and right subtrees differ by at most 1.
3) For a binary search tree to be balanced, the heights of left and right subtrees should be close to equal to avoid a skewed or degenerate tree structure.
Union-find data structures can be used to efficiently generate random mazes. A maze can be represented as a grid of cells where each cell is initially isolated by walls. Removing walls corresponds to union operations, joining the cells' sets. A maze is generated by randomly performing unions until the entrance and exit cells are in the same set, connected by a path through the maze.
The document discusses different types of linked lists, including singly linked lists, doubly linked lists, and circularly linked lists. It provides code examples for implementing linked lists in C++ and compares the time complexity of different linked list operations. It also describes how a circularly linked list can be used to solve the Josephus problem of eliminating people seated in a circle.
The document discusses binary search trees and different ways to traverse them. It explains that traversing a binary search tree can be done in preorder, inorder, or postorder fashion by recursively visiting the left child, then the node, then the right child in different orders. Searching for a value in a balanced binary search tree takes O(log n) time, while searching an unsorted linked list takes O(n) time.
The document discusses deleting nodes from a binary search tree (BST). There are three cases to consider when deleting a node: 1) if the node is a leaf, it can be deleted immediately, 2) if the node has one child, its parent pointer is redirected to the child node, 3) if the node has two children, it is replaced with its inorder successor. The algorithm and C++ code for deleting nodes from a BST is presented.
The document discusses deletion in AVL trees and outlines 5 cases to consider when deleting nodes from an AVL tree. It also discusses expression trees and parse trees, providing examples of an expression tree for a mathematical expression and a parse tree for an SQL query. Other uses of binary trees mentioned include their use in compilers for expression trees, parse trees, and abstract syntax trees.
The document discusses various data structures including skip lists, AVL trees, and hashing. It explains that skip lists allow for logarithmic-time operations and are simple to implement. Hashing provides constant-time operations by mapping keys to array indices via a hash function, but collisions must be handled. Common hash functions discussed include summing character codes or converting to a number in a prime base.
The document discusses different methods for handling collisions in hash tables, which occur when two keys hash to the same slot. It describes linear probing, where the next empty slot is used to store the colliding key; quadratic probing which uses a quadratic function to determine subsequent slots; and chaining, where each slot contains a linked list of colliding keys. It notes the advantages and disadvantages of each approach.
The document discusses recursion and different traversal methods for binary trees. It explains how the call stack is used during recursive function calls and shows examples of preorder and inorder recursive tree traversals. It then describes how to perform non-recursive inorder traversal using an explicit stack. Finally, it introduces level-order traversal, which visits all nodes at each level from left to right before proceeding to the next level.
The document describes a simulation of customer transactions at a bank with 4 tellers. It discusses how customers arrive at certain times, are assigned to the shortest teller queue if a teller is available, or must wait in line if all tellers are busy. The simulation proceeds by maintaining a priority queue of upcoming arrival and departure events and processing customers from the queue. Statistics like total wait time are tracked to calculate the average time customers spend at the bank. Code for implementing the simulation with data structures like queues and priority queues is also presented.
The document discusses implementing a stack data structure using both an array and linked list. A stack is a last-in, first-out data structure where elements can only be inserted or removed from one end, called the top. The key stack operations of push, pop, top, isEmpty and isFull are described. Implementing a stack with an array allows for constant time operations but has size limitations, while a linked list avoids size limits but has slower insertion and removal.
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
How to Fix the Import Error in the Odoo 17Celine George
An import error occurs when a program fails to import a module or library, disrupting its execution. In languages like Python, this issue arises when the specified module cannot be found or accessed, hindering the program's functionality. Resolving import errors is crucial for maintaining smooth software operation and uninterrupted development processes.
How to Manage Your Lost Opportunities in Odoo 17 CRMCeline George
Odoo 17 CRM allows us to track why we lose sales opportunities with "Lost Reasons." This helps analyze our sales process and identify areas for improvement. Here's how to configure lost reasons in Odoo 17 CRM
Exploiting Artificial Intelligence for Empowering Researchers and Faculty, In...Dr. Vinod Kumar Kanvaria
Exploiting Artificial Intelligence for Empowering Researchers and Faculty,
International FDP on Fundamentals of Research in Social Sciences
at Integral University, Lucknow, 06.06.2024
By Dr. Vinod Kumar Kanvaria
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
বাংলাদেশের অর্থনৈতিক সমীক্ষা ২০২৪ [Bangladesh Economic Review 2024 Bangla.pdf] কম্পিউটার , ট্যাব ও স্মার্ট ফোন ভার্সন সহ সম্পূর্ণ বাংলা ই-বুক বা pdf বই " সুচিপত্র ...বুকমার্ক মেনু 🔖 ও হাইপার লিংক মেনু 📝👆 যুক্ত ..
আমাদের সবার জন্য খুব খুব গুরুত্বপূর্ণ একটি বই ..বিসিএস, ব্যাংক, ইউনিভার্সিটি ভর্তি ও যে কোন প্রতিযোগিতা মূলক পরীক্ষার জন্য এর খুব ইম্পরট্যান্ট একটি বিষয় ...তাছাড়া বাংলাদেশের সাম্প্রতিক যে কোন ডাটা বা তথ্য এই বইতে পাবেন ...
তাই একজন নাগরিক হিসাবে এই তথ্য গুলো আপনার জানা প্রয়োজন ...।
বিসিএস ও ব্যাংক এর লিখিত পরীক্ষা ...+এছাড়া মাধ্যমিক ও উচ্চমাধ্যমিকের স্টুডেন্টদের জন্য অনেক কাজে আসবে ...
it describes the bony anatomy including the femoral head , acetabulum, labrum . also discusses the capsule , ligaments . muscle that act on the hip joint and the range of motion are outlined. factors affecting hip joint stability and weight transmission through the joint are summarized.
Introduction to AI for Nonprofits with Tapp NetworkTechSoup
Dive into the world of AI! Experts Jon Hill and Tareq Monaur will guide you through AI's role in enhancing nonprofit websites and basic marketing strategies, making it easy to understand and apply.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.