Takashi Umeda is a researcher interested in recommendation algorithms, information diffusion on the internet, and consumer behavior in electronic commerce. He was born in Gifu Prefecture in 1985 and studied at Shizuoka University from 2003-2007 and the Tokyo Institute of Technology from 2007-2009. His bachelor's thesis examined direct financing in Silicon Valley using agent-based modeling and his master's thesis evaluated collaborative filtering using agent-based simulation in light of market environments. His research aims to design recommendation algorithms for electronic commerce by modeling interaction with market environments and evaluating collaborative filtering techniques.
The document discusses asymptotic notations that are used to describe the time complexity of algorithms. It introduces big O notation, which describes asymptotic upper bounds, big Omega notation for lower bounds, and big Theta notation for tight bounds. Common time complexities are described such as O(1) for constant time, O(log N) for logarithmic time, and O(N^2) for quadratic time. The notations allow analyzing how efficiently algorithms use resources like time and space as the input size increases.
It is a classification technique based on Bayes’ Theorem with an independence assumption among predictors. In simple terms, a Naive Bayes classifier assumes that the presence of a particular feature in a class is unrelated to the presence of any other feature.
The Naïve Bayes classifier is a popular supervised machine learning algorithm used for classification tasks such as text classification. It belongs to the family of generative learning algorithms, which means that it models the distribution of inputs for a given class or category. This approach is based on the assumption that the features of the input data are conditionally independent given the class, allowing the algorithm to make predictions quickly and accurately.
In statistics, naive Bayes classifiers are considered as simple probabilistic classifiers that apply Bayes’ theorem. This theorem is based on the probability of a hypothesis, given the data and some prior knowledge. The naive Bayes classifier assumes that all features in the input data are independent of each other, which is often not true in real-world scenarios. However, despite this simplifying assumption, the naive Bayes classifier is widely used because of its efficiency and good performance in many real-world applications.
Moreover, it is worth noting that naive Bayes classifiers are among the simplest Bayesian network models, yet they can achieve high accuracy levels when coupled with kernel density estimation. This technique involves using a kernel function to estimate the probability density function of the input data, allowing the classifier to improve its performance in complex scenarios where the data distribution is not well-defined. As a result, the naive Bayes classifier is a powerful tool in machine learning, particularly in text classification, spam filtering, and sentiment analysis, among others.
For example, a fruit may be considered to be an apple if it is red, round, and about 3 inches in diameter. Even if these features depend on each other or upon the existence of the other features, all of these properties independently contribute to the probability that this fruit is an apple and that is why it is known as ‘Naive’.
An NB model is easy to build and particularly useful for very large data sets. Along with simplicity, Naive Bayes is known to outperform even highly sophisticated classification methods.
ch_5 Game playing Min max and Alpha Beta pruning.pptSanGeet25
Game-Playing & Adversarial Search was covered in two lectures. Minimax search finds the optimal strategy but is impractical for large games. Minimax with alpha-beta pruning improves search efficiency by pruning subtrees that cannot affect the result. Iterative deepening allows more search within time limits by incrementally increasing search depth. Heuristics help guide search and handle limited lookahead.
This document discusses cybercrime and how to prevent becoming a victim. It begins by explaining why we should be aware of cybercrime given our increasing online activities. The objectives are then outlined as providing awareness of cybercrime, recognizing methods, understanding cyber laws, and learning to avoid victimization. Various types of cybercrime are defined including those against persons, property, and government. Examples like phishing, hacking, and cyber terrorism are described. The history of cybercrime in India involves many website hacks and defacements. Laws are still lacking to fully address cybercrime. Awareness, security software, and caution are recommended for protection.
The document discusses data structures and arrays. It begins by defining data, data structures, and how data structures affect program design. It then categorizes data structures as primitive and non-primitive. Linear and non-linear data structures are described as examples of non-primitive structures. The document focuses on arrays as a linear data structure, covering array declaration, representation in memory, calculating size, types of arrays, and basic operations like traversing, searching, inserting, deleting and sorting. Two-dimensional arrays are also introduced.
A comprehensive tutorial on Convolutional Neural Networks (CNN) which talks about the motivation behind CNNs and Deep Learning in general, followed by a description of the various components involved in a typical CNN layer. It explains the theory involved with the different variants used in practice and also, gives a big picture of the whole network by putting everything together.
Next, there's a discussion of the various state-of-the-art frameworks being used to implement CNNs to tackle real-world classification and regression problems.
Finally, the implementation of the CNNs is demonstrated by implementing the paper 'Age ang Gender Classification Using Convolutional Neural Networks' by Hassner (2015).
Introduction to Artificial Intelligence.pptxRSAISHANKAR
My name is R. Sai Shankar. In here, I'm publish a small PowerPoint Presentation on Artificial Intelligence. Here is the link for my YouTube Channel "Learn AI With Shankar". Please Like Share Subscribe. Thank you.
https://youtu.be/3N5C99sb-gc
The document discusses various tree data structures and algorithms related to binary trees. It begins with an introduction to different types of binary trees such as strict binary trees, complete binary trees, and extended binary trees. It then covers tree traversal algorithms including preorder, inorder and postorder traversal. The document also discusses representations of binary trees using arrays and linked lists. Finally, it explains algorithms for operations on binary search trees such as searching, insertion, deletion and rebalancing through rotations in AVL trees.
PPT on Analysis Of Algorithms.
The ppt includes Algorithms,notations,analysis,analysis of algorithms,theta notation, big oh notation, omega notation, notation graphs
Stack is a last-in, first-out (LIFO) data structure where elements are inserted and removed from the top. Pushing adds an element to the top of the stack, while popping removes the top element. A stack overflow occurs when pushing to a full stack, while a stack underflow happens when popping an empty stack. Stack applications include system startup/shutdown processes, function calling where the last function called is the first to return, and argument passing in C where arguments are pushed right-to-left and popped left-to-right.
Selection sort is an in-place comparison sorting algorithm where the minimum element from the unsorted section of the list is selected in each pass and swapped with the first element. It has a time complexity of O(n2) making it inefficient for large lists. The algorithm involves dividing the list into sorted and unsorted sublists, finding the minimum element in the unsorted sublist, swapping it with the first element and moving the imaginary wall between the two sublists by one element. This process is repeated for n-1 passes to completely sort an input list of n elements. Pseudocode for the algorithm using a nested for loop to find the minimum element and swap it is also provided.
1) Stacks are linear data structures that follow the LIFO (last-in, first-out) principle. Elements can only be inserted or removed from one end called the top of the stack.
2) The basic stack operations are push, which adds an element to the top of the stack, and pop, which removes an element from the top.
3) Stacks have many applications including evaluating arithmetic expressions by converting them to postfix notation and implementing the backtracking technique in recursive backtracking problems like tower of Hanoi.
Stack and its Applications : Data Structures ADTSoumen Santra
Stacks are a data structure that follow the last-in, first-out (LIFO) principle. Elements are inserted and removed from the same end called the top of the stack. Common stack operations include push to add an element, pop to remove an element, peek to view the top element, and isEmpty to check if the stack is empty. Stacks have various applications like representing function call stacks, evaluating mathematical expressions, and solving puzzles like the Towers of Hanoi. They can be implemented using arrays or linked lists.
This document discusses binary search trees, including:
- Binary search trees allow for fast addition and removal of data by organizing nodes in a way that satisfies ordering properties.
- New nodes are inserted by recursively searching the tree and placing the node in the proper position to maintain ordering - left subtrees must be less than the root and right subtrees greater than or equal.
- The insert function recursively moves down the tree until an unused leaf node is found in the correct position based on comparing its data to the data being inserted.
Merge sort is a divide and conquer algorithm that divides an array into halves, recursively sorts the halves, and then merges the sorted halves back together. The key steps are:
1. Divide the array into equal halves until reaching base cases of arrays with one element.
2. Recursively sort the left and right halves by repeating the divide step.
3. Merge the sorted halves back into a single sorted array by comparing elements pairwise and copying the smaller element into the output array.
Merge sort has several advantages including running in O(n log n) time in all cases, accessing data sequentially with low random access needs, and being suitable for external sorting of large data sets that do not fit in memory
Doubly Linked List || Operations || AlgorithmsShubham Sharma
Doubly linked list and operations on it. Insertion, Deletion, Traversing at all locations- First, Last, Middle.
Basic definitions and structured example.
Algorithms for all the operations.
Binary search trees are binary trees where all left descendants of a node are less than the node's value and all right descendants are greater. This structure allows for efficient search, insertion, and deletion operations. The document provides definitions and examples of binary search tree properties and operations like creation, traversal, searching, insertion, deletion, and finding minimum and maximum values. Applications include dynamically maintaining a sorted dataset to enable efficient search, insertion, and deletion.
Linked lists are linear data structures where each node contains a data field and a pointer to the next node. There are two types: singly linked lists where each node has a single next pointer, and doubly linked lists where each node has next and previous pointers. Common operations on linked lists include insertion and deletion which have O(1) time complexity for singly linked lists but require changing multiple pointers for doubly linked lists. Linked lists are useful when the number of elements is dynamic as they allow efficient insertions and deletions without shifting elements unlike arrays.
1) The document discusses complexity analysis of algorithms, which involves determining the time efficiency of algorithms by counting the number of basic operations performed based on input size.
2) It covers motivations for complexity analysis, machine independence, and analyzing best, average, and worst case complexities.
3) Simple rules are provided for determining the complexity of code structures like loops, nested loops, if/else statements, and switch cases based on the number of iterations and branching.
Queue is a first-in first-out (FIFO) data structure where elements can only be added to the rear of the queue and removed from the front of the queue. It has two pointers - a front pointer pointing to the front element and a rear pointer pointing to the rear element. Queues can be implemented using arrays or linked lists. Common queue operations include initialization, checking if empty/full, enqueue to add an element, and dequeue to remove an element. The document then describes how these operations work for queues implemented using arrays, linked lists, and circular arrays. It concludes by providing exercises to implement specific queue tasks.
The document discusses different types of queues including their representations, operations, and applications. It describes queues as linear data structures that follow a first-in, first-out principle. Common queue operations are insertion at the rear and deletion at the front. Queues can be represented using arrays or linked lists. Circular queues and priority queues are also described as variants that address limitations of standard queues. Real-world and technical applications of queues include CPU scheduling, cashier lines, and data transfer between processes.
The document describes a doubly linked list data structure. Each node in a doubly linked list contains pointers to both the next and previous nodes, allowing traversal in either direction. Common operations on doubly linked lists include inserting and deleting nodes at the beginning, end, or anywhere in the list. Pseudocode algorithms are provided to demonstrate how to implement these operations by updating the pointer references between nodes.
The document discusses various sorting algorithms that use the divide-and-conquer approach, including quicksort, mergesort, and heapsort. It provides examples of how each algorithm works by recursively dividing problems into subproblems until a base case is reached. Code implementations and pseudocode are presented for key steps like partitioning arrays in quicksort, merging sorted subarrays in mergesort, and adding and removing elements from a heap data structure in heapsort. The algorithms are compared in terms of their time and space complexity and best uses.
presentation about bubble sort
presented by: Ahmed al-butty
Arab Open University - Riyadh , Saudi Arabia
the content
Introduction to Sorting Algorithms
What is Bubble Sort
Bubble Sort Algorithm
Example of Bubble Sort
Complexity Analysis
When to Choose Bubble Sort
Searching and sorting
Types of Searching
1. Linear Searching
2. Binary Searching
Types of Sorting
1.Selection Sort
2. Insertion Sort
3.Bubble Sort
And the examples of Linear searching, Binary Searching
And also the examples of Selection sort, Insertion sort and Bubble sort and describing them in detail in this ppt
An array is a data structure that stores fixed number of items of the same type. It allows fast access of elements using indices. Basic array operations include traversing elements, inserting/deleting elements, searching for elements, and updating elements. Arrays are zero-indexed and elements are accessed via their index.
The document discusses various searching and sorting algorithms. It describes linear search, binary search, selection sort, bubble sort, and heapsort. For each algorithm, it provides pseudocode examples and analyzes their performance in terms of number of comparisons required in the worst case. Linear search requires N comparisons in the worst case, while binary search requires log N comparisons. Selection sort and bubble sort both require approximately N^2 comparisons, while heapsort requires 1.5NlogN comparisons.
The document discusses linked stacks and linked queues. It provides an introduction to linked stacks and linked queues and how they are commonly implemented using singly linked lists. It then describes the key operations for each - push, pop, enqueue, and dequeue. Algorithms for each operation are presented using pseudocode. Examples of applications that can make use of linked stacks and queues are given, such as balancing symbols in an expression and representing polynomials.
a presentation covering all the topics on Stacks and Queues in Data Structures using C++. Includes self explanatory diagrams, algorithms and program pieces.
The document discusses various tree data structures and algorithms related to binary trees. It begins with an introduction to different types of binary trees such as strict binary trees, complete binary trees, and extended binary trees. It then covers tree traversal algorithms including preorder, inorder and postorder traversal. The document also discusses representations of binary trees using arrays and linked lists. Finally, it explains algorithms for operations on binary search trees such as searching, insertion, deletion and rebalancing through rotations in AVL trees.
PPT on Analysis Of Algorithms.
The ppt includes Algorithms,notations,analysis,analysis of algorithms,theta notation, big oh notation, omega notation, notation graphs
Stack is a last-in, first-out (LIFO) data structure where elements are inserted and removed from the top. Pushing adds an element to the top of the stack, while popping removes the top element. A stack overflow occurs when pushing to a full stack, while a stack underflow happens when popping an empty stack. Stack applications include system startup/shutdown processes, function calling where the last function called is the first to return, and argument passing in C where arguments are pushed right-to-left and popped left-to-right.
Selection sort is an in-place comparison sorting algorithm where the minimum element from the unsorted section of the list is selected in each pass and swapped with the first element. It has a time complexity of O(n2) making it inefficient for large lists. The algorithm involves dividing the list into sorted and unsorted sublists, finding the minimum element in the unsorted sublist, swapping it with the first element and moving the imaginary wall between the two sublists by one element. This process is repeated for n-1 passes to completely sort an input list of n elements. Pseudocode for the algorithm using a nested for loop to find the minimum element and swap it is also provided.
1) Stacks are linear data structures that follow the LIFO (last-in, first-out) principle. Elements can only be inserted or removed from one end called the top of the stack.
2) The basic stack operations are push, which adds an element to the top of the stack, and pop, which removes an element from the top.
3) Stacks have many applications including evaluating arithmetic expressions by converting them to postfix notation and implementing the backtracking technique in recursive backtracking problems like tower of Hanoi.
Stack and its Applications : Data Structures ADTSoumen Santra
Stacks are a data structure that follow the last-in, first-out (LIFO) principle. Elements are inserted and removed from the same end called the top of the stack. Common stack operations include push to add an element, pop to remove an element, peek to view the top element, and isEmpty to check if the stack is empty. Stacks have various applications like representing function call stacks, evaluating mathematical expressions, and solving puzzles like the Towers of Hanoi. They can be implemented using arrays or linked lists.
This document discusses binary search trees, including:
- Binary search trees allow for fast addition and removal of data by organizing nodes in a way that satisfies ordering properties.
- New nodes are inserted by recursively searching the tree and placing the node in the proper position to maintain ordering - left subtrees must be less than the root and right subtrees greater than or equal.
- The insert function recursively moves down the tree until an unused leaf node is found in the correct position based on comparing its data to the data being inserted.
Merge sort is a divide and conquer algorithm that divides an array into halves, recursively sorts the halves, and then merges the sorted halves back together. The key steps are:
1. Divide the array into equal halves until reaching base cases of arrays with one element.
2. Recursively sort the left and right halves by repeating the divide step.
3. Merge the sorted halves back into a single sorted array by comparing elements pairwise and copying the smaller element into the output array.
Merge sort has several advantages including running in O(n log n) time in all cases, accessing data sequentially with low random access needs, and being suitable for external sorting of large data sets that do not fit in memory
Doubly Linked List || Operations || AlgorithmsShubham Sharma
Doubly linked list and operations on it. Insertion, Deletion, Traversing at all locations- First, Last, Middle.
Basic definitions and structured example.
Algorithms for all the operations.
Binary search trees are binary trees where all left descendants of a node are less than the node's value and all right descendants are greater. This structure allows for efficient search, insertion, and deletion operations. The document provides definitions and examples of binary search tree properties and operations like creation, traversal, searching, insertion, deletion, and finding minimum and maximum values. Applications include dynamically maintaining a sorted dataset to enable efficient search, insertion, and deletion.
Linked lists are linear data structures where each node contains a data field and a pointer to the next node. There are two types: singly linked lists where each node has a single next pointer, and doubly linked lists where each node has next and previous pointers. Common operations on linked lists include insertion and deletion which have O(1) time complexity for singly linked lists but require changing multiple pointers for doubly linked lists. Linked lists are useful when the number of elements is dynamic as they allow efficient insertions and deletions without shifting elements unlike arrays.
1) The document discusses complexity analysis of algorithms, which involves determining the time efficiency of algorithms by counting the number of basic operations performed based on input size.
2) It covers motivations for complexity analysis, machine independence, and analyzing best, average, and worst case complexities.
3) Simple rules are provided for determining the complexity of code structures like loops, nested loops, if/else statements, and switch cases based on the number of iterations and branching.
Queue is a first-in first-out (FIFO) data structure where elements can only be added to the rear of the queue and removed from the front of the queue. It has two pointers - a front pointer pointing to the front element and a rear pointer pointing to the rear element. Queues can be implemented using arrays or linked lists. Common queue operations include initialization, checking if empty/full, enqueue to add an element, and dequeue to remove an element. The document then describes how these operations work for queues implemented using arrays, linked lists, and circular arrays. It concludes by providing exercises to implement specific queue tasks.
The document discusses different types of queues including their representations, operations, and applications. It describes queues as linear data structures that follow a first-in, first-out principle. Common queue operations are insertion at the rear and deletion at the front. Queues can be represented using arrays or linked lists. Circular queues and priority queues are also described as variants that address limitations of standard queues. Real-world and technical applications of queues include CPU scheduling, cashier lines, and data transfer between processes.
The document describes a doubly linked list data structure. Each node in a doubly linked list contains pointers to both the next and previous nodes, allowing traversal in either direction. Common operations on doubly linked lists include inserting and deleting nodes at the beginning, end, or anywhere in the list. Pseudocode algorithms are provided to demonstrate how to implement these operations by updating the pointer references between nodes.
The document discusses various sorting algorithms that use the divide-and-conquer approach, including quicksort, mergesort, and heapsort. It provides examples of how each algorithm works by recursively dividing problems into subproblems until a base case is reached. Code implementations and pseudocode are presented for key steps like partitioning arrays in quicksort, merging sorted subarrays in mergesort, and adding and removing elements from a heap data structure in heapsort. The algorithms are compared in terms of their time and space complexity and best uses.
presentation about bubble sort
presented by: Ahmed al-butty
Arab Open University - Riyadh , Saudi Arabia
the content
Introduction to Sorting Algorithms
What is Bubble Sort
Bubble Sort Algorithm
Example of Bubble Sort
Complexity Analysis
When to Choose Bubble Sort
Searching and sorting
Types of Searching
1. Linear Searching
2. Binary Searching
Types of Sorting
1.Selection Sort
2. Insertion Sort
3.Bubble Sort
And the examples of Linear searching, Binary Searching
And also the examples of Selection sort, Insertion sort and Bubble sort and describing them in detail in this ppt
An array is a data structure that stores fixed number of items of the same type. It allows fast access of elements using indices. Basic array operations include traversing elements, inserting/deleting elements, searching for elements, and updating elements. Arrays are zero-indexed and elements are accessed via their index.
The document discusses various searching and sorting algorithms. It describes linear search, binary search, selection sort, bubble sort, and heapsort. For each algorithm, it provides pseudocode examples and analyzes their performance in terms of number of comparisons required in the worst case. Linear search requires N comparisons in the worst case, while binary search requires log N comparisons. Selection sort and bubble sort both require approximately N^2 comparisons, while heapsort requires 1.5NlogN comparisons.
The document discusses linked stacks and linked queues. It provides an introduction to linked stacks and linked queues and how they are commonly implemented using singly linked lists. It then describes the key operations for each - push, pop, enqueue, and dequeue. Algorithms for each operation are presented using pseudocode. Examples of applications that can make use of linked stacks and queues are given, such as balancing symbols in an expression and representing polynomials.
a presentation covering all the topics on Stacks and Queues in Data Structures using C++. Includes self explanatory diagrams, algorithms and program pieces.
This document discusses queues, including:
1. Queues follow a First-In First-Out (FIFO) methodology where the first item stored is the first item accessed.
2. Queues can be implemented using arrays or linked lists, with two pointers - a front pointer and rear pointer - to keep track of the first and last elements.
3. The basic queue operations are enqueue, which adds an item to the rear, and dequeue, which removes an item from the front.
The document discusses data structures and algorithms including stacks, queues, and their implementations using arrays and linked lists. Key points:
1. Stacks follow LIFO principle and allow insertion/removal at one end only. Queues follow FIFO principle. Both can be implemented using arrays or linked lists.
2. Common stack operations like push, pop, and peek have O(1) time complexity. Queue operations like enqueue and dequeue also have O(1) time complexity.
3. Linked list implementations of stacks and queues allocate memory dynamically and don't have size limits like arrays.
4. A circular queue treats the last node as connected to the first, forming a ring. This allows insertion
1) A queue is a first-in first-out (FIFO) data structure where elements can only be added to the rear of the queue and removed from the front of the queue.
2) The components of a queue include the front and rear pointers, elements that hold data, and the maximum size of the queue.
3) Queues can be implemented using arrays or linked lists, with operations including initialization, checking for empty/full, enqueue to add elements, and dequeue to remove elements.
The document discusses stacks, queues and linked lists. It provides details about the operations and implementations of each:
Stacks follow the LIFO principle and have push and pop operations. Queues follow the FIFO principle with insertion at the rear and deletion from the front.
Linked lists consist of nodes with data and links. They allow efficient insertion/removal anywhere through use of pointers. Linked lists can implement stacks and queues. Operations on linked lists include insertion, deletion, and traversal. Implementations of stacks and queues using linked lists are also provided through code examples.
This presentation summarizes stack and queue data structures. It includes:
- An introduction to linear and non-linear data structures, including arrays, stacks, and queues.
- Definitions of stacks as LIFO data structures and queues as FIFO data structures. Operations for each like push, pop, enqueue, dequeue are described.
- Algorithms for common operations on stacks and queues like insertion, deletion, and display are provided in pseudocode.
- Examples of applications of stacks and queues in areas like reversing strings, scheduling, and buffers.
- Differences between stacks and queues are outlined.
- Code examples in C of implementing stack push/pop and queue enqueue/dequeue operations
This document discusses queues, which are data structures that allow insertion of elements at one end and deletion at the other end on a first-in first-out basis. It describes two common representations of queues using arrays and linked lists. It also covers circular queues which use an array as a circular buffer. The key operations for queues - enqueue to insert and dequeue to remove elements - are presented along with algorithms to implement these operations for different queue representations. Finally, the document briefly introduces deques, which allow insertion and removal from both ends.
This document discusses implementing stacks and queues using linked lists. For a stack, elements are inserted and removed from the head (start) of the linked list for constant time operations. For a queue, elements are inserted at the head and removed from the tail (end) of the linked list, requiring traversing to the second last node for removal. Implementing stacks and queues with linked lists avoids size limitations of arrays and uses dynamic memory allocation.
The document discusses stacks and queues, which are linear data structures. It defines a stack as a first-in, last-out (FILO) structure where elements can only be inserted or removed from one end. A queue is defined as a first-in, first-out (FIFO) structure where elements can only be inserted at one end and removed from the other. The document then describes common stack and queue operations like push, pop, enqueue, dequeue and provides examples of their applications. It also discusses two common implementations of stacks and queues using arrays and linked lists.
This document discusses different data structures used to implement queues and priority queues. It describes:
- Queues as first-in, first-out linear lists that allow insertion at the rear and deletion at the front.
- Two common implementations of queues using arrays and linked lists.
- Deques, which allow insertion and deletion from both ends.
- Priority queues, where elements have priorities and higher priority elements are processed first.
A queue is a first-in first-out (FIFO) data structure where elements are inserted at the rear end and deleted from the front end. It maintains two pointers - a front pointer pointing to the front element and a rear pointer pointing to the rear element. New elements are added by incrementing the rear pointer and elements are removed by incrementing the front pointer. Common queue operations include enqueue() to add an element, dequeue() to remove an element, peek() to access the front element without removing it, and functions to check if the queue is full or empty.
This document describes how to implement a queue using a linked list. It outlines the necessary steps: defining a Node structure with data and next pointers, initializing front and rear pointers to NULL, and implementing functions for enqueue, dequeue, and display. The enqueue function adds a new node to the rear. Dequeue removes the front node. Display traverses the list from front to rear printing the data values.
A queue is a first-in, first-out (FIFO) data structure that can be implemented using either a linear array or linked list. Elements are added to the rear of the queue and removed from the front. A priority queue is a collection of elements where each element has a priority and higher priority elements are processed before lower priority ones. A priority queue can be implemented using a one-way linked list where each node stores the element, priority, and link. Elements are deleted from the front of the list and inserted in order of descending priority.
The document discusses stacks and queues as data structures. Stacks follow LIFO (Last In First Out) and involve push and pop operations on an array or linked list. Queues follow FIFO (First In First Out) and involve insert and delete operations, with insertion at the rear and deletion at the front. The document provides examples of implementing stacks and queues using arrays and linked lists, and describes the basic operations like creation, insertion, deletion, checking for empty/full.
The document discusses stacks and queues as data structures. Stacks follow LIFO (Last In First Out) and allow insertion and deletion from one end only. Queues follow FIFO (First In First Out) and allow insertion from one end and deletion from the other. Both can be implemented using arrays or linked lists. Common operations on stacks are push and pop, while common operations on queues are insert and delete.
This presentation provides an in-depth overview of Stacks and Queues, two fundamental data structures used in computer science and programming. The presentation covers key concepts, definitions, and operations for both data structures, including push and pop operations for stacks, and enqueue and dequeue operations for queues.
Key topics include:
The LIFO (Last In, First Out) and FIFO (First In, First Out) principles.
Array-based and linked list-based implementations of stacks and queues.
Real-world applications of stacks (e.g., expression evaluation, undo mechanisms) and queues (e.g., task scheduling, BFS traversal).
Practical examples and visualizations to help understand how stacks and queues work in various algorithms.
Whether you're new to data structures or looking to refresh your knowledge, this presentation will help you grasp the core concepts and applications of stacks and queues in programming and computer science.
Ideal for:
Computer Science students
Aspiring software engineers
Programming enthusiasts
Anyone looking to improve their understanding of data structures and algorithms
The document discusses different data structures including stacks, queues, linked lists, and their implementations. It defines stacks as LIFO structures that can add and remove items from one end only. Queues are FIFO structures that add to one end and remove from the other. Linked lists store data in nodes that point to the next node. Stacks, queues and linked lists can all be implemented using arrays or by linking nodes. Priority queues and deques are also discussed.
This document defines and provides examples of partial order relations. It discusses the key properties of a partial order being reflexive, antisymmetric, and transitive. Examples are given to show that the relation of greater than or equal to (≥) forms a partial order on integers, while division (|) forms a partial order on positive integers. The document also discusses comparability, total orders, well-ordered sets, and Hasse diagrams which are used to visually represent partial orders.
The primary focus of the PPT is to develop the initial skill of using HTML & CSS programming language to develop a static web page like Portfolio.
This PowerPoint Presentation is of Front End Design.
This PPT will give an entire view on developing the static web page.
This PPT covers the entire topic of Macro Assembler. This Includes the topic such as design of a macro assembler, 3 passes of macro assembler etc.
This is the PPT of System Programming.
This is an PPT about the Icons that are used in Graphical User Interface, the Images that are used for developing a web page & the use of multimedia for various purpose.
This is an PowerPoint Presentation of Front End Design.
This PPT describes about the "Project Tracking" activity & statistical process control at Infosys.
It covers the entire topic such as project tracking, activities tracking, defect tracking, issue tracking, etc.
It covers all main activity of SPC such as SPC analysis, control chart for SPC etc.
This PowerPoint presentation is of "Software Project Management".
This is the PowerPoint presentation on the topic "Peephole Optimization". This presentation covers the entire topic of peephole optimization.
This PowerPoint presentation is of Compiler Design.
This is the PPT of "Routing in Manet". It covers the entire topic of routing protocol.
This PowerPoint presentation is of Data Communication & Computer Network.
The document discusses the design of a two-pass macro preprocessor. In pass one, macro definitions are identified and stored in a macro definition table along with their parameters. A macro name table is also created. In pass two, macro calls are identified and replaced by retrieving the corresponding macro definition and substituting actual parameters for formal parameters using an argument list array. Databases like the macro definition table, macro name table, and argument list array are used to store and retrieve macro information to enable expansion of macro calls. The algorithm scans the input sequentially in each pass to process macro definitions and calls.
This document discusses Vehicular Ad-Hoc Networks (VANETs) which allow vehicles to communicate with each other to share safety and traffic information. It outlines the architecture of VANETs including vehicle-to-vehicle and vehicle-to-infrastructure communication. The document also discusses security issues in VANETs such as bogus information attacks, identity disclosure, and denial-of-service attacks. It proposes the use of authentication, message integrity, privacy, traceability and availability to address these security requirements. The document assumes that roadways are divided into regions managed by trusted roadside infrastructure units.
This document discusses breadth-first search (BFS) and depth-first search (DFS) algorithms for traversing graphs. It provides examples of how BFS uses a queue to search all neighbors at the current level before moving to the next level, while DFS uses a stack and explores each branch as far as possible before backtracking. The document compares key differences between BFS and DFS such as their time and space complexities, usefulness for finding shortest paths, and whether queues or stacks are used. Application areas for each algorithm are also mentioned.
Secant method in Numerical & Statistical MethodMeghaj Mallick
This is an PPT of a Mathematical Paper i.e Numerical & Statistical Method. It contsin the following topic such as "Secant method in Numerical & Statistical Method ".
This document discusses communication and barriers to effective communication. It defines communication as the exchange of information, ideas, thoughts and feelings between individuals through speech, writing and behavior. It then outlines some common barriers to communication, including badly expressed messages, loss in transmission, semantic problems, over or under communication, prejudices on the sender's part, and poor attention, inattentive listening, evaluation, interests/attitudes and refutation on the receiver's part. The document suggests identifying and addressing such barriers to improve communication.
This document provides an introduction to hashing and hash tables. It defines hashing as a data structure that uses a hash function to map values to keys for fast retrieval. It gives an example of mapping list values to array indices using modulo. The document discusses hash tables and their operations of search, insert and delete in O(1) time. It describes collisions that occur during hash function mapping and resolution techniques like separate chaining and linear probing.
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2025-06-08 Abraham 02 (shared slides).pptxDale Wells
Lesson 2 of 9 in a Heritage Bible Master Class study of Abraham, the man God called ”My friend” (Isa. 41:8)
The Heritage Bible Master Class is a non-denominational discussion-based adult Bible class. We meet every Sunday morning at 10:15 in the Administration Building at Heritage Palms Country Club, on the south side of Fred Waring, just east of Jefferson Street in Indio, CA. We’d love to have you drop by to check us out.
AI Intelligence: Exploring the Future of Artificial Intelligencesayalikerimova20
AI Intelligence is a forward-thinking event designed to unite AI enthusiasts, developers, researchers, and industry professionals under one roof. The event explores the dynamic and rapidly evolving world of Artificial Intelligence — from foundational theories to advanced, real-world applications.
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FUTURE OF FITNESS 2025 KEYNOTE BRYAN OROURKE BEYOND ACTIV SINGAPORE 2025Bryan K. O'Rourke
The Future of Fitness 2025 | Bryan K. O’Rourke Keynote at Beyond Activ Singapore
Discover the top trends shaping the global fitness and wellness industry in 2025 and beyond. In this compelling keynote, Bryan K. O’Rourke—CEO of Core Health & Fitness, global strategist, and futurist—shares bold insights into the future of healthspan, longevity, recovery, and the bifurcation of fitness markets. Delivered live at Beyond Activ Singapore, this talk explores how AI, technology, shifting demographics, luxury wellness, and socioeconomic divides are creating both unprecedented challenges and powerful opportunities for fitness professionals, operators, and brands.
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Seminar Presented by Natnael Dechasa Title: Brain Cheat Codes: The Science-Ba...Nati1986
This engaging and well-structured presentation offers a psychologically grounded exploration of key personal development "codes" designed to inspire and equip young professionals and university students. Through clear, actionable insights and practical takeaways, the session empowers attendees to unlock their potential, build resilience, and achieve their goals. Ideal for workshops, seminars, or motivational events, the content is delivered in a visually appealing, easy-to-follow format that encourages reflection and growth.
How Does a Configuration Management Plan Mitigate Risks?Writegenic AI
One of the primary purposes of a Configuration Management Plan is to mitigate risks by controlling configuration changes and ensuring proper tracking. The CMP identifies potential risks related to changes, such as errors introduced by incorrect versions or unapproved modifications.
Timothy J. Los, JD, LL.M. (Tax) – Global Investor, Family Office & Profession...Timothy Los
Discover the professional journey of Timothy J. Los, JD, LL.M. (Tax)—an investor, traveler, and Managing Partner of both Rante Corporation and the Office of the Los Family Ltd (UK). This sleek, infographic-style deck showcases:
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Timothy J. Los, JD, LL.M. (Tax) – Global Investor, Family Office & Profession...Timothy Los
Stack & Queue using Linked List in Data Structure
1. Presented BY : Shraddha Malviya
“Stack and Queue using Linked List”
Roll No. : MCA/25018/18
2. Stack
A stack is an ordered list with the restriction that element are
added or deleted from only one end of list termed top of stack. The
other end of the list which lies ‘inactive’ is termed bottom of stack.
3. Stack using linked list
A linked stack is a linear list of elements commonly
implemented as a singly linked list whose start
pointer perform the role of the top pointer of stack .
c b a
top
Linked representation of stack
4. Stack operation :
Push operation-
c a
top
b
Linked stack S
Push ‘d’ into S
cd ab
top
top
Push operation
PUSH_LINKSTACK(TOP,ITEM)
Call GETNODE(X)
DATA(X) = ITEM /*frame node item */
LINK(X) = TOP /* insert into x into stack */
TOP = X /*reset Top pointer */
end PUSH_LINKSTACK.
5. Pop operation-
c ab
Linked stack Stop
Pop ‘c’ from S
c ab
top
top
Push operation
POP_LINKSTACK(TOP,ITEM)
if(TOP=0)
then call LINKSTACK_EMPTY
else
{
TEMP=TOP;
ITEM=DATA(TOP);
TOP=LINK(TOP);
}
Call RETURN (TEMP)
end POP_LINKSTACK
6. Queue
A Queue is a linear list in which all insertion are
made at one end of the list known as rear or tail of
queue and all deletion are made at the other end
known as front or head of the queue . An insertion
operation is also referred to as enqueuing a queue
and deletion operation is referred to as dequeuing a
queue.
7. Queue using linked list
A linked queue is also linear list of element
commonly implemented as a singly linked list but
with two pointer ,Front and Rear . The start pointer
of the singly linked list plays the role of Front while
the pointer to the last node is set to play the role
of Rear .
a b c
front
rear
Linked representation of queue
8. Queue operation :
Insert operation--
a b
front
c
rear
Insert ‘d into queue’
a b dc
rear
front
rear
Insertion operation
INSERT_LINKQUEUE(FRONT,REAR,
ITEM)
Call GETNODE (X);
DATA (X) = ITEM;
LINK (X) = NIL;
if(FRONT = 0)
then FRONT = REAR = X;
else
{
LINK (REAR) = X;
REAR = X;
}
end INSERT_LINKQUEUE
9. Delete operation--
a b c
rear
front
Delete ‘a’ from queue
front
a b c
rear
front
Delete operation
DELETE_LINKQUEUE (FRONT , ITEM)
if(FRONT = 0)
then call LINKQUEUE_EMPTY;
else
{
TEMP = FRONT;
ITEM= DATA(TEMP);
FRONT = LINK(TEMP);
}
call RETURN (TEMP);
end DELETE_LINKQUEUE