The document discusses different types of queues, including simple, circular, priority, and double-ended queues. It describes the basic queue operations of enqueue and dequeue, where new elements are added to the rear of the queue and existing elements are removed from the front. Circular queues are more memory efficient than linear queues by connecting the last queue element back to the first, forming a circle. Priority queues remove elements based on priority rather than order of insertion. Double-ended queues allow insertion and removal from both ends. Common applications of queues include CPU and disk scheduling, synchronization between asynchronous processes, and call center phone systems.
The document provides tips for writing an effective blog. It defines what a blog is and its typical components like title, body, permalink and post date. It emphasizes the importance of considering ideas, organization, voice, word choice, sentence fluency and presentation when writing. It advises writing with the reader in mind, making the content valuable, proofreading for errors, keeping it short and interesting, using keywords to help with search engines, writing clearly with short sentences and common expressions, and keeping the copy lively, factual, tight, clear, short and optimized for search engines.
Linked lists are linear data structures where elements are linked using pointers. The three main types are singly, doubly, and circular linked lists. Linked lists allow dynamic memory allocation and fast insertion/deletion compared to arrays but slower access. A linked list contains nodes, each with a data field and pointer to the next node. Basic operations on linked lists include insertion, deletion, traversal, and search. Doubly linked lists include pointers to both the next and previous nodes.
This document discusses key concepts related to production analysis including:
1. It defines production as the process of transforming inputs into outputs and describes a production function as the relationship between inputs and outputs.
2. It outlines short run, long run, and very long run periods and explains factors of production, total product, average product, and marginal product.
3. It describes the three stages of production - increasing, constant, and diminishing returns - and the law of diminishing marginal returns as it relates to a variable input factor.
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.
Queues can be implemented using linked lists by allocating memory dynamically for each new element and linking them together. Two pointers - Front and Rear - are used to mark the front and rear of the queue. Elements contain a data part and an address part linking to the next element. Insertions occur at the rear and deletions at the front. The linked list start pointer is used as Front, while Rear points to the last element. An empty queue is indicated when Front and Rear are NULL.
Brief about how LinkedIn can be used as a B2B marketing & Lead Generation tool. I'm a freelancer, helping organizations increase their revenue by LinkedIn activities & high quality lead generation.
A queue is a non-primitive linear data structure that follows the FIFO (first-in, first-out) principle. Elements are added to the rear of the queue and removed from the front. Common operations on a queue include insertion (enqueue) and deletion (dequeue). Queues have many real-world applications like waiting in lines and job scheduling. They can be represented using arrays or linked lists.
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.
Queue is an abstract data structure, somewhat similar to Stacks. Unlike stacks, a queue is open at both its ends. One end is always used to insert data (enqueue) and the other is used to remove data (dequeue). Queue follows First-In-First-Out methodology, i.e., the data item stored first will be accessed first.
A circular queue is a fixed size data structure that follows FIFO (first in, first out) principles. Elements are added to the rear of the queue and removed from the front. When the rear reaches the end, it wraps around to the beginning so the queue space is used efficiently. Common circular queue operations include enqueue to add an element, dequeue to remove an element, and display to output all elements.
This document discusses stacks and their applications. It defines a stack as a Last In First Out (LIFO) data structure where newly added items are placed on top. The core stack operations of PUSH, POP, and PEEK are described. An array implementation of stacks is presented and animations demonstrate push and pop operations. Applications of stacks like checking for balanced braces, converting infix to postfix notation, and postfix calculators are explained with examples. Pseudocode provides an algorithm for infix to postfix conversion using a stack.
OVERVIEW:
Introduction
Definition
Example of Threaded BT.
Types & Structure
One-way .
Double-way.
Structure.
Traversal
Algorithm for Traversal
Traversal Example
Inserting
Algorithm for Inserting
Inserting Example
Comparison With Binary Tree
Advantages and Disadvantages
Why Threaded BT are used?
Conclusion
Reference
Stack is a linear data structure that follows the LIFO (Last In First Out) principle. Elements are inserted and removed from the top of the stack. Stack can be implemented using arrays or linked lists. Common stack operations are push, which adds an element to the top, and pop, which removes an element from the top.
The document discusses converting expressions from infix to postfix notation. In infix notation, operators are between operands. In postfix notation, operators follow operands. The algorithm scans the infix expression left to right, appending operands to the output and handling operators and parentheses by pushing/popping from a stack based on precedence. An example converts the infix expression A * (B + C) - D / E to postfix AB+C*+DE/-.
This document discusses stacks and queues as linear data structures. It defines stacks as last-in, first-out (LIFO) collections where the last item added is the first removed. Queues are first-in, first-out (FIFO) collections where the first item added is the first removed. Common stack and queue operations like push, pop, insert, and remove are presented along with algorithms and examples. Applications of stacks and queues in areas like expression evaluation, string reversal, and scheduling are also covered.
This document discusses priority queues. It defines a priority queue as a queue where insertion and deletion are based on some priority property. Items with higher priority are removed before lower priority items. There are two main types: ascending priority queues remove the smallest item, while descending priority queues remove the largest item. Priority queues are useful for scheduling jobs in operating systems, where real-time jobs have highest priority and are scheduled first. They are also used in network communication to manage limited bandwidth.
Graph traversal techniques are used to search vertices in a graph and determine the order to visit vertices. There are two main techniques: breadth-first search (BFS) and depth-first search (DFS). BFS uses a queue and visits the nearest vertices first, producing a spanning tree. DFS uses a stack and visits vertices by going as deep as possible first, also producing a spanning tree. Both techniques involve marking visited vertices to avoid loops.
Each node in a doubly linked list contains two pointers - one pointing to the next node and one pointing to the previous node. This allows traversal in both directions through the list. A doubly linked list supports common operations like insertion and deletion at both ends of the list as well as anywhere in the list by updating the relevant pointer fields of the nodes. While requiring more space per node, doubly linked lists allow easy traversal backwards through the list and reversing of the list.
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 different notation styles for representing arithmetic expressions, including infix, prefix, and postfix notations. It provides examples of converting expressions between these notations. Infix notation is the conventional style that humans use, but prefix and postfix notations are better suited for computer parsing. The document also covers parsing expressions, operator precedence, and the steps to convert between infix and prefix and infix and postfix notations.
The document discusses different types of queues, including their definitions, properties, and implementations. It defines a queue as a linear data structure with two ends - one for adding elements and one for removing them, following a FIFO (first-in, first-out) approach. Key points covered include common queue operations like insertion and removal; circular queues which wrap elements around to avoid overflow; priority queues which order elements by priority; and deques which allow additions and removals from both ends.
Quicksort is a divide and conquer sorting algorithm that works by partitioning an array around a pivot value. It then recursively sorts the sub-arrays on each side. The key steps are: 1) Choose a pivot element to split the array into left and right halves, with all elements on the left being less than the pivot and all on the right being greater; 2) Recursively quicksort the left and right halves; 3) Combine the now-sorted left and right halves into a fully sorted array. The example demonstrates quicksorting an array of 6 elements by repeatedly partitioning around a pivot until the entire array is sorted.
The document discusses applications of stacks, including reversing strings and lists, Polish notation for mathematical expressions, converting between infix, prefix and postfix notations, evaluating postfix and prefix expressions, recursion, and the Tower of Hanoi problem. Recursion involves defining a function in terms of itself, with a stopping condition. Stacks can be used to remove recursion by saving local variables at each step.
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.
This document discusses data abstraction and abstract data types (ADTs). It defines an ADT as a collection of data along with a set of operations on that data. An ADT specifies what operations can be performed but not how they are implemented. This allows data structures to be developed independently from solutions and hides implementation details behind the ADT's operations. The document provides examples of list ADTs and an array-based implementation of a list ADT in C++.
LINEAR QUEUE with Diagram and C implementation.
Operations of LINEAR QUEUE
Drawback of LINEAR QUEUE
CIRCULAR QUEUE with Diagram and C implementation
Operations of CIRCULAR QUEUE
PRIORITY QUEUE with Diagram and C implementation
Operations of PRIORITY QUEUE
CASE STUDIES
EXAMPLES
The document discusses different types of queues including linear queue, circular queue, and double ended queue (deque). It provides algorithms for common queue operations like insertion and deletion. For linear and circular queues, insertion adds to the rear and deletion removes from the front. Deque allows insertion and deletion from both front and rear, and there are two types - input restricted allows insertion only at rear, output restricted allows deletion only at front.
A queue is a non-primitive linear data structure that follows the FIFO (first-in, first-out) principle. Elements are added to the rear of the queue and removed from the front. Common operations on a queue include insertion (enqueue) and deletion (dequeue). Queues have many real-world applications like waiting in lines and job scheduling. They can be represented using arrays or linked lists.
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.
Queue is an abstract data structure, somewhat similar to Stacks. Unlike stacks, a queue is open at both its ends. One end is always used to insert data (enqueue) and the other is used to remove data (dequeue). Queue follows First-In-First-Out methodology, i.e., the data item stored first will be accessed first.
A circular queue is a fixed size data structure that follows FIFO (first in, first out) principles. Elements are added to the rear of the queue and removed from the front. When the rear reaches the end, it wraps around to the beginning so the queue space is used efficiently. Common circular queue operations include enqueue to add an element, dequeue to remove an element, and display to output all elements.
This document discusses stacks and their applications. It defines a stack as a Last In First Out (LIFO) data structure where newly added items are placed on top. The core stack operations of PUSH, POP, and PEEK are described. An array implementation of stacks is presented and animations demonstrate push and pop operations. Applications of stacks like checking for balanced braces, converting infix to postfix notation, and postfix calculators are explained with examples. Pseudocode provides an algorithm for infix to postfix conversion using a stack.
OVERVIEW:
Introduction
Definition
Example of Threaded BT.
Types & Structure
One-way .
Double-way.
Structure.
Traversal
Algorithm for Traversal
Traversal Example
Inserting
Algorithm for Inserting
Inserting Example
Comparison With Binary Tree
Advantages and Disadvantages
Why Threaded BT are used?
Conclusion
Reference
Stack is a linear data structure that follows the LIFO (Last In First Out) principle. Elements are inserted and removed from the top of the stack. Stack can be implemented using arrays or linked lists. Common stack operations are push, which adds an element to the top, and pop, which removes an element from the top.
The document discusses converting expressions from infix to postfix notation. In infix notation, operators are between operands. In postfix notation, operators follow operands. The algorithm scans the infix expression left to right, appending operands to the output and handling operators and parentheses by pushing/popping from a stack based on precedence. An example converts the infix expression A * (B + C) - D / E to postfix AB+C*+DE/-.
This document discusses stacks and queues as linear data structures. It defines stacks as last-in, first-out (LIFO) collections where the last item added is the first removed. Queues are first-in, first-out (FIFO) collections where the first item added is the first removed. Common stack and queue operations like push, pop, insert, and remove are presented along with algorithms and examples. Applications of stacks and queues in areas like expression evaluation, string reversal, and scheduling are also covered.
This document discusses priority queues. It defines a priority queue as a queue where insertion and deletion are based on some priority property. Items with higher priority are removed before lower priority items. There are two main types: ascending priority queues remove the smallest item, while descending priority queues remove the largest item. Priority queues are useful for scheduling jobs in operating systems, where real-time jobs have highest priority and are scheduled first. They are also used in network communication to manage limited bandwidth.
Graph traversal techniques are used to search vertices in a graph and determine the order to visit vertices. There are two main techniques: breadth-first search (BFS) and depth-first search (DFS). BFS uses a queue and visits the nearest vertices first, producing a spanning tree. DFS uses a stack and visits vertices by going as deep as possible first, also producing a spanning tree. Both techniques involve marking visited vertices to avoid loops.
Each node in a doubly linked list contains two pointers - one pointing to the next node and one pointing to the previous node. This allows traversal in both directions through the list. A doubly linked list supports common operations like insertion and deletion at both ends of the list as well as anywhere in the list by updating the relevant pointer fields of the nodes. While requiring more space per node, doubly linked lists allow easy traversal backwards through the list and reversing of the list.
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 different notation styles for representing arithmetic expressions, including infix, prefix, and postfix notations. It provides examples of converting expressions between these notations. Infix notation is the conventional style that humans use, but prefix and postfix notations are better suited for computer parsing. The document also covers parsing expressions, operator precedence, and the steps to convert between infix and prefix and infix and postfix notations.
The document discusses different types of queues, including their definitions, properties, and implementations. It defines a queue as a linear data structure with two ends - one for adding elements and one for removing them, following a FIFO (first-in, first-out) approach. Key points covered include common queue operations like insertion and removal; circular queues which wrap elements around to avoid overflow; priority queues which order elements by priority; and deques which allow additions and removals from both ends.
Quicksort is a divide and conquer sorting algorithm that works by partitioning an array around a pivot value. It then recursively sorts the sub-arrays on each side. The key steps are: 1) Choose a pivot element to split the array into left and right halves, with all elements on the left being less than the pivot and all on the right being greater; 2) Recursively quicksort the left and right halves; 3) Combine the now-sorted left and right halves into a fully sorted array. The example demonstrates quicksorting an array of 6 elements by repeatedly partitioning around a pivot until the entire array is sorted.
The document discusses applications of stacks, including reversing strings and lists, Polish notation for mathematical expressions, converting between infix, prefix and postfix notations, evaluating postfix and prefix expressions, recursion, and the Tower of Hanoi problem. Recursion involves defining a function in terms of itself, with a stopping condition. Stacks can be used to remove recursion by saving local variables at each step.
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.
This document discusses data abstraction and abstract data types (ADTs). It defines an ADT as a collection of data along with a set of operations on that data. An ADT specifies what operations can be performed but not how they are implemented. This allows data structures to be developed independently from solutions and hides implementation details behind the ADT's operations. The document provides examples of list ADTs and an array-based implementation of a list ADT in C++.
LINEAR QUEUE with Diagram and C implementation.
Operations of LINEAR QUEUE
Drawback of LINEAR QUEUE
CIRCULAR QUEUE with Diagram and C implementation
Operations of CIRCULAR QUEUE
PRIORITY QUEUE with Diagram and C implementation
Operations of PRIORITY QUEUE
CASE STUDIES
EXAMPLES
The document discusses different types of queues including linear queue, circular queue, and double ended queue (deque). It provides algorithms for common queue operations like insertion and deletion. For linear and circular queues, insertion adds to the rear and deletion removes from the front. Deque allows insertion and deletion from both front and rear, and there are two types - input restricted allows insertion only at rear, output restricted allows deletion only at front.
The document defines and explains queues, including their representation as a FIFO data structure with enqueue and dequeue operations at opposite ends. It covers types of queues like double-ended queues, circular queues, and priority queues. Applications of queues include batch processing, simulation, queueing theory, and computer networks.
A queue is a linear data structure where insertion is done at one end called the rear and deletion is done at the other end called the front. There are different types of queues including simple, circular, deque, and priority queues. A priority queue allows insertion and removal of items from any position based on priority. Common queue operations are insertion, deletion, and examples of queue usage include lines at registers and traffic signals.
The document discusses different types of queues, including simple queues, circular queues, priority queues, and deques. It provides details on how each type of queue is implemented and how elements are inserted and removed. Simple queues use an array and only allow insertion at the rear and removal at the front. Circular queues also use an array but allow wrapping around to the beginning so the queue never fills. Priority queues order elements by priority when inserting and removing. Deques allow insertion and removal from both the front and rear.
An ordered collection of items from which items may be deleted from one end called the front and into which items may be inserted from other end called rear is known as Queue.
It is a linear data structure.
It is called the First In First Out (FIFO) list. Since in queue, the first element will be the first element out.
The power point presentation shows the Implementation of Queue operations using arrays and Linked List. Further, It also demonstrates about Circular queue operations.
This document discusses different types of queues and their applications. It describes queues as linear data structures that follow a first-in, first-out principle. Common queue operations like insertion and deletion are explained. The document also covers array and linked representations of queues, as well as different queue types like circular queues, deques, and priority queues. Real-world and computer science applications of queues are provided.
A queue is a first-in, first-out (FIFO) collection where elements are inserted at the rear and deleted from the front. A circular queue solves the problem of overflow by making the queue circular, so the rear wraps around to the front when full. Operations on a circular queue include insertion, which adds elements to the rear until the queue is full and the rear wraps to the front, and deletion, which removes elements from the front. A priority queue processes elements according to priority, with higher priority elements removed before lower priority ones.
1. A queue is a collection of items that are inserted at one end and removed from the other, following a first-in first-out (FIFO) order. Common queue operations are enqueue to insert and dequeue to remove.
2. Queues can be implemented using arrays or linked lists. Array implementation uses a front and rear pointer to track the first and last elements. Linked list implementation uses front and rear pointers to point to the first and last nodes.
3. A priority queue is like a regular queue but allows extracting elements based on priority rather than strictly FIFO order. Higher priority elements are processed before lower priority ones.
This document discusses stacks and their implementation and use. It begins by defining a stack as a list of elements where insertion and deletion can only occur at one end, called the top. The two basic stack operations are described as push, which inserts an element, and pop, which deletes an element. A stack follows the LIFO (last in, first out) principle. Stacks can be represented using arrays or linked lists. The push and pop operations for each representation are then explained in steps. The document also covers infix, postfix, and prefix notation for arithmetic expressions and provides an algorithm to convert infix to postfix notation using a stack.
The document discusses different types of queues and linked lists. It provides descriptions and examples of:
- FIFO queues and their static and dynamic representations using arrays and linked lists
- Priority queues and their implementations
- Circular queues and their operations
- Linked list types including singly linked, doubly linked, and circular linked lists
- Common operations on each like insertion, deletion, and traversal
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 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.
A stack is a linear data structure that follows the LIFO (Last In First Out) principle. Elements are added and removed from the top of the stack. Common operations on a stack include push to add an element and pop to remove an element. A stack can be implemented using arrays or pointers in static or dynamic ways respectively. Stacks have applications in reversing words, undo operations, and backtracking in algorithms.
- Queues follow a First-In First-Out (FIFO) ordering principle where elements are inserted at the rear and removed from the front.
- Queues can be implemented using arrays or linked lists. Circular queues use arrays to avoid empty space issues.
- Priority queues order elements by priority rather than insertion order, with the highest priority element removed first. They have applications like job scheduling.
Collections in .net technology (2160711)Janki Shah
Collections in .NET Framework.
- What is collections?
- Needs of Collections/ importance of collection
- various most useful classes of collection such as
ArrayList, Hashtable, Stack, Queue, BitArray, SortedList
Gauss Elimination & Gauss Jordan Methods in Numerical & Statistical MethodsJanki Shah
The document discusses methods for solving systems of linear equations. It introduces Gauss elimination and Gauss Jordan methods. Gauss elimination transforms the augmented matrix of the system into row echelon form through elementary row operations, then back-substitutes to solve for the variables. Gauss Jordan additionally transforms the matrix to reduced row echelon form to read solutions directly from the matrix. An example demonstrates applying each method to solve a system of equations.
This document discusses types of network addresses and internet address classes. It contains the following key points:
- There are 32-bit global internet addresses that include network and host identifiers in dotted decimal notation like 192.228.17.57.
- Internet addresses have application, network, and data link layers with examples provided.
- InterNIC is responsible for network layer IP addresses and application layer domain names.
- There are five classes of internet addresses - Classes A, B, and C are available to organizations, while Classes D and E are reserved for special purposes.
- Class A addresses start with 1-126 and allow for 16 million addresses. Class B starts with 128-191 allowing 65
Contents:
1.What is number system?
2.Conversions of number from one radix to another
3.Complements (1's, 2's, 9's, 10's)
4.Binary Arithmetic ( Addition, subtraction, multiplication, division)
Exception Handling in object oriented programming using C++Janki Shah
This document discusses exception handling in C++. It introduces exception handling mechanisms like try-catch-throw, multiple catch, catch-all, and rethrowing exceptions. Try-catch-throw handles exceptions by using a try block to detect and throw exceptions, which are then caught and handled in a catch block. Multiple catch allows one try block to have multiple catch blocks to handle different exception types. Catch-all can catch all exception types with a generic catch. Rethrowing exceptions rethrows the current exception to an outer try-catch block.
Newly poured concrete opposing hot and windy conditions is considerably susceptible to plastic shrinkage cracking. Crack-free concrete structures are essential in ensuring high level of durability and functionality as cracks allow harmful instances or water to penetrate in the concrete resulting in structural damages, e.g. reinforcement corrosion or pressure application on the crack sides due to water freezing effect. Among other factors influencing plastic shrinkage, an important one is the concrete surface humidity evaporation rate. The evaporation rate is currently calculated in practice by using a quite complex Nomograph, a process rather tedious, time consuming and prone to inaccuracies. In response to such limitations, three analytical models for estimating the evaporation rate are developed and evaluated in this paper on the basis of the ACI 305R-10 Nomograph for “Hot Weather Concreting”. In this direction, several methods and techniques are employed including curve fitting via Genetic Algorithm optimization and Artificial Neural Networks techniques. The models are developed and tested upon datasets from two different countries and compared to the results of a previous similar study. The outcomes of this study indicate that such models can effectively re-develop the Nomograph output and estimate the concrete evaporation rate with high accuracy compared to typical curve-fitting statistical models or models from the literature. Among the proposed methods, the optimization via Genetic Algorithms, individually applied at each estimation process step, provides the best fitting result.
AI-Powered Data Management and Governance in RetailIJDKP
Artificial intelligence (AI) is transforming the retail industry’s approach to data management and decisionmaking. This journal explores how AI-powered techniques enhance data governance in retail, ensuring data quality, security, and compliance in an era of big data and real-time analytics. We review the current landscape of AI adoption in retail, underscoring the need for robust data governance frameworks to handle the influx of data and support AI initiatives. Drawing on literature and industry examples, we examine established data governance frameworks and how AI technologies (such as machine learning and automation) are augmenting traditional data management practices. Key applications are identified, including AI-driven data quality improvement, automated metadata management, and intelligent data lineage tracking, illustrating how these innovations streamline operations and maintain data integrity. Ethical considerations including customer privacy, bias mitigation, transparency, and regulatory compliance are discussed to address the challenges of deploying AI in data governance responsibly.
Deepfake Phishing: A New Frontier in Cyber ThreatsRaviKumar256934
n today’s hyper-connected digital world, cybercriminals continue to develop increasingly sophisticated methods of deception. Among these, deepfake phishing represents a chilling evolution—a combination of artificial intelligence and social engineering used to exploit trust and compromise security.
Deepfake technology, once a novelty used in entertainment, has quickly found its way into the toolkit of cybercriminals. It allows for the creation of hyper-realistic synthetic media, including images, audio, and videos. When paired with phishing strategies, deepfakes can become powerful weapons of fraud, impersonation, and manipulation.
This document explores the phenomenon of deepfake phishing, detailing how it works, why it’s dangerous, and how individuals and organizations can defend themselves against this emerging threat.
Welcome to the May 2025 edition of WIPAC Monthly celebrating the 14th anniversary of the WIPAC Group and WIPAC monthly.
In this edition along with the usual news from around the industry we have three great articles for your contemplation
Firstly from Michael Dooley we have a feature article about ammonia ion selective electrodes and their online applications
Secondly we have an article from myself which highlights the increasing amount of wastewater monitoring and asks "what is the overall" strategy or are we installing monitoring for the sake of monitoring
Lastly we have an article on data as a service for resilient utility operations and how it can be used effectively.
Welcome to MIND UP: a special presentation for Cloudvirga, a Stewart Title company. In this session, we’ll explore how you can “mind up” and unlock your potential by using generative AI chatbot tools at work.
Curious about the rise of AI chatbots? Unsure how to use them-or how to use them safely and effectively in your workplace? You’re not alone. This presentation will walk you through the practical benefits of generative AI chatbots, highlight best practices for safe and responsible use, and show how these tools can help boost your productivity, streamline tasks, and enhance your workday.
Whether you’re new to AI or looking to take your skills to the next level, you’ll find actionable insights to help you and your team make the most of these powerful tools-while keeping security, compliance, and employee well-being front and center.
This research presents the optimization techniques for reinforced concrete waffle slab design because the EC2 code cannot provide an efficient and optimum design. Waffle slab is mostly used where there is necessity to avoid column interfering the spaces or for a slab with large span or as an aesthetic purpose. Design optimization has been carried out here with MATLAB, using genetic algorithm. The objective function include the overall cost of reinforcement, concrete and formwork while the variables comprise of the depth of the rib including the topping thickness, rib width, and ribs spacing. The optimization constraints are the minimum and maximum areas of steel, flexural moment capacity, shear capacity and the geometry. The optimized cost and slab dimensions are obtained through genetic algorithm in MATLAB. The optimum steel ratio is 2.2% with minimum slab dimensions. The outcomes indicate that the design of reinforced concrete waffle slabs can be effectively carried out using the optimization process of genetic algorithm.
David Boutry - Specializes In AWS, Microservices And PythonDavid Boutry
With over eight years of experience, David Boutry specializes in AWS, microservices, and Python. As a Senior Software Engineer in New York, he spearheaded initiatives that reduced data processing times by 40%. His prior work in Seattle focused on optimizing e-commerce platforms, leading to a 25% sales increase. David is committed to mentoring junior developers and supporting nonprofit organizations through coding workshops and software development.
Jacob Murphy Australia - Excels In Optimizing Software ApplicationsJacob Murphy Australia
In the world of technology, Jacob Murphy Australia stands out as a Junior Software Engineer with a passion for innovation. Holding a Bachelor of Science in Computer Science from Columbia University, Jacob's forte lies in software engineering and object-oriented programming. As a Freelance Software Engineer, he excels in optimizing software applications to deliver exceptional user experiences and operational efficiency. Jacob thrives in collaborative environments, actively engaging in design and code reviews to ensure top-notch solutions. With a diverse skill set encompassing Java, C++, Python, and Agile methodologies, Jacob is poised to be a valuable asset to any software development team.
OPTIMIZING DATA INTEROPERABILITY IN AGILE ORGANIZATIONS: INTEGRATING NONAKA’S...ijdmsjournal
Agile methodologies have transformed organizational management by prioritizing team autonomy and
iterative learning cycles. However, these approaches often lack structured mechanisms for knowledge
retention and interoperability, leading to fragmented decision-making, information silos, and strategic
misalignment. This study proposes an alternative approach to knowledge management in Agile
environments by integrating Ikujiro Nonaka and Hirotaka Takeuchi’s theory of knowledge creation—
specifically the concept of Ba, a shared space where knowledge is created and validated—with Jürgen
Habermas’s Theory of Communicative Action, which emphasizes deliberation as the foundation for trust
and legitimacy in organizational decision-making. To operationalize this integration, we propose the
Deliberative Permeability Metric (DPM), a diagnostic tool that evaluates knowledge flow and the
deliberative foundation of organizational decisions, and the Communicative Rationality Cycle (CRC), a
structured feedback model that extends the DPM, ensuring long-term adaptability and data governance.
This model was applied at Livelo, a Brazilian loyalty program company, demonstrating that structured
deliberation improves operational efficiency and reduces knowledge fragmentation. The findings indicate
that institutionalizing deliberative processes strengthens knowledge interoperability, fostering a more
resilient and adaptive approach to data governance in complex organizations.
The main purpose of the current study was to formulate an empirical expression for predicting the axial compression capacity and axial strain of concrete-filled plastic tubular specimens (CFPT) using the artificial neural network (ANN). A total of seventy-two experimental test data of CFPT and unconfined concrete were used for training, testing, and validating the ANN models. The ANN axial strength and strain predictions were compared with the experimental data and predictions from several existing strength models for fiber-reinforced polymer (FRP)-confined concrete. Five statistical indices were used to determine the performance of all models considered in the present study. The statistical evaluation showed that the ANN model was more effective and precise than the other models in predicting the compressive strength, with 2.8% AA error, and strain at peak stress, with 6.58% AA error, of concrete-filled plastic tube tested under axial compression load. Similar lower values were obtained for the NRMSE index.
2. Queue
• Queue is Linear Data Structure
• It follows First In First Out(FIFO) principal
• It has two pointers front and rear
e.g.:
10 20 30 40 50
A[0] A[1] A[2] A[3] A[4]
Insertion
(ENQUEUE)
Deletion
(DEQUEUE)
3. Operations on Queue
Insertion:
Algorithm:
Step 1: If REAR = MAX – 1 then
Write “Queue is Overflow”
Goto step 4
[End of IF]
Step 2: IF FRONT=-1 and REAR=-1
SET FRONT=REAR=0
ELSE
SET REAR=REAR+1
[END OF IF]
Step 3: SET QUEUE [REAR] = NUM
Step 4: EXIT
4. Example of Insertion in Queue
A[0] A[1] A[2] A[3] A[4]
F=R=(-1)
10
A[0] A[1] A[2] A[3] A[4]
F=R=0
10 20
F=0 R=1
A[0] A[1] A[2] A[3] A[4]
9. Why Circular Queue is needed?
• Problem:
– Wastage of memory in standard queue in DEQUEUE
operation
10. What is Circular Queue?
• The Arrangement of the elements Q[0], Q[1],
...,Q[n] in a circular fashion with Q[1]
following Q[n] is called Circular Queue.
• The last node is connected to first node to
make a circle.
• Initially, Both Front and Rear pointers points
to the beginning of the array.
• It is also known as “Ring Buffer”.
12. Operations on Circular Queue
Insertion:
Algorithm:
Step 1: IF FRONT=0 and REAR=MAX-1 Then
Write “Overflow”
Goto Step 4
[END OF IF]
Step 2: IF FRONT = REAR=-1 then
SET FRONT=REAR=0
ELSE IF REAR=MAX-1 and FRONT!=0
SET REAR=0
ELSE
SET REAR=REAR+1
[END OF IF]
Step 3: SET QUEUE[REAR]=VAL
Step 4: EXIT
17. Operations on Circular Queue
Deletion:
Algorithm:
Step 1: If FRONT = -1 then
Write ("Circular Queue Underflow“)
GOTO Step 4
Step 2: SET VAL=QUEUE[FRONT]
Step 3: If FRONT = REAR then
SET FRONT=REAR=-1
ELSE
IF FRONT=MAX-1
SET FRONT=0
ELSE
SET FRONT=FRONT+1
[END OF IF]
[END OF IF]
Step 4: EXIT
23. Priority Queue
• In priority queue, each element is assigned a
priority.
• Priority of an element determines the order in
which the elements will be processed.
• Rules:
1. An element with higher priority will processed
before an element with a lower priority.
2. Two elements with the same priority are
processed on a First Come First Serve basis.
24. Types of Priority Queue
1. Ascending Priority Queue
In this type of priority queue, elements can be
inserted into any order but only the smallest
element can be removed.
2. Descending Priority Queue
In this type of priority queue, elements can be
inserted into any order but only the largest element
can be removed.
25. Array Representation of Priority Queue
Insertion Operation:
• While inserting elements in priority queue we
will add it at the appropriate position
depending on its priority
• It is inserted in such a way that the elements
are always ordered either in Ascending or
descending sequence
26. Array Representation of Priority Queue
15 10
20 15 10
25 15 13 10
A[0] A[1] A[2] A[3] A[4]
Front Rear
A[0] A[1] A[2] A[3] A[4]
Front Rear
A[0] A[1] A[2] A[3] A[4]
Front Rear
27. Array Representation of Priority Queue
Deletion Operation:
• While deletion, the element at the front is
always deleted.
28. Array Representation of Priority Queue
20 15 13 10
15 13 10
13 10
A[0] A[1] A[2] A[3] A[4]
Front Rear
A[0] A[1] A[2] A[3] A[4]
Front Rear
A[0] A[1] A[2] A[3] A[4]
Front Rear
30. Deque / Double Ended Queue
• A list in which elements can be inserted or
deleted either end
• It is also known as “Head-Tail Linked List”
• It has two pointers LEFT and RIGHT, which
point to either end of the deque.
• Dequeue can be implemented using Circular
Array or a Circular doubly linked list where
Dequeue[n-1] is followed by Dequeue[0]
31. Types of Deque
• Input Restricted Deque:-
In this dequeue, insertion can be done only at one of
the end, while deletion can be done from both ends.
• Output Restricted Deque:-
In this dequeue, deletion can be done only at
one of the ends, while insertions can be done
on both ends