Singly linked lists allow for efficient insertion and deletion of elements without shifting other elements. They have dynamic size and use less memory than arrays if the list is sparsely populated. However, random access is not efficient as elements are not stored contiguously in memory. Common operations like search, insertion, and deletion have O(n) time complexity due to the need to traverse the list sequentially. Space complexity is O(n) to store the elements and references between nodes.
singly link list project in dsa.....by rohit malavRohit malav
Singly Linked Lists are a type of data structure. In a singly linked list, each node in the list stores the contents and a pointer or reference to the next node in the list. It does not store any pointer or reference to the previous node. ... The last node in a single linked list points to nothing.
The document discusses data structures and algorithms. It begins by defining data structures as organized data and allowed operations. It then discusses arrays, linked lists, binary trees, and their implementations. Arrays allow fast access but fixed size, while linked lists and trees can grow dynamically but have slower access. Binary tree operations like search, insert, and delete have logarithmic time complexity due to the tree height being logarithmic in the number of nodes. The document provides examples of various data structure implementations and traversals.
This document discusses different data structures. It begins by defining a data structure as an organization of data in different ways. It then classifies common data structures as arrays, linked lists, stacks, queues, trees and graphs. It provides definitions and examples of algorithms, arrays, and linked lists. It also includes algorithms for operations on arrays and linked lists like insertion, deletion and traversal. Finally, it discusses implementation of singly and doubly linked lists as stacks and deletion operations in linked lists.
The document discusses different data structures and their implementations and applications. It covers arrays, linked lists, stacks, queues, binary trees, and binary search. The key points are:
- Arrays allow fast access but have fixed size; linked lists can grow dynamically but access is slower.
- Binary trees allow fast (O(log n)) search, insertion, and deletion operations due to their hierarchical structure.
- Stacks and queues are useful for modeling LIFO and FIFO data access with applications like function calls and job scheduling.
- Binary search runs in O(log n) time by recursively dividing the search space for sorted data.
Revisiting a data structures in detail with linked list stack and queuessuser7319f8
This document discusses various data structures including arrays, stacks, queues, and linked lists. It provides code examples for creating and manipulating each type of data structure. Specifically, it shows code for inserting and deleting elements from arrays and linked lists. It also includes algorithms and code for common stack and queue operations like push, pop, enqueue, and dequeue. The document provides a detailed overview of linear and non-linear data structures.
This document discusses linked lists and their implementation in C. It defines linked lists as dynamic data structures where each node contains a data field and a pointer to the next node. The document covers representing linked lists in C using self-referential structures, creating and connecting nodes, and various types of linked lists. It also summarizes common linked list operations like traversal, insertion, and deletion at different positions through algorithms and code examples.
The document discusses linked lists and their implementation. It begins by listing the objectives, which are to describe linked lists, how they can be implemented using linked structures, and how to implement various operations on linked lists. It then defines linked lists and describes how they can be implemented using either arrays or linked structures. The rest of the document discusses implementing linked lists using linked nodes, representing them in memory, and how to perform common operations like traversing, searching, inserting and deleting elements from the linked list.
The document discusses lists and linked lists. It begins by describing lists and their implementations using arrays and linked lists. It then focuses on linked list implementations, describing linear linked lists and their representation, operations like traversal, search, insert, and delete. Doubly linked lists are also covered, along with their representation and similar operations. The document provides detailed code examples for many of the linked list operations.
singly link list project in dsa.....by rohit malavRohit malav
Singly Linked Lists are a type of data structure. In a singly linked list, each node in the list stores the contents and a pointer or reference to the next node in the list. It does not store any pointer or reference to the previous node. ... The last node in a single linked list points to nothing.
The document discusses data structures and algorithms. It begins by defining data structures as organized data and allowed operations. It then discusses arrays, linked lists, binary trees, and their implementations. Arrays allow fast access but fixed size, while linked lists and trees can grow dynamically but have slower access. Binary tree operations like search, insert, and delete have logarithmic time complexity due to the tree height being logarithmic in the number of nodes. The document provides examples of various data structure implementations and traversals.
This document discusses different data structures. It begins by defining a data structure as an organization of data in different ways. It then classifies common data structures as arrays, linked lists, stacks, queues, trees and graphs. It provides definitions and examples of algorithms, arrays, and linked lists. It also includes algorithms for operations on arrays and linked lists like insertion, deletion and traversal. Finally, it discusses implementation of singly and doubly linked lists as stacks and deletion operations in linked lists.
The document discusses different data structures and their implementations and applications. It covers arrays, linked lists, stacks, queues, binary trees, and binary search. The key points are:
- Arrays allow fast access but have fixed size; linked lists can grow dynamically but access is slower.
- Binary trees allow fast (O(log n)) search, insertion, and deletion operations due to their hierarchical structure.
- Stacks and queues are useful for modeling LIFO and FIFO data access with applications like function calls and job scheduling.
- Binary search runs in O(log n) time by recursively dividing the search space for sorted data.
Revisiting a data structures in detail with linked list stack and queuessuser7319f8
This document discusses various data structures including arrays, stacks, queues, and linked lists. It provides code examples for creating and manipulating each type of data structure. Specifically, it shows code for inserting and deleting elements from arrays and linked lists. It also includes algorithms and code for common stack and queue operations like push, pop, enqueue, and dequeue. The document provides a detailed overview of linear and non-linear data structures.
This document discusses linked lists and their implementation in C. It defines linked lists as dynamic data structures where each node contains a data field and a pointer to the next node. The document covers representing linked lists in C using self-referential structures, creating and connecting nodes, and various types of linked lists. It also summarizes common linked list operations like traversal, insertion, and deletion at different positions through algorithms and code examples.
The document discusses linked lists and their implementation. It begins by listing the objectives, which are to describe linked lists, how they can be implemented using linked structures, and how to implement various operations on linked lists. It then defines linked lists and describes how they can be implemented using either arrays or linked structures. The rest of the document discusses implementing linked lists using linked nodes, representing them in memory, and how to perform common operations like traversing, searching, inserting and deleting elements from the linked list.
The document discusses lists and linked lists. It begins by describing lists and their implementations using arrays and linked lists. It then focuses on linked list implementations, describing linear linked lists and their representation, operations like traversal, search, insert, and delete. Doubly linked lists are also covered, along with their representation and similar operations. The document provides detailed code examples for many of the linked list operations.
The document discusses lists and linked lists. It begins by defining a list as a homogeneous collection of elements with a linear relationship between elements that can be ordered or unordered. Lists can be implemented using arrays or linked lists. The document then discusses implementing lists using arrays and linked lists. It covers linked list definitions, representations, and common operations like traversing, searching, inserting and deleting elements. It also discusses different types of linked lists like linear linked lists, doubly linked lists, and their implementations.
The document discusses lists and linked lists. It begins by defining a list as a homogeneous collection of elements with a linear relationship between elements that can be ordered or unordered. Lists can be implemented using arrays or linked lists. The document then discusses implementing lists using arrays and linked lists. It covers linked list definitions, representations, and common operations like traversing, searching, inserting and deleting elements. It also discusses different types of linked lists like linear linked lists, doubly linked lists, and their implementations.
The document discusses lists and linked lists. It begins by describing lists and their implementations using arrays and linked lists. It then focuses on linked list implementations, describing linear linked lists and their representation, operations like traversal, search, insert, and delete. It also covers doubly linked lists, their representation, and similar common operations. The document provides detailed code examples for many of the linked list operations.
The document discusses lists and linked lists. It begins by defining a list as a homogeneous collection of elements with a linear relationship between elements that can be ordered or unordered. Lists can be implemented using arrays or linked lists. The document then discusses implementing lists using arrays and linked lists. It covers linked list definitions, representations, and common operations like traversing, searching, inserting and deleting elements. It also discusses different types of linked lists like linear linked lists, doubly linked lists, and their implementations.
The document discusses linked lists and their implementation. It begins by listing the objectives, which are to describe linked lists, how they can be implemented using linked structures, and how to implement various operations on linked lists. It then defines linked lists and describes how they can be implemented using either arrays or linked structures. The rest of the document discusses implementing linked lists using linked nodes, representing them in memory, and how to perform common operations like traversing, searching, inserting and deleting elements from the linked list.
we are innovative,we are different,we are genius so they call us idiots
Visit us for movies,videos,documentaries,sports,funny pics and many more join www.globalidiots.com
Linked list and its operations - Traversalkasthurimukila
The document discusses linked lists and operations performed on singly linked lists. It defines a linked list as a data structure containing nodes that point to the next node in the list. Singly linked lists contain nodes with a data field and pointer to the next node. Common operations on singly linked lists include traversing the list, inserting and deleting nodes from different positions, searching for a node, sorting list elements, and merging two linked lists.
Data structures and Algorithm analysis_Lecture 2.pptxAhmedEldesoky24
This document discusses different data structures for lists, including abstract data types (ADTs), arrays, singly linked lists, and doubly linked lists. It describes common list operations like insert, remove, find, and their time complexities for each implementation. Array-based lists allow direct access but expensive updates. Linked lists have efficient insertion/deletion but slow random access. Doubly linked lists and circular lists add previous pointers for easier traversal in both directions.
A linked list is a data structure where each node contains a data field and a reference to the next node. The head node points to the first node, and nodes are connected through next references. Linked lists allow for efficient insertions and deletions compared to arrays. Common types include singly linked, doubly linked, circular singly linked, and circular doubly linked lists. Operations on linked lists include insertion, deletion, and searching.
This document discusses linked lists and representing stacks and queues using linked lists. It provides information on different types of linked lists including singly, doubly, and circular linked lists. It describes inserting, deleting, and traversing nodes in a singly linked list. It also provides a C program example to implement a stack using a linked list with functions for push, pop, and display operations. The document discusses how linked lists are dynamic data structures that can grow and shrink in size as needed, unlike arrays.
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 different types of linked lists including singly linked lists, circular linked lists, and doubly linked lists. It provides details on representing stacks and queues using linked lists. Key advantages of linked lists over arrays are that linked lists can dynamically grow in size as needed, elements can be inserted and deleted without shifting other elements, and there is no memory wastage. Operations like insertion, deletion, traversal, and searching are described for singly linked lists along with sample C code to implement a linked list, stack, and queue.
The document outlines the key concepts of linked lists including:
- Linked lists allow for dynamic resizing and efficient insertion/deletion unlike arrays.
- A linked list contains nodes that have a data field and a pointer to the next node.
- Common operations on linked lists include insertion, deletion, searching, and traversing the list.
- The time complexity of these operations depends on whether it's at the head, tail, or interior node.
- Linked lists can be implemented using classes for the node and linked list objects.
The document discusses linked lists and their advantages over arrays. It begins with an overview of arrays and their pros and cons, then introduces linked lists as an alternative that overcomes some of the limitations of arrays. Key points covered include:
- Linked lists store elements in separate blocks of memory connected via pointers, unlike arrays which use a single block.
- This allows linked lists to dynamically allocate memory as needed, rather than having a fixed size like arrays.
- Common linked list operations like inserting and deleting nodes are described, including handling different cases like empty lists.
- Functions for traversing the list, printing elements, copying lists, and deleting nodes are presented.
This document discusses arrays and linked lists. It provides information on:
- What arrays and linked lists are and how they are used to store data in memory. Arrays use indexes to access data while linked lists use nodes connected through pointers.
- Common operations for each including insertion, deletion, and searching. For arrays this includes shifting elements, while for linked lists it involves manipulating the pointers between nodes.
- Specific implementation details for single linked lists, including defining node structures and performing operations at different points in the list.
This document provides an overview of different data structures and sorting algorithms. It begins with an introduction to data structures and describes linear data structures like arrays, stacks, queues, and linked lists as well as non-linear data structures like trees and graphs. It then provides more detailed descriptions of stacks, queues, linked lists, and common sorting algorithms like selection sort and bubble sort.
The document discusses linked lists as an alternative to arrays for storing data. It provides 3 key points:
1. Linked lists store data in nodes that are linked together using pointers, rather than in a fixed contiguous block of memory like arrays. Each node contains a data field and a pointer to the next node.
2. Common linked list operations like insertion, deletion, and searching have time complexities of O(1) or O(n) depending on the position in the list, which can be more efficient than arrays that require shifting elements.
3. The document presents a simple C++ implementation of a linked list using Node and List classes to demonstrate how to implement basic linked list functions like insertion, deletion
The document discusses three basic data structures - lists, stacks, and queues. It describes lists and their operations like printing, finding elements, inserting, and removing elements. Lists can be implemented using arrays or linked lists. Linked lists allow constant-time insertion and removal by linking nodes through next pointers. The document also provides code for initializing, inserting, and removing elements from a doubly linked list.
The document discusses data structures and abstract data types (ADTs). It provides examples of linear lists and linked lists as implementations of the ADT linear list. Key points made include:
- An ADT defines operations on a data structure without specifying its implementation.
- Linked lists provide flexibility for insertion and deletion compared to arrays.
- The main linked list operations are insertion, deletion, finding an element, and traversal.
- Queues and stacks are examples of linear lists with restricted insertion/deletion points.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
The document discusses lists and linked lists. It begins by defining a list as a homogeneous collection of elements with a linear relationship between elements that can be ordered or unordered. Lists can be implemented using arrays or linked lists. The document then discusses implementing lists using arrays and linked lists. It covers linked list definitions, representations, and common operations like traversing, searching, inserting and deleting elements. It also discusses different types of linked lists like linear linked lists, doubly linked lists, and their implementations.
The document discusses lists and linked lists. It begins by defining a list as a homogeneous collection of elements with a linear relationship between elements that can be ordered or unordered. Lists can be implemented using arrays or linked lists. The document then discusses implementing lists using arrays and linked lists. It covers linked list definitions, representations, and common operations like traversing, searching, inserting and deleting elements. It also discusses different types of linked lists like linear linked lists, doubly linked lists, and their implementations.
The document discusses lists and linked lists. It begins by describing lists and their implementations using arrays and linked lists. It then focuses on linked list implementations, describing linear linked lists and their representation, operations like traversal, search, insert, and delete. It also covers doubly linked lists, their representation, and similar common operations. The document provides detailed code examples for many of the linked list operations.
The document discusses lists and linked lists. It begins by defining a list as a homogeneous collection of elements with a linear relationship between elements that can be ordered or unordered. Lists can be implemented using arrays or linked lists. The document then discusses implementing lists using arrays and linked lists. It covers linked list definitions, representations, and common operations like traversing, searching, inserting and deleting elements. It also discusses different types of linked lists like linear linked lists, doubly linked lists, and their implementations.
The document discusses linked lists and their implementation. It begins by listing the objectives, which are to describe linked lists, how they can be implemented using linked structures, and how to implement various operations on linked lists. It then defines linked lists and describes how they can be implemented using either arrays or linked structures. The rest of the document discusses implementing linked lists using linked nodes, representing them in memory, and how to perform common operations like traversing, searching, inserting and deleting elements from the linked list.
we are innovative,we are different,we are genius so they call us idiots
Visit us for movies,videos,documentaries,sports,funny pics and many more join www.globalidiots.com
Linked list and its operations - Traversalkasthurimukila
The document discusses linked lists and operations performed on singly linked lists. It defines a linked list as a data structure containing nodes that point to the next node in the list. Singly linked lists contain nodes with a data field and pointer to the next node. Common operations on singly linked lists include traversing the list, inserting and deleting nodes from different positions, searching for a node, sorting list elements, and merging two linked lists.
Data structures and Algorithm analysis_Lecture 2.pptxAhmedEldesoky24
This document discusses different data structures for lists, including abstract data types (ADTs), arrays, singly linked lists, and doubly linked lists. It describes common list operations like insert, remove, find, and their time complexities for each implementation. Array-based lists allow direct access but expensive updates. Linked lists have efficient insertion/deletion but slow random access. Doubly linked lists and circular lists add previous pointers for easier traversal in both directions.
A linked list is a data structure where each node contains a data field and a reference to the next node. The head node points to the first node, and nodes are connected through next references. Linked lists allow for efficient insertions and deletions compared to arrays. Common types include singly linked, doubly linked, circular singly linked, and circular doubly linked lists. Operations on linked lists include insertion, deletion, and searching.
This document discusses linked lists and representing stacks and queues using linked lists. It provides information on different types of linked lists including singly, doubly, and circular linked lists. It describes inserting, deleting, and traversing nodes in a singly linked list. It also provides a C program example to implement a stack using a linked list with functions for push, pop, and display operations. The document discusses how linked lists are dynamic data structures that can grow and shrink in size as needed, unlike arrays.
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 different types of linked lists including singly linked lists, circular linked lists, and doubly linked lists. It provides details on representing stacks and queues using linked lists. Key advantages of linked lists over arrays are that linked lists can dynamically grow in size as needed, elements can be inserted and deleted without shifting other elements, and there is no memory wastage. Operations like insertion, deletion, traversal, and searching are described for singly linked lists along with sample C code to implement a linked list, stack, and queue.
The document outlines the key concepts of linked lists including:
- Linked lists allow for dynamic resizing and efficient insertion/deletion unlike arrays.
- A linked list contains nodes that have a data field and a pointer to the next node.
- Common operations on linked lists include insertion, deletion, searching, and traversing the list.
- The time complexity of these operations depends on whether it's at the head, tail, or interior node.
- Linked lists can be implemented using classes for the node and linked list objects.
The document discusses linked lists and their advantages over arrays. It begins with an overview of arrays and their pros and cons, then introduces linked lists as an alternative that overcomes some of the limitations of arrays. Key points covered include:
- Linked lists store elements in separate blocks of memory connected via pointers, unlike arrays which use a single block.
- This allows linked lists to dynamically allocate memory as needed, rather than having a fixed size like arrays.
- Common linked list operations like inserting and deleting nodes are described, including handling different cases like empty lists.
- Functions for traversing the list, printing elements, copying lists, and deleting nodes are presented.
This document discusses arrays and linked lists. It provides information on:
- What arrays and linked lists are and how they are used to store data in memory. Arrays use indexes to access data while linked lists use nodes connected through pointers.
- Common operations for each including insertion, deletion, and searching. For arrays this includes shifting elements, while for linked lists it involves manipulating the pointers between nodes.
- Specific implementation details for single linked lists, including defining node structures and performing operations at different points in the list.
This document provides an overview of different data structures and sorting algorithms. It begins with an introduction to data structures and describes linear data structures like arrays, stacks, queues, and linked lists as well as non-linear data structures like trees and graphs. It then provides more detailed descriptions of stacks, queues, linked lists, and common sorting algorithms like selection sort and bubble sort.
The document discusses linked lists as an alternative to arrays for storing data. It provides 3 key points:
1. Linked lists store data in nodes that are linked together using pointers, rather than in a fixed contiguous block of memory like arrays. Each node contains a data field and a pointer to the next node.
2. Common linked list operations like insertion, deletion, and searching have time complexities of O(1) or O(n) depending on the position in the list, which can be more efficient than arrays that require shifting elements.
3. The document presents a simple C++ implementation of a linked list using Node and List classes to demonstrate how to implement basic linked list functions like insertion, deletion
The document discusses three basic data structures - lists, stacks, and queues. It describes lists and their operations like printing, finding elements, inserting, and removing elements. Lists can be implemented using arrays or linked lists. Linked lists allow constant-time insertion and removal by linking nodes through next pointers. The document also provides code for initializing, inserting, and removing elements from a doubly linked list.
The document discusses data structures and abstract data types (ADTs). It provides examples of linear lists and linked lists as implementations of the ADT linear list. Key points made include:
- An ADT defines operations on a data structure without specifying its implementation.
- Linked lists provide flexibility for insertion and deletion compared to arrays.
- The main linked list operations are insertion, deletion, finding an element, and traversal.
- Queues and stacks are examples of linear lists with restricted insertion/deletion points.
A SYSTEMATIC RISK ASSESSMENT APPROACH FOR SECURING THE SMART IRRIGATION SYSTEMSIJNSA Journal
The smart irrigation system represents an innovative approach to optimize water usage in agricultural and landscaping practices. The integration of cutting-edge technologies, including sensors, actuators, and data analysis, empowers this system to provide accurate monitoring and control of irrigation processes by leveraging real-time environmental conditions. The main objective of a smart irrigation system is to optimize water efficiency, minimize expenses, and foster the adoption of sustainable water management methods. This paper conducts a systematic risk assessment by exploring the key components/assets and their functionalities in the smart irrigation system. The crucial role of sensors in gathering data on soil moisture, weather patterns, and plant well-being is emphasized in this system. These sensors enable intelligent decision-making in irrigation scheduling and water distribution, leading to enhanced water efficiency and sustainable water management practices. Actuators enable automated control of irrigation devices, ensuring precise and targeted water delivery to plants. Additionally, the paper addresses the potential threat and vulnerabilities associated with smart irrigation systems. It discusses limitations of the system, such as power constraints and computational capabilities, and calculates the potential security risks. The paper suggests possible risk treatment methods for effective secure system operation. In conclusion, the paper emphasizes the significant benefits of implementing smart irrigation systems, including improved water conservation, increased crop yield, and reduced environmental impact. Additionally, based on the security analysis conducted, the paper recommends the implementation of countermeasures and security approaches to address vulnerabilities and ensure the integrity and reliability of the system. By incorporating these measures, smart irrigation technology can revolutionize water management practices in agriculture, promoting sustainability, resource efficiency, and safeguarding against potential security threats.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
Redefining brain tumor segmentation: a cutting-edge convolutional neural netw...IJECEIAES
Medical image analysis has witnessed significant advancements with deep learning techniques. In the domain of brain tumor segmentation, the ability to
precisely delineate tumor boundaries from magnetic resonance imaging (MRI)
scans holds profound implications for diagnosis. This study presents an ensemble convolutional neural network (CNN) with transfer learning, integrating
the state-of-the-art Deeplabv3+ architecture with the ResNet18 backbone. The
model is rigorously trained and evaluated, exhibiting remarkable performance
metrics, including an impressive global accuracy of 99.286%, a high-class accuracy of 82.191%, a mean intersection over union (IoU) of 79.900%, a weighted
IoU of 98.620%, and a Boundary F1 (BF) score of 83.303%. Notably, a detailed comparative analysis with existing methods showcases the superiority of
our proposed model. These findings underscore the model’s competence in precise brain tumor localization, underscoring its potential to revolutionize medical
image analysis and enhance healthcare outcomes. This research paves the way
for future exploration and optimization of advanced CNN models in medical
imaging, emphasizing addressing false positives and resource efficiency.
A review on techniques and modelling methodologies used for checking electrom...nooriasukmaningtyas
The proper function of the integrated circuit (IC) in an inhibiting electromagnetic environment has always been a serious concern throughout the decades of revolution in the world of electronics, from disjunct devices to today’s integrated circuit technology, where billions of transistors are combined on a single chip. The automotive industry and smart vehicles in particular, are confronting design issues such as being prone to electromagnetic interference (EMI). Electronic control devices calculate incorrect outputs because of EMI and sensors give misleading values which can prove fatal in case of automotives. In this paper, the authors have non exhaustively tried to review research work concerned with the investigation of EMI in ICs and prediction of this EMI using various modelling methodologies and measurement setups.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
Electric vehicle and photovoltaic advanced roles in enhancing the financial p...IJECEIAES
Climate change's impact on the planet forced the United Nations and governments to promote green energies and electric transportation. The deployments of photovoltaic (PV) and electric vehicle (EV) systems gained stronger momentum due to their numerous advantages over fossil fuel types. The advantages go beyond sustainability to reach financial support and stability. The work in this paper introduces the hybrid system between PV and EV to support industrial and commercial plants. This paper covers the theoretical framework of the proposed hybrid system including the required equation to complete the cost analysis when PV and EV are present. In addition, the proposed design diagram which sets the priorities and requirements of the system is presented. The proposed approach allows setup to advance their power stability, especially during power outages. The presented information supports researchers and plant owners to complete the necessary analysis while promoting the deployment of clean energy. The result of a case study that represents a dairy milk farmer supports the theoretical works and highlights its advanced benefits to existing plants. The short return on investment of the proposed approach supports the paper's novelty approach for the sustainable electrical system. In addition, the proposed system allows for an isolated power setup without the need for a transmission line which enhances the safety of the electrical network
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
1. 1
Singly Linked Lists
• What is a singly-linked list?
• Why linked lists?
• Singly-linked lists vs. 1D-arrays
• Representation
• Space Analysis
• Creation, Append and Prepend
• Traversal
• Search
• Insertion after and before an element
• Deletion
• Time Complexity: Singly-linked lists vs. 1D-arrays
2. 2
What is a Singly-linked list?
• A singly linked list is a dynamic data structure consisting of a
sequence of nodes, forming a linear ordering.
• Each node stores:
– Element (data object)
– Reference (i.e., address) to the next node
Node:
Singly-linked list:
3. 3
Why linked lists?
• Linked lists are used to implement many important data structures
such as stacks, queues, graphs, hash tables, etc.
• Linked lists are used as components of some data structures.
Examples: B+ trees, skip lists, etc.
• LISP An important programming language in artificial intelligence
makes extensive use of linked lists in performing symbolic
processing.
• Memory management: An important role of operating systems. An
operating system must decide how to allocate and reclaim storage
for processes running on the system. A linked list can be used to
keep track of portions of memory that are available for allocation.
• Scrolled lists, components found in graphical user interfaces, can be
implemented using linked lists.
4. 4
Singly-linked lists vs. 1D-arrays
ID-array Singly-linked list
Fixed size: Resizing is expensive Dynamic size
Insertions and Deletions are inefficient:
Elements are usually shifted
Insertions and Deletions are efficient: No
shifting
Random access i.e., efficient indexing No random access
Not suitable for operations requiring
accessing elements by index such as sorting
No memory waste if the array is full or almost
full; otherwise may result in much memory
waste.
Extra storage needed for references; however
uses exactly as much memory as it needs
Sequential access is faster because of greater
locality of references [Reason: Elements in
contiguous memory locations]
Sequential access is slow because of low locality
of references [Reason: Elements not in
contiguous memory locations]
5. 5
Representation
• We are using a representation in which a linked list has both head
and tail references:
public class MyLinkedList{
protected Element head;
protected Element tail;
public final class Element{
Object data;
Element next;
Element(Object obj, Element element){
data = obj;
next = element;
}
public Object getData(){return data;}
public Element getNext(){return next;}
}
// . . .
}
6. 6
Representation: Space Analysis
• Assume:
– There are n nodes in the list
– All data references are null
• Number of references in the list and space required:
Required space
Total
Reference
SizeOfSinglyLinkedListElementReference
1
head
SizeOfSinglyLinkedListElementReference
1
tail
n*SizeOfSinglyLinkedListElementReference
n
next
n*SizeOfObjectReference
n
data
• Total space = (n + 2)*SizeOfSinglyLinkedListElementReference
+ n*SizeOfObjectReference
• Hence space complexity is O(n)
7. 7
List Creation
• An empty list is created as follows:
• Once created, elements can be inserted into the list using either the
append or prepend methods:
• Also if we have a reference to a node (an element), we can use the
insertAfter or InsertBefore methods of the Element class
MyLinkedList list = new MyLinkedList();
for (int k = 0; k < 10; k++)
list.append(new Integer(k));
8. 8
public void append(Object obj){
Element element = new Element(obj, null);
if(head == null)
head = element;
else
tail.next = element;
tail = element;
}
Insertion at the end (Append)
Complexity is O(1)
9. 9
public void prepend(Object obj) {
Element element = new Element(obj, head);
if(head == null)
tail = element;
head = element;
}
Insertion at the beginning (Prepend)
Complexity is O(1)
10. 10
Traversal
Begin at the first node, then follow each next reference until the
traversal condition is satisfied or until you come to the end.
To move an Element reference e from one node to the next use:
Example: Count the number of nodes in a linked list.
public int countNodes(){
int count = 0;
Element e = head;
while(e != null){
count++;
e = e.next;
}
return count;
}
e = e.next;
Complexity is O(n)
11. 11
Searching
• To search for an element, we traverse from head until we locate the object or
we reach the end of the list.
• Example: Count the number of nodes with data field equal to a given object.
public int countNodes(Object obj){
int count = 0;
Element e = head;
while(e != null){
if(e.data.equals(obj))
count++;
e = e.next;
}
return count;
}
Complexity is ….
• The following reference relationships are useful in searching:
e.next e.next.next e.next.next.next
e.next.data e.next.next.data
e
e.data
However, it is important to ensure that next is not null in such expressions
12. 12
Insertion after an element
• To insert an object y after a node x:
• Move a reference e from the beginning of the list to node x:
Element e = head;
if(e == null) throw new IllegalArgumentException(“not found”);
while(e != null && !e.data.equals(x)){
e = e.next;
}
if(e == null) throw new IllegalArgumentException(“not found”);
• Create a new node containing y as data and let its next reference refer to the
node after node x:
Element element = new Element(y, e.next);
• Make the next reference of node x refer to node y:
e.next = element;
• If the new node was inserted at the end of the list, update the tail reference:
if(element.next == null) tail = element;
e
e.next
x
e
e.next
x
y
element
e
e.next
x
y
element
13. 13
Insertion after an element
Complexity is
public void insertAfter(Object obj) {
// create a new node for obj2 and make it refer to the node
// after obj1 node
Element element = new Element(obj, this.next);
// make obj1 node refer to the new node
this.next = element;
// update tail if the new node was inserted at the end
if(this == tail)
tail = next;
}
Complexity is O(1)
O(n)
• The insertAfter method of the Element class is invoked as:
MyLinkedList.Element e = list.find(obj1);
if(e != null)
e.insertAfter(obj2); // insert obj2 after obj1
else
System.out.println("Element to insert before not found");
• Within the insertAfter method this refers to obj1 node:
• Note: The total complexity of the insert after operation is O(n) because find is O(n)
14. 14
Insertion before an element
• To insert an object y before a node x:
• Move a reference previous from the beginning of the list to the node before
node x:
Element e = head, previous;
if(e == null) throw new IllegalArgumentException(“not found”);
while(e != null && ! e.data.equals(x)){
previous = e;
e = e.next;
}
if(e == null) throw new IllegalArgumentException(“not found”);
• Create a new node containing y as data and let its next reference refer to the
node x:
Element element = new Element(y, e);
• Make the next reference of the node before node x refer to node y:
if(e == head)
head = element;
else
previous.next = element;
e
x
previous
y
element
e
x
previous
y
element
e
x
previous
15. 15
Insertion before an element
public void insertBefore(Object obj) {
// create a new node for obj2, make this node point to obj1 node
Element element = new Element(obj, this);
if(this == head){
head = element;
return;
}
Element previous = head;
// move previous to node before obj1 node
while(previous.next != this) {
previous = previous.next;
}
previous.next = element; // insert
}
Complexity is
MyLinkedList.Element e = list.find(obj1);
if(e != null)
e.insertBefore(obj2); // insert obj2 before obj1
else
System.out.println("Element to insert before not found");
• The insertBefore method of the Element class is invoked as:
• Within the insertBefore method this refers to obj1 node:
Complexity is O(n)
O(n)
16. 16
Deletion
• To delete a node x:
• Move a reference previous from the beginning of the list to the node before
node x:
Element e = head, previous;
if(e == null) throw new IllegalArgumentException(“not found”);
while(e != null && ! e.data.equals(x)){
previous = e;
e = e.next;
}
if(e == null) throw new IllegalArgumentException(“not found”);
• Bypass the node to be deleted:
if(e == head){
if(head.next == null)
head = tail = e = null;
else{
head = head.next;
}
else{
previous.next = e.next;
if(tail == e)
tail = previous;
}
e = null;
e
x
previous
e
x
previous
17. 17
Deletion – Deleting First and Last Element
public void extractFirst() {
if(head == null)
throw new IllegalArgumentException("item not found");
head = head.next;
if(head == null)
tail = null;
}
public void extractLast() {
if(tail == null)
throw new IllegalArgumentException("item not found");
if (head == tail)
head = tail = null;
else {
Element previous = head;
while(previous.next != tail)
previous = previous.next;
previous.next = null;
tail = previous;
}
}
Complexity is …
Complexity is …
18. 18
public void extract(Object obj) {
Element element = head;
Element previous = null;
while(element != null && ! element.data.equals(obj)) {
previous = element;
element = element.next;
}
if(element == null)
throw new IllegalArgumentException("item not found");
if(element == head)
head = element.next;
else
previous.next = element.next;
if(element == tail)
tail = previous;
}
Deletion of an arbitrary element
• To delete an element, we use either the extract method of MyLinkedList or
that of the Element inner class.
• The MyLinkedList extract method (code similar to that in slide 16):
Complexity is …
try{
list.extract(obj1);
} catch(IllegalArgumentException e){
System.out.println("Element not found");
}
• The method is invoked as:
19. 19
public void extract() {
Element element = null;
if(this == head)
head = next;
else{
element = head;
while(element != null && element.next != this){
element = element.next;
}
if(element == null)
throw new InvalidOperationException(“Not found”);
element.next = next;
}
if(this == tail)
tail = element;
}
Deletion of an arbitrary element
• The Element extract method invocation and implementation:
Complexity is …
MyLinkedList.Element e = list.find(obj1);
if(e != null)
e.extract();
else
System.out.println("Element not found");
20. 20
Time Complexity: Singly-linked lists vs. 1D-arrays
Operation ID-Array Complexity Singly-linked list Complexity
Insert at beginning O(n) O(1)
Insert at end O(1) O(1) if the list has tail reference
O(n) if the list has no tail reference
Insert at middle* O(n) O(n)
Delete at beginning O(n) O(1)
Delete at end O(1) O(n)
Delete at middle* O(n):
O(1) access followed by O(n)
shift
O(n):
O(n) search, followed by O(1) delete
Search O(n) linear search
O(log n) Binary search
O(n)
Indexing: What is
the element at a
given position k?
O(1) O(n)
* middle: neither at the beginning nor at the end
21. 21
Exercises
• Using the Element extract method is less efficient than using the
MyLinkedList extract method. Why?
• For the MyLinkedList class, Implement each of the following
methods:
– String toString()
– Element find(Object obj)
– void insertAt(int n) //counting the nodes from 1.
– void deleteBefore(Object obj) // delete node before obj node
State the complexity of each method.
• Which methods are affected if we do not use the tail reference in
MyLinkedList class.
22. 22
Doubly Linked Lists
• What is a doubly-linked list?
• Representation
• Space Analysis
• Doubly-linked lists vs. Singly-linked lists
• Creation, Append and Prepend
• Traversal
• Insertion before an element
• Deletion
23. 23
What is a Doubly-linked list?
• A doubly linked list is a dynamic data structure consisting of a
sequence of nodes, forming a linear ordering.
• Each node stores:
– Element (data object)
– Reference (i.e., address) to the next node
– Reference (i.e., address) to the previous node
Node:
Doubly-linked list:
24. 24
Representation
public class DoublyLinkedList{
protected Element head, tail;
//. . .
public class Element {
Object data;
Element next, previous;
Element(Object obj, Element next, Element previous){
data = obj; this.next = next;
this.previous = previous;
}
public Object getData(){return data;}
public Element getNext(){return next;}
public Element getPrevious(){return previous;}
// . . .
}
}
25. 25
Doubly-Linked Lists: Space Analysis
• Assume:
– There are n nodes in the list
– All data references are null
• Number of references in the list and space required:
Required space
Total
Reference
SizeOfDoublyLinkedListElementReference
1
head
SizeOfDoublyLinkedListElementReference
1
tail
n*SizeOfDoublyLinkedListElementReference
n
next
n*SizeOfDoublyLinkedListElementReference
n
previous
n*SizeOfSizeOfObjectReference
n
data
• Total space = (2n + 2)*SizeOfDoublyLinkedListElementReference
+ n*SizeOfObjectReference
• Hence space complexity is O(n)
26. 26
Doubly-Linked Lists vs. Singly-linked lists
• A doubly-linked list allows traversing the list in either direction.
• Modifying a doubly-linked list usually requires changing more references,
but is sometimes simpler because there is no need to keep track of the
address of the previous node. In singly-linked list, this is required in delete
and insert before operations.
The extractLast operation is O(1) in doubly-linked list whereas it is
O(n) is singly-linked list
• Doubly-linked lists are used to implement dequeues (double-ended queues
that support insert or delete operations at either end).
• A singly-linked list uses less memory than an equivalent doubly-linked list.
27. 27
List Creation and Insertion
• An empty doubly-linked list is created as follows:
DoublyLinkedList list = new DoublyLinkedList();
• Like a singly-linked list, once created, elements can be inserted into
the list using either the append or prepend methods:
for (int k = 0; k < 10; k++)
list.append(new Int(k));
• Also if we have a reference to a node (an element), we can use the
insertAfter or InsertBefore methods of the Element class.
28. 28
Insertion at the end (append)
public void append(Object obj){
Element element = new Element(obj, null, tail);
if(head == null)
head = tail = element;
else {
tail.next = element;
tail = element;
}
}
Complexity is …
29. 29
Insertion at the beginning (prepend)
public void prepend(Object obj){
Element element = new Element(obj, head, null);
if(head == null)
head = tail = element;
else {
head.previous = element;
head = element;
}
}
Complexity is …
30. 30
Traversal
For DoublyLinked list, traversal can be done in either direction.
Forward, starting from the head, or backward starting from the tail.
Example: Count the number of nodes in a linked list.
Element e = head;
while (e != null) {
//do something
e = e.next;
}
Element e = tail;
while (e != null) {
//do something
e = e.previous;
}
public int countNodes(){
int count = 0;
Element e = head;
while(e != null){
count++;
e = e.next;
}
return count;
}
Complexity is …
31. 31
public int sumLastNnodes(int n){
if(n <= 0)
throw new IllegalArgumentException("Wrong: " + n);
if(head == null)
throw new ListEmptyException();
int count = 0, sum = 0;
Element e = tail;
while(e != null && count < n){
sum += (Integer)e.data;
count++;
e = e.previous;
}
if(count < n)
throw new IllegalArgumentException(“No. of nodes < "+n);
return sum;
}
Traversal (cont’d)
Example: The following computes the sum of the last n
nodes:
Complexity is …
32. 32
Insertion before an element
• Inserting before the current node (this) that is neither the first nor the
last node:
Complexity is …
Element element = new Element(obj, this, this.previous);
this.previous.next = element;
this.previous = element;
33. 33
Deletion
• To delete an element, we use either the extract method of
DoublyLinkedList or that of the Element inner class.
public void extract(Object obj){
Element element = head;
while((element != null) && (!element.data.equals(obj)))
element = element.next;
if(element == null)
throw new IllegalArgumentException("item not found");
if(element == head) {
head = element.next;
if(element.next != null)
element.next.previous = null;
}else{
element.previous.next = element.next;
if(element.next != null)
element.next.previous = element.previous;
}
if(element == tail)
tail = element.previous;
}
Complexity is …
34. 34
Exercises
• For the DoublyLinkedList class, Implement each of the following
methods and state its complexity.
– String toString()
– Element find(Object obj)
– void ExtractLast()
– void ExtractFirst()
– void ExtractLastN(int n)
• For the DoublyLinkedList.Element inner class, implement each of
the following methods and state its complexity.
– void insertBefore()
– void insertAfter()
– void extract()
• What are the methods of DoublyLinkedList and its Element inner
class that are more efficient than those of MyLinkedList class?