In this playlist
https://youtube.com/playlist?list=PLT...
I'll illustrate algorithms and data structures course, and implement the data structures using java programming language.
the playlist language is arabic.
The Topics:
--------------------
1- Arrays
2- Linear and Binary search
3- Linked List
4- Recursion
5- Algorithm analysis
6- Stack
7- Queue
8- Binary search tree
9- Selection sort
10- Insertion sort
11- Bubble sort
12- merge sort
13- Quick sort
14- Graphs
15- Hash table
16- Binary Heaps
Reference : Object-Oriented Data Structures Using Java - Third Edition by NELL DALE, DANEIEL T.JOYCE and CHIP WEIMS
Slides is owned by College of Computing & Information Technology
King Abdulaziz University, So thanks alot for these great materials
In this playlist
https://youtube.com/playlist?list=PLT...
I'll illustrate algorithms and data structures course, and implement the data structures using java programming language.
the playlist language is arabic.
The Topics:
--------------------
1- Arrays
2- Linear and Binary search
3- Linked List
4- Recursion
5- Algorithm analysis
6- Stack
7- Queue
8- Binary search tree
9- Selection sort
10- Insertion sort
11- Bubble sort
12- merge sort
13- Quick sort
14- Graphs
15- Hash table
16- Binary Heaps
Reference : Object-Oriented Data Structures Using Java - Third Edition by NELL DALE, DANEIEL T.JOYCE and CHIP WEIMS
Slides is owned by College of Computing & Information Technology
King Abdulaziz University, So thanks alot for these great materials
Heap Sort in Design and Analysis of algorithmssamairaakram
Brief description of Heap Sort and its types.it includes Binary Tree and its types. analysis and algorithm of Heap Sort. comparison b/w Heap,Qucik and Merge Sort.
Mahlobo Foundation is a private equity company with a fund raised and managed by investment professionals. It was started in 2015 by Thabo and Nthabiseng Mahlobo to perform a broad economic development function and engage in the business of extending long term support to small businesses, entrepreneurs and industrialists. We do this by supporting and financing emerging businesses that will benefit the South African economy, creating jobs and alleviating poverty. We have prioritised Agriculture, Urbanization, ICT, SMME's and Leadership Development as our key focus areas.
Mandate
· Promote economic development and growth, human resources development and entrepreneurial capacity in Africa
· Support sustainable development projects and programmes in Africa
· Focus on providing financial support to entrepreneurs.
Que é movimento? O mundo que nos cerca está em movimento. Aprender ciências é muito mais divertido com esta série nova, prática e empolgante de livros de atividades. Cheio de projetos e experiências simples que podem ser feitos em casa, cada volume apresenta princípios científicos básicos. Fáceis de fazer, as experiências são demonstradas com seqüências fotográficas e instruções claras passo a passo.
This was made for our course Intermediate Accounting. We were asked to present on "Full Disclosure in Financial Reporting" by our course instructor and this what we did
A presentation on NORA or namely Non Obvious Relationship Awareness profiling software. This presentation goes into scenario basis profiling system that NORA does and gives a peak into NORA
The Imperium at Capitol Commons
Only 4 units to a floor composed of 2 and 3 Bedroom Units
Only 226 units available
Mobile: +63 917 852 7444
Email: theortigasspecialists@gmail.com
Website: www.theortigasspecialists.weebly.com
Heap Sort in Design and Analysis of algorithmssamairaakram
Brief description of Heap Sort and its types.it includes Binary Tree and its types. analysis and algorithm of Heap Sort. comparison b/w Heap,Qucik and Merge Sort.
Mahlobo Foundation is a private equity company with a fund raised and managed by investment professionals. It was started in 2015 by Thabo and Nthabiseng Mahlobo to perform a broad economic development function and engage in the business of extending long term support to small businesses, entrepreneurs and industrialists. We do this by supporting and financing emerging businesses that will benefit the South African economy, creating jobs and alleviating poverty. We have prioritised Agriculture, Urbanization, ICT, SMME's and Leadership Development as our key focus areas.
Mandate
· Promote economic development and growth, human resources development and entrepreneurial capacity in Africa
· Support sustainable development projects and programmes in Africa
· Focus on providing financial support to entrepreneurs.
Que é movimento? O mundo que nos cerca está em movimento. Aprender ciências é muito mais divertido com esta série nova, prática e empolgante de livros de atividades. Cheio de projetos e experiências simples que podem ser feitos em casa, cada volume apresenta princípios científicos básicos. Fáceis de fazer, as experiências são demonstradas com seqüências fotográficas e instruções claras passo a passo.
This was made for our course Intermediate Accounting. We were asked to present on "Full Disclosure in Financial Reporting" by our course instructor and this what we did
A presentation on NORA or namely Non Obvious Relationship Awareness profiling software. This presentation goes into scenario basis profiling system that NORA does and gives a peak into NORA
The Imperium at Capitol Commons
Only 4 units to a floor composed of 2 and 3 Bedroom Units
Only 226 units available
Mobile: +63 917 852 7444
Email: theortigasspecialists@gmail.com
Website: www.theortigasspecialists.weebly.com
In computer science, tree traversal (also known as tree search) is a form of graph traversal and refers to the process of visiting (checking and/or updating) each node in a tree data structure, exactly once. Such traversals are classified by the order in which the nodes are visited. The following algorithms are described for a binary tree, but they may be generalized to other trees as well.
Combines the better attributes of merge sort and insertion sort.
Like merge sort, but unlike insertion sort, running time is O(nlgn).
Like insertion sort, but unlike merge sort, sorts in place.
Students will be able to learn the concepts of advanced trees like Splay Tree, B Tree, Red Black Tree, Priority Queue or Heap. In Heap Data Structure the following methods are covered: Binary Heap, d-heap, Leftist Heap and Skew Heap.
Industrial Training at Shahjalal Fertilizer Company Limited (SFCL)MdTanvirMahtab2
This presentation is about the working procedure of Shahjalal Fertilizer Company Limited (SFCL). A Govt. owned Company of Bangladesh Chemical Industries Corporation under Ministry of Industries.
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About
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Technical Specifications
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
Key Features
Indigenized remote control interface card suitable for MAFI system CCR equipment. Compatible for IDM8000 CCR. Backplane mounted serial and TCP/Ethernet communication module for CCR remote access. IDM 8000 CCR remote control on serial and TCP protocol.
• Remote control: Parallel or serial interface
• Compatible with MAFI CCR system
• Copatiable with IDM8000 CCR
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
Application
• Remote control: Parallel or serial interface.
• Compatible with MAFI CCR system.
• Compatible with IDM8000 CCR.
• Compatible with Backplane mount serial communication.
• Compatible with commercial and Defence aviation CCR system.
• Remote control system for accessing CCR and allied system over serial or TCP.
• Indigenized local Support/presence in India.
• Easy in configuration using DIP switches.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Hierarchical Digital Twin of a Naval Power SystemKerry Sado
A hierarchical digital twin of a Naval DC power system has been developed and experimentally verified. Similar to other state-of-the-art digital twins, this technology creates a digital replica of the physical system executed in real-time or faster, which can modify hardware controls. However, its advantage stems from distributing computational efforts by utilizing a hierarchical structure composed of lower-level digital twin blocks and a higher-level system digital twin. Each digital twin block is associated with a physical subsystem of the hardware and communicates with a singular system digital twin, which creates a system-level response. By extracting information from each level of the hierarchy, power system controls of the hardware were reconfigured autonomously. This hierarchical digital twin development offers several advantages over other digital twins, particularly in the field of naval power systems. The hierarchical structure allows for greater computational efficiency and scalability while the ability to autonomously reconfigure hardware controls offers increased flexibility and responsiveness. The hierarchical decomposition and models utilized were well aligned with the physical twin, as indicated by the maximum deviations between the developed digital twin hierarchy and the hardware.
Cosmetic shop management system project report.pdfKamal Acharya
Buying new cosmetic products is difficult. It can even be scary for those who have sensitive skin and are prone to skin trouble. The information needed to alleviate this problem is on the back of each product, but it's thought to interpret those ingredient lists unless you have a background in chemistry.
Instead of buying and hoping for the best, we can use data science to help us predict which products may be good fits for us. It includes various function programs to do the above mentioned tasks.
Data file handling has been effectively used in the program.
The automated cosmetic shop management system should deal with the automation of general workflow and administration process of the shop. The main processes of the system focus on customer's request where the system is able to search the most appropriate products and deliver it to the customers. It should help the employees to quickly identify the list of cosmetic product that have reached the minimum quantity and also keep a track of expired date for each cosmetic product. It should help the employees to find the rack number in which the product is placed.It is also Faster and more efficient way.
Final project report on grocery store management system..pdfKamal Acharya
In today’s fast-changing business environment, it’s extremely important to be able to respond to client needs in the most effective and timely manner. If your customers wish to see your business online and have instant access to your products or services.
Online Grocery Store is an e-commerce website, which retails various grocery products. This project allows viewing various products available enables registered users to purchase desired products instantly using Paytm, UPI payment processor (Instant Pay) and also can place order by using Cash on Delivery (Pay Later) option. This project provides an easy access to Administrators and Managers to view orders placed using Pay Later and Instant Pay options.
In order to develop an e-commerce website, a number of Technologies must be studied and understood. These include multi-tiered architecture, server and client-side scripting techniques, implementation technologies, programming language (such as PHP, HTML, CSS, JavaScript) and MySQL relational databases. This is a project with the objective to develop a basic website where a consumer is provided with a shopping cart website and also to know about the technologies used to develop such a website.
This document will discuss each of the underlying technologies to create and implement an e- commerce website.
Saudi Arabia stands as a titan in the global energy landscape, renowned for its abundant oil and gas resources. It's the largest exporter of petroleum and holds some of the world's most significant reserves. Let's delve into the top 10 oil and gas projects shaping Saudi Arabia's energy future in 2024.
2. Why study Heapsort?
• It is a well-known, traditional sorting
algorithm you will be expected to know
• Heapsort is always O(n log n)
– Quicksort is usually O(n log n) but in the worst
case slows to O(n2
)
– Quicksort is generally faster, but Heapsort is
better in time-critical applications
• Heapsort is a really cool algorithm!
3. What is a “heap”?
• Definitions of heap:
1. A large area of memory from which the
programmer can allocate blocks as needed, and
deallocate them (or allow them to be garbage
collected) when no longer needed
2. A balanced, left-justified binary tree in which
no node has a value greater than the value in its
parent
• These two definitions have little in common
• Heapsort uses the second definition
4. Balanced binary trees
• Recall:
– The depth of a node is its distance from the root
– The depth of a tree is the depth of the deepest node
• A binary tree of depth n is balanced if all the
nodes at depths 0 through n-2 have two children
Balanced Balanced Not balanced
n-2
n-1
n
5. Left-justified binary trees
• A balanced binary tree is left-justified if:
– all the leaves are at the same depth, or
– all the leaves at depth n+1 are to the left of all
the nodes at depth n
Left-justified Not left-justified
6. Plan of attack
• First, we will learn how to turn a binary tree into a
heap
• Next, we will learn how to turn a binary tree back
into a heap after it has been changed in a certain
way
• Finally (this is the cool part) we will see how to
use these ideas to sort an array
7. The heap property
• A node has the heap property if the value in the
node is as large as or larger than the values in its
children
• All leaf nodes automatically have the heap property
• A binary tree is a heap if all nodes in it have the
heap property
12
8 3
Blue node has
heap property
12
8 12
Blue node has
heap property
12
8 14
Blue node does not
have heap property
8. siftUp
• Given a node that does not have the heap property, you can
give it the heap property by exchanging its value with the
value of the larger child
• This is sometimes called sifting up
• Notice that the child may have lost the heap property
14
8 12
Blue node has
heap property
12
8 14
Blue node does not
have heap property
9. Constructing a heap I
• A tree consisting of a single node is automatically
a heap
• We construct a heap by adding nodes one at a time:
– Add the node just to the right of the rightmost node in
the deepest level
– If the deepest level is full, start a new level
• Examples:
Add a new
node here
Add a new
node here
10. Constructing a heap II
• Each time we add a node, we may destroy the
heap property of its parent node
• To fix this, we sift up
• But each time we sift up, the value of the topmost
node in the sift may increase, and this may destroy
the heap property of its parent node
• We repeat the sifting up process, moving up in the
tree, until either
– We reach nodes whose values don’t need to be
swapped (because the parent is still larger than both
children), or
– We reach the root
12. Other children are not affected
• The node containing 8 is not affected because its parent gets larger,
not smaller
• The node containing 5 is not affected because its parent gets larger,
not smaller
• The node containing 8 is still not affected because, although its
parent got smaller, its parent is still greater than it was originally
12
10 5
8 14
12
14 5
8 10
14
12 5
8 10
13. A sample heap
• Here’s a sample binary tree after it has been heapified
• Notice that heapified does not mean sorted
• Heapifying does not change the shape of the binary tree;
this binary tree is balanced and left-justified because it
started out that way
19
1418
22
321
14
119
15
25
1722
14. Removing the root
• Notice that the largest number is now in the root
• Suppose we discard the root:
• How can we fix the binary tree so it is once again balanced
and left-justified?
• Solution: remove the rightmost leaf at the deepest level
and use it for the new root
19
1418
22
321
14
119
15
1722
11
15. The reHeap method I
• Our tree is balanced and left-justified, but no longer a heap
• However, only the root lacks the heap property
• We can siftUp() the root
• After doing this, one and only one of its children may have
lost the heap property
19
1418
22
321
14
9
15
1722
11
16. The reHeap method II
• Now the left child of the root (still the number 11) lacks
the heap property
• We can siftUp() this node
• After doing this, one and only one of its children may have
lost the heap property
19
1418
22
321
14
9
15
1711
22
17. The reHeap method III
• Now the right child of the left child of the root (still the
number 11) lacks the heap property:
• We can siftUp() this node
• After doing this, one and only one of its children may have
lost the heap property —but it doesn’t, because it’s a leaf
19
1418
11
321
14
9
15
1722
22
18. The reHeap method IV
• Our tree is once again a heap, because every node in it has
the heap property
• Once again, the largest (or a largest) value is in the root
• We can repeat this process until the tree becomes empty
• This produces a sequence of values in order largest to smallest
19
1418
21
311
14
9
15
1722
22
19. Sorting
• What do heaps have to do with sorting an array?
• Here’s the neat part:
– Because the binary tree is balanced and left justified, it
can be represented as an array
– All our operations on binary trees can be represented as
operations on arrays
– To sort:
heapify the array;
while the array isn’t empty {
remove and replace the root;
reheap the new root node;
}
20. Mapping into an array
• Notice:
– The left child of index i is at index 2*i+1
– The right child of index i is at index 2*i+2
– Example: the children of node 3 (19) are 7 (18) and 8 (14)
19
1418
22
321
14
119
15
25
1722
25 22 17 19 22 14 15 18 14 21 3 9 11
0 1 2 3 4 5 6 7 8 9 10 11 12
21. Removing and replacing the root
• The “root” is the first element in the array
• The “rightmost node at the deepest level” is the last
element
• Swap them...
• ...And pretend that the last element in the array no longer
exists—that is, the “last index” is 11 (9)
25 22 17 19 22 14 15 18 14 21 3 9 11
0 1 2 3 4 5 6 7 8 9 10 11 12
11 22 17 19 22 14 15 18 14 21 3 9 25
0 1 2 3 4 5 6 7 8 9 10 11 12
22. Reheap and repeat
• Reheap the root node (index 0, containing 11)...
• ...And again, remove and replace the root node
• Remember, though, that the “last” array index is changed
• Repeat until the last becomes first, and the array is sorted!
22 22 17 19 21 14 15 18 14 11 3 9 25
0 1 2 3 4 5 6 7 8 9 10 11 12
9 22 17 19 22 14 15 18 14 21 3 22 25
0 1 2 3 4 5 6 7 8 9 10 11 12
11 22 17 19 22 14 15 18 14 21 3 9 25
0 1 2 3 4 5 6 7 8 9 10 11 12
23. Analysis I
• Here’s how the algorithm starts:
heapify the array;
• Heapifying the array: we add each of n nodes
– Each node has to be sifted up, possibly as far as the root
• Since the binary tree is perfectly balanced, sifting up
a single node takes O(log n) time
– Since we do this n times, heapifying takes n*O(log n)
time, that is, O(n log n) time
24. Analysis II
• Here’s the rest of the algorithm:
while the array isn’t empty {
remove and replace the root;
reheap the new root node;
}
• We do the while loop n times (actually, n-1 times),
because we remove one of the n nodes each time
• Removing and replacing the root takes O(1) time
• Therefore, the total time is n times however long it
takes the reheap method
25. Analysis III
• To reheap the root node, we have to follow one
path from the root to a leaf node (and we might
stop before we reach a leaf)
• The binary tree is perfectly balanced
• Therefore, this path is O(log n) long
– And we only do O(1) operations at each node
– Therefore, reheaping takes O(log n) times
• Since we reheap inside a while loop that we do n
times, the total time for the while loop is
n*O(log n), or O(n log n)
26. Analysis IV
• Here’s the algorithm again:
heapify the array;
while the array isn’t empty {
remove and replace the root;
reheap the new root node;
}
• We have seen that heapifying takes O(n log n) time
• The while loop takes O(n log n) time
• The total time is therefore O(n log n) + O(n log n)
• This is the same as O(n log n) time