Optimization problems can be divided into two categories, depending on whether the variables are continuous or discrete:
An optimization problem with discrete variables is known as a discrete optimization, in which an object such as an integer, permutation or graph must be found from a countable set.
A problem with continuous variables is known as a continuous optimization, in which an optimal value from a continuous function must be found. They can include constrained problems and multimodal problems.
Optimization problems can be divided into two categories, depending on whether the variables are continuous or discrete:
An optimization problem with discrete variables is known as a discrete optimization, in which an object such as an integer, permutation or graph must be found from a countable set.
A problem with continuous variables is known as a continuous optimization, in which an optimal value from a continuous function must be found. They can include constrained problems and multimodal problems.
Analysis and design of algorithms part 4Deepak John
Complexity Theory - Introduction. P and NP. NP-Complete problems. Approximation algorithms. Bin packing, Graph coloring. Traveling salesperson Problem.
Textbook Solutions refer https://pythonxiisolutions.blogspot.com/
Practical's Solutions refer https://prippython12.blogspot.com/
Self Invocation is useful in Functions, that is how it gets its name Recursion.
Recursive Function
Recursion Vs Iteration
How recursion works?
Binary Search-Recursive implementation
Algorithm Design and Complexity - Course 4 - Heaps and Dynamic ProgammingTraian Rebedea
Course 4 for the Algorithm Design and Complexity course at the Faculty of Engineering in Foreign Languages - Politehnica University of Bucharest, Romania
Dynamic Programming is a method for solving a complex problem by breaking it down into a collection of simpler subproblems, solving each of those subproblems just once, and storing their solutions using a memory-based data structure (array, map,etc).
Analysis and design of algorithms part 4Deepak John
Complexity Theory - Introduction. P and NP. NP-Complete problems. Approximation algorithms. Bin packing, Graph coloring. Traveling salesperson Problem.
Textbook Solutions refer https://pythonxiisolutions.blogspot.com/
Practical's Solutions refer https://prippython12.blogspot.com/
Self Invocation is useful in Functions, that is how it gets its name Recursion.
Recursive Function
Recursion Vs Iteration
How recursion works?
Binary Search-Recursive implementation
Algorithm Design and Complexity - Course 4 - Heaps and Dynamic ProgammingTraian Rebedea
Course 4 for the Algorithm Design and Complexity course at the Faculty of Engineering in Foreign Languages - Politehnica University of Bucharest, Romania
Dynamic Programming is a method for solving a complex problem by breaking it down into a collection of simpler subproblems, solving each of those subproblems just once, and storing their solutions using a memory-based data structure (array, map,etc).
This slide explains the conversion procedure from ER Diagram to Relational Schema.
1. Entity set to Relation
2. Relationship set to Relation
3. Attributes to Columns, Primary key, Foreign Keys
1. What is Entity Relationship Model
2. Entity and Entity Set
3. Relationship and Relationship Set
4. Attributes and it's kinds
5. Participation Constraints and Mapping Cardinality
6. Aggregation, Specialization, and Generalization
7. Some Sample ERD models
This note includes the followings:
- Database Create, Drop Operations
- Database Table Create, Drop Operations
- Database Table Alter Operation
- Data insertion
- Data deletion
- Existing data update
- Searching data from data table (showing all record, specific columns, specific rows, column aliasing, sorting data, limiting data, distinct data)
- Aggregate functions
- Group by clause
- Having clause
- Types of table joins
- Table aliasing, Inner Join, Left/Right Join, Self Join
- Subquery operation (scalar subquery, column subquery, row subquery, correlated subquery, derived table)
This note contains some sample MySQL query practices based on the HR Schema database. The practice sections are from the following categories:
- DDL statements
- Basic Select statements
- Aggregate operations
- Join operations
This lecture slide contains:
- Difference between FA, PDA and TM
- Formal definition of TM
- TM transition function and configuration
- Designing TM for different languages
- Simulating TM for different strings
This slide contains,
1) Some terminologies like yields, derives, word, derivation
2) Leftmost and Rightmost derivation
3) Ambiguity checking
4) Parse tree generation and ambiguity checking
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
Embracing GenAI - A Strategic ImperativePeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
June 3, 2024 Anti-Semitism Letter Sent to MIT President Kornbluth and MIT Cor...Levi Shapiro
Letter from the Congress of the United States regarding Anti-Semitism sent June 3rd to MIT President Sally Kornbluth, MIT Corp Chair, Mark Gorenberg
Dear Dr. Kornbluth and Mr. Gorenberg,
The US House of Representatives is deeply concerned by ongoing and pervasive acts of antisemitic
harassment and intimidation at the Massachusetts Institute of Technology (MIT). Failing to act decisively to ensure a safe learning environment for all students would be a grave dereliction of your responsibilities as President of MIT and Chair of the MIT Corporation.
This Congress will not stand idly by and allow an environment hostile to Jewish students to persist. The House believes that your institution is in violation of Title VI of the Civil Rights Act, and the inability or
unwillingness to rectify this violation through action requires accountability.
Postsecondary education is a unique opportunity for students to learn and have their ideas and beliefs challenged. However, universities receiving hundreds of millions of federal funds annually have denied
students that opportunity and have been hijacked to become venues for the promotion of terrorism, antisemitic harassment and intimidation, unlawful encampments, and in some cases, assaults and riots.
The House of Representatives will not countenance the use of federal funds to indoctrinate students into hateful, antisemitic, anti-American supporters of terrorism. Investigations into campus antisemitism by the Committee on Education and the Workforce and the Committee on Ways and Means have been expanded into a Congress-wide probe across all relevant jurisdictions to address this national crisis. The undersigned Committees will conduct oversight into the use of federal funds at MIT and its learning environment under authorities granted to each Committee.
• The Committee on Education and the Workforce has been investigating your institution since December 7, 2023. The Committee has broad jurisdiction over postsecondary education, including its compliance with Title VI of the Civil Rights Act, campus safety concerns over disruptions to the learning environment, and the awarding of federal student aid under the Higher Education Act.
• The Committee on Oversight and Accountability is investigating the sources of funding and other support flowing to groups espousing pro-Hamas propaganda and engaged in antisemitic harassment and intimidation of students. The Committee on Oversight and Accountability is the principal oversight committee of the US House of Representatives and has broad authority to investigate “any matter” at “any time” under House Rule X.
• The Committee on Ways and Means has been investigating several universities since November 15, 2023, when the Committee held a hearing entitled From Ivory Towers to Dark Corners: Investigating the Nexus Between Antisemitism, Tax-Exempt Universities, and Terror Financing. The Committee followed the hearing with letters to those institutions on January 10, 202
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Unit 8 - Information and Communication Technology (Paper I).pdfThiyagu K
This slides describes the basic concepts of ICT, basics of Email, Emerging Technology and Digital Initiatives in Education. This presentations aligns with the UGC Paper I syllabus.
Honest Reviews of Tim Han LMA Course Program.pptxtimhan337
Personal development courses are widely available today, with each one promising life-changing outcomes. Tim Han’s Life Mastery Achievers (LMA) Course has drawn a lot of interest. In addition to offering my frank assessment of Success Insider’s LMA Course, this piece examines the course’s effects via a variety of Tim Han LMA course reviews and Success Insider comments.
CLASS 11 CBSE B.St Project AIDS TO TRADE - INSURANCE
DS & Algo 6 - Dynamic Programming
1. Mohammad Imam Hossain, Lecturer, Dept. of CSE, UIU. Email: imambuet11@gmail.com
Dynamic Programming
Dynamic Programming (DP) is an algorithmic technique for solving an optimization problem by breaking it down into
simpler subproblems and utilizing the fact that the optimal solution to the overall problem depends upon the optimal
solution to its subproblems.
Characteristics of DP
1) Overlapping Subproblems: Subproblems are smaller versions of the original problem. Any problem has
overlapping sub-problems if finding its solution involves solving the same subproblem multiple times.
2) Optimal Substructure Property: Any problem has optimal substructure property if its overall optimal solution
can be constructed from the optimal solutions of its subproblems.
For Fibonacci numbers,
Recursive formula: 𝑓𝑖𝑏(𝑛) = {
0; 𝑛 = 0
1; 𝑛 = 1
𝑓𝑖𝑏(𝑛 − 1) + 𝑓𝑖𝑏(𝑛 − 2); 𝑛 > 1
2. Mohammad Imam Hossain, Lecturer, Dept. of CSE, UIU. Email: imambuet11@gmail.com
DP Methods
1) Top-down with Memorization: In this approach, we try to solve the bigger problem by recursively finding the
solution to smaller sub-problems. Whenever we solve a sub-problem, we cache its result so that we don’t end
up solving it repeatedly if it’s called multiple times. Instead, we can just return the saved result. This technique
of storing the results of already solved subproblems is called Memorization.
Recursive Implementation Top-down with Memorization
int fib(int term){
if(term==0){
return 0; ///base condition 1
}
else if(term==1){
return 1; ///base condition 2
}
else{
///recursive subproblems
int myresult=fib(term-1)
+fib(term-2);
return myresult;
}
}
int cache[100]={0};
int memfib(int term){
if(term==0){
return 0; ///base condition 1
}
else if(term==1){
return 1; ///base condition 1
}
else{
///checking the cache memory
if(cache[term]!=0){
///found
return cache[term];
}
else{
///not found
cache[term]=memfib(term-1)
+memfib(term-2);
return cache[term];
}
}
}
2) Bottom-up with Tabulation: Tabulation is the opposite of the top-down approach and avoids recursion. In this
approach, we solve the problem “bottom-up” (i.e. by solving all the related sub-problems first). This is typically
done by filling up an n-dimensional table. Based on the results in the table, the solution to the top/original
problem is then computed.
Recursive Implementation Bottom-up with Tabulation
int fib(int term){
if(term==0){
return 0; ///base condition 1
}
else if(term==1){
return 1; ///base condition 2
}
else{
///recursive subproblems
int myresult=fib(term-1)
+fib(term-2);
return myresult;
}
}
int dptable[100];
int dpfib(int term){
dptable[0]=0; ///base condition 1
dptable[1]=1; ///base condition 2
///filling up the table
for(int t=2;t<=term;t++){
dptable[t]=dptable[t-1]+dptable[t-2];
}
return dptable[term];
}
3. Mohammad Imam Hossain, Lecturer, Dept. of CSE, UIU. Email: imambuet11@gmail.com
Practice 1 – Staircase problem
There are n stairs, a person standing at the bottom wants to reach the top. The person can climb either 1 stair or 2 stairs
at a time. Count the number of ways, the person can reach the top.
Ref: https://www.geeksforgeeks.org/count-ways-reach-nth-stair/
Practice 2 – Tiling problem
Given a “2 x n” board and tiles of size “2 x 1”, count the number of ways to tile the given board using the 2 x 1 tiles. A tile
can either be placed horizontally i.e., as a 1 x 2 tile or vertically i.e., as 2 x 1 tile.
Ref: https://www.geeksforgeeks.org/tiling-problem/
Practice 3 – Friends pairing problem
Given n friends, each one can remain single or can be paired up with some other friend. Each friend can be paired only
once. Find out the total number of ways in which friends can remain single or can be paired up.
Ref: https://www.geeksforgeeks.org/friends-pairing-problem/
Practice 4 – House thief
There are n houses build in a line, each of which contains some value in it. A thief is going to steal the maximal value of
these houses, but he can’t steal in two adjacent houses because the owner of the stolen houses will tell his two
neighbors left and right side. What is the maximum stolen value?
Ref: https://www.geeksforgeeks.org/find-maximum-possible-stolen-value-houses/
Practice 5 – Minimum jumps to reach end
Given an array of integers where each element represents the max number of steps that can be made forward from that
element. Write a function to return the minimum number of jumps to reach the end of the array (starting from the first
element). If an element is 0, they cannot move through that element. If the end isn’t reachable, return -1.
Ref: https://www.geeksforgeeks.org/minimum-number-of-jumps-to-reach-end-of-a-given-array/
Problem 6 – Catalan Number
Find out the nth
Catalan number.
First few Catalan numbers for n = 0, 1, 2, 3, 4, … are 1, 1, 2, 5, 14, 42, … etc.
Recursive formula: 𝐶(𝑛) = {
1; 𝑛 = 0
∑ 𝐶(𝑖) ∗ 𝐶(𝑛 − 1 − 𝑖)
𝑛−1
𝑖=0
Ref: https://www.geeksforgeeks.org/program-nth-catalan-number/
4. Mohammad Imam Hossain, Lecturer, Dept. of CSE, UIU. Email: imambuet11@gmail.com
Practice 7 – Binomial coefficient
Write a function that takes two parameters n, r and returns the value of Binomial Coefficient C(n, r) or, nCr.
Ref: https://www.geeksforgeeks.org/binomial-coefficient-dp-9/
Practice 8 – Permutation coefficient
Write a function that takes two parameters n, r and returns the value of nPr.
Ref: https://www.geeksforgeeks.org/permutation-coefficient/
Practice 9 – Subset sum
Given a set of non-negative integers, and a value sum, determine if there is a subset of the given set with sum equal to
given sum.
Ref: https://www.geeksforgeeks.org/subset-sum-problem-dp-25/
Practice 10 – 0/1 Knapsack problem
Given weights and values of n items, put these items in a knapsack of capacity W to get the maximum total value in the
knapsack. In other words, given two integer arrays val[0..n-1] and wt[0..n-1] which represent values and weights
associated with n items respectively. Also given an integer W which represents knapsack capacity, find out the maximum
value subset of val[] such that sum of the weights of this subset is smaller than or equal to W. You cannot break an item,
either pick the complete item or don’t pick it (0-1 property).
Ref: https://www.geeksforgeeks.org/0-1-knapsack-problem-dp-10/
Practice 11 – Longest Common Subsequence
Given two sequences, find the length of longest subsequence present in both of them. A subsequence is a sequence that
appears in the same relative order, but not necessarily contiguous. For example, “abc”, “abg”, “bdf”, “aeg”, ‘”acefg”, ..
etc are subsequences of “abcdefg”.
Ref: https://www.geeksforgeeks.org/longest-common-subsequence-dp-4/
Practice 12 – Edit Distance
Given two strings str1 and str2 and 3 operations (Insert, Replace, Delete) that can be performed on str1. Find minimum
number of edits (operations) required to convert ‘str1’ into ‘str2’. All of the above operations are of equal cost.
Ref: https://www.geeksforgeeks.org/edit-distance-dp-5/