Apresentação sobre o algoritmo de ordenação Counting Sort, apresentada no 2º semestre de 2014, como um dos requisitos da disciplina de Projeto e Análise de Algoritmos, no Mestrado em Ciência da Computação, pela Universidade Federal de Lavras (UFLA). Disciplina ministrada pelo professor Dr. Sanderson L. Gonzaga de Oliveira.
Counting sort is a sorting algorithm that works on integer keys within a specific range. It works by counting the number of objects with each distinct key value and using arithmetic to determine the position of each object in the output sequence without comparing elements. The algorithm uses three arrays: an input array, an output array, and a counting array. It iterates through the input array to count the frequency of each key value in the counting array. Then iterates through the counting array to calculate cumulative frequencies, and finally iterates through the input array again to place each object in the output array based on its key value's counted position. Counting sort runs in O(n+k) time where n is the number of elements and k is the maximum key
Counting Sort and Radix Sort AlgorithmsSarvesh Rawat
Counting sort is an integer sorting algorithm that works by counting the number of objects that have each distinct key value and using arithmetic to determine the position of each object in the sorted output. It runs in O(n+k) time where n is the number of elements and k is the largest element. It requires an extra array to store counts of each key value. Radix sort is an extension of counting sort that sorts elements based on individual digits by performing counting sort repeatedly on each digit, from least to most significant.
Counting sort is an algorithm that sorts elements by counting the number of occurrences of each unique element in an array. It works by:
1) Creating a count array to store the count of each unique object in the input array.
2) Modifying the count array to store cumulative counts.
3) Creating an output array by using the modified count array to output elements in sorted order.
Material de apoio das aulas de tutoria de Algoritmos e Estrutura de dados da Universidade Federal de Ouro Preto, Campus João Monlevade. O conteúdo abordado é uma revisão sobre structs na linguagem de programação C.
The document contains a data structures lab manual with experiments on various data structure topics like arrays, stacks, queues, linked lists, and binary search trees. It includes C programs and explanations for inserting and deleting elements from arrays, stacks and queues. It also includes programs for matrix operations, sparse matrix representation, linear and binary searches. The experiments cover basic operations on common data structures.
This document provides information about Python lists. Some key points:
- Lists can store multiple elements of any data type. They are versatile for working with multiple elements.
- Lists maintain element order and allow duplicate elements. Elements are accessed via indexes.
- Lists support operations like concatenation, membership testing, slicing, and methods to add/remove elements.
- Nested lists allow lists within lists, for representing matrices and other complex data structures.
Counting sort is a sorting algorithm that works on integer keys within a specific range. It works by counting the number of objects with each distinct key value and using arithmetic to determine the position of each object in the output sequence without comparing elements. The algorithm uses three arrays: an input array, an output array, and a counting array. It iterates through the input array to count the frequency of each key value in the counting array. Then iterates through the counting array to calculate cumulative frequencies, and finally iterates through the input array again to place each object in the output array based on its key value's counted position. Counting sort runs in O(n+k) time where n is the number of elements and k is the maximum key
Counting Sort and Radix Sort AlgorithmsSarvesh Rawat
Counting sort is an integer sorting algorithm that works by counting the number of objects that have each distinct key value and using arithmetic to determine the position of each object in the sorted output. It runs in O(n+k) time where n is the number of elements and k is the largest element. It requires an extra array to store counts of each key value. Radix sort is an extension of counting sort that sorts elements based on individual digits by performing counting sort repeatedly on each digit, from least to most significant.
Counting sort is an algorithm that sorts elements by counting the number of occurrences of each unique element in an array. It works by:
1) Creating a count array to store the count of each unique object in the input array.
2) Modifying the count array to store cumulative counts.
3) Creating an output array by using the modified count array to output elements in sorted order.
Material de apoio das aulas de tutoria de Algoritmos e Estrutura de dados da Universidade Federal de Ouro Preto, Campus João Monlevade. O conteúdo abordado é uma revisão sobre structs na linguagem de programação C.
The document contains a data structures lab manual with experiments on various data structure topics like arrays, stacks, queues, linked lists, and binary search trees. It includes C programs and explanations for inserting and deleting elements from arrays, stacks and queues. It also includes programs for matrix operations, sparse matrix representation, linear and binary searches. The experiments cover basic operations on common data structures.
This document provides information about Python lists. Some key points:
- Lists can store multiple elements of any data type. They are versatile for working with multiple elements.
- Lists maintain element order and allow duplicate elements. Elements are accessed via indexes.
- Lists support operations like concatenation, membership testing, slicing, and methods to add/remove elements.
- Nested lists allow lists within lists, for representing matrices and other complex data structures.
The document discusses multidimensional arrays and provides examples of declaring and using two-dimensional arrays in Java. It describes how to represent tables of data using two-dimensional arrays, initialize arrays, access elements, and perform common operations like summing elements. The document also introduces the concept of ragged arrays and declares a three-dimensional array could be used to store student exam scores with multiple parts.
The document discusses various data structures and algorithms. It begins with an overview of common data structures like arrays, lists, stacks, queues, and linked lists. It then provides detailed explanations of stack, queue, circular queue, priority queue, double ended queue, and various linked list implementations including singly linked lists, doubly linked lists, and circular linked lists. For each data structure, it discusses operations like insertion, deletion, traversal, and implementations in C/C++ using structures and pointers.
The document discusses the role of the parser in compiler design. It explains that the parser takes a stream of tokens from the lexical analyzer and checks if the source program satisfies the rules of the context-free grammar. If so, it creates a parse tree representing the syntactic structure. Parsers are categorized as top-down or bottom-up based on the direction they build the parse tree. The document also covers context-free grammars, derivations, parse trees, ambiguity, and techniques for eliminating left-recursion from grammars.
Domain Modeling Made Functional (KanDDDinsky 2019)Scott Wlaschin
(video at https://fsharpforfunandprofit.com/ddd/)
Statically typed functional programming languages encourage a very different way of thinking about types. The type system is your friend, not an annoyance, and can be used in many ways that might not be familiar to OO programmers. Types can be used to represent the domain in a fine-grained, self documenting way. And in many cases, types can even be used to encode business rules so that you literally cannot create incorrect code. You can then use the static type checking almost as an instant unit test — making sure that your code is correct at compile time. In this talk, we'll look at some of the ways you can use types as part of a domain driven design process, with some simple real world examples in F#. No jargon, no maths, and no prior F# experience necessary.
O documento descreve como criar procedimentos no programa SuperLogo, incluindo procedimentos básicos como quadrado, triângulo e círculo. Também mostra como criar desenhos complexos usando subprocedimentos e variáveis, além de instruções sobre como salvar e abrir arquivos no SuperLogo.
This document provides an overview of insertion sort, including:
- How insertion sort works by dividing an array into sorted and unsorted parts, inserting unsorted elements into the sorted part in each pass.
- The algorithm scans the array from left to right, inserting each element into the correct position in the previously sorted subarray.
- Runtime is O(n^2) in the worst and average cases due to multiple comparisons and shifts that may be required.
- Pseudocode and Java code examples are provided to demonstrate implementation.
- Advantages are simplicity and efficiency for small datasets, while disadvantages include poor performance for large arrays compared to other algorithms.
The document discusses graphs and graph algorithms. It defines what a graph is, including different types of graphs. It covers graph representations using adjacency matrices and lists. Graph traversal algorithms like breadth-first search and depth-first search are explained. Applications of graphs in real world are provided. Minimum spanning tree algorithms like Prim's and Kruskal's are summarized. Dijkstra's shortest path algorithm is outlined in steps.
The document discusses various sorting and searching algorithms:
- Bubble sort, selection sort, and insertion sort are described along with their time complexities of O(n^2).
- Linear search is discussed, with the number of comparisons growing linearly with the size of the list.
- Applications of sorting and searching are mentioned but not detailed.
The document discusses several common sorting algorithms: bubble sort, selection sort, insertion sort, merge sort, and quick sort. Bubble sort works by scanning an array from left to right, swapping adjacent elements that are out of order. Selection sort finds the smallest element, swaps it into the first position, then repeats to find the next smallest. Insertion sort inserts new elements into the correct position in a sorted array. Merge sort divides an array in half, sorts the halves, and merges them back together. Quick sort chooses a pivot element and partitions the array into sub-arrays based on element values relative to the pivot.
Algorithms Lecture 3: Analysis of Algorithms IIMohamed Loey
We will discuss the following: Maximum Pairwise Product, Fibonacci, Greatest Common Divisors, Naive algorithm is too slow. The Efficient algorithm is much better. Finding the correct algorithm requires knowing something interesting about the problem
Lisp Macros in 20 Minutes (Featuring Clojure)Phil Calçado
"We just started holding 20 minutes presentations during lunch time in the ThoughtWorks Sydney office. For the first session I gave a not-that-short talk on Lisp macros using Clojure. The slides are below.
It turns out that 20 minutes is too little time to actually acquire content but I think at least we now have some people interested in how metaprogramming can be more than monkey patching."
http://fragmental.tw/2009/01/20/presentation-slides-macros-in-20-minutes/
The document describes various HTML elements and their attributes. It lists elements like fonts, images, paragraphs, lists, tables, and hyperlinks. It provides examples of how each element is coded in HTML along with possible attributes like font face, color, and size; image source, width, and height; paragraph alignment; list type; table borders, colors, and merging cells. The document is intended as a tutorial on basic HTML elements and tags.
Learn how to use arrays in Java, how to enter array, how to traverse an array, how to print array and more array operations.
Watch the video lesson and access the hands-on exercises here: https://softuni.org/code-lessons/java-foundations-certification-arrays
Stacks are linear data structures where elements are inserted and removed from the same end, known as the top. Common stack operations include push to add an element, pop to remove the top element, and peek to view the top element without removing it. Stacks are often implemented using arrays or linked lists and have O(1) time complexity for operations. Some applications of stacks include reversing data, converting numbers between bases, expression conversions, and backtracking problems like N-Queens.
O documento discute algoritmos gulosos para o problema do troco mínimo, onde o objetivo é representar um valor com o menor número possível de moedas. Ele apresenta a definição formal do problema, um exemplo passo a passo e uma análise da corretude do algoritmo guloso proposto para o conjunto de moedas {1, 5, 25, 50, 100}.
O documento descreve o algoritmo de ordenação Insertion Sort, explicando como ele ordena um vetor de maneira crescente e decrescente através de repetidas passagens que movem elementos para suas posições corretas.
O documento discute validação de dados e a estrutura de repetição "faça-enquanto". A validação de dados é usada para garantir que os dados digitados pelo usuário estejam corretos através do uso de condições. A estrutura "faça-enquanto" executa um bloco de instruções repetidamente enquanto uma condição for verdadeira, diferente de "enquanto" que testa a condição no início.
Binary search provides an efficient O(log n) solution for searching a sorted list. It works by repeatedly dividing the search space in half and focusing on only one subdivision, based on comparing the search key to the middle element. This recursively narrows down possible locations until the key is found or the entire list has been searched. Binary search mimics traversing a binary search tree built from the sorted list, with divide-and-conquer reducing the search space at each step.
The document discusses multidimensional arrays in C, including two-dimensional and three-dimensional arrays. It explains the syntax for declaring multidimensional arrays and how they are logically and physically stored in memory as one-dimensional arrays. The document also covers passing multidimensional arrays to functions, including type conversions, and initializing multidimensional arrays.
The document discusses multidimensional arrays and provides examples of declaring and using two-dimensional arrays in Java. It describes how to represent tables of data using two-dimensional arrays, initialize arrays, access elements, and perform common operations like summing elements. The document also introduces the concept of ragged arrays and declares a three-dimensional array could be used to store student exam scores with multiple parts.
The document discusses various data structures and algorithms. It begins with an overview of common data structures like arrays, lists, stacks, queues, and linked lists. It then provides detailed explanations of stack, queue, circular queue, priority queue, double ended queue, and various linked list implementations including singly linked lists, doubly linked lists, and circular linked lists. For each data structure, it discusses operations like insertion, deletion, traversal, and implementations in C/C++ using structures and pointers.
The document discusses the role of the parser in compiler design. It explains that the parser takes a stream of tokens from the lexical analyzer and checks if the source program satisfies the rules of the context-free grammar. If so, it creates a parse tree representing the syntactic structure. Parsers are categorized as top-down or bottom-up based on the direction they build the parse tree. The document also covers context-free grammars, derivations, parse trees, ambiguity, and techniques for eliminating left-recursion from grammars.
Domain Modeling Made Functional (KanDDDinsky 2019)Scott Wlaschin
(video at https://fsharpforfunandprofit.com/ddd/)
Statically typed functional programming languages encourage a very different way of thinking about types. The type system is your friend, not an annoyance, and can be used in many ways that might not be familiar to OO programmers. Types can be used to represent the domain in a fine-grained, self documenting way. And in many cases, types can even be used to encode business rules so that you literally cannot create incorrect code. You can then use the static type checking almost as an instant unit test — making sure that your code is correct at compile time. In this talk, we'll look at some of the ways you can use types as part of a domain driven design process, with some simple real world examples in F#. No jargon, no maths, and no prior F# experience necessary.
O documento descreve como criar procedimentos no programa SuperLogo, incluindo procedimentos básicos como quadrado, triângulo e círculo. Também mostra como criar desenhos complexos usando subprocedimentos e variáveis, além de instruções sobre como salvar e abrir arquivos no SuperLogo.
This document provides an overview of insertion sort, including:
- How insertion sort works by dividing an array into sorted and unsorted parts, inserting unsorted elements into the sorted part in each pass.
- The algorithm scans the array from left to right, inserting each element into the correct position in the previously sorted subarray.
- Runtime is O(n^2) in the worst and average cases due to multiple comparisons and shifts that may be required.
- Pseudocode and Java code examples are provided to demonstrate implementation.
- Advantages are simplicity and efficiency for small datasets, while disadvantages include poor performance for large arrays compared to other algorithms.
The document discusses graphs and graph algorithms. It defines what a graph is, including different types of graphs. It covers graph representations using adjacency matrices and lists. Graph traversal algorithms like breadth-first search and depth-first search are explained. Applications of graphs in real world are provided. Minimum spanning tree algorithms like Prim's and Kruskal's are summarized. Dijkstra's shortest path algorithm is outlined in steps.
The document discusses various sorting and searching algorithms:
- Bubble sort, selection sort, and insertion sort are described along with their time complexities of O(n^2).
- Linear search is discussed, with the number of comparisons growing linearly with the size of the list.
- Applications of sorting and searching are mentioned but not detailed.
The document discusses several common sorting algorithms: bubble sort, selection sort, insertion sort, merge sort, and quick sort. Bubble sort works by scanning an array from left to right, swapping adjacent elements that are out of order. Selection sort finds the smallest element, swaps it into the first position, then repeats to find the next smallest. Insertion sort inserts new elements into the correct position in a sorted array. Merge sort divides an array in half, sorts the halves, and merges them back together. Quick sort chooses a pivot element and partitions the array into sub-arrays based on element values relative to the pivot.
Algorithms Lecture 3: Analysis of Algorithms IIMohamed Loey
We will discuss the following: Maximum Pairwise Product, Fibonacci, Greatest Common Divisors, Naive algorithm is too slow. The Efficient algorithm is much better. Finding the correct algorithm requires knowing something interesting about the problem
Lisp Macros in 20 Minutes (Featuring Clojure)Phil Calçado
"We just started holding 20 minutes presentations during lunch time in the ThoughtWorks Sydney office. For the first session I gave a not-that-short talk on Lisp macros using Clojure. The slides are below.
It turns out that 20 minutes is too little time to actually acquire content but I think at least we now have some people interested in how metaprogramming can be more than monkey patching."
http://fragmental.tw/2009/01/20/presentation-slides-macros-in-20-minutes/
The document describes various HTML elements and their attributes. It lists elements like fonts, images, paragraphs, lists, tables, and hyperlinks. It provides examples of how each element is coded in HTML along with possible attributes like font face, color, and size; image source, width, and height; paragraph alignment; list type; table borders, colors, and merging cells. The document is intended as a tutorial on basic HTML elements and tags.
Learn how to use arrays in Java, how to enter array, how to traverse an array, how to print array and more array operations.
Watch the video lesson and access the hands-on exercises here: https://softuni.org/code-lessons/java-foundations-certification-arrays
Stacks are linear data structures where elements are inserted and removed from the same end, known as the top. Common stack operations include push to add an element, pop to remove the top element, and peek to view the top element without removing it. Stacks are often implemented using arrays or linked lists and have O(1) time complexity for operations. Some applications of stacks include reversing data, converting numbers between bases, expression conversions, and backtracking problems like N-Queens.
O documento discute algoritmos gulosos para o problema do troco mínimo, onde o objetivo é representar um valor com o menor número possível de moedas. Ele apresenta a definição formal do problema, um exemplo passo a passo e uma análise da corretude do algoritmo guloso proposto para o conjunto de moedas {1, 5, 25, 50, 100}.
O documento descreve o algoritmo de ordenação Insertion Sort, explicando como ele ordena um vetor de maneira crescente e decrescente através de repetidas passagens que movem elementos para suas posições corretas.
O documento discute validação de dados e a estrutura de repetição "faça-enquanto". A validação de dados é usada para garantir que os dados digitados pelo usuário estejam corretos através do uso de condições. A estrutura "faça-enquanto" executa um bloco de instruções repetidamente enquanto uma condição for verdadeira, diferente de "enquanto" que testa a condição no início.
Binary search provides an efficient O(log n) solution for searching a sorted list. It works by repeatedly dividing the search space in half and focusing on only one subdivision, based on comparing the search key to the middle element. This recursively narrows down possible locations until the key is found or the entire list has been searched. Binary search mimics traversing a binary search tree built from the sorted list, with divide-and-conquer reducing the search space at each step.
The document discusses multidimensional arrays in C, including two-dimensional and three-dimensional arrays. It explains the syntax for declaring multidimensional arrays and how they are logically and physically stored in memory as one-dimensional arrays. The document also covers passing multidimensional arrays to functions, including type conversions, and initializing multidimensional arrays.
The document discusses arrays in C++. It explains that arrays can be passed to functions like variables passed by reference. The functions know the array's position and type in memory without needing its size. Constant array parameters can be used to prevent changing the values in the array. An example program defines a function to fill, sort, and print an integer array. It takes user input, sorts the numbers in ascending order, and prints the sorted array.
The document discusses various sorting algorithms and their time complexities, including counting sort, radix sort, bucket sort, and lower bounds for comparison-based sorting. Counting sort counts the number of occurrences of each key and uses the counts to place the elements in output array in correct positions. Radix sort performs counting sort repeatedly based on each digit of keys written in a given base. Bucket sort distributes elements into buckets based on their hashed values and sorts individual buckets. The time complexity of bucket sort is linear on average if elements are randomly distributed.
The document summarizes the output of labs 5, 6, and 7 from a computer engineering course. Lab 5 implements non-restoring division using a register-based algorithm. Lab 6 compares FIFO and LRU page replacement algorithms. Lab 7 implements Booth's multiplication algorithm for signed numbers using registers. Code snippets are provided for each lab along with sample inputs/outputs.
The document describes the dynamic programming algorithm for calculating the edit distance between two strings. It defines edit distance as the minimum number of insertions, deletions or substitutions needed to change one string into the other. The algorithm uses a table c[i,j] to store the edit distance between the prefixes of the two strings x[1..i] and y[1..j], calculating values in the table using a recursive formula until it reaches the final edit distance value c[|x|,|y|].
The document discusses the relationship between arrays and pointers in C programming. It explains that arrays store a consecutive series of variables under a single name, and each element of the array has its own unique memory address. Pointers can be used to reference array elements, where the array name represents the base address of the array and pointer arithmetic allows accessing elements. It provides examples of declaring and initializing arrays, accessing elements using pointers, and how pointers can be incremented or decremented to traverse the array.
Media pembelajaran matematika (operasi bilangan Bulat)adekfatimah
The document discusses different models for performing addition and subtraction on integer numbers using a number line approach. It explains modeling addition and subtraction visually by moving left or right on the number line based on the signs and values of the numbers. Several examples are shown of calculating expressions like 2 + 3, -2 + 3, 2 - 3, and 2 + (-3) using the number line models. The forward-backward model and two arrow models are described as ways to represent the operations and determine the sum or difference.
This document introduces integers and provides information about their properties. It defines integers as whole numbers and their negative counterparts. Positive integers are those to the right of zero and have values greater than zero, while negative integers are to the left of zero and have values less than zero. The document then discusses comparing and performing operations on integers, including addition, subtraction, multiplication, and division. Key rules are provided, such as keeping the sign of the integer with the larger absolute value when adding a positive and negative integer. Examples are worked through to demonstrate the integer rules and properties.
The document contains examples of C code snippets and questions about their output. It covers topics like control flow, arrays, pointers, structures, file handling and more. The examples demonstrate basic programming concepts in C like loops, conditional statements, operators, data types and more.
The document discusses insertion sort and its analysis. It begins by providing an overview of insertion sort, describing how it works to sort a sequence by iteratively inserting elements into their sorted position. It then gives pseudocode for insertion sort and works through an example. Next, it analyzes insertion sort's runtime, showing it is O(n^2) in the worst case and O(n) in the best case. The document concludes by introducing the divide and conquer approach for sorting, which will be covered in the next section on merge sort.
This document discusses various sorting algorithms including merge sort. It begins with an introduction to sorting and searching. It then provides pseudocode for the merge sort algorithm which works by dividing the array into halves, recursively sorting the halves, and then merging the sorted halves back together. An example is provided to illustrate the merge sort process. Key steps include dividing, conquering by recursively sorting subarrays, and combining through merging. The overall time complexity of merge sort is O(n log n).
Comparison sorting algorithms work by making pairwise comparisons between elements to determine the order in a sorted list. They have a lower bound of Ω(n log n) time complexity due to needing to traverse a decision tree with a minimum of n log n comparisons. Counting sort is a non-comparison sorting algorithm that takes advantage of key assumptions about the data to count and place elements directly into the output array in linear time O(n+k), where n is the number of elements and k is the range of possible key values.
The document contains Python code snippets that use nested for loops and while loops to generate various patterns and perform calculations. The code snippets include programs to:
1) Generate asterisk patterns in ascending and descending order using nested for loops.
2) Print multiplication tables and number patterns using for loops.
3) Calculate the number of times a number can be divided by 3 before becoming less than or equal to 10 using a while loop.
4) Calculate the sum of powers of 2 from 1 to 20 using a while True loop with a break statement.
5) Modify an existing while loop to calculate the sum of odd numbers from 1 to 100 using a continue statement.
The document contains 14 questions related to C++ functions for arrays and 2D arrays. The questions cover topics like shifting array elements, finding extra elements in arrays, arranging positive and negative numbers, calculating row and column sums of 2D arrays, displaying diagonals and products of rows for 2D arrays, and swapping rows of a 2D array. Functions with appropriate parameters and logic are provided as answers to implement the described tasks.
This document provides an introduction to Python for high school programmers. It covers background information on Python, key concepts like data types and operators, and basics of the language like variables, collections, control flow, and object-oriented programming. Code examples are included to demonstrate various features. The presentation aims to get students started with Python and provide an overview of what it can do.
The document summarizes a lecture on algorithms that covered insertion sort, analyzing its time complexity, and an introduction to the divide and conquer approach and merge sort. It included pseudocode for insertion sort algorithms and discussed how merge sort follows the divide and conquer paradigm by dividing the problem into subproblems, solving them recursively, and combining the solutions. Pseudocode was also provided for the merge sort algorithm.
The document discusses order of operations and exponents. It explains that when evaluating arithmetic expressions, operations should be performed in a specific order: 1) operations within grouping symbols, 2) multiplication and division from left to right, and 3) addition and subtraction from left to right. Exponents are defined as the number of times a base is used as a factor, with the exponent written as a superscript. Examples are provided to demonstrate applying order of operations correctly.
This document discusses and provides code examples for three sorting algorithms: insertion sort, selection sort, and quicksort. It includes pseudocode for insertion sort and describes its worst case performance on sample data. Selection sort code is shown along with an example of its worst case. Quicksort is briefly explained. Merge sort is also listed along with sample data being sorted.
O documento discute computação numérica utilizando máquinas de Turing. Primeiramente, apresenta como máquinas de Turing podem ser usadas para calcular funções numéricas, representando números na fita através de sequências de 1s. Em seguida, mostra exemplos de funções numéricas como sucessor, zero e adição, e como elas podem ser computadas por máquinas de Turing. Por fim, discute como operações sequenciais de funções podem ser representadas por uma única máquina de Turing através da composição de suas partes
O documento descreve a hierarquia de Chomsky, que classifica as linguagens formais em quatro tipos principais com base na potência expressiva de suas gramáticas geradoras e reconhecedores associados. O documento explica cada tipo de linguagem formal na hierarquia, começando pelas linguagens regulares no nível 3 e terminando com as linguagens recursivamente enumeráveis no nível 0.
1) O documento apresenta algoritmos aproximativos para problemas NP-difíceis como cobertura de vértices, caixeiro viajante e soma de subconjuntos;
2) Para o problema de cobertura de vértices é apresentado um algoritmo 2-aproximativo de tempo polinomial;
3) Para o problema do caixeiro viajante é apresentado um algoritmo que constrói um ciclo hamiltoniano a partir de uma árvore geradora mínima, garantindo que o comprimento do ciclo seja no máximo o comprimento do ciclo ótimo
O documento descreve o algoritmo SMA* (Simplified Memory-Bounded A*), que é uma variação do algoritmo A* projetada para lidar com restrições de memória. O SMA* explora os nós da fronteira de maneira semelhante ao A*, mas pode esquecer nós antigos para liberar memória quando necessário, garantindo assim que sempre encontre a solução ótima se houver espaço suficiente na memória.
Palestra sobre Javascript realizada no primeiro ciclo do Plano de Geração de Conhecimento realizado em outubro de 2013, no LEMAF - Universidade Federal de Lavras.
O Plano de geração de conhecimento é um trabalho realizado para tutoria de desenvolvedores com estagiários no estudo de tecnologias, com o objetivo de disseminação de conhecimento.
Palestra ministrada por Fernando Simeone, Carlos Eduardo Chessi Melo, Eduardo Assis da Silva e José Henrique Santos Andrade .
### Atualização 20/02/2015
Palestra melhorada, com algumas correções. Reapresentada por Fernando Simeone e Carlos Eduardo Chessi Melo na SETI (Semana de Tecnologia da Informação) na Universidade Federal de Lavras.
Este documento fornece um guia sobre startups. Ele discute definições de startups e requisitos iniciais, ideias e problemas, desenvolvimento do produto, e gerenciamento do produto. O guia oferece conselhos sobre entendendo o problema, desenvolvendo rapidamente, recebendo feedback, atraindo visitantes e ganhando dinheiro.
What is an RPA CoE? Session 2 – CoE RolesDianaGray10
In this session, we will review the players involved in the CoE and how each role impacts opportunities.
Topics covered:
• What roles are essential?
• What place in the automation journey does each role play?
Speaker:
Chris Bolin, Senior Intelligent Automation Architect Anika Systems
ScyllaDB is making a major architecture shift. We’re moving from vNode replication to tablets – fragments of tables that are distributed independently, enabling dynamic data distribution and extreme elasticity. In this keynote, ScyllaDB co-founder and CTO Avi Kivity explains the reason for this shift, provides a look at the implementation and roadmap, and shares how this shift benefits ScyllaDB users.
In our second session, we shall learn all about the main features and fundamentals of UiPath Studio that enable us to use the building blocks for any automation project.
📕 Detailed agenda:
Variables and Datatypes
Workflow Layouts
Arguments
Control Flows and Loops
Conditional Statements
💻 Extra training through UiPath Academy:
Variables, Constants, and Arguments in Studio
Control Flow in Studio
Essentials of Automations: Exploring Attributes & Automation ParametersSafe Software
Building automations in FME Flow can save time, money, and help businesses scale by eliminating data silos and providing data to stakeholders in real-time. One essential component to orchestrating complex automations is the use of attributes & automation parameters (both formerly known as “keys”). In fact, it’s unlikely you’ll ever build an Automation without using these components, but what exactly are they?
Attributes & automation parameters enable the automation author to pass data values from one automation component to the next. During this webinar, our FME Flow Specialists will cover leveraging the three types of these output attributes & parameters in FME Flow: Event, Custom, and Automation. As a bonus, they’ll also be making use of the Split-Merge Block functionality.
You’ll leave this webinar with a better understanding of how to maximize the potential of automations by making use of attributes & automation parameters, with the ultimate goal of setting your enterprise integration workflows up on autopilot.
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Keywords: AI, Containeres, Kubernetes, Cloud Native
Event Link: https://meine.doag.org/events/cloudland/2024/agenda/#agendaId.4211
This talk will cover ScyllaDB Architecture from the cluster-level view and zoom in on data distribution and internal node architecture. In the process, we will learn the secret sauce used to get ScyllaDB's high availability and superior performance. We will also touch on the upcoming changes to ScyllaDB architecture, moving to strongly consistent metadata and tablets.
AI in the Workplace Reskilling, Upskilling, and Future Work.pptxSunil Jagani
Discover how AI is transforming the workplace and learn strategies for reskilling and upskilling employees to stay ahead. This comprehensive guide covers the impact of AI on jobs, essential skills for the future, and successful case studies from industry leaders. Embrace AI-driven changes, foster continuous learning, and build a future-ready workforce.
Read More - https://bit.ly/3VKly70
Must Know Postgres Extension for DBA and Developer during MigrationMydbops
Mydbops Opensource Database Meetup 16
Topic: Must-Know PostgreSQL Extensions for Developers and DBAs During Migration
Speaker: Deepak Mahto, Founder of DataCloudGaze Consulting
Date & Time: 8th June | 10 AM - 1 PM IST
Venue: Bangalore International Centre, Bangalore
Abstract: Discover how PostgreSQL extensions can be your secret weapon! This talk explores how key extensions enhance database capabilities and streamline the migration process for users moving from other relational databases like Oracle.
Key Takeaways:
* Learn about crucial extensions like oracle_fdw, pgtt, and pg_audit that ease migration complexities.
* Gain valuable strategies for implementing these extensions in PostgreSQL to achieve license freedom.
* Discover how these key extensions can empower both developers and DBAs during the migration process.
* Don't miss this chance to gain practical knowledge from an industry expert and stay updated on the latest open-source database trends.
Mydbops Managed Services specializes in taking the pain out of database management while optimizing performance. Since 2015, we have been providing top-notch support and assistance for the top three open-source databases: MySQL, MongoDB, and PostgreSQL.
Our team offers a wide range of services, including assistance, support, consulting, 24/7 operations, and expertise in all relevant technologies. We help organizations improve their database's performance, scalability, efficiency, and availability.
Contact us: info@mydbops.com
Visit: https://www.mydbops.com/
Follow us on LinkedIn: https://in.linkedin.com/company/mydbops
For more details and updates, please follow up the below links.
Meetup Page : https://www.meetup.com/mydbops-databa...
Twitter: https://twitter.com/mydbopsofficial
Blogs: https://www.mydbops.com/blog/
Facebook(Meta): https://www.facebook.com/mydbops/
QR Secure: A Hybrid Approach Using Machine Learning and Security Validation F...AlexanderRichford
QR Secure: A Hybrid Approach Using Machine Learning and Security Validation Functions to Prevent Interaction with Malicious QR Codes.
Aim of the Study: The goal of this research was to develop a robust hybrid approach for identifying malicious and insecure URLs derived from QR codes, ensuring safe interactions.
This is achieved through:
Machine Learning Model: Predicts the likelihood of a URL being malicious.
Security Validation Functions: Ensures the derived URL has a valid certificate and proper URL format.
This innovative blend of technology aims to enhance cybersecurity measures and protect users from potential threats hidden within QR codes 🖥 🔒
This study was my first introduction to using ML which has shown me the immense potential of ML in creating more secure digital environments!
GlobalLogic Java Community Webinar #18 “How to Improve Web Application Perfor...GlobalLogic Ukraine
Під час доповіді відповімо на питання, навіщо потрібно підвищувати продуктивність аплікації і які є найефективніші способи для цього. А також поговоримо про те, що таке кеш, які його види бувають та, основне — як знайти performance bottleneck?
Відео та деталі заходу: https://bit.ly/45tILxj
MySQL InnoDB Storage Engine: Deep Dive - MydbopsMydbops
This presentation, titled "MySQL - InnoDB" and delivered by Mayank Prasad at the Mydbops Open Source Database Meetup 16 on June 8th, 2024, covers dynamic configuration of REDO logs and instant ADD/DROP columns in InnoDB.
This presentation dives deep into the world of InnoDB, exploring two ground-breaking features introduced in MySQL 8.0:
• Dynamic Configuration of REDO Logs: Enhance your database's performance and flexibility with on-the-fly adjustments to REDO log capacity. Unleash the power of the snake metaphor to visualize how InnoDB manages REDO log files.
• Instant ADD/DROP Columns: Say goodbye to costly table rebuilds! This presentation unveils how InnoDB now enables seamless addition and removal of columns without compromising data integrity or incurring downtime.
Key Learnings:
• Grasp the concept of REDO logs and their significance in InnoDB's transaction management.
• Discover the advantages of dynamic REDO log configuration and how to leverage it for optimal performance.
• Understand the inner workings of instant ADD/DROP columns and their impact on database operations.
• Gain valuable insights into the row versioning mechanism that empowers instant column modifications.
AppSec PNW: Android and iOS Application Security with MobSFAjin Abraham
Mobile Security Framework - MobSF is a free and open source automated mobile application security testing environment designed to help security engineers, researchers, developers, and penetration testers to identify security vulnerabilities, malicious behaviours and privacy concerns in mobile applications using static and dynamic analysis. It supports all the popular mobile application binaries and source code formats built for Android and iOS devices. In addition to automated security assessment, it also offers an interactive testing environment to build and execute scenario based test/fuzz cases against the application.
This talk covers:
Using MobSF for static analysis of mobile applications.
Interactive dynamic security assessment of Android and iOS applications.
Solving Mobile app CTF challenges.
Reverse engineering and runtime analysis of Mobile malware.
How to shift left and integrate MobSF/mobsfscan SAST and DAST in your build pipeline.
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
Getting the Most Out of ScyllaDB Monitoring: ShareChat's TipsScyllaDB
ScyllaDB monitoring provides a lot of useful information. But sometimes it’s not easy to find the root of the problem if something is wrong or even estimate the remaining capacity by the load on the cluster. This talk shares our team's practical tips on: 1) How to find the root of the problem by metrics if ScyllaDB is slow 2) How to interpret the load and plan capacity for the future 3) Compaction strategies and how to choose the right one 4) Important metrics which aren’t available in the default monitoring setup.
"Scaling RAG Applications to serve millions of users", Kevin GoedeckeFwdays
How we managed to grow and scale a RAG application from zero to thousands of users in 7 months. Lessons from technical challenges around managing high load for LLMs, RAGs and Vector databases.
119. Conclusão
• Counting Sort é um algoritmo de complexidade
linear;
• Não respeita o limite inferior 𝝮 (n lg n) aplicado a
algoritmos baseados em comparações;
120. Conclusão
• Counting Sort é um algoritmo de complexidade
linear;
• Não respeita o limite inferior 𝝮 (n lg n) aplicado a
algoritmos baseados em comparações;
• Possui complexidade O(n) quando K ≤ n;
121. Conclusão
• Counting Sort é um algoritmo de complexidade
linear;
• Não respeita o limite inferior 𝝮 (n lg n) aplicado a
algoritmos baseados em comparações;
• Possui complexidade O(n) quando K ≤ n;
• É um algoritmo estável, valores iguais
permanecem na mesma ordem entre si.
123. Referências
CORMEN, T. H.; LEISERSON, C. E.; RIVEST, R. L.; STEIN, C.
Introduction to Algorithms, Third Edition. 3rd. ed. [S.l.]: The
MIT Press, 2009. ISBN 0262033844, 9780262033848.
!
Gonzaga de Oliveira, S.L. . Algoritmos e seus fundamentos. 1.
ed. Lavras: Editora UFLA, 2011. v. 300. 440p .