Es tracta de fer sèries de nombres naturals consecutius de forma que cada nombre sumat al seu anterior doni un quadrat perfecte i sumat al seu posterior també. http://calaix2.blogspot.com.es/2018/05/fem-series-de-quadrats.html
Es tracta de fer sèries de nombres naturals consecutius de forma que cada nombre sumat al seu anterior doni un quadrat perfecte i sumat al seu posterior també. http://calaix2.blogspot.com.es/2018/05/fem-series-de-quadrats.html
Globelink International reveals statistics on winter sports injuries and warns travellers about the dangers of adventurous winter vacation.
New research by Globelink has found out the most dangerous countries for fans of winter activities and the categories of tourist that are more likely to get injured. The infographic also shows how serious injuries obtained while skiing or snowboarding can be, how much they can cost travellers if something goes wrong on their winter vacation and why it is crucial to take out winter sports travel insurance.
This document discusses depth-first search (DFS) algorithms and their applications to finding spanning trees and articulation points in graphs. It begins by explaining how DFS generalizes preorder tree traversal and avoids cycles in arbitrary graphs by marking visited vertices. DFS takes O(V+E) time on graphs. The document then explains how DFS can be used to find a depth-first spanning tree and identify biconnected components and articulation points via numbering schemes like num(v) and low(v).
This document summarizes an algorithm for distributed depth-first search (DDFS) of a graph. It begins with background on depth-first search and discusses previous DDFS algorithms. It then presents a new DDFS algorithm that uses dynamic backtracking to reduce the number of return messages. Each node tracks its lowest ancestor split point to bypass returning messages up the tree until that point. The algorithm constructs the DFS tree by exploring neighbors with forward messages and backing up with return messages. Its message and time complexity is between |V| and 2|V|-2, an improvement over previous DDFS algorithms.
The document discusses different types of problem-solving agents and search algorithms. It describes single-state, sensorless, contingency, and exploration problem types. It also summarizes common uninformed search strategies like breadth-first search, uniform-cost search, depth-first search, depth-limited search, and iterative deepening search and analyzes their properties in terms of completeness, time complexity, space complexity, and optimality. Examples of problems that can be modeled as state space searches are also provided, like the vacuum world, 8-puzzle, and robotic assembly problems.
Globelink International reveals statistics on winter sports injuries and warns travellers about the dangers of adventurous winter vacation.
New research by Globelink has found out the most dangerous countries for fans of winter activities and the categories of tourist that are more likely to get injured. The infographic also shows how serious injuries obtained while skiing or snowboarding can be, how much they can cost travellers if something goes wrong on their winter vacation and why it is crucial to take out winter sports travel insurance.
This document discusses depth-first search (DFS) algorithms and their applications to finding spanning trees and articulation points in graphs. It begins by explaining how DFS generalizes preorder tree traversal and avoids cycles in arbitrary graphs by marking visited vertices. DFS takes O(V+E) time on graphs. The document then explains how DFS can be used to find a depth-first spanning tree and identify biconnected components and articulation points via numbering schemes like num(v) and low(v).
This document summarizes an algorithm for distributed depth-first search (DDFS) of a graph. It begins with background on depth-first search and discusses previous DDFS algorithms. It then presents a new DDFS algorithm that uses dynamic backtracking to reduce the number of return messages. Each node tracks its lowest ancestor split point to bypass returning messages up the tree until that point. The algorithm constructs the DFS tree by exploring neighbors with forward messages and backing up with return messages. Its message and time complexity is between |V| and 2|V|-2, an improvement over previous DDFS algorithms.
The document discusses different types of problem-solving agents and search algorithms. It describes single-state, sensorless, contingency, and exploration problem types. It also summarizes common uninformed search strategies like breadth-first search, uniform-cost search, depth-first search, depth-limited search, and iterative deepening search and analyzes their properties in terms of completeness, time complexity, space complexity, and optimality. Examples of problems that can be modeled as state space searches are also provided, like the vacuum world, 8-puzzle, and robotic assembly problems.
The document discusses various graph algorithms and representations including:
- Adjacency lists and matrices for representing graphs
- Breadth-first search (BFS) which explores edges from a source vertex s level-by-level
- Depth-first search (DFS) which explores "deeper" first, producing a depth-first forest
- Classifying edges as tree, back, forward, or cross based on vertex colors in DFS
- Topological sorting of directed acyclic graphs (DAGs)
- Strongly connected components (SCCs) in directed graphs and using the transpose
Graph Traversal Algorithms - Depth First Search TraversalAmrinder Arora
This document discusses graph traversal techniques, specifically depth-first search (DFS) and breadth-first search (BFS). It provides pseudocode for DFS and explains key properties like edge classification, time complexity of O(V+E), and applications such as finding connected components and articulation points.
Analysis of Feature Selection Algorithms (Branch & Bound and Beam search)Parinda Rajapaksha
Branch & Bound and Beam search algorithms were illustrated according to the feature selection domain. Presentation is structured as follows,
- Motivation
- Introduction
- Analysis
- Algorithm
- Pseudo Code
- Illustration of examples
- Applications
- Observations and Recommendations
- Comparison between two algorithms
- References