- published: 05 Mar 2016
- views: 8675
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Graph Theory in Data Structure(Hindi, English) with Example for students of IP University Delhi and Other Universities, Engineering, MCA, BCA, B.Sc, M.Sc Colleges.
- published: 20 Jun 2016
- views: 283
Introduction to graph theory terminology. The pace is very fast, so this is geared for those who have had prior exposure to the content. Second installment of Data Structures in 5 Minutes.
For clearer photos of the whiteboard:
Graphs Photo 1: http://i1160.photobucket.com/albums/q499/dicksontsai/Public%20photos/Data%20Structures%20in%205%20Minutes/IMG_2591_zps8b37b878.jpg
Graphs Photo 2:
http://i1160.photobucket.com/albums/q499/dicksontsai/Public%20photos/Data%20Structures%20in%205%20Minutes/IMG_2592_zpsec253f75.jpg
Several comments:
* The top of the adjacency matrix got cut off, but it should be C D E F.
* Pseudocode for DFS and BFS can be easily searched on the Internet. Choosing which vertex to explore first is arbitrary. The important distinction is searching deeply vs. searching one edge away at a time from the start.
* We did not have the time to go over the Königsberg problem, which is the problem associated with Euler's seminal work on graph theory. It's a fun application of graphs, and should also be well-documented on the internet.
*Please leve any constructive feedback below. Thanks for watching!
DISCLAIMER: This video in no way comprehensively covers the lecture notes, nor are considered "official" by any instructor. I am undertaking this series as a way to help study for the final. Please refer to the lecture notes themselves as the authoritative source. For these videos, I try my best to adhere to fair use: No part of this video may be used for any monetary gain.
- published: 04 May 2013
- views: 28557
This is the fourth in a series of videos about the graph data structure. This is an explanation of Dijkstra’s algorithm for finding the shortest path between one vertex in a graph and another. Indeed, this explains how Dijkstra’s shortest path algorithm generates a set of information that includes the shortest paths from a starting vertex and every other vertex in the graph. It also mentions why Dijkstra’s shortest path algorithm is an example of a greedy algorithm.
- published: 07 May 2016
- views: 4725
CS 61B: Data Structures - Fall 2006
Instructor Jonathan Shewchuk
Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language.
http://www.cs.berkeley.edu
- published: 30 Jul 2008
- views: 64517
This is the first in a series of videos about the graph data structure. It mentions the applications of graphs, defines various terminology associated with graphs, and describes how a graph can be represented programmatically by means of adjacency lists or an adjacency matrix.
- published: 27 Apr 2016
- views: 929
Graphs are collections of things and the relationships or connections between them. The data in a graph are called nodes or vertices. The connections between the nodes are called edges.
🐦 Beau Carnes on Twitter: https://twitter.com/carnesbeau
⭐JavaScript Tutorials Playlists⭐
▶JavaScript Basics: https://www.youtube.com/playlist?list=PLWKjhJtqVAbk2qRZtWSzCIN38JC_NdhW5
▶Data Structures and Algorithms: https://www.youtube.com/playlist?list=PLWKjhJtqVAbkso-IbgiiP48n-O-JQA9PJ
▶Design Patterns: https://www.youtube.com/playlist?list=PLWKjhJtqVAbnZtkAI3BqcYxKnfWn_C704
▶ES6: https://www.youtube.com/playlist?list=PLWKjhJtqVAbljtmmeS0c-CEl2LdE-eR_F
▶Clean Code: https://www.youtube.com/playlist?list=PLWKjhJtqVAbkK24EaPurzMq0-kw5U9pJh
-
We're busy people who learn to code, then practice by building projects for nonprofits. Learn Full-stack JavaScript, build a portfolio, and get great references with our open source community.
Join our community at https://freecodecamp.com
Read great tech articles at https://medium.freecodecamp.com
- published: 21 May 2017
- views: 297
This video introduces graphs, used in computing to store and manipulate networks--of people, computers, cities, etc. The lesson goes over the different kinds of graphs--undirected, directed, and weighted variations of both--and shows how they can be stored in a program using a simple structure called the adjacency matrix. This video is part of a series on data structures and algorithms by Sesh Venugopal. http://www.cs.rutgers.edu/~venugopa
- published: 31 May 2013
- views: 39976
First demonstration of an interactive 3D fly-over of a city. The data is a point-cloud originating from an Aerial LIDAR scan. This particular dataset is a part of the city of Middelburg, made available in the AHN2 test data set [2]. Colors are reconstructed from 2D Texture, so these are not the directly scanned colors.
We generate a level-of-detail data structure in OpenSceneGraph to dynamically show different densities of points, and is loading over the network. With this ~20 Million point cloud, update rates are between 15~60 fps depending on how many points are visible in a certain view. We are optimizing the datastructure to balance frame rate with visual quality. 3D Navigation is done with a SpaceMouse device.
Point Cloud visualizations have nice visual quality, especially under motion and 3D stereo, both of which are used in the VR systems in our group [1].
Please note that these visualizations are inherently difficult for regular video compression algorithms to process without introducing disturbing visual artifacts. Download the wmv file below for a higher-quality impression, or see a static screenshot [3].
[1] http://visualisation.tudelft.nl/VRVis
[2] http://www.ahn.nl/
[3] http://graphics.tudelft.nl/~gerwin/media/3dtopo/Screenshot_pointcloud.png
- published: 13 Feb 2009
- views: 4147
Screencast of Andromeda.
Advanced tool for interactive browsing of video annotations
Concept Cloud
Shows the concepts with more instances in a cloud view
Graph browsing
Graph representation of semantic data structure
Multiple automatic layout algorithm for spatial positioning and manual drag & drop
Multimedia content access
Thumbnails view of the intances of each concept
Access to video metadata and playing from the annotation frame
User generated content integration
Access to social content related to ontology concepts.
Images from Flickr, videos from YouTube and real time tweets from Twitter
--
Marco Bertini, Andrea Ferracani, Nicola Martorana, Marco Meoni, Giuseppe Serra.
MICC - Media Integration Communication Center - Firenze - Italia (Florence - Italy).
- published: 18 May 2010
- views: 120
Graph (abstract data type)
In computer science, a graph is an abstract data type that is meant to implement the undirected graph and directed graph concepts from mathematics.
A graph data structure consists of a finite (and possibly mutable) set of vertices or nodes or points, together with a set of unordered pairs of these vertices for an undirected graph or a set of ordered pairs for a directed graph. These pairs are known as edges, arcs, or lines for an undirected graph and as arrows, directed edges, directed arcs, or directed lines for a directed graph. The vertices may be part of the graph structure, or may be external entities represented by integer indices or references.
A graph data structure may also associate to each edge some edge value, such as a symbolic label or a numeric attribute (cost, capacity, length, etc.).
Operations
The basic operations provided by a graph data structure G usually include:
adjacent(G, x, y): tests whether there is an edge from the vertices x to y;neighbors(G, x): lists all vertices y such that there is an edge from the vertices x to y;
This page contains text from Wikipedia, the Free Encyclopedia -
https://wn.com/Graph_(abstract_data_type)
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
Data structure
In computer science, a data structure is a particular way of organizing data in a computer so that it can be used efficiently. Data structures can implement one or more particular abstract data types (ADT), which are the means of specifying the contract of operations and their complexity. In comparison, a data structure is a concrete implementation of the contract provided by an ADT.
Different kinds of data structures are suited to different kinds of applications, and some are highly specialized to specific tasks. For example, relational databases most commonly use B-tree indexes for data retrieval, while compiler implementations usually use hash tables to look up identifiers.
Data structures provide a means to manage large amounts of data efficiently for uses such as large databases and internet indexing services. Usually, efficient data structures are key to designing efficient algorithms. Some formal design methods and programming languages emphasize data structures, rather than algorithms, as the key organizing factor in software design. Storing and retrieving can be carried out on data stored in both main memory and in secondary memory.
This page contains text from Wikipedia, the Free Encyclopedia -
https://wn.com/Data_structure
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
Data
Data (/ˈdeɪtə/ DAY-tə, /ˈdætə/ DA-tə, or /ˈdɑːtə/ DAH-tə) is a set of values of qualitative or quantitative variables; restated, pieces of data are individual pieces of information. Data is measured, collected and reported, and analyzed, whereupon it can be visualized using graphs or images. Data as a general concept refers to the fact that some existing information or knowledge is represented or coded in some form suitable for better usage or processing.
Raw data, i.e. unprocessed data, is a collection of numbers, characters; data processing commonly occurs by stages, and the "processed data" from one stage may be considered the "raw data" of the next. Field data is raw data that is collected in an uncontrolled in situ environment. Experimental data is data that is generated within the context of a scientific investigation by observation and recording.
The Latin word "data" is the plural of "datum", and still may be used as a plural noun in this sense. Nowadays, though, "data" is most commonly used in the singular, as a mass noun (like "information", "sand" or "rain").
This page contains text from Wikipedia, the Free Encyclopedia -
https://wn.com/Data
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
Graph
Graph may refer to:
In information science:
In mathematics:
- Graph theory, the study of such graphs
In computer science:
Other uses:
See also
This page contains text from Wikipedia, the Free Encyclopedia -
https://wn.com/Graph
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
This article is licensed under the Creative Commons Attribution-ShareAlike 3.0 Unported License, which means that you can copy and modify it as long as the entire work (including additions) remains under this license.
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40:26Chapter 51 Introduction to Graphs in Data Structure Hindi
Chapter 51 Introduction to Graphs in Data Structure Hindi -
4:17Graph Theory in Data Structure(Hindi, English) with Example
Graph Theory in Data Structure(Hindi, English) with ExampleGraph Theory in Data Structure(Hindi, English) with Example
Graph Theory in Data Structure(Hindi, English) with Example for students of IP University Delhi and Other Universities, Engineering, MCA, BCA, B.Sc, M.Sc Colleges. -
6:14Graphs - Data Structures in 5 Minutes
Graphs - Data Structures in 5 MinutesGraphs - Data Structures in 5 Minutes
Introduction to graph theory terminology. The pace is very fast, so this is geared for those who have had prior exposure to the content. Second installment of Data Structures in 5 Minutes. For clearer photos of the whiteboard: Graphs Photo 1: http://i1160.photobucket.com/albums/q499/dicksontsai/Public%20photos/Data%20Structures%20in%205%20Minutes/IMG_2591_zps8b37b878.jpg Graphs Photo 2: http://i1160.photobucket.com/albums/q499/dicksontsai/Public%20photos/Data%20Structures%20in%205%20Minutes/IMG_2592_zpsec253f75.jpg Several comments: * The top of the adjacency matrix got cut off, but it should be C D E F. * Pseudocode for DFS and BFS can be easily searched on the Internet. Choosing which vertex to explore first is arbitrary. The important distinction is searching deeply vs. searching one edge away at a time from the start. * We did not have the time to go over the Königsberg problem, which is the problem associated with Euler's seminal work on graph theory. It's a fun application of graphs, and should also be well-documented on the internet. *Please leve any constructive feedback below. Thanks for watching! DISCLAIMER: This video in no way comprehensively covers the lecture notes, nor are considered "official" by any instructor. I am undertaking this series as a way to help study for the final. Please refer to the lecture notes themselves as the authoritative source. For these videos, I try my best to adhere to fair use: No part of this video may be used for any monetary gain. -
10:52Graph Data Structure 4. Dijkstra’s Shortest Path Algorithm
Graph Data Structure 4. Dijkstra’s Shortest Path AlgorithmGraph Data Structure 4. Dijkstra’s Shortest Path Algorithm
This is the fourth in a series of videos about the graph data structure. This is an explanation of Dijkstra’s algorithm for finding the shortest path between one vertex in a graph and another. Indeed, this explains how Dijkstra’s shortest path algorithm generates a set of information that includes the shortest paths from a starting vertex and every other vertex in the graph. It also mentions why Dijkstra’s shortest path algorithm is an example of a greedy algorithm. -
50:08CS 61B Lecture 27: Graphs
CS 61B Lecture 27: GraphsCS 61B Lecture 27: Graphs
CS 61B: Data Structures - Fall 2006 Instructor Jonathan Shewchuk Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language. http://www.cs.berkeley.edu -
56:42Data Structures - Trees and Graphs
Data Structures - Trees and Graphs -
7:59Graph Data Structure 1. Terminology and Representation (algorithms)
Graph Data Structure 1. Terminology and Representation (algorithms)Graph Data Structure 1. Terminology and Representation (algorithms)
This is the first in a series of videos about the graph data structure. It mentions the applications of graphs, defines various terminology associated with graphs, and describes how a graph can be represented programmatically by means of adjacency lists or an adjacency matrix. -
4:53Graph Data Structure Intro - Beau teaches JavaScript
Graph Data Structure Intro - Beau teaches JavaScriptGraph Data Structure Intro - Beau teaches JavaScript
Graphs are collections of things and the relationships or connections between them. The data in a graph are called nodes or vertices. The connections between the nodes are called edges. 🐦 Beau Carnes on Twitter: https://twitter.com/carnesbeau ⭐JavaScript Tutorials Playlists⭐ ▶JavaScript Basics: https://www.youtube.com/playlist?list=PLWKjhJtqVAbk2qRZtWSzCIN38JC_NdhW5 ▶Data Structures and Algorithms: https://www.youtube.com/playlist?list=PLWKjhJtqVAbkso-IbgiiP48n-O-JQA9PJ ▶Design Patterns: https://www.youtube.com/playlist?list=PLWKjhJtqVAbnZtkAI3BqcYxKnfWn_C704 ▶ES6: https://www.youtube.com/playlist?list=PLWKjhJtqVAbljtmmeS0c-CEl2LdE-eR_F ▶Clean Code: https://www.youtube.com/playlist?list=PLWKjhJtqVAbkK24EaPurzMq0-kw5U9pJh - We're busy people who learn to code, then practice by building projects for nonprofits. Learn Full-stack JavaScript, build a portfolio, and get great references with our open source community. Join our community at https://freecodecamp.com Read great tech articles at https://medium.freecodecamp.com -
32:37Chapter 52 Representation of Graph in Data Structure hindi
Chapter 52 Representation of Graph in Data Structure hindi -
16:28Graphs - Types and Representation
Graphs - Types and RepresentationGraphs - Types and Representation
This video introduces graphs, used in computing to store and manipulate networks--of people, computers, cities, etc. The lesson goes over the different kinds of graphs--undirected, directed, and weighted variations of both--and shows how they can be stored in a program using a simple structure called the adjacency matrix. This video is part of a series on data structures and algorithms by Sesh Venugopal. http://www.cs.rutgers.edu/~venugopa -
0:28Interactive 3D visualization of Point Clouds
Interactive 3D visualization of Point CloudsInteractive 3D visualization of Point Clouds
First demonstration of an interactive 3D fly-over of a city. The data is a point-cloud originating from an Aerial LIDAR scan. This particular dataset is a part of the city of Middelburg, made available in the AHN2 test data set [2]. Colors are reconstructed from 2D Texture, so these are not the directly scanned colors. We generate a level-of-detail data structure in OpenSceneGraph to dynamically show different densities of points, and is loading over the network. With this ~20 Million point cloud, update rates are between 15~60 fps depending on how many points are visible in a certain view. We are optimizing the datastructure to balance frame rate with visual quality. 3D Navigation is done with a SpaceMouse device. Point Cloud visualizations have nice visual quality, especially under motion and 3D stereo, both of which are used in the VR systems in our group [1]. Please note that these visualizations are inherently difficult for regular video compression algorithms to process without introducing disturbing visual artifacts. Download the wmv file below for a higher-quality impression, or see a static screenshot [3]. [1] http://visualisation.tudelft.nl/VRVis [2] http://www.ahn.nl/ [3] http://graphics.tudelft.nl/~gerwin/media/3dtopo/Screenshot_pointcloud.png -
3:35Andromeda video browsing
Andromeda video browsingAndromeda video browsing
Screencast of Andromeda. Advanced tool for interactive browsing of video annotations Concept Cloud Shows the concepts with more instances in a cloud view Graph browsing Graph representation of semantic data structure Multiple automatic layout algorithm for spatial positioning and manual drag & drop Multimedia content access Thumbnails view of the intances of each concept Access to video metadata and playing from the annotation frame User generated content integration Access to social content related to ontology concepts. Images from Flickr, videos from YouTube and real time tweets from Twitter -- Marco Bertini, Andrea Ferracani, Nicola Martorana, Marco Meoni, Giuseppe Serra. MICC - Media Integration Communication Center - Firenze - Italia (Florence - Italy). -
55:16RFC: AvocadoDB Query Language
RFC: AvocadoDB Query LanguageRFC: AvocadoDB Query Language
AvocacoDB is a young nosql open source database. The REST API for AvocadoDB is already available and stable and people are writing APIs using it. AvocadoDB offers more complex data structures like graphs and lists REST is not enough. We implemented a first version of a query language some time ago which is very similar to SQL and UNQL. Then we realized that this approach was not completely satisfying as some queries cannot expressed very well with it, especially multi-valued attributes/lists. UNQL addresses this partly, but does not go far enough. Another issue are graphs. AvocadoDB supports querying graphs, neither SQL nor UNQL offer any "natural" graph traversal facilities. In this talk, Jan Steemann, presents the concept for AvocadoDB's query language. Please leave your comments on avocadodb.org or via twitter @avcoadodb -
31:530321 - Getting beer in and out of Neo4j
0321 - Getting beer in and out of Neo4j0321 - Getting beer in and out of Neo4j
DATASET: https://docs.google.com/spreadsheet/ccc?key=0Ah0qwaznhrupdEpxdXBCSmZuUjA2TTJZRm1ORy0zcUE Graph Databases have long been the realm of highly technical IT development professionals. But those days are gone. In this non-technical seminar, hosted by one of Neo Technology's non-technical staff, we will explain just how easy it is for average business people to start using graph databases, and get value from it. The subject of this webinar will be tasty as well: Belgian Beers - and how we easily got this dataset into Neo4j. We will also explore what this Neo4j database delivers, and how even this simple graph oriented data structure immediately yielded value for a non-technical person. Check out an extensive blog post about it here: http://blog.neo4j.org/2013/01/fun-with-beer-and-graphs.html
-
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Graph Theory in Data Structure(Hindi, English) with Example
Graph Theory in Data Structure(Hindi, English) with Example for students of IP University Delhi and Other Universities, Engineering, MCA, BCA, B.Sc, M.Sc Colleges.
published: 20 Jun 2016 -
Graphs - Data Structures in 5 Minutes
Introduction to graph theory terminology. The pace is very fast, so this is geared for those who have had prior exposure to the content. Second installment of Data Structures in 5 Minutes. For clearer photos of the whiteboard: Graphs Photo 1: http://i1160.photobucket.com/albums/q499/dicksontsai/Public%20photos/Data%20Structures%20in%205%20Minutes/IMG_2591_zps8b37b878.jpg Graphs Photo 2: http://i1160.photobucket.com/albums/q499/dicksontsai/Public%20photos/Data%20Structures%20in%205%20Minutes/IMG_2592_zpsec253f75.jpg Several comments: * The top of the adjacency matrix got cut off, but it should be C D E F. * Pseudocode for DFS and BFS can be easily searched on the Internet. Choosing which vertex to explore first is arbitrary. The important distinction is searching deeply vs. searching one ...
published: 04 May 2013 -
Graph Data Structure 4. Dijkstra’s Shortest Path Algorithm
This is the fourth in a series of videos about the graph data structure. This is an explanation of Dijkstra’s algorithm for finding the shortest path between one vertex in a graph and another. Indeed, this explains how Dijkstra’s shortest path algorithm generates a set of information that includes the shortest paths from a starting vertex and every other vertex in the graph. It also mentions why Dijkstra’s shortest path algorithm is an example of a greedy algorithm.
published: 07 May 2016 -
CS 61B Lecture 27: Graphs
CS 61B: Data Structures - Fall 2006 Instructor Jonathan Shewchuk Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language. http://www.cs.berkeley.edu
published: 30 Jul 2008 -
-
Graph Data Structure 1. Terminology and Representation (algorithms)
This is the first in a series of videos about the graph data structure. It mentions the applications of graphs, defines various terminology associated with graphs, and describes how a graph can be represented programmatically by means of adjacency lists or an adjacency matrix.
published: 27 Apr 2016 -
Graph Data Structure Intro - Beau teaches JavaScript
Graphs are collections of things and the relationships or connections between them. The data in a graph are called nodes or vertices. The connections between the nodes are called edges. 🐦 Beau Carnes on Twitter: https://twitter.com/carnesbeau ⭐JavaScript Tutorials Playlists⭐ ▶JavaScript Basics: https://www.youtube.com/playlist?list=PLWKjhJtqVAbk2qRZtWSzCIN38JC_NdhW5 ▶Data Structures and Algorithms: https://www.youtube.com/playlist?list=PLWKjhJtqVAbkso-IbgiiP48n-O-JQA9PJ ▶Design Patterns: https://www.youtube.com/playlist?list=PLWKjhJtqVAbnZtkAI3BqcYxKnfWn_C704 ▶ES6: https://www.youtube.com/playlist?list=PLWKjhJtqVAbljtmmeS0c-CEl2LdE-eR_F ▶Clean Code: https://www.youtube.com/playlist?list=PLWKjhJtqVAbkK24EaPurzMq0-kw5U9pJh - We're busy people who learn to code, then practice by building p...
published: 21 May 2017 -
-
Graphs - Types and Representation
This video introduces graphs, used in computing to store and manipulate networks--of people, computers, cities, etc. The lesson goes over the different kinds of graphs--undirected, directed, and weighted variations of both--and shows how they can be stored in a program using a simple structure called the adjacency matrix. This video is part of a series on data structures and algorithms by Sesh Venugopal. http://www.cs.rutgers.edu/~venugopa
published: 31 May 2013 -
Interactive 3D visualization of Point Clouds
First demonstration of an interactive 3D fly-over of a city. The data is a point-cloud originating from an Aerial LIDAR scan. This particular dataset is a part of the city of Middelburg, made available in the AHN2 test data set [2]. Colors are reconstructed from 2D Texture, so these are not the directly scanned colors. We generate a level-of-detail data structure in OpenSceneGraph to dynamically show different densities of points, and is loading over the network. With this ~20 Million point cloud, update rates are between 15~60 fps depending on how many points are visible in a certain view. We are optimizing the datastructure to balance frame rate with visual quality. 3D Navigation is done with a SpaceMouse device. Point Cloud visualizations have nice visual quality, especially under mo...
published: 13 Feb 2009 -
Andromeda video browsing
Screencast of Andromeda. Advanced tool for interactive browsing of video annotations Concept Cloud Shows the concepts with more instances in a cloud view Graph browsing Graph representation of semantic data structure Multiple automatic layout algorithm for spatial positioning and manual drag & drop Multimedia content access Thumbnails view of the intances of each concept Access to video metadata and playing from the annotation frame User generated content integration Access to social content related to ontology concepts. Images from Flickr, videos from YouTube and real time tweets from Twitter -- Marco Bertini, Andrea Ferracani, Nicola Martorana, Marco Meoni, Giuseppe Serra. MICC - Media Integration Communication Center - Firenze - Italia (Florence - Italy).
published: 18 May 2010 -
RFC: AvocadoDB Query Language
AvocacoDB is a young nosql open source database. The REST API for AvocadoDB is already available and stable and people are writing APIs using it. AvocadoDB offers more complex data structures like graphs and lists REST is not enough. We implemented a first version of a query language some time ago which is very similar to SQL and UNQL. Then we realized that this approach was not completely satisfying as some queries cannot expressed very well with it, especially multi-valued attributes/lists. UNQL addresses this partly, but does not go far enough. Another issue are graphs. AvocadoDB supports querying graphs, neither SQL nor UNQL offer any "natural" graph traversal facilities. In this talk, Jan Steemann, presents the concept for AvocadoDB's query language. Please leave your comments on a...
published: 18 Apr 2012 -
0321 - Getting beer in and out of Neo4j
DATASET: https://docs.google.com/spreadsheet/ccc?key=0Ah0qwaznhrupdEpxdXBCSmZuUjA2TTJZRm1ORy0zcUE Graph Databases have long been the realm of highly technical IT development professionals. But those days are gone. In this non-technical seminar, hosted by one of Neo Technology's non-technical staff, we will explain just how easy it is for average business people to start using graph databases, and get value from it. The subject of this webinar will be tasty as well: Belgian Beers - and how we easily got this dataset into Neo4j. We will also explore what this Neo4j database delivers, and how even this simple graph oriented data structure immediately yielded value for a non-technical person. Check out an extensive blog post about it here: http://blog.neo4j.org/2013/01/fun-with-beer-and-graph...
published: 21 Mar 2013 -
ChiSC: Max DeMarzi - Is Your Problem a Graph Problem?
You learned early on that one of the secrets to programming is using the right data structure. Learn the "secret" to the graph database, Neo4j. Learn when to use this tool for the job and when to stick to your relational database. See how different "Domain Specific Languages" help you approach your problems in different ways. Max De Marzi, is a seasoned web developer. He started building websites in 1996 and has worked with Ruby on Rails since 2006. The web forced Max to wear many hats and master a wide range of technologies. He can be a system admin, database developer, graphic designer, back-end engineer and data scientist in the course of one afternoon. Max is a graph database enthusiast. He built the Neography Ruby Gem, a rest api wrapper to the Neo4j Graph Database. He is addicted...
published: 16 Jan 2013 -
DNA Sequence Filtering and Analysis - Jason Pell
Within the past decade, the amount of DNA sequencing data generated from next-generation sequencing platforms has exploded. As a result, biology has been propelled as a field in need of better scaling algorithms and data structures to efficiently analyze data. Jason Pell will present features of khmer, a software package developed in the GED Lab at Michigan State University, to efficiently filter and analyze data generated by next-generation sequencing platforms. More specifically, he will present the use of the Bloom filter and Counting Bloom filter data structures for assembly graph traversal and k-mer counting, respectively. The khmer software package is written primarily in C++ and wrapped in Python. It is released under the BSD license and is available at http://www.github.com/ged-lab...
published: 08 Nov 2012 -
After Effects Template - Infographics Infocharts Package
http://videohive.net/item/infographics-infocharts-package/3945627?sso?ref=creativestone92 INFOCHARTS Package (AE CS 5.0, Full HD) is an expression-based After Effects template that provides quick and flexible creative solutions for infographics. Combine easily several types of graphs (pie charts, line graph, bar graphs, concentric lines, worldmap with all countries, area graphs….). Add to the final composition one or several included widgets (markers, averages, loaders, panels…). Built to be intuitive and flexible, and no prior knowledge of AE expressions is necessary. Create simple and elegant infographics with InfoCharts Package from included Charts systems.Custom expressions were created to make entering data as easy as possible. All expressions have been universalized to work in any l...
published: 20 May 2013 -
The Graph Traversal Programming Pattern by Marko Rodriguez
Slides: http://www.slideshare.net/slidarko/graph-windycitydb2010 A graph is a structure composed of a set of vertices (i.e. nodes, dots) connected to one another by a set of edges (i.e. links, lines). The concept of a graph has been around since the late 19th century, however, only in recent decades has there been a strong resurgence in the development of both graph theories and applications. In applied computing, since the late 1960s, the interlinked table structure of the relational database has been the predominant information storage and retrieval paradigm. With the growth of graph/network-based data and the need to efficiently process such data, new data management systems have been developed. In contrast to the index-intensive, set-theoretic operations of relational databases, graph...
published: 09 Jul 2010 -
Autopilot Visualizer - A data visualization application for exploring IT infrastructure automation
The AutoPilot Visualizer is a software tool for exploring complex data structures used in the automation of maintenance and supervision of large-scale IT infrastructures. The environment is a visual front-end to the underlying AutoPilot system by Arago, a company that specialises in the automation of data environments using artificial intelligence techniques and graph-based algorithms. FELD was commissioned to develop a visualisation application which represents the data in a way that makes the system easier to navigate and more intuitive to understand – both for system specialists and for non-expert users. The environment is centered around the graph-browser where the main structure is clustered into several subgraphs, each representing a different part of the system. All events tha...
published: 28 Nov 2013 -
Houdini and Mathematica
This is really cool! We can connect Mathematica to Houdini and use many of its powerful capabilities. In this example a scattering of points is created and then we find their nearest neighbours (VEX) and draw their connections (Python). I then send this as a graph structure to Mathematica and compute the clustering based on the topology of the network, the metric being the steps that connect one node to another. That together with the shortest path between two points is then send back to Houdini and displayed. The general procedure to send and get data from Houdini to Mathematica is as follows: -Prepare your data in Houdini by sending it through python and export in a suitable format. In this case a .tgf for the nodes and connections -Let the Python script call the external mathscript ...
published: 07 Dec 2012
Chapter 51 Introduction to Graphs in Data Structure Hindi
- Order: Reorder
- Duration: 40:26
- Updated: 05 Mar 2016
- views: 8675
Graph Theory in Data Structure(Hindi, English) with Example
- Order: Reorder
- Duration: 4:17
- Updated: 20 Jun 2016
- views: 283
Graph Theory in Data Structure(Hindi, English) with Example for students of IP University Delhi and Other Universities, Engineering, MCA, BCA, B.Sc, M.Sc Colleg...
Graph Theory in Data Structure(Hindi, English) with Example for students of IP University Delhi and Other Universities, Engineering, MCA, BCA, B.Sc, M.Sc Colleges.
https://wn.com/Graph_Theory_In_Data_Structure(Hindi,_English)_With_Example
Graph Theory in Data Structure(Hindi, English) with Example for students of IP University Delhi and Other Universities, Engineering, MCA, BCA, B.Sc, M.Sc Colleges.
- published: 20 Jun 2016
- views: 283
Graphs - Data Structures in 5 Minutes
- Order: Reorder
- Duration: 6:14
- Updated: 04 May 2013
- views: 28557
Introduction to graph theory terminology. The pace is very fast, so this is geared for those who have had prior exposure to the content. Second installment of D...
Introduction to graph theory terminology. The pace is very fast, so this is geared for those who have had prior exposure to the content. Second installment of Data Structures in 5 Minutes.
For clearer photos of the whiteboard:
Graphs Photo 1: http://i1160.photobucket.com/albums/q499/dicksontsai/Public%20photos/Data%20Structures%20in%205%20Minutes/IMG_2591_zps8b37b878.jpg
Graphs Photo 2:
http://i1160.photobucket.com/albums/q499/dicksontsai/Public%20photos/Data%20Structures%20in%205%20Minutes/IMG_2592_zpsec253f75.jpg
Several comments:
* The top of the adjacency matrix got cut off, but it should be C D E F.
* Pseudocode for DFS and BFS can be easily searched on the Internet. Choosing which vertex to explore first is arbitrary. The important distinction is searching deeply vs. searching one edge away at a time from the start.
* We did not have the time to go over the Königsberg problem, which is the problem associated with Euler's seminal work on graph theory. It's a fun application of graphs, and should also be well-documented on the internet.
*Please leve any constructive feedback below. Thanks for watching!
DISCLAIMER: This video in no way comprehensively covers the lecture notes, nor are considered "official" by any instructor. I am undertaking this series as a way to help study for the final. Please refer to the lecture notes themselves as the authoritative source. For these videos, I try my best to adhere to fair use: No part of this video may be used for any monetary gain.
https://wn.com/Graphs_Data_Structures_In_5_Minutes
Introduction to graph theory terminology. The pace is very fast, so this is geared for those who have had prior exposure to the content. Second installment of Data Structures in 5 Minutes.
For clearer photos of the whiteboard:
Graphs Photo 1: http://i1160.photobucket.com/albums/q499/dicksontsai/Public%20photos/Data%20Structures%20in%205%20Minutes/IMG_2591_zps8b37b878.jpg
Graphs Photo 2:
http://i1160.photobucket.com/albums/q499/dicksontsai/Public%20photos/Data%20Structures%20in%205%20Minutes/IMG_2592_zpsec253f75.jpg
Several comments:
* The top of the adjacency matrix got cut off, but it should be C D E F.
* Pseudocode for DFS and BFS can be easily searched on the Internet. Choosing which vertex to explore first is arbitrary. The important distinction is searching deeply vs. searching one edge away at a time from the start.
* We did not have the time to go over the Königsberg problem, which is the problem associated with Euler's seminal work on graph theory. It's a fun application of graphs, and should also be well-documented on the internet.
*Please leve any constructive feedback below. Thanks for watching!
DISCLAIMER: This video in no way comprehensively covers the lecture notes, nor are considered "official" by any instructor. I am undertaking this series as a way to help study for the final. Please refer to the lecture notes themselves as the authoritative source. For these videos, I try my best to adhere to fair use: No part of this video may be used for any monetary gain.
- published: 04 May 2013
- views: 28557
Graph Data Structure 4. Dijkstra’s Shortest Path Algorithm
- Order: Reorder
- Duration: 10:52
- Updated: 07 May 2016
- views: 4725
This is the fourth in a series of videos about the graph data structure. This is an explanation of Dijkstra’s algorithm for finding the shortest path between o...
This is the fourth in a series of videos about the graph data structure. This is an explanation of Dijkstra’s algorithm for finding the shortest path between one vertex in a graph and another. Indeed, this explains how Dijkstra’s shortest path algorithm generates a set of information that includes the shortest paths from a starting vertex and every other vertex in the graph. It also mentions why Dijkstra’s shortest path algorithm is an example of a greedy algorithm.
https://wn.com/Graph_Data_Structure_4._Dijkstra’S_Shortest_Path_Algorithm
This is the fourth in a series of videos about the graph data structure. This is an explanation of Dijkstra’s algorithm for finding the shortest path between one vertex in a graph and another. Indeed, this explains how Dijkstra’s shortest path algorithm generates a set of information that includes the shortest paths from a starting vertex and every other vertex in the graph. It also mentions why Dijkstra’s shortest path algorithm is an example of a greedy algorithm.
- published: 07 May 2016
- views: 4725
CS 61B Lecture 27: Graphs
- Order: Reorder
- Duration: 50:08
- Updated: 30 Jul 2008
- views: 64517
CS 61B: Data Structures - Fall 2006
Instructor Jonathan Shewchuk
Fundamental dynamic data structures, including linear lists, queues, trees, and other linked ...
CS 61B: Data Structures - Fall 2006
Instructor Jonathan Shewchuk
Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language.
http://www.cs.berkeley.edu
https://wn.com/Cs_61B_Lecture_27_Graphs
CS 61B: Data Structures - Fall 2006
Instructor Jonathan Shewchuk
Fundamental dynamic data structures, including linear lists, queues, trees, and other linked structures; arrays strings, and hash tables. Storage management. Elementary principles of software engineering. Abstract data types. Algorithms for sorting and searching. Introduction to the Java programming language.
http://www.cs.berkeley.edu
- published: 30 Jul 2008
- views: 64517
Data Structures - Trees and Graphs
- Order: Reorder
- Duration: 56:42
- Updated: 29 Nov 2016
- views: 1569
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https://wn.com/Data_Structures_Trees_And_Graphs
Graph Data Structure 1. Terminology and Representation (algorithms)
- Order: Reorder
- Duration: 7:59
- Updated: 27 Apr 2016
- views: 929
This is the first in a series of videos about the graph data structure. It mentions the applications of graphs, defines various terminology associated with gra...
This is the first in a series of videos about the graph data structure. It mentions the applications of graphs, defines various terminology associated with graphs, and describes how a graph can be represented programmatically by means of adjacency lists or an adjacency matrix.
https://wn.com/Graph_Data_Structure_1._Terminology_And_Representation_(Algorithms)
This is the first in a series of videos about the graph data structure. It mentions the applications of graphs, defines various terminology associated with graphs, and describes how a graph can be represented programmatically by means of adjacency lists or an adjacency matrix.
- published: 27 Apr 2016
- views: 929
Graph Data Structure Intro - Beau teaches JavaScript
- Order: Reorder
- Duration: 4:53
- Updated: 21 May 2017
- views: 297
Graphs are collections of things and the relationships or connections between them. The data in a graph are called nodes or vertices. The connections between th...
Graphs are collections of things and the relationships or connections between them. The data in a graph are called nodes or vertices. The connections between the nodes are called edges.
🐦 Beau Carnes on Twitter: https://twitter.com/carnesbeau
⭐JavaScript Tutorials Playlists⭐
▶JavaScript Basics: https://www.youtube.com/playlist?list=PLWKjhJtqVAbk2qRZtWSzCIN38JC_NdhW5
▶Data Structures and Algorithms: https://www.youtube.com/playlist?list=PLWKjhJtqVAbkso-IbgiiP48n-O-JQA9PJ
▶Design Patterns: https://www.youtube.com/playlist?list=PLWKjhJtqVAbnZtkAI3BqcYxKnfWn_C704
▶ES6: https://www.youtube.com/playlist?list=PLWKjhJtqVAbljtmmeS0c-CEl2LdE-eR_F
▶Clean Code: https://www.youtube.com/playlist?list=PLWKjhJtqVAbkK24EaPurzMq0-kw5U9pJh
-
We're busy people who learn to code, then practice by building projects for nonprofits. Learn Full-stack JavaScript, build a portfolio, and get great references with our open source community.
Join our community at https://freecodecamp.com
Read great tech articles at https://medium.freecodecamp.com
https://wn.com/Graph_Data_Structure_Intro_Beau_Teaches_Javascript
Graphs are collections of things and the relationships or connections between them. The data in a graph are called nodes or vertices. The connections between the nodes are called edges.
🐦 Beau Carnes on Twitter: https://twitter.com/carnesbeau
⭐JavaScript Tutorials Playlists⭐
▶JavaScript Basics: https://www.youtube.com/playlist?list=PLWKjhJtqVAbk2qRZtWSzCIN38JC_NdhW5
▶Data Structures and Algorithms: https://www.youtube.com/playlist?list=PLWKjhJtqVAbkso-IbgiiP48n-O-JQA9PJ
▶Design Patterns: https://www.youtube.com/playlist?list=PLWKjhJtqVAbnZtkAI3BqcYxKnfWn_C704
▶ES6: https://www.youtube.com/playlist?list=PLWKjhJtqVAbljtmmeS0c-CEl2LdE-eR_F
▶Clean Code: https://www.youtube.com/playlist?list=PLWKjhJtqVAbkK24EaPurzMq0-kw5U9pJh
-
We're busy people who learn to code, then practice by building projects for nonprofits. Learn Full-stack JavaScript, build a portfolio, and get great references with our open source community.
Join our community at https://freecodecamp.com
Read great tech articles at https://medium.freecodecamp.com
- published: 21 May 2017
- views: 297
Chapter 52 Representation of Graph in Data Structure hindi
- Order: Reorder
- Duration: 32:37
- Updated: 09 Mar 2016
- views: 18957
Graphs - Types and Representation
- Order: Reorder
- Duration: 16:28
- Updated: 31 May 2013
- views: 39976
This video introduces graphs, used in computing to store and manipulate networks--of people, computers, cities, etc. The lesson goes over the different kinds of...
This video introduces graphs, used in computing to store and manipulate networks--of people, computers, cities, etc. The lesson goes over the different kinds of graphs--undirected, directed, and weighted variations of both--and shows how they can be stored in a program using a simple structure called the adjacency matrix. This video is part of a series on data structures and algorithms by Sesh Venugopal. http://www.cs.rutgers.edu/~venugopa
https://wn.com/Graphs_Types_And_Representation
This video introduces graphs, used in computing to store and manipulate networks--of people, computers, cities, etc. The lesson goes over the different kinds of graphs--undirected, directed, and weighted variations of both--and shows how they can be stored in a program using a simple structure called the adjacency matrix. This video is part of a series on data structures and algorithms by Sesh Venugopal. http://www.cs.rutgers.edu/~venugopa
- published: 31 May 2013
- views: 39976
Interactive 3D visualization of Point Clouds
- Order: Reorder
- Duration: 0:28
- Updated: 19 Jun 2014
- views: 4147
First demonstration of an interactive 3D fly-over of a city. The data is a point-cloud originating from an Aerial LIDAR scan. This particular dataset is a part ...
First demonstration of an interactive 3D fly-over of a city. The data is a point-cloud originating from an Aerial LIDAR scan. This particular dataset is a part of the city of Middelburg, made available in the AHN2 test data set [2]. Colors are reconstructed from 2D Texture, so these are not the directly scanned colors.
We generate a level-of-detail data structure in OpenSceneGraph to dynamically show different densities of points, and is loading over the network. With this ~20 Million point cloud, update rates are between 15~60 fps depending on how many points are visible in a certain view. We are optimizing the datastructure to balance frame rate with visual quality. 3D Navigation is done with a SpaceMouse device.
Point Cloud visualizations have nice visual quality, especially under motion and 3D stereo, both of which are used in the VR systems in our group [1].
Please note that these visualizations are inherently difficult for regular video compression algorithms to process without introducing disturbing visual artifacts. Download the wmv file below for a higher-quality impression, or see a static screenshot [3].
[1] http://visualisation.tudelft.nl/VRVis
[2] http://www.ahn.nl/
[3] http://graphics.tudelft.nl/~gerwin/media/3dtopo/Screenshot_pointcloud.png
https://wn.com/Interactive_3D_Visualization_Of_Point_Clouds
First demonstration of an interactive 3D fly-over of a city. The data is a point-cloud originating from an Aerial LIDAR scan. This particular dataset is a part of the city of Middelburg, made available in the AHN2 test data set [2]. Colors are reconstructed from 2D Texture, so these are not the directly scanned colors.
We generate a level-of-detail data structure in OpenSceneGraph to dynamically show different densities of points, and is loading over the network. With this ~20 Million point cloud, update rates are between 15~60 fps depending on how many points are visible in a certain view. We are optimizing the datastructure to balance frame rate with visual quality. 3D Navigation is done with a SpaceMouse device.
Point Cloud visualizations have nice visual quality, especially under motion and 3D stereo, both of which are used in the VR systems in our group [1].
Please note that these visualizations are inherently difficult for regular video compression algorithms to process without introducing disturbing visual artifacts. Download the wmv file below for a higher-quality impression, or see a static screenshot [3].
[1] http://visualisation.tudelft.nl/VRVis
[2] http://www.ahn.nl/
[3] http://graphics.tudelft.nl/~gerwin/media/3dtopo/Screenshot_pointcloud.png
- published: 13 Feb 2009
- views: 4147
Andromeda video browsing
- Order: Reorder
- Duration: 3:35
- Updated: 03 Jun 2014
- views: 120
Screencast of Andromeda.
Advanced tool for interactive browsing of video annotations
Concept Cloud
Shows the concepts with more instances in a cloud view
Gra...
Screencast of Andromeda.
Advanced tool for interactive browsing of video annotations
Concept Cloud
Shows the concepts with more instances in a cloud view
Graph browsing
Graph representation of semantic data structure
Multiple automatic layout algorithm for spatial positioning and manual drag & drop
Multimedia content access
Thumbnails view of the intances of each concept
Access to video metadata and playing from the annotation frame
User generated content integration
Access to social content related to ontology concepts.
Images from Flickr, videos from YouTube and real time tweets from Twitter
--
Marco Bertini, Andrea Ferracani, Nicola Martorana, Marco Meoni, Giuseppe Serra.
MICC - Media Integration Communication Center - Firenze - Italia (Florence - Italy).
https://wn.com/Andromeda_Video_Browsing
Screencast of Andromeda.
Advanced tool for interactive browsing of video annotations
Concept Cloud
Shows the concepts with more instances in a cloud view
Graph browsing
Graph representation of semantic data structure
Multiple automatic layout algorithm for spatial positioning and manual drag & drop
Multimedia content access
Thumbnails view of the intances of each concept
Access to video metadata and playing from the annotation frame
User generated content integration
Access to social content related to ontology concepts.
Images from Flickr, videos from YouTube and real time tweets from Twitter
--
Marco Bertini, Andrea Ferracani, Nicola Martorana, Marco Meoni, Giuseppe Serra.
MICC - Media Integration Communication Center - Firenze - Italia (Florence - Italy).
- published: 18 May 2010
- views: 120
RFC: AvocadoDB Query Language
- Order: Reorder
- Duration: 55:16
- Updated: 17 Jun 2014
- views: 180
AvocacoDB is a young nosql open source database.
The REST API for AvocadoDB is already available and stable and people are writing APIs using it. AvocadoDB off...
AvocacoDB is a young nosql open source database.
The REST API for AvocadoDB is already available and stable and people are writing APIs using it. AvocadoDB offers more complex data structures like graphs and lists REST is not enough. We implemented a first version of a query language some time ago which is very similar to SQL and UNQL.
Then we realized that this approach was not completely satisfying as some queries cannot expressed very well with it, especially multi-valued attributes/lists. UNQL addresses this partly, but does not go far enough. Another issue are graphs. AvocadoDB supports querying graphs, neither SQL nor UNQL offer any "natural" graph traversal facilities.
In this talk, Jan Steemann, presents the concept for AvocadoDB's query language. Please leave your comments on avocadodb.org or via twitter @avcoadodb
https://wn.com/Rfc_Avocadodb_Query_Language
AvocacoDB is a young nosql open source database.
The REST API for AvocadoDB is already available and stable and people are writing APIs using it. AvocadoDB offers more complex data structures like graphs and lists REST is not enough. We implemented a first version of a query language some time ago which is very similar to SQL and UNQL.
Then we realized that this approach was not completely satisfying as some queries cannot expressed very well with it, especially multi-valued attributes/lists. UNQL addresses this partly, but does not go far enough. Another issue are graphs. AvocadoDB supports querying graphs, neither SQL nor UNQL offer any "natural" graph traversal facilities.
In this talk, Jan Steemann, presents the concept for AvocadoDB's query language. Please leave your comments on avocadodb.org or via twitter @avcoadodb
- published: 18 Apr 2012
- views: 180
0321 - Getting beer in and out of Neo4j
- Order: Reorder
- Duration: 31:53
- Updated: 18 Jun 2014
- views: 473
DATASET: https://docs.google.com/spreadsheet/ccc?key=0Ah0qwaznhrupdEpxdXBCSmZuUjA2TTJZRm1ORy0zcUE
Graph Databases have long been the realm of highly technical I...
DATASET: https://docs.google.com/spreadsheet/ccc?key=0Ah0qwaznhrupdEpxdXBCSmZuUjA2TTJZRm1ORy0zcUE
Graph Databases have long been the realm of highly technical IT development professionals. But those days are gone. In this non-technical seminar, hosted by one of Neo Technology's non-technical staff, we will explain just how easy it is for average business people to start using graph databases, and get value from it. The subject of this webinar will be tasty as well: Belgian Beers - and how we easily got this dataset into Neo4j. We will also explore what this Neo4j database delivers, and how even this simple graph oriented data structure immediately yielded value for a non-technical person.
Check out an extensive blog post about it here: http://blog.neo4j.org/2013/01/fun-with-beer-and-graphs.html
https://wn.com/0321_Getting_Beer_In_And_Out_Of_Neo4J
DATASET: https://docs.google.com/spreadsheet/ccc?key=0Ah0qwaznhrupdEpxdXBCSmZuUjA2TTJZRm1ORy0zcUE
Graph Databases have long been the realm of highly technical IT development professionals. But those days are gone. In this non-technical seminar, hosted by one of Neo Technology's non-technical staff, we will explain just how easy it is for average business people to start using graph databases, and get value from it. The subject of this webinar will be tasty as well: Belgian Beers - and how we easily got this dataset into Neo4j. We will also explore what this Neo4j database delivers, and how even this simple graph oriented data structure immediately yielded value for a non-technical person.
Check out an extensive blog post about it here: http://blog.neo4j.org/2013/01/fun-with-beer-and-graphs.html
- published: 21 Mar 2013
- views: 473
ChiSC: Max DeMarzi - Is Your Problem a Graph Problem?
- Order: Reorder
- Duration: 54:36
- Updated: 15 Jun 2014
- views: 443
You learned early on that one of the secrets to programming is using the right data structure. Learn the "secret" to the graph database, Neo4j. Learn when to us...
You learned early on that one of the secrets to programming is using the right data structure. Learn the "secret" to the graph database, Neo4j. Learn when to use this tool for the job and when to stick to your relational database. See how different "Domain Specific Languages" help you approach your problems in different ways.
Max De Marzi, is a seasoned web developer. He started building websites in 1996 and has worked with Ruby on Rails since 2006. The web forced Max to wear many hats and master a wide range of technologies. He can be a system admin, database developer, graphic designer, back-end engineer and data scientist in the course of one afternoon. Max is a graph database enthusiast. He built the Neography Ruby Gem, a rest api wrapper to the Neo4j Graph Database. He is addicted to learning new things, loves a challenge and finding pragmatic solutions. Max is very easy to work with, focuses under pressure and has the patience of a rock.
https://wn.com/Chisc_Max_Demarzi_Is_Your_Problem_A_Graph_Problem
You learned early on that one of the secrets to programming is using the right data structure. Learn the "secret" to the graph database, Neo4j. Learn when to use this tool for the job and when to stick to your relational database. See how different "Domain Specific Languages" help you approach your problems in different ways.
Max De Marzi, is a seasoned web developer. He started building websites in 1996 and has worked with Ruby on Rails since 2006. The web forced Max to wear many hats and master a wide range of technologies. He can be a system admin, database developer, graphic designer, back-end engineer and data scientist in the course of one afternoon. Max is a graph database enthusiast. He built the Neography Ruby Gem, a rest api wrapper to the Neo4j Graph Database. He is addicted to learning new things, loves a challenge and finding pragmatic solutions. Max is very easy to work with, focuses under pressure and has the patience of a rock.
- published: 16 Jan 2013
- views: 443
DNA Sequence Filtering and Analysis - Jason Pell
- Order: Reorder
- Duration: 27:08
- Updated: 13 Jun 2014
- views: 275
Within the past decade, the amount of DNA sequencing data generated from next-generation sequencing platforms has exploded. As a result, biology has been propel...
Within the past decade, the amount of DNA sequencing data generated from next-generation sequencing platforms has exploded. As a result, biology has been propelled as a field in need of better scaling algorithms and data structures to efficiently analyze data. Jason Pell will present features of khmer, a software package developed in the GED Lab at Michigan State University, to efficiently filter and analyze data generated by next-generation sequencing platforms. More specifically, he will present the use of the Bloom filter and Counting Bloom filter data structures for assembly graph traversal and k-mer counting, respectively. The khmer software package is written primarily in C++ and wrapped in Python. It is released under the BSD license and is available at http://www.github.com/ged-lab/khmer.
This talk was presented at PyData NYC 2012: http://nyc2012.pydata.org/. If you are interested in this topic, be sure to check out PyData Silicon Valley in March of 2013: http://sv2013.pydata.org/
https://wn.com/Dna_Sequence_Filtering_And_Analysis_Jason_Pell
Within the past decade, the amount of DNA sequencing data generated from next-generation sequencing platforms has exploded. As a result, biology has been propelled as a field in need of better scaling algorithms and data structures to efficiently analyze data. Jason Pell will present features of khmer, a software package developed in the GED Lab at Michigan State University, to efficiently filter and analyze data generated by next-generation sequencing platforms. More specifically, he will present the use of the Bloom filter and Counting Bloom filter data structures for assembly graph traversal and k-mer counting, respectively. The khmer software package is written primarily in C++ and wrapped in Python. It is released under the BSD license and is available at http://www.github.com/ged-lab/khmer.
This talk was presented at PyData NYC 2012: http://nyc2012.pydata.org/. If you are interested in this topic, be sure to check out PyData Silicon Valley in March of 2013: http://sv2013.pydata.org/
- published: 08 Nov 2012
- views: 275
After Effects Template - Infographics Infocharts Package
- Order: Reorder
- Duration: 1:38
- Updated: 19 Jun 2014
- views: 125
http://videohive.net/item/infographics-infocharts-package/3945627?sso?ref=creativestone92
INFOCHARTS Package (AE CS 5.0, Full HD) is an expression-based After ...
http://videohive.net/item/infographics-infocharts-package/3945627?sso?ref=creativestone92
INFOCHARTS Package (AE CS 5.0, Full HD) is an expression-based After Effects template that provides quick and flexible creative solutions for infographics. Combine easily several types of graphs (pie charts, line graph, bar graphs, concentric lines, worldmap with all countries, area graphs….). Add to the final composition one or several included widgets (markers, averages, loaders, panels…). Built to be intuitive and flexible, and no prior knowledge of AE expressions is necessary. Create simple and elegant infographics with InfoCharts Package from included Charts systems.Custom expressions were created to make entering data as easy as possible. All expressions have been universalized to work in any language.
•Clean and stylish design
•Smooth animations
•Fast render
•User friendly
•Modular structure, combine easily several graph systems
•Unlimited data series for the Line Graph chart
•Upto 20 values for the BarGraph 01
•BarGraph 02, allows to reach higher values numbers very easily
•Included 10 projects files
•Preview sequence used for preview file, inluded in each file
•Easy color customization, value editing
•Numerous useful settings
•Full HD resolution (1080p)
•AE CS 5.0 and higher
•Free font link included
Preview music: this track IS NOT included. SoundProdigy created it; you can buy it on AudioJungle:
http://audiojungle.net/item/beautiful-day-joy-and-happy-motivations/26843
infographics, statistics, infocharts, chart, graph, pie chart, concentric lines, corporate, business, report presentation, bar graph line chart, area graph, dashboards, data visualization, world map
https://wn.com/After_Effects_Template_Infographics_Infocharts_Package
http://videohive.net/item/infographics-infocharts-package/3945627?sso?ref=creativestone92
INFOCHARTS Package (AE CS 5.0, Full HD) is an expression-based After Effects template that provides quick and flexible creative solutions for infographics. Combine easily several types of graphs (pie charts, line graph, bar graphs, concentric lines, worldmap with all countries, area graphs….). Add to the final composition one or several included widgets (markers, averages, loaders, panels…). Built to be intuitive and flexible, and no prior knowledge of AE expressions is necessary. Create simple and elegant infographics with InfoCharts Package from included Charts systems.Custom expressions were created to make entering data as easy as possible. All expressions have been universalized to work in any language.
•Clean and stylish design
•Smooth animations
•Fast render
•User friendly
•Modular structure, combine easily several graph systems
•Unlimited data series for the Line Graph chart
•Upto 20 values for the BarGraph 01
•BarGraph 02, allows to reach higher values numbers very easily
•Included 10 projects files
•Preview sequence used for preview file, inluded in each file
•Easy color customization, value editing
•Numerous useful settings
•Full HD resolution (1080p)
•AE CS 5.0 and higher
•Free font link included
Preview music: this track IS NOT included. SoundProdigy created it; you can buy it on AudioJungle:
http://audiojungle.net/item/beautiful-day-joy-and-happy-motivations/26843
infographics, statistics, infocharts, chart, graph, pie chart, concentric lines, corporate, business, report presentation, bar graph line chart, area graph, dashboards, data visualization, world map
- published: 20 May 2013
- views: 125
The Graph Traversal Programming Pattern by Marko Rodriguez
- Order: Reorder
- Duration: 41:46
- Updated: 20 Jun 2014
- views: 3816
Slides: http://www.slideshare.net/slidarko/graph-windycitydb2010
A graph is a structure composed of a set of vertices (i.e. nodes, dots) connected to one anoth...
Slides: http://www.slideshare.net/slidarko/graph-windycitydb2010
A graph is a structure composed of a set of vertices (i.e. nodes, dots) connected to one another by a set of edges (i.e. links, lines). The concept of a graph has been around since the late 19th century, however, only in recent decades has there been a strong resurgence in the development of both graph theories and applications. In applied computing, since the late 1960s, the interlinked table structure of the relational database has been the predominant information storage and retrieval paradigm. With the growth of graph/network-based data and the need to efficiently process such data, new data management systems have been developed. In contrast to the index-intensive, set-theoretic operations of relational databases, graph databases make use of index-free traversals. This presentation will discuss the graph traversal programming pattern and its application to problem-solving with graph databases.
https://wn.com/The_Graph_Traversal_Programming_Pattern_By_Marko_Rodriguez
Slides: http://www.slideshare.net/slidarko/graph-windycitydb2010
A graph is a structure composed of a set of vertices (i.e. nodes, dots) connected to one another by a set of edges (i.e. links, lines). The concept of a graph has been around since the late 19th century, however, only in recent decades has there been a strong resurgence in the development of both graph theories and applications. In applied computing, since the late 1960s, the interlinked table structure of the relational database has been the predominant information storage and retrieval paradigm. With the growth of graph/network-based data and the need to efficiently process such data, new data management systems have been developed. In contrast to the index-intensive, set-theoretic operations of relational databases, graph databases make use of index-free traversals. This presentation will discuss the graph traversal programming pattern and its application to problem-solving with graph databases.
- published: 09 Jul 2010
- views: 3816
Autopilot Visualizer - A data visualization application for exploring IT infrastructure automation
- Order: Reorder
- Duration: 2:09
- Updated: 20 Jun 2014
- views: 1348
The AutoPilot Visualizer is a software tool for exploring complex data structures used in the automation of maintenance and supervision of large-scale IT infras...
The AutoPilot Visualizer is a software tool for exploring complex data structures used in the automation of maintenance and supervision of large-scale IT infrastructures.
The environment is a visual front-end to the underlying AutoPilot system by Arago, a company that specialises in the automation of data environments using artificial intelligence techniques and graph-based algorithms.
FELD was commissioned to develop a visualisation application which represents the data in a way that makes the system easier to navigate and more intuitive to understand – both for system specialists and for non-expert users.
The environment is centered around the graph-browser where the main structure is clustered into several subgraphs, each representing a different part of the system.
All events that occur in the system via the connected API are represented by agents that show the progress of any issue that may arise in real time.
The software is designed to run on a range of different devices – from single-screen laptops and tablets to multi-screen setups in control room environments.
https://wn.com/Autopilot_Visualizer_A_Data_Visualization_Application_For_Exploring_It_Infrastructure_Automation
The AutoPilot Visualizer is a software tool for exploring complex data structures used in the automation of maintenance and supervision of large-scale IT infrastructures.
The environment is a visual front-end to the underlying AutoPilot system by Arago, a company that specialises in the automation of data environments using artificial intelligence techniques and graph-based algorithms.
FELD was commissioned to develop a visualisation application which represents the data in a way that makes the system easier to navigate and more intuitive to understand – both for system specialists and for non-expert users.
The environment is centered around the graph-browser where the main structure is clustered into several subgraphs, each representing a different part of the system.
All events that occur in the system via the connected API are represented by agents that show the progress of any issue that may arise in real time.
The software is designed to run on a range of different devices – from single-screen laptops and tablets to multi-screen setups in control room environments.
- published: 28 Nov 2013
- views: 1348
Houdini and Mathematica
- Order: Reorder
- Duration: 0:59
- Updated: 20 Jun 2014
- views: 1432
This is really cool!
We can connect Mathematica to Houdini and use many of its powerful capabilities.
In this example a scattering of points is created and th...
This is really cool!
We can connect Mathematica to Houdini and use many of its powerful capabilities.
In this example a scattering of points is created and then we find their nearest neighbours (VEX) and draw their connections (Python). I then send this as a graph structure to Mathematica and compute the clustering based on the topology of the network, the metric being the steps that connect one node to another. That together with the shortest path between two points is then send back to Houdini and displayed.
The general procedure to send and get data from Houdini to Mathematica is as follows:
-Prepare your data in Houdini by sending it through python and export in a suitable format. In this case a .tgf for the nodes and connections
-Let the Python script call the external mathscript
-Wait for it to do it's stuff and read back with Python
This gives you more or less painless integration of H with M
https://wn.com/Houdini_And_Mathematica
This is really cool!
We can connect Mathematica to Houdini and use many of its powerful capabilities.
In this example a scattering of points is created and then we find their nearest neighbours (VEX) and draw their connections (Python). I then send this as a graph structure to Mathematica and compute the clustering based on the topology of the network, the metric being the steps that connect one node to another. That together with the shortest path between two points is then send back to Houdini and displayed.
The general procedure to send and get data from Houdini to Mathematica is as follows:
-Prepare your data in Houdini by sending it through python and export in a suitable format. In this case a .tgf for the nodes and connections
-Let the Python script call the external mathscript
-Wait for it to do it's stuff and read back with Python
This gives you more or less painless integration of H with M
- published: 07 Dec 2012
- views: 1432
- Playlist
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40:26
Chapter 51 Introduction to Graphs in Data Structure Hindi
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published: 05 Mar 2016
Chapter 51 Introduction to Graphs in Data Structure Hindi
Chapter 51 Introduction to Graphs in Data Structure Hindi
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- published: 05 Mar 2016
- views: 8675
4:17
Graph Theory in Data Structure(Hindi, English) with Example
Graph Theory in Data Structure(Hindi, English) with Example for students of IP University ...
published: 20 Jun 2016
Graph Theory in Data Structure(Hindi, English) with Example
Graph Theory in Data Structure(Hindi, English) with Example
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- published: 20 Jun 2016
- views: 283
6:14
Graphs - Data Structures in 5 Minutes
Introduction to graph theory terminology. The pace is very fast, so this is geared for tho...
published: 04 May 2013
Graphs - Data Structures in 5 Minutes
Graphs - Data Structures in 5 Minutes
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- published: 04 May 2013
- views: 28557
10:52
Graph Data Structure 4. Dijkstra’s Shortest Path Algorithm
This is the fourth in a series of videos about the graph data structure. This is an expla...
published: 07 May 2016
Graph Data Structure 4. Dijkstra’s Shortest Path Algorithm
Graph Data Structure 4. Dijkstra’s Shortest Path Algorithm
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- published: 07 May 2016
- views: 4725
50:08
CS 61B Lecture 27: Graphs
CS 61B: Data Structures - Fall 2006
Instructor Jonathan Shewchuk
Fundamental dynamic dat...
published: 30 Jul 2008
CS 61B Lecture 27: Graphs
CS 61B Lecture 27: Graphs
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- published: 30 Jul 2008
- views: 64517
56:42
Data Structures - Trees and Graphs
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published: 29 Nov 2016
Data Structures - Trees and Graphs
Data Structures - Trees and Graphs
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- published: 29 Nov 2016
- views: 1569
7:59
Graph Data Structure 1. Terminology and Representation (algorithms)
This is the first in a series of videos about the graph data structure. It mentions the a...
published: 27 Apr 2016
Graph Data Structure 1. Terminology and Representation (algorithms)
Graph Data Structure 1. Terminology and Representation (algorithms)
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- published: 27 Apr 2016
- views: 929
4:53
Graph Data Structure Intro - Beau teaches JavaScript
Graphs are collections of things and the relationships or connections between them. The da...
published: 21 May 2017
Graph Data Structure Intro - Beau teaches JavaScript
Graph Data Structure Intro - Beau teaches JavaScript
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- published: 21 May 2017
- views: 297
32:37
Chapter 52 Representation of Graph in Data Structure hindi
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Visit www.mysirg.com for all FREE lectures
published: 09 Mar 2016
Chapter 52 Representation of Graph in Data Structure hindi
Chapter 52 Representation of Graph in Data Structure hindi
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- published: 09 Mar 2016
- views: 18957
16:28
Graphs - Types and Representation
This video introduces graphs, used in computing to store and manipulate networks--of peopl...
published: 31 May 2013
Graphs - Types and Representation
Graphs - Types and Representation
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- published: 31 May 2013
- views: 39976
0:28
Interactive 3D visualization of Point Clouds
First demonstration of an interactive 3D fly-over of a city. The data is a point-cloud ori...
published: 13 Feb 2009
Interactive 3D visualization of Point Clouds
Interactive 3D visualization of Point Clouds
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- published: 13 Feb 2009
- views: 4147
3:35
Andromeda video browsing
Screencast of Andromeda.
Advanced tool for interactive browsing of video annotations
Con...
published: 18 May 2010
Andromeda video browsing
Andromeda video browsing
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- published: 18 May 2010
- views: 120
55:16
RFC: AvocadoDB Query Language
AvocacoDB is a young nosql open source database.
The REST API for AvocadoDB is already av...
published: 18 Apr 2012
RFC: AvocadoDB Query Language
RFC: AvocadoDB Query Language
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- published: 18 Apr 2012
- views: 180
31:53
0321 - Getting beer in and out of Neo4j
DATASET: https://docs.google.com/spreadsheet/ccc?key=0Ah0qwaznhrupdEpxdXBCSmZuUjA2TTJZRm1O...
published: 21 Mar 2013
0321 - Getting beer in and out of Neo4j
0321 - Getting beer in and out of Neo4j
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- published: 21 Mar 2013
- views: 473
Chapter 51 Introduction to Graphs in Data Structur...
Graph Theory in Data Structure(Hindi, English) wit...
Graphs - Data Structures in 5 Minutes...
Graph Data Structure 4. Dijkstra’s Shortest Path A...
CS 61B Lecture 27: Graphs...
Data Structures - Trees and Graphs...
Graph Data Structure 1. Terminology and Representa...
Graph Data Structure Intro - Beau teaches JavaScri...
Chapter 52 Representation of Graph in Data Structu...
Graphs - Types and Representation...
Interactive 3D visualization of Point Clouds...
Andromeda video browsing...
RFC: AvocadoDB Query Language...
0321 - Getting beer in and out of Neo4j...
ChiSC: Max DeMarzi - Is Your Problem a Graph Probl...
DNA Sequence Filtering and Analysis - Jason Pell...
After Effects Template - Infographics Infocharts P...
The Graph Traversal Programming Pattern by Marko R...
Autopilot Visualizer - A data visualization applic...
Houdini and Mathematica...
See more photos of graph (data structure)
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Trump's son-in-law ready to talk with investigators about Russian contacts
Edit TVNZ 28 May 2017
President Donald Trump's son-in-law and now top White House adviser Jared Kushner proposed a secret back channel between the Kremlin and the Trump transition team during a December meeting with a leading Russian diplomat. Jared Kushner reportedly met with the Russian ambassador last year to discuss setting up a communications channel with the Kremlin. Source. Associated Press ... Tillerson was sworn in on February 1 ... ....
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Police: Suspect in Portland stabbings ranted about Muslims
Edit Atlanta Journal 27 May 2017
PORTLAND, Ore. A man who police say fatally stabbed two people who tried to stop him from yelling anti-Islamic slurs on a Portland light-rail train spent time in prison for robbery and kidnapping charges years ago, according to court records and a defense attorney ... He will make a first court appearance Monday, and it wasn't immediately clear if he had an attorney. A phone at his home in Portland rang unanswered early Saturday ... _____ ... ....
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G7 Ends with Trump Pitted Against the Leaders of Europe on a Number of Key Issues
Edit Newsweek 27 May 2017
Under pressure from allies, U.S. President Donald Trump backed a pledge to fight protectionism on Saturday, but refused to endorse a global climate change accord, saying he needed more time to decide ... Trump, who has previously called global warming a hoax, tweeted that he would make a decision next week on whether to back the 2015 Paris Agreement on curbing carbon emissions following lengthy discussions with G7 partners ... The U.S ... U.S ... ....
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Jupiter surprises in first trove of data from NASA’s Juno mission
Edit Astronomy/Spaceflight Now 27 May 2017
This image shows Jupiter’s south pole, as seen by NASA’s Juno spacecraft from an altitude of 32,000 miles (52,000 kilometres). Image credit. NASA/JPL-Caltech/SwRI/MSSS/Betsy Asher Hall/Gervasio Robles ... “The general theme of our discoveries is really how different Jupiter looks from what we expected,” said Scott Bolton, Juno’s principal investigator at the Southwest Research Institute in San Antonio ... Credit ... ....
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Protests hit held Kashmir after killing of militant leader
Edit Dawn 28 May 2017
SRINAGAR. In scenes reminiscent of what transpired in the aftermath of popular militant leader Burhan Wani’s killing, a civilian lost his life and dozens of others were injured on Saturday after massive anti-India protests and clashes erupted in India-held Kashmir following the death of a top militant commander and his associate in a gun battle with Indian troops ... The two were not the only militants to be slain on Saturday....
We inherited the legacy of jungle raj in UP, says Yogi Adityanath
Edit Asian Age 28 May 2017
Adityanath is under attack over the increasing crime graph in Uttar Pradesh ... ....
Nawaz wants to keep control over everything, says Imran
Edit The News International 28 May 2017
ISLAMABAD. The Chairman of Pakistan Tehreek-e-Insaf (PTI), Imran Khan, said on Saturday that the Pakistan Muslim League-Nawaz (PML-N) government had not enacted any law to eliminate corruption ... His father NS, cldnt play cricket without his own umpires ... “We will clean sweep Khyber Pakhtunkhwa in the upcoming general elections as the party’s popularity graph in the province had gone up,” said the PTI chief ... ....
CBSE Class 12 Results 2017: The Curious Case of 'Magic Mark 95'
Edit News18 28 May 2017
The CBSE Class 12 results 2017 are scheduled to be declared by Sunday noon. Millions of students are awaiting their admission to colleges and universities across the country — with most institutions judging them solely on the basis of their Class 12 marks ... Here's a look.. CBSE’s MAGIC FIGURE - 95 ... And here are the graphs for the Maths, Physics, Economics and Accountancy papers among others — ... "It's a little unfair ... ISC’s MISSING NUMBERS....
Labor has no choice. It should acccept the new Gonski model and argue for more funding
Edit The Guardian 28 May 2017
Greg Jericho. Unlike the US’s Congressional Budget Office, Australia’s Parliamentary Budget Office does not provide analysis on the real-world impacts of policy. Gonski reforms. Grogonomics. Labor has no choice ... In 2014, Joe Hockey gave Labor a massive help by including within the budget papers a graph and a line boasting that the changes to funding of education and health “will achieve cumulative savings of over $80bn by 2024‑25” ... ....
'Khatra hai': Fear grips Dalits & Thakurs in Saharanpur flashpoint Shabbirpur
Edit Yahoo Daily News 28 May 2017
'Khatra hai'. Fear grips Dalits & Thakurs in Saharanpur flashpoint Shabbirpur. “The officers have gone to the houses across the road,” a Dalit villager remarks, as we ask him for directions. “I can't go there, khatra hai,” he says, as he walks briskly towards his house ... The Bhim Army's graph continues to rise after the 9 May incident, when the local police booked the organisation and its members, including Ravan, in two dozen cases ... ....
100th Anniversary of Mathematician Bill Tutte, Who Helped End WWII
Edit War History Online 27 May 2017
He turned his attention to the theory of graphs. The graphs that Tutte was interested in are abstract networks which consist of objects known as vertices or nodes and the interactions between them (called edges or links). A network of train stations and the rails connecting them, or the hyperlinks connecting web pages which make up the World Wide Web are the kind of graphs Tutte was interested in....
Pakistan Tehreek-e-Insaf poll campaign to start after Ramazan: Imran
Edit The Siasat Daily 27 May 2017'Baahubali 2: The Conclusion' box-office collection: Film’s Hindi version starts fifth week with a bang
Edit The Times of India 27 May 2017
SS Rajamouli's 'Baahubali 2. The Conclusion' may have entered its fifth week but the magnum opus hasn't lost steam ... With this, the total collection of the Hindi version stands at a staggering Rs 489.17 crore ... The film has maintained a steady graph, recording a collection of Rs 246.47 crore in week one, followed by Rs 142.52 crore in week two, Rs 69.43 crore in week three and approximately Rs 29 crore in its fourth week ... 'Baahubali 2....
Sachin Tendulkar movie release: Will these controversies of Master Blaster be a part of Sachin: A Billion Dreams?
Edit Yahoo Daily News 27 May 2017
Sachin Tendulkar’s much-awaited biopic, Sachin. A Billion Dreams is all set to release on May 26, 2017 ... A Billion Dreams Movie Review on Twitter by celebs. Sachin Tendulkar film gets a roaring reception as #SachinPremiere trends! ... 1 ... More ... With a career graph that began around the same time, Sachin and Kambli set various records, but Sachin flew through and made records as Vinod Kambli’s career n cricket collapsed in a short span of time ... ....
Can this chart really show what happens next to the stock market?
Edit City A.M. 26 May 2017
On the first page was the following graph and – in a show of dissent that ought to please its originator – we have some issues with it ... As you can see, one line on the graph shows the progress of the S&P; 500, the main US equity market, over the last 18 months or so while the other illustrates the effect of US economic data surprises over the same period....
FactCheck Q&A;: Which party has a better track record on the economy?
Edit Channel 4 26 May 2017
This next graph gives us a different perspective on people’s earnings ... This graph shows how the picture has changed since 1979 ... But within the context of the rest of the graph, the Conservative’s record is marred by the large increases in inequality in previous years ... The graph shows the percentage difference between men’s and women’s hourly earnings ... Here’s the graph from the IFS....
SA ranks third, behind Australia and Canada, in terms of number of mines
Edit Business Day 26 May 2017- 1
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