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LASCNN Algorithm
In graph theory, LASCNN is a Localized Algorithm for Segregation of Critical/Non-critical Nodes The algorithm works on the principle of distinguishing between critical and non-critical nodes for network connectivity based on limited topology information. The algorithm finds the critical nodes with partial information within a few hops. This algorithm can distinguish the critical nodes of the network with high precision, indeed, accuracy can reach 100% when identifying non-critical nodes. The performance of LASCNN is scalable and quite competitive compared to other schemes. Pseudocode The LASCNN algorithm establishes a -hop neighbor list and a duplicate free pair wise connection list based on {{Var, k-hop information. If the neighbors stay connected then the node is non-critical. Function LASCNN(MAHSN) For ∀ A ∈ MAHSN If (A->ConnList.getSize() 1) then A->SetNonCritical() = LEAF Else Continue = TRUE While (Continue TRUE) ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Critical Nodes Application
Critical or Critically may refer to: *Critical, or critical but stable, medical states **Critical, or intensive care medicine *Critical juncture, a discontinuous change studied in the social sciences. *Critical Software, a company specializing in mission and business critical information systems *Critical theory, a school of thought that critiques society and culture by applying knowledge from the social sciences and the humanities * Critically endangered, a risk status for wild species *Criticality (status), the condition of sustaining a nuclear chain reaction Art, entertainment, and media * ''Critical'' (novel), a medical thriller written by Robin Cook * ''Critical'' (TV series), a Sky 1 TV series * "Critical" (''Person of Interest''), an episode of the American television drama series ''Person of Interest'' *"Critical", a 1999 single by Zion I People *Cr1TiKaL (born 1994), an American YouTuber and Twitch streamer See also *Critic *Criticality (other) *Critical Conditi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
PWCT
PWCT is a free open source visual programming language for software development. Goal Programming Without Coding Technology (PWCT) is designed to be a general-purpose visual programming language that can be used for applications and systems development. PWCT can also be used for introducing programming concepts. The project was founded in December 2005 as a free-open source project that supports designing applications through visual programming then generating the source code. The software supports code generation in many textual programming languages. The environment support the time dimension where the programmer can play programs as a movie to learn how to create them step-by-step and get better understanding of the program logic. Changing time is done using a timeline slider which allow the programmer to select a specific point in time to view. History * PWCT was registered on SourceForge in December 2005 * PWCT 1.0 was released on 18 October 2008 * PWCT 1.1 was releas ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Connectivity (graph Theory)
In mathematics and computer science, connectivity is one of the basic concepts of graph theory: it asks for the minimum number of elements (nodes or edges) that need to be removed to separate the remaining nodes into two or more isolated subgraphs. It is closely related to the theory of network flow problems. The connectivity of a graph is an important measure of its resilience as a network. Connected vertices and graphs In an undirected graph , two '' vertices'' and are called connected if contains a path from to . Otherwise, they are called disconnected. If the two vertices are additionally connected by a path of length , i.e. by a single edge, the vertices are called adjacent. A graph is said to be connected if every pair of vertices in the graph is connected. This means that there is a path between every pair of vertices. An undirected graph that is not connected is called disconnected. An undirected graph ''G'' is therefore disconnected if there exist two vertices ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dynamic Connectivity
In computing and graph theory, a dynamic connectivity structure is a data structure that dynamically maintains information about the connected components of a graph. The set ''V'' of vertices of the graph is fixed, but the set ''E'' of edges can change. The three cases, in order of difficulty, are: * Edges are only added to the graph (this can be called ''incremental connectivity''); * Edges are only deleted from the graph (this can be called ''decremental connectivity''); * Edges can be either added or deleted (this can be called ''fully dynamic connectivity''). After each addition/deletion of an edge, the dynamic connectivity structure should adapt itself such that it can give quick answers to queries of the form "is there a path between ''x'' and ''y''?" (equivalently: "do vertices ''x'' and ''y'' belong to the same connected component?"). Incremental connectivity If edges can only be added, then the dynamic connectivity problem can be solved by a Disjoint-set data structure. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Strength Of A Graph
In the branch of mathematics called graph theory, the strength of an undirected graph corresponds to the minimum ratio ''edges removed''/''components created'' in a decomposition of the graph in question. It is a method to compute partitions of the set of vertices and detect zones of high concentration of edges, and is analogous to graph toughness which is defined similarly for vertex removal. Definitions The strength \sigma(G) of an undirected simple graph ''G'' = (''V'', ''E'') admits the three following definitions: * Let \Pi be the set of all partitions of V, and \partial \pi be the set of edges crossing over the sets of the partition \pi\in\Pi, then \displaystyle\sigma(G)=\min_\frac. * Also if \mathcal T is the set of all spanning trees of ''G'', then :: \sigma(G)=\max\left\. * And by linear programming duality, :: \sigma(G)=\min\left\. Complexity Computing the strength of a graph can be done in polynomial time, and the first such algorithm was disco ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cheeger Constant (graph Theory)
In mathematics, the Cheeger constant (also Cheeger number or isoperimetric number) of a graph is a numerical measure of whether or not a graph has a "bottleneck". The Cheeger constant as a measure of "bottleneckedness" is of great interest in many areas: for example, constructing well-connected networks of computers, card shuffling. The graph theoretical notion originated after the Cheeger isoperimetric constant of a compact Riemannian manifold. The Cheeger constant is named after the mathematician Jeff Cheeger. Definition Let be an undirected finite graph with vertex set and edge set . For a collection of vertices , let denote the collection of all edges going from a vertex in to a vertex outside of (sometimes called the ''edge boundary'' of ): :\partial A := \. Note that the edges are unordered, i.e., \ = \. The Cheeger constant of , denoted , is defined by :h(G) := \min \left\. The Cheeger constant is strictly positive if and only if is a connected graph. Intuitive ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Critical Point (network Science)
In network science, a critical point is a value of average degree, which separates random networks that have a giant component from those that do not (i.e. it separates a network in a subcritical regime from one in a supercritical regime). Considering a random network with an average degree \langle k\rangle the critical point is \langle k\rangle = 1 where the average degree is defined by the fraction of the number of edges (e) and nodes (N) in the network, that is \langle k\rangle =\frac. Subcritical regime In a subcritical regime the network has no giant component, only small clusters. In the special case of \langle k\rangle =0 the network is not connected at all. A random network is in a subcritical regime until the average degree exceeds the critical point, that is the network is in a subcritical regime as long as \langle k\rangle 1. Example on different regimes Consider a speed dating event as an example, with the participants as the nodes of the network. At the begi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Depth-first Search
Depth-first search (DFS) is an algorithm for traversing or searching tree or graph data structures. The algorithm starts at the root node (selecting some arbitrary node as the root node in the case of a graph) and explores as far as possible along each branch before backtracking. Extra memory, usually a stack, is needed to keep track of the nodes discovered so far along a specified branch which helps in backtracking of the graph. A version of depth-first search was investigated in the 19th century by French mathematician Charles Pierre Trémaux as a strategy for solving mazes. Properties The time and space analysis of DFS differs according to its application area. In theoretical computer science, DFS is typically used to traverse an entire graph, and takes time where , V, is the number of vertices and , E, the number of edges. This is linear in the size of the graph. In these applications it also uses space O(, V, ) in the worst case to store the stack of vertices on th ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Breadth-first Search
Breadth-first search (BFS) is an algorithm for searching a tree data structure for a node that satisfies a given property. It starts at the tree root and explores all nodes at the present depth prior to moving on to the nodes at the next depth level. Extra memory, usually a queue, is needed to keep track of the child nodes that were encountered but not yet explored. For example, in a chess endgame a chess engine may build the game tree from the current position by applying all possible moves, and use breadth-first search to find a win position for white. Implicit trees (such as game trees or other problem-solving trees) may be of infinite size; breadth-first search is guaranteed to find a solution node if one exists. In contrast, (plain) depth-first search, which explores the node branch as far as possible before backtracking and expanding other nodes, may get lost in an infinite branch and never make it to the solution node. Iterative deepening depth-first search avoids ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Networks
Network, networking and networked may refer to: Science and technology * Network theory, the study of graphs as a representation of relations between discrete objects * Network science, an academic field that studies complex networks Mathematics * Networks, a graph with attributes studied in network theory ** Scale-free network, a network whose degree distribution follows a power law ** Small-world network, a mathematical graph in which most nodes are not neighbors, but have neighbors in common * Flow network, a directed graph where each edge has a capacity and each edge receives a flow Biology * Biological network, any network that applies to biological systems * Ecological network, a representation of interacting species in an ecosystem * Neural network, a network or circuit of neurons Technology and communication * Artificial neural network, a computing system inspired by animal brains * Broadcast network, radio stations, television stations, or other electronic media outlets ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Network Theory
Network theory is the study of graphs as a representation of either symmetric relations or asymmetric relations between discrete objects. In computer science and network science, network theory is a part of graph theory: a network can be defined as a graph in which nodes and/or edges have attributes (e.g. names). Network theory has applications in many disciplines including statistical physics, particle physics, computer science, electrical engineering, biology, archaeology, economics, finance, operations research, climatology, ecology, public health, sociology, and neuroscience. Applications of network theory include logistical networks, the World Wide Web, Internet, gene regulatory networks, metabolic networks, social networks, epistemological networks, etc.; see List of network theory topics for more examples. Euler's solution of the Seven Bridges of Königsberg problem is considered to be the first true proof in the theory of networks. Network optimization Network pr ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
