Edge

Spectral Properties Of Social Networks
section{Spectral Analysis of Social Networks}
The exttt{spectrum} of a graph is the set of its eigenvalues of the exttt{adjacency matrix}. The
eigenvalue spectrum of complex networks provides information about their structural properties.
There has been much research work on spectral properties of uncorrelated random graphs, however,
there is less information on the spectral properties of social networks or sparse complex networks.
We, therefore, want to address this research gap by analyzing the spectral properties of several real–
life networks. The singular value distributions of selected social networks are shown in Figure~
ef{singular_values}. The shows that most social networks have an exponential cutoff distribution.
The Figure ... Show more content on Helpwriting.net ...
In order to quantify the effect of the random and targeted removal of nodes on these networks, we
study, in each of the networks, what fraction of nodes are remaining after the random or targeted
removal of a particular node together with all its out–going links. This process may break an initially
connected core into various disconnected components. Therefore, the simplest quantitative measure
of damage on the network is given by the relative size of the Largest Connected Component (LCC)
of the remaining network. Figure~ ef{fig:LCC_attack} shows the topological resilience of Facebook
social network and other complex networks from different network domains. The topological
resilience of their corresponding exttt{ER} and exttt{random power–law} models is also studied for
the purpose of comparison. The effect of nodes removal on the diameter of these networks is also
studied. These results are shown in the Figure~ ef{fig:diameter_attack}. %egin{pics}[h]{The
effect of Nodes removal on the LCC of 4 Social networks}{fig:robustness_social}
% addsubpic{Change in the LCC of different networks with nodes removal between 0 and 100%}
{width=0.45 extwidth}{robust_lcc}label{fig:LCC_attack}
% addsubpic{Change in the Diameter of different networks with nodes removal between 0 and
100%}{width=0.45 extwidth}{robust_diam}label{fig:diameter_attack}
%end{pics}
egin{pics}[h]{The effect on the LCC of 4
... Get more on HelpWriting.net ...

M14056009 Key Questions
1. 7.5/8
The height in metres of a ball dropped from the top of the CN Tower is given by h(t)= –4.9t2+450,
where t is time elapsed in seconds.
(a) Draw the graph of h with respect to time
(b) Find the average velocity for the first 2 seconds after the ball was dropped h(0)=(0,450), h(2)=
(2,430.4)
= (430.4–450)/(2–0)
= –9.8m/s √
(c) Find the average velocity for the following time intervals
(1) 1 ≤ t ≤ 4 h(1)=(1,445.1) h(4)=(4,371.6)
= (371.6–445.1)/(4–1)
= –24.5m/s √
(2) 1 ≤ t ≤ 2 h(1)=(1,445.1) h(2)=(2,430.4)
= (430.4–445.1)/(2–1)
= –14.7m/s √
(3) 1 ≤ t ≤ 1.5 h(1)=(1,445.1) h(1.5)=(1.5, 438.98)
= (438.98–445.1)/(1.5–1)
= –12.25m/s √
(d) Use the secant method to approximate the instantaneous velocity at t=1 h(0.5) = (0.5, 448.78) ...
Show more content on Helpwriting.net ...
H(2)= –5(2)2+20(2)+1 = –20+40+1 =21 H(2+h)= –5(2+h)2 + 20(2+h) +1 = –5(4+4h+h2) +
40+20h+1 = –20–20h–5h2+40+20h+1= –5h2+21 lim(h–0) H(2+h)–H(2)/h = –5h2+21–21/h = –5h
= –5(0) = 0 √
(b) A particle's motion is described by the equation d=t2–8t+15 where d and t are measured in
metres and seconds. Show that the particle is at rest when t = 4.
D(4)= (4)2–8(4)+15 =16–32+15= –1 D(4+h)= (4+h)2–8(4+h)+15= 16+8h+h2–32–8h+15= h2–1
limD(4+h)–D(4)/h = h2–1+1/h = h =0 √
6. 4/4
For the following graph
(a) Determine the intervals between which the rate of change is positive and negative. The function
is increasing at x–1 and x1, hence its rate of change is positive. The function is decreasing at –
1x1, hence its rate of change is negative. √

(b) State where the rate of change is zero. The instantaneous rate of change is zero at x=–1 and x=1
√
(c) List the local maximums and minimums of the function. F(–1) is a local maximum and F(1) is a
local minimum. √
7. 10/10
For the function f(x) =2x3–7x2+4x+1 (a) Find the instantaneous rate of change at x=0 and x=1 (1)
F(0+h) = 2(h)3 – 7(h)2+4(h)+1 =2h3–7h2+4h+1 F(0) = 1 lim(h–0) (F(0+h)–F(0))/h = (2h3–
7h2+4h+1–1)/h = (2h3–7h2+4h)/h = 2h2–7h+4 = 4 ∴the instantaneous rate of change at x=0 is 4 √

Graph Theory Concepts and Strategies with Ticket to Ride...
Ticket to Ride is a board game created by Alan R. Moon that has been growing in popularity since
its first release in 2004 by Days of Wonder. The game components include a map with cities and
defined train routes, sets of 45 colored, plastic train car tokens for up to five players, destination
tickets, and colored train cards. The premise of the game involves collecting enough of the colored
train cards to claim or build train routes to connect various major cities in the United States and
southern Canada to earn points as well as completing routes designated on the destination tickets.
The game itself is not only a fun way to spend hours playing but it is also a good tool to showcase
various concepts in graph theory and combinatorics. ... Show more content on Helpwriting.net ...
There are also multi–colored locomotive that are used like wild cards. The colored train cards are
shown in Figure 2. The second part of the set up to deal out five destination tickets (three, if not
playing with the Mega Game expansion) a minimum of three which must be retained. Any
destination tickets not kept by a player are returned to draw pile for later in the game. Note that
some versions of the game remove any discarded tickets from play for the rest of the game. An
example of a destination ticket is shown in Figure 3.
On a player's turn, he/she chooses one of three options: Build a train connecting two adjacent cities
using sets of colored train cards to earn points immediately, draw up to two additional colored train
cards to be used later to build a train, or draw three additional destination tickets keeping a
minimum of one to earn points at the end of the game. Play continues in this fashion for each player
until one player has two or fewer train tokens left and then everyone still has one more turn.
The points earned from building a train connecting two adjacent cities are based on the length of the
route with the longer routes earning more points per train token. Routes of length one and two earn
only one point per token while a route of length three earns a total of four

Relational Database And Relational Databases
3.1 Introduction
3.1.1 Graph Databases
A graph database represents data and relationships between this data using concepts from graph data
structures like nodes, edges and properties. Nodes represents the data entities, properties represent
information about the nodes and edges which connect two nodes or a node and a property represent
the relationship between the connected elements. [1] Figure 3.1 Property Graph Model [2]
3.1.2 Triple stores
Triple store is a specific implementation of a graph database that is optimized for storing and
retrieval of triples. A triple is a representation of data in subject–predicate–object relationship. [3]
3.2 Comparison with Relational Database systems
3.2.1 Graph Database and Relational database
Relational databases have a fixed schema. Each table is a set of rows, each of which has a fixed set
of attributes. This type of structure implies that all the rows have values for all the attributes for this
representation to be efficient. However, in recent years, there has been an explosion of unstructured
information like tweets, product reviews, semantic web etc which cannot be represented in the
structured format demanded by the tables. Moreover, it becomes very difficult to find patterns in a
table as it would involve joins of many tables. In contrast, in graph databases, each element in the
database contains a direct connection to its adjacent element. This information helps us to easily find
the interconnectedness of the nodes and

Team Member Duties : Neeraj Kumar ( Team Leader )
Team Member Duties
Neeraj Kumar (Team Leader)
 Selecting and understanding the concept based on the past research experience on sensor database
networks and distributed programming.
 Strategic plan design on weekly basis helped in completion of project.
 Implementation of leader election algorithm.
 Dividing and assigning the task based on the team members interest area and capabilities.
 Managing the whole project with full cooperation with all team members with good team
communication.
Satish Ekambaram
 Drafting the whole paper with APA format.
 Deep research on the value and need of the leader election algorithm in mobile ad hoc network.
 Finding out the real applications implementing the leader election algorithm.
Srikanth Bommana
 Good research on the history related topic with the whole project.
 Research on what the mobile ad hoc network and its need and evolution.
 Finding out the very brief and good conclusion of the whole project. Abstract
Technology advancement is growing very rapidly one example we can see surrounding us is
wireless networks and its related very complex applications such as sensor database network,
robotics military and so on. At the starting point following paper represents about the mobile ad hoc
network and related basic history. After that research paper explores the problems related with the
current technology and major drawbacks. Later paper shows the need of the leader election
algorithm and its implementation. At the end it

The Edge Geodetic Domination Number
ABSTRACT In this paper the concept of upper edge geodetic domination number (UEGD number)
and upper connected edge geodetic domination number (UCEGD number) of a graph is studied. An
edge geodetic domination set (EGD set) S in a connected graph is minimal EGD set if no proper
subset of S is an edge geodetic domination set. The maximum cardinality of all the minimal edge
geodetic domination set is called UEGD number. An EGD set S in a connected graph is minimal
CEGD set if no proper subset of S is a CEGD set. The maximum cardinality of all the minimal
connected edge geodetic domination set is called UCEGD number. Here the UEGD number and
UCEGD number of certain graphs are identified. Also for two positive integers p and q there exist
some connected graph with EGD number p and UEGD number q. Similarly for two positive integers
p and q there exist some connected graph with CEGD number p and UCEGD number q.
Keywords
Geodetic domination number, edge geodetic domination number, upper edge geodetic domination
number, upper connected edge geodetic domination number.
AMS subject Classification: 05C12, 05C05
1 INTRODUCTION
By a graph G = (V, E) we consider a finite undirected graph without loops or multiple edges. The
order and size of a graph are denoted by p and q respectively. For the basic graph theoretic notations
and terminology we refer to Buckley and Harary [4].For vertices u and v in a connected graph G, the
distance d(u, v) is the length of a shortest uv path in G. A

Mathematics Has Become A Part Of Our Life
ABSTRACT: Mathematics has become part of our life. Graph Theory is a branch of mathematics
that plays a major role in every field of human being. In this paper we define different matrices
associated with the Graphs along with some properties of a graph. And Rank of rank of an incidence
matrix. Key Words: Adjacency matrix, Incidence matrix, Degree matrix, Circuit matrix and Line
graph. INTRODUCTION: Incidence Matrix is one of methods of representing the graph. Let G =
(V,E) be graph whose vertices and edges are labeled as v_1,v_2,........v_n and e_1,e_2,........e_m. An
incidence matrix B associated with graph G of order n×m is defined by b_ij={█(1 if v_i is incident
with e_j@0 Otherwise )┤ [4] The graph and its incidence matrix are shown as follows: The
incidence matrix contains only two elements 0 and 1. Such a matrix is called a binary matrix or (0 1)
– matrix. For a given any geometric representation of a graph without self–loops we can easily write
its corresponding incidence matrix. On the other hand if we were given an incidence matrix B we
can construct a graph without any difficulty. The graph and its incidence matrix are simply two
alternative ways of representing the same graph. [1] PROPERTIES: Some observations of incidence
matrix and it's graph. Since every edge is incident on exactly two

Annotated Bibliography On Import Java
/*package adsa;*/
/** * * @author GOPIKRISHN */ import java.util.HashSet; import java.util.Iterator; import
java.util.Random; import java.util.Set; import java.util.InputMismatchException;
public class AdjListGraph
{
private int distances[]; private int nodes; public static final int MAX_VALUE = 999; private
SetInteger visited; private SetInteger unvisited; private int adjacencyMatrix[][]; public
AdjListGraph(int nodes) //Constructor { this.nodes = nodes; distances = new int[nodes + 1]; visited
= new HashSetInteger(); unvisited = new HashSetInteger(); adjacencyMatrix = new int[nodes
+ 1][nodes + 1]; } public void Dijkstra(int AdjacencyMatrix[][], int source) { int evaluationNode;
for (int i = 1; i = nodes; i++) for (int j = 1; j = nodes; j++) adjacencyMatrix[i][j] =
AdjacencyMatrix[i][j]; for (int i = 1; i = nodes; i++) { distances[i] = Integer.MAX_VALUE; }
unvisited.add(source); distances[source] = 0; while (!unvisited.isEmpty()) { evaluationNode =
getNodeWithMinimumDistanceFromUnvisited(); unvisited.remove(evaluationNode);
visited.add(evaluationNode); evaluateNeighbours(evaluationNode); } } private int
getNodeWithMinimumDistanceFromUnvisited() { int min ; int

Use Of A Theory And Pagerank Algorithm
Mathematics in Football
The purpose of this report is to research the use of mathematics in football. In particular, we have
researched the use of network theory and PageRank algorithm. The report aims to consider which
strategies are optimal and discuss whether teams ought to adopt a more mathematical approach to
on–field play.
Introduction
Network theory is becoming more and more used within football to help teams analyse and change
their style of play. It consists of a collection of nodes, with edges joining them that are weighted
depending on how frequent a path is used. In football, the nodes represent the players of a team, the
edges will be the passes between them and the weight will be the amount of passes between them.
We will ... Show more content on Helpwriting.net ...
The PageRank algorithm gives more weight to a link if it comes from a high–ranking page. In terms
of football this means a pass from a 'popular' player is more valuable than a pass from a player who
is hardly involved in the game. Player's statistics constantly change throughout the game and the
PageRank score of a player depends on the score of his teammates so all scores must be computed at
the same time and the algorithm is only finished once the game has ended. In summary, PageRank
algorithm roughly assigns to each player the probability that he will have the ball after a reasonable
number of passes have been made. [8]
Mathematical Background
One way to analyse players position is closeness centrality, which is defined as the inverse geodesic
distance of a node in the network [1]:
(1)
Where Aij is the total amount of passes from player i to j. This formula uses incoming and outgoing
passes as equal measure. This will show how well connected the players are to each other.
Another way is betweenness centrality, which measures the extent to which a node lies on paths
between other nodes[2]:
(2)
Where is the number of geodesic paths from j to k going through i and is the total number of
geodesic paths.
The PageRank algorithm can be defined by: (3)

Where = is the total number of passes made by player , is a heuristic parameter that represents the
probability of the player keeping the

Hafordan Function Essay
3.27. Cut vertex: Let G= (V, E) be a connected graph. A vertex V ϵ G is called a cut vertex of graph
G, if G – V results in a disconnected graph G.
3.28. Cut edge: Let G= (V, E) be a connected graph, an edge E ϵ G is called a cut edge of graph G, if
G–E result in a disconnected graph G.
3.29. Euler graph: A connected graph G=(V, E) is said to be Euler graph (traversable), if there exists
a path which includes, (which contains each edge of the graph G exactly once) and each vertex at
least once (if we can draw the graph on a plain paper without repeating any edge or letting the pen).
Such a path is called Euler path. ... Show more content on Helpwriting.net ...
A Hamiltonian path presents the efficiency of including every vertex in the route.
4.2. Traffic Signal Lights:
To study the traffic control problem at an arbitrary point of intersection, it has to be modeled
mathematically by using a simple graph for the traffic accumulation data problem. The set of edges
of the rudimentary graph will represent the communication link between the set of nodes at an
intersection. In the graph stand for the traffic control problem, the traffic streams which may move
at the same time at an intersection without any difference will be joined by an edge and the streams
which cannot move together will not be connected by an edge.
The functioning of traffic lights i.e. turning Green/Red/Yellow lights and timing between them. Here
vertex coloring technique is utilised to solve contravenes of time and space by identifying the
chromatic number for the number of cycles needed.
4.3. Social Networks:
We connect with friends via social media or a video gets viral, here user is a Vertex and other
connected users produce an edge, therefore videos get viral when reached to certain connections. In
sociology, economics, political science, medicine, social biology, psychology, anthropology, history,
and related fields, one often wants to study a society by examining the structure of connections
within the society. This could befriend networks in a high school or Facebook, support networks in a
village or political/business

Gossip-Based Algorithms
1. INTRODUCTION
Gossip–based algorithm plays a major part for distributing simple and efficient information in large
networks. One of the examples of gossip–based algorithm is rumor –spreading model. It is also
called as rumor mongering. It is introduced by Daley Kendall (D K model) in the context of
duplicated databases. The rumor spreading algorithm is an example of epidemic process. It is mainly
used to examine in the view of mathematics. The algorithm follows synchronous rounds. The main
aim of rumor spreading is to spread a rumor to all nodes in a social network in small no of rounds.
At the beginning of the round, the information is sent to initial node known as start node. Then the
information is sent to all nodes. The node having information will not accept to receive the
information again. While executing the algorithm the graph and degree of nodes must be constant.
In case of dynamic networks, an evolving graph is introduced to study the behavior of graph and
nodes.
Fig. 1 Graph connected with rumors
1.1. Problem statement:
To begin with the rumor spreading algorithm mainly concentrates the broadcasting of message that
is the information should reach all nodes of a graph. Secondly it concerns about the completion time
i.e., within how many rounds the information is reached to all nodes. From the above research the
problem can be stated as :each node transfers the rumor what has but in cases the node might not be
knowing what information that the neighbour

Connectivity And Related Survivability Issues Of Wsns
In the previous section, we mainly focus on the connectivity and related survivability issues of
WSNs. It is the foundation that we deploy WSNs to achieve its main objective which is to monitor
the field of interest / detect desired data and it is coverage that determines whether the field of
interest is under strict surveillance or not. So, in this section, we will summarize the related work on
integrated connectivity and coverage problem in WSN. In [68], [69], it's clear that connectivity only
requires that the location of any active node be within the communication range of one or more
active nodes such that all active nodes can form a connected communication backbone, while
coverage requires all locations in the coverage region be ... Show more content on Helpwriting.net
...
The objective of the research efforts on relationship between coverage and connectivity is to utilize
the minimum number of sensor nodes to achieve required coverage degree while maintaining
desired system connectivity.
In the following parts of this section, we will firstly summarize the related work on analyzing the
relationship between the sensing range Rs and communication range Rc. Then, we demonstrate the
research efforts on finding critical conditions for achieving connectivity and coverage. Finally, we
survey the approaches on connectivity and coverage in WSNs.
Critical condition for 1–coverage to achieve 1–connectivity:
In [68], [69], authors first time proved the sufficient condition for 1–coverage imply to 1–
connectivity: for a set of sensors that at least 1–cover a convex region A, the communication graph
is connected if Rc≥ 2Rs. Based on this result, when we design a WSN system, we can focus on
node deployment strategy and elimiate the connectivity problem by assuming the Rc≥ 2Rs. Zhang
and Hou in [70] present a distributed Optimal Geographical Density Control (OGDC) scheme that
considers the integrated combine coverage and connectivity problem. The objective of this work is
to minimize the number of active nodes in the WSN. Similar to [68], [69], the authors also proved
that coverage implies connectivity when Rc≥ 2Rs. In OGDC, the nodes can automatically

Business Enterprise Task 2 Opportunity Analysis
Business Enterprise Task 2 Opportunity Analysis
By Peter Murtagh and Joe Curran
Happy Housing
We have come up with an idea for an app that is very scarce on the market. The idea is to create an
app that will allow different estate agents to display their properties that they have on their online
websites, on our app. In the following assignment we describe the opportunity analysis. This is
looking at the opportunity in terms of the market, the competition, the target market, the extent of
demand and the industry.
1. Market opportunity
The idea that we are going to propose is an app to gather all information the user inserts about
properties for sale by other estate agents. We feel that is a need in the market because there isn't any
other form of app across the various markets that try's to do what we are proposing. We found the
idea by looking through newspapers and noticing that the estate agents had websites but no mention
of apps. We decided to look into the aspect of a property app. There was very few if any and
therefore went forth with the proposal of creating our property app. We see that this type of app has
tried to be tested. The Belfast Telegraph has attempted this approach to creating an app. They have
named theirs Property news. However they have not used it to its full potential as they have only
included it on the apple store. In doing this they have left out the android and windows markets and
there for them users too.
2. Explain the proposed

Old Fire Station
Site analysis
1. The Old Fire Station #1 is located in South Beach, in the intersection between Jefferson Ave and
11th St. was built in 1967. It is still currently functioning but it is going to be relocated to the current
parking lot across the street. We are planning to give a different use to the empty building but due to
deterioration over time, a lot of work has to be done to reinforce the structure and redesigning the
plumbing, HVAC and electrical systems of the building. The site is currently owned by the city and
it is classified as GU (government use) but the location is designated as residential multifamily low
intensity therefore we are planning to use it as affordable housing or offices.
2. Land Location: 1051 Jefferson Avenue, Miami beach, FL, 33139
3. Property Value: ... Show more content on Helpwriting.net ...
For more information refer to the code chapter 143, division 3, or in the Land use, zoning and
building code information section.
7. Site map:
8. Parcel Size:
Adjusted Area: 11,213 Sq Ft
Lot Size: 21,000 Sq Ft
9. The building has been used since its construction in 1967 as a fire station. It is the first fire station
that was built in south beach. 10. Market needs: To follow the client wishes, due to the highly
raising prices of real estate, we were considering building affordable housing. Also, another option
is to construct offices for the city to use.
11. Miami–Dade county stats shows that in the period of 2007–2015, weekly wages have declined
15.9% while real estate prices have been increasing. In average, to be able to mortage on a home at
the upper limit of the lowest tier homes, the person should have an income of 40,300 USD per year,
while the average income per year in Miami–dade county is of 38,000 USD.
The average price on the housing surrounding the fire station is around 300,000 USD
Graph of Average Weekly Wages (2015 USD)
Graph of single–family home

Multi-objective Reconfiguration of Electrical Distribution...
EDSs are mainly designed meshed but operated radially for some technical and financial concerns.
Distribution networks can be represented with a graph in ordered pairs consisting of a set of
vertices, i.e. buses and a set of edges, i.e. branches; in terms of mathematics this equivalents to a
sparse matrix which its non–zero elements signifies the existence of an edge in the system. On this
basis a typical distribution network is radial if it forms a tree where each load bus is exactly supplied
from one source node, i.e. substation bus [11]. This suggests MOEDNRC problem as identifying the
set of non–dominated trees of the given graph. In this section we've devised a heuristic technique
based on this idea as well as the rules defined in [30] to retain the connectivity and radial properties
of individuals during the optimization process. It's worth mentioning that these properties are
broadly disturbed by EAs due to the stochastic nature of these algorithms unless a heuristic plan is
devised to preserve the mentioned properties. As a result generation of infeasible agents in sheer
numbers by EAs is quite a normal observation. The proposed technique is able to prevail over this
shortcoming and would increase the performance of EAs as well. Before proceeding with the
designed technique, some terminologies are first introduced to set the stage for the plan.
Loop vectors (LVs)
The term LV is used to identify branches contributing to forming loops in EDSs when all

The Proliferation Of Gps Enabled Mobile Devises And The...
III.RELATED WORKS Here we are discussing some papers related to k–cover group queries
clustering in geo–social networks. 1. A General Framework for Geo–Social Query Processing In this
paper make a case for concerning the proliferation of GPS enabled mobile devises and the
popularity of social networking have recently light emitting diode to the zoom of Geo–Social
Networks (GEOSN s). GEOSN s has created a fertile ground for new location based social
interactions. These are expedited by GEOSN queries that extract helpful info combining each the
social relationships and therefore the current location of the users. This paper constitutes the rst
systematic work on GEOSN question process. A general framework that ores exile knowledge
management and algorithmic style. The design segregates the social, geographical and question
process modules. every GEOSN question is processed via a clear combination of primitive queries
issued to the social and geographical Modules.to demonstrate the facility of framework by
introducing several asic and advanced question sorts, and making numerous solutions for each
type. Finally, perform Associate in Nursing thorough Experimental analysis with real and synthetic
datasets, supported realistic implementations with each business software (such as mongodb) and
progressive analysis strategies. Results conform the viability of our framework in typical large–scale
GEOSN.. 2. The Where and When of Finding New Friends: Analysis of a Location

Description Of A Graph
Use the map to create a graph where vertices represent street intersections and edges represent
streets. Define c(u,v) = 1 for all edges (u,v). Since a street can be traversed, start off by creating a
directed edge in each direction, then make the transformation to a flow problem with no antiparallel
edges as described in the section. Make the home the source and the school the sink. If there exist at
least two distinct paths from source to sink then the flow will be at least 2 because we could assign
f(u,v) = 1 for each of those edges. However, if there is at most one distinct path from source to sink
then there must exist a bridge edge (u, v) whose removal would disconnect s from t. Since c(u, v) =
1, the flow into u is at most 1. We may ... Show more content on Helpwriting.net ...
Exercise 26.2–10
Suppose we already have a maximum flow f. Consider a new graph G where we set the capacity of
edge (u, v) to f (u, v). Run Ford–Fulkerson, with the mod– ification that we remove an edge if its
flow reaches its capacity. In other words, if f(u,v) = c(u,v) then there should be no reverse edge
appearing in residual network. This will still produce correct output in our case because we never
exceed the actual maximum flow through an edge, so it is never advantageous to cancel flow. The
augmenting paths chosen in this modified version of Ford– Fulkerson are precisely the ones we
want. There are at most |E| because every augmenting path produces at least one edge whose flow is
equal to its capacity, which we set to be the actual flow for the edge in a maximum flow, and our
modification prevents us from ever destroying this progress.
Problem 26–5
a. Since the capacity of a cut is the sum of the capacity of the edges going from a vertex on one side
to a vertex on the other, it is less than or equal to the sum of the capacities of all of the edges. Since
each of the edges has a capacity that is ≤ C, if we were to replace the capacity of each edge with C,
we would only be potentially increasing the sum of the capacities of all the edges. After so changing
the capacities of the edges, the sum of the capacities of all the edges is equal to C|E|, potentially an
overestimate of the original capacity of any cut, and so of the minimum cut.
b.

Data And The Standard Model Of Its Representation As Well...
In this Chapter, we present the background needed to understand the work proposed in this thesis.
As our research mainly concerns with securing provenance, Section 2.1 will cover provenance data
and the standard model of its representation as well as the applications of securing provenance.
Section 2.2 introduces graph databases that will be used later in storing provenance in our prototype.
Section 2.3 explores workflow systems and workflow provenance. Section 2.4 illustrates the main
security principles that will be tackled in the thesis and inference problem that attacks privacy.
Finally, Section 2.5 summarizes the main content of this chapter.
2.1 What is provenance?
Provenance (aka lineage) is a descriptive metadata (i.e. data about data). It specifies not only the
properties of an object but also the history of deriving this object. As provenance touches many
different domains and applications, it has different definitions that represent different views of
provenance such as Description of the origins of data and the process by which it arrived at the
database [20],Metadata recording the process of experiment workflows, annotations, and notes
about experiments [50].
The rationale behind provenance has been long established, for example log files and metadata, but
the term provenance is recent and it is gaining popularity particularly in workflow systems.
Descriptive metadata only becomes part of provenance when one also specifies its relationship to
deriving an

Should Zoning Laws Be Responsible For The Cleanup?
Even though you didn't cause the contamination, as the owner you are responsible for the cleanup.
Because of the spill, selling the property in the future will be a hassle. The actual value for this
property will be greatly decreased. Even if all of the hazardous materials get cleaned up, the
property will be considered tainted to potential buyers.
A local businessman has applied for a permit to construct a bar that will feature adult dancing in a
commercially zoned area across the street from your residential subdivision. As an owner of a
$250,000 house within the subdivision, would you favor or oppose this development? What effect
do you think it could have on the value of your property? If you were opposed, how could you fight
approval of the permit?
The development of an adult dancing business around a residential area can give a negative
reputation to the neighborhood. Therefore, resulting in a negative affect on property values. There
should be zoning laws in place to protect the property values in the subdivision. An adult business
such as this should only be allowed in zoned areas that are specified for this type of business, not
around residential subdivisions. The residents of the subdivision should assemble and argue the
zoning laws to the correct people.
A medium–size city has proposed to build a greenway along a creek that flows through the center
of the city. The city wants to clear a strip about 50 feet wide and construct a paved path for bicycles
and

mth221 r2 network flows case study Essay
23
Network Flows
Author: versity. Arthur M. Hobbs, Department of Mathematics, Texas AM Uni–
Prerequisites: The prerequisites for this chapter are graphs and trees. See
Sections 9.1 and 10.1 of Discrete Mathematics and Its Applications.
Introduction
In this chapter we solve three very different problems.
Example 1
Joe the plumber has made an interesting offer. He says he has lots of short pieces of varying gauges
of copper pipe; they are nearly worthless to him, but for only 1/5 of the usual cost of installing a
plumbing connection under your house, he will use a bunch of T– and Y–joints he picked up at a
distress sale and these small pipes to build the network shown in Figure 1. He claims that it will
deliver three gallons per minute ... Show more content on Helpwriting.net ...
Example 4
Find a flow in the graph of Figure 3.
Solution:
The path p = s, b, a, t extends from s to t, and seen as a sequence of pipes, the largest amount of flow
that could travel along it is the minimum of the capacities of the pipes comprising it. This minimum
is 2, which is c(s, b)
Chapter 23 Network Flows
Figure 3.
411
A small capacitated s,t–graph.
and also c(b, a). Thus we put number pairs on each of the edges, the second entry being 2 for each

edge in the path and 0 for the other two edges. The result is shown in Figure 4.
Figure 4.
Graph of Figure 3 with flow along path s,b,a,t.
There are two ways we can view a flow, and Example 4 illustrates them both. One view is to trace
out the path from the source to the sink of one or more units of flow. In the example, path p is such a
path. The other view is to measure the total flow in each edge of the graph. This view is shown in
the example by our placing the amount of flow along each edge. Since there is actually only one
flow, namely the orderly procession of fluid from the source to the sink through the network, these
two views must be equivalent.
When solving the problem of finding maximum flows through the graph, the second view is
preferable for two reasons. If we are searching a very large network by hand, it may well be
impossible for us to find a best set

Connectivity And Network Security : Connectivity
Connectivity and Network Security
1. Introduction In this paper, we will look into three topics: connectivity, Menger 's theorem, and
network flows to further understand the application of connectivity such as network systems. In
graph theory, connectivity is an important topic and can be applied to many different areas. By
considering the connectivity of the graph(network system map), we will be able to see clearly the
problems of the graph(the system), such as low–connectivity that may lead to the vulnerability of an
attack. Once we know the properties of the graph(the system), we can determine or change how the
graph is or should be.
2. Connectivity
A graph G is connected if for all pairs u, v ∈ G, there is a path in G from u to v. Note that it suffices
for there to be a walk from u to v. [Graph Theory, p. 9] A walk in G is a sequence of vertices
v0,v1,v2,...,vk, and a sequence of edges (vi, vi+1) ∈ E(G). A walk is a path if all vi are distinct.
[graph_theory_notes, p. 8] Figure 1 [Graph Theory, p. 9]
A (connected) component of G is a connected subgraph that is maximal by inclusion. We say G is
connected if and only if it has one connected component. [Graph Theory, p. 9]
Figure 2 [Graph Theory, p. 9]
2.1 Vertex connectivity
A vertex cut in a connected graph G = (V,E) is a set S ⊆ V such that GS:= G[V S] has more than one
connected component. A cut vertex is a vertex v such that {v} is a cut. [Graph Theory, p. 17]
Notation GS= G[V S] means that, given a subset

A German Family With Young ( Pre School ) Essay
A German family with young (pre–school) children is moving to London for work (with a bank in
The City) for a period of at least two years. Explain the options of where they might live and make a
recommendation.
Situation:
From an Estate Agent's view, what is the best advice to give a banker's family moving to London for
a limited time only?
Introduction
As a German family moves to London for work with a bank in The City, they ask for advice on how
and where to live in London. From an estate agent's view, this report looks into the London housing
market, presents advantages and disadvantages to investment options and recommends a property
for the family.
I. The Family
The father is Frank Schmidt, 38 years old and working as a banker. He earns an annual income of
GBP 280,000.00 and works 38 hours per week plus overtime. His wife, Corinna Schmidt, 36 years
old, is the mother of the two children and self–employed as a sales agent. She works approximately
15 hours per week and earns about GBP 20,000.00 per year. Their children are Lea Schmidt, 6 years
old and Lucas Schmidt, 4 years old, both in preschool.
i. Requirements The family moves to London because the father was offered a job with a bank in
The City. Therefore, public transportation should be nearby and a good traffic connection from their
home to The City is required. Also, a school and preschool are needed close to their abode because
they will stay in London for at least two years. Specifically, the

How Rent Control Has Helped New York Economically And How...
This essay would be an economic analysis concerning how rent control is used to ensure housing is
affordable in New York. Using the market model, information and numerical statistics, this essay
would prove how rent control has helped New York economically and how London currently has
rent inflation. An explanation will then be given to why London needs to introduce rent control, and
if London does not do that, there would be some serious consequences. An economic analysis will
be given to the effects of introduction of rent control in London. Rent control is used to ensure
housing is affordable. Rent control basically means price control usually set by the government that
limits the amount a property owner can charge for renting out a home, apartment or any other real
estate. Rent control acts as a price ceiling by preventing rents from being charged higher than a
certain price. It is argued that governments need to help the poor find affordable housing by placing
a ceiling on the rents the landlords charge their tenants. In New York, 77% of households renting
rather than owning their homes, according to the National Low Income Housing Coalition. Carl
Weisbrod, chairman of the New York City planning commission, said rent regulation is essential
for the future of the city, for its economic goals, for social equality to make a city attractive and
available for all, rich, poor and middle class. Weisbrod added that the programme will ensure New
York remains

Distribution Of Minimum Spanning Trees
Distributed Veriﬁcation of Minimum Spanning Trees
Authors: Amos Korman, Shay Kutten
Problem Statement: A graph and a tree is given as input in a distributed manner and the algorithm is
should be able to verifiy if the tree is a Minimum Spanning Tree (MST).
Detailed Explanation of the Problem Statement
Definitions
Spanning tree: A spanning tree of an undirected graph is a subgraph which is a tree and includes all
the vertices of G.
Minimum Spanning Tree (MST) : A spanning tree of a graph whose weight (sum of weight of its
edges) is less than or equal to the weight of all other spanning trees of the graph.
Verification of a Spanning Tree: A graph and a tree is given as input and the algorithm should check
if the tree is an MST for the graph.
In distributed verification of Minimum Spanning Trees, the input is provided in a distributed manner
which means that each node of the graph knows which of its edges belong to the tree. A node does
not have any knowledge of the edges which do not emanate from it. The verification algorithm
should label the vertices of the graph so that every node, given its own label and the labels of its
neighbours only is able to detect if these edges are MST edges or not and whether the input tree is
an MST.
Motivation
The motivation for working on verification algorithms is that verification is easier than computation.
In a distributed setting verification is even more important because the tree is given in a distributed
manner and computing such a

The Plan For The Group Adventure
For our group adventure, we did something that no one would expect. After considering Professor
Carly's recommendation, we decide to go with it. We decide to meet up before class on Wednesday
at the nearby Starbucks. But, we met at Starbucks an hour before class, which is 0700 am. It was the
only option for all of us since there wasn't any time slot that is available for all of us. It was really
tough waking up for the group adventure, but it was fun. While drinking coffee and eating breakfast,
we get to know more about each other and we got close very well. Other than meeting at Starbucks,
we get together again at Walter Library, where we discussed for our upcoming group presentation.
There, we discussed various of things, and cleared ... Show more content on Helpwriting.net ...
For example, while making for our group presentation, I recommend to the group using Prezi, which
is an online based presentation slide. Although it was my responsibility in making the slide look
good during the presentation, I decided that we all should have the chance to edit the slide, and
make it look good, rather than I doing it by myself, therefore, by doing that way, there won't be any
superiority feeling towards one another. Another concepts is Group Cohesiveness. Having a good
bond within the group members is a must, since it will allow us all to work more efficiently,
resulting higher quality of result. Building cohesiveness is like bringing us together. The main
strategic to build group cohesiveness are encouraging compatible membership, develop shared
goals, accomplish task, develop a positive history of cooperation, and promote acceptance of group
members (80). During our group adventure, we developed our group cohesiveness very well. Our
first meeting was very awkward, we encourage one another, talk about where we came from. During
our first meeting at Starbucks, we enjoy each other's company where we talk about life, school,
traveling, and work experiences. We shared the same goal from the beginning where we all aim to
get good grades from this class through the small group projects. Our first time working together is
when preparing our group adventure presentation. We work very cooperatively, dividing jobs within
one another,

Explanation Of A Computer System
#include
#include //in this version, you only need left //and right rotation, not 4 cases
#include
#include using namespace std;
struct Node
{
int data; struct Node* left; struct Node* right; int height;
};
//a function to calculate height of the tree int height(struct Node* root)
{
if(root == NULL) { return 0; //if there is no node, return 0 } return root–height; //else, repeat the
function
}
//a helper function to create a new node faster
Node* newNode(int data)
{
Node* node = new Node(); node–data = data; node–left = NULL; node–right = NULL; node–
height = 1; // new node is added at leaf return (node); //return the pointer to the newly created node
}
//rotations
Node* rightRotate(Node* input)
{
Node* x ... Show more content on Helpwriting.net ...
If this node is unbalanced, there are 4 cases //Left Left case //notice balance will change depends on
how you //calculate your balance factor if(balance 1 data node–left–data) { return
rightRotate(node); }
//Right Right case if(balance –1 data node–right–data) { return leftRotate(node); }
//Left Right case if(balance 1 data node–left–data) { node–left = leftRotate(node–left);
return rightRotate(node); }
//Right Left case if(balance –1 data node–right–data) { //swapping using rightRotate,

since it is a pointer node–right = rightRotate(node–right); return leftRotate(node); }
//return the (unchanged) node pointer return node; }
Node* FindMinNode(Node* root) //find the minimum value node in the tree
{
Node* current = root; //keep traversing to the leftest leaf since it WILL be in the left while(current–
left != NULL) { current = current–left; } return current;
}
//recursion are like moving from stations to
//stations
Node* deleteNode(Node* root, int data)
{
//1. Perform standard BST delete if(root == NULL) { return root; } //if the key to be deleted is
smaller than //root's key, then go left, recursively if( data root–data) { root–left =
deleteNode(root–left, data); }
//if the key to be deleted is bigger than //root's key, then go right, recursively else if(data root–
data) { root–right =

The Power Of Representing Problems As A Knowledge Network
Abstract– IN this paper we review the power of representing problems as a knowledge network and
some of the applications of knowledge networks in civil engineering through explaining the search
methodology of Dijkstra and kruskal algorithms which are two of the most common algorithms
applied in this field
Keywords–Knowledge Network; Graph Theory; Civil Engineering, dijkstras algorithm, kruskal
algoithm; shortest path; minimum spanning tree; trusses
I. INTRODUCTION
This paper reviews 3 applications for knowledge networks in civil engineering, but before we
review these problem we talk about the importance of problem representation and how it can
transfer the experience of in certain field to another, that's what Simon did in the known number
scrabble game.
In section two we explain what is knowledge network and how does it work, in section three we
review the shortest path problem and how to apply dijkstra algorithm, in section four we review the
minimum spanning tree (MST) problem and how to solve it using kruskal algorithm, in section five
we explain the representation of trusses as a networks and how could this be useful.
II. KNOWLEDGE NETWORK
The network consists of group of points represented by nodes and are connected through group of
lines called edges, if every edge in the graph has a direction then the graph is directed
Figure 1: connected network
III. WHY DO WE REPRESENT PROBLEMS
Representation of problems help us to transfer the experience we have

Model Development By Dependency Network Structure Inference
3.2. Model development by dependency network structure inference
Inference of network structures from data is a common procedure in Systems Science research [1],
utilized, for example, in Systems Biology to reconstruct and integrate genomic, proteomic and
metabolic pathways [2, 3] and in Neuroinformatics to understand the anatomical tracts and the
functional networks of the brain [4]. Consequently, several available methods have been defined and
implemented by computational algorithms in the Artificial intelligence (AI) field, to simultaneously
explore numerous variables. One of these AI approaches were Bayesian networks (BN), first
proposed by Judea Pearl in the 1980s with further developments by investigators from diverse fields
[5]. The general form of BN model is given by the chain rule: where P(X_v) is the joint probability
distribution over the set of X_v variables, P(X_v/X_pa(v) ) is the conditional probability distribution
of X_v given X_pa(v) that is parent variable of each X_v variable [6]. The chain rule in (1)
factorizes the dependence–independence pairwise relations as also encrypts conditional
independence relations between two variables given a third one, and the extensions to
neighborhoods by Markov blankets (See Pearl [7], Kjærulff Madsen [6], Nagarajan, Scutari,
Lèbre [8] and Neapolitan [9] for more details).
The full structure factorized by the chain rule is represented by a directed acyclic graph (DAG),
defined as G=(V,E), where V denotes the set

A Necessary Condition For The Storage Of Information
A necessary condition for the storage of information in the computer 's memory is the ability to
transform this very information in the appropriate form for your computer. In the event that this
condition is satisfied, it is necessary to determine the structure, it is suitable for information is
present, one that will provide a set of capabilities required to work with it. Here, the structure refers
to the way the information by which the aggregate of individual elements form a unity, due to their
relationship with each other. Assembled for any rules and logically related between the data can be
processed very efficiently, since for them the overall structure provides a set of management
capabilities – one of the things by which achieved good results in solving various problems. But not
every object is present in any form, and possibly do for him there is only one single method of
interpretation, therefore, a definite plus for the programmer to know all existing data structures. So
often have to make a choice between the different methods of data storage, and this choice depends
on the performance of the product. Speaking of not computing can show a single case where the
information is visible to a clear structure. A good example is the book of different content. They are
divided into pages, paragraphs and chapters are, as a rule, table of contents, i.e. the interface to use
them. In broad terms, the structure has any living creature without organic unlikely, have been able

Online Forums And Platforms Of Social Media
2. SOCIAL MEDIAANALYTICS
The several online forums and platforms that allow a person to synthesize, update, delete and
exchange data is Social media [10]. Social media can be categorized [30, 31] as:
Social networks: The explosion of startups is causing new social networks to pop up.
Blogs: The best way to put an end to that silly belief is to read a large number of blogs.
Microblogs: Studies by Treude et al., Storey, and Yuan et al. have shown that a wealth of interesting
information is stored in these microblogs.
Social news: Sift through journals so that others don 't have to.
Social bookmarking: Popular way to return to your site regularly to see if there something new and
interesting.
Media sharing: Where content hunters ... Show more content on Helpwriting.net ...
Social media analytics has seen a widespread application in marketing of late. This is due to the
growing adoption of social media by people [32]. Forrester Research [5], projects social media to be
one of the fastest growing marketing channels in the US between 2010 and 2015 [33]. User–
generated content and interactions between the network entities are the two main sources of
information in social media. Social media analytics can be categorized into two groups based on
this:
Content–based analytics: This type of analytics deals with large amounts of unstructured and noisy
data (Text, audio, video and images) created and exchanged by users on social media platforms, as
discussed earlier, can be applied to derive insight from such data. Data processing challenges can be
solved by adopting big data technologies.
Structure–based analytics (Social network analytics): This type of analytics deals with gaining
intelligence from the participants' relationships and creating structural attributes of a social network.
The structure of a social network is created with the help of nodes and edges, as a network graph,
where each participant is represented by a node and each edge represents the relationship between
two participants. We discuss two kinds of graphs, social graphs and activity graphs [34].
In social graphs, an edge between a pair of nodes only indicates the existence of a relationship
between two corresponding participants. Social graphs can be analyzed to

Chronicle Of A Death Foretold By Gabriel Garcia Marquez
The novella Chronicle of a Death Foretold, a journalistic account of a historical murder, is written
by author Gabriel García Márquez. Continually through his career Garcia Marquez employs
journalistic writing techniques in his fiction, and particularly in Chronicle of a Death Foretold in
order to produce a seemingly more authentic and credible work( Gardener 3–4). This particular
novel reads as if it is fictional. However, readers are interested to know that the account is based on
a factual event. It is based on an event involving some of the authors closest friends thirty years
before the novel's date of publication. It is believed to be A perfect integration of literature and
journalism(Gardener 1). Marquez tells readers he uses ... Show more content on Helpwriting.net ...
The novel's precise detailing of the time of each event and the matter–of–fact usage of language
helps to bring this style to life (Pelayo 116). The technique of 'Chronicling' is presented from the
very beginning when the novella states, On the day they were going to kill him, Santiago Nasar got
up at five–thirty in the morning to wait for the boat the bishop was coming on (Marquez 169). This
type of exact factual evidence allows readers to be pulled back into reality. It also leaves the 'why' of
Santiago Nasar's death and the social milieu that despises the murder to be left unclear to readers
(Aghaei 13). This is a part of the style of prolepsis which entails the narration of an event before
an earlier event takes place. This helps the author to keep the reader in suspense of how it happens.
In this specific novel readers follow the story step–by–step through the successive events (Aghaei
13). Additionally, the narrator's lack of personal commentary keeps the novella to appear objective,
accurate, and neutral. This technique is used in real world journalism by reporters and journalists
worldwide. Garcia Marquez expresses his views on the presentation of facts by stating 'The key is
to tell it straight'(Gardener 13).
The novella as a whole is written in a pseudo journalistic style. This means that the story is told
through a series of flashbacks and interviews used to help describe and support the events taking
place. This style

Grade Hierarchy Analysis Call Graph
According to Figure 2.8, node 7, node 8 and node 9 do not have any other predecessors except node
5 node 6 and by removing non–instantiated methods they become head nodes. So, I should
remove these heads from graph and this new graph can be considered as RTA result for the given
CHA Call Graph (Figure 2.9).
Figure 2.9: The result of removing head nodes from graph
To clarify this approach, I will use the computed Class Hierarchy Analysis Call Graph from the first
example (Figure 2.6) and convert it to RTA. Since set of instantiated classes contains Class B
Class C, according to the algorithm, I have to remove node A.m( ).
Moreover, if I check Call Graph again, I will find that node Interface.( ) has a reflexive edge and it's
indegree=1 . Therefore, this node should be deleted as well.
Figure 2.10 illustrates a conversion from CHA to RTA:
CHA retrieved call graph
Removing non–instantiated node Removing non–connected node
Figure 2.10: CHA to RTA conversion
2.3.3 Class Type Analysis (CTA)
CTA's main idea is narrowing down the set of reachable methods of a call site b.n( ) inside method
A.m( ) by keeping track of available target types within class A. Since CTA algorithm is
refinement of CHA and RTA, I can reuse CHA or RTA Call Graph result in CTA and decrease the set
of reachable methods of a call b.n( ) to make it more precise.
CTA algorithm implementation has three phases:
a) Class Graph Generation
b) Data flow
c) Call Graph Generation
a)

Application Of A Distributed Agricultural Sensor Network
Abstract– As the world's population continues to grow, new agricultural technologies will be needed
to keep up with the growing demand. To accomplish this, agricultural systems must increase
production while at the same time more effectively utilizing and conserving the resources that go
into that production. One possible solution is the collection and analysis of environmental data. IoT
sensor networks can cheaply provide distributed data that can be used to improve plant health,
increase harvest yields, and decrease waste. The primary focus of this project will be to prototype a
distributed agricultural sensor network that will be able to monitor the environment, network and
analyze the data on the cloud, and finally provide feedback to ... Show more content on
Helpwriting.net ...
This is an active area of IoT research and will be the primary focus of this project. If data can be
effectively gathered, networked, and analyzed, then that data can then be used to impart real and
significant change on the environment. For agricultural systems this will result in improved plant
health, increased harvest yields, and decreased waste. A. Background One of the most utilized and
standardized IoT stacks is the IEEE 802.11.4, 6LoWPAN, RPL, and CoAP stack. The IoT stack
layers are similar to OSI and they share many of the same abstraction layer divisions. These
similarities assist with the interoperability of IoT protocols with those of the Internet. The
IEEE802.15.4 protocol defines the physical and link layers of stack. These layers define how data is
modulated onto the channel, how the channel is shared between multiple users, as well as the low–
level packet checks and retransmissions. IEEE802.15.4 operates in the 2.4GHz ISM band using
Quadrature Phase–Shift Keying with additional Direct Sequence Spread Spectrum encoding. This
allows the radio to better reject noise and other interference. IEEE802.15.4 utilizes 16, 5MHz
channels in order to generate a data throughput of 250kbps. The maximum payload size is 127 Bytes
[1]. Compared to WiFi, the data rate and maximum packet size is significantly less. These
characteristics are the result of the limited hardware used for

Analysis Of Local Search Algorithm For STP
From the tree SP we presented in the algorithm that we have obtained via Local Search Algorithm
for STP, we have generated the matrix of cost. This is done by assigning a cost to all the edges of
tree SP and by assigning a cost on n no. of nodes to all the other edges in graph. This assignment
of cost helps in recognizing the cost of the longest possible path between a pair of nodes in any
spanning tree is n−1 (i.e. it passes n−1 edges) while the cost of the shortest path between any pair of
nodes without using of SPT edges is at least n (i.e. passes one edge). Consequently, the 802.1d
protocol will produce the intended spanning tree SP.
3.5 DATA GENERATION
In this section we progress by generating network topologies and traffic ... Show more content on
Helpwriting.net ...
root = 1; in_tree = {root}; considered = ∅; while #in_tree n do select (u ∈in_tree) and (u !∈
considered); selectnum_branch∈ [min..max] ; foreach i ∈ [1..num_branch] do if #in_tree n then
select (v ∈ [1..n]) and (u /∈in_tree); creatEdge(u, v); in_tree = in_tree + {v} end end considered =
considered + u; end To the obtained spanning tree from above algorithm we add two types of edges
so that we can get a bi–connected graph. The bi–connected graph has a significance that if any of the
edge becomes down then also the network will be connected via another edge. This gives us
assurance of always up time for a network. This means in case of link failure alternate link will
always be present to ensure the network connectivity.
In this type1 edge connect a leaf with the higher level node while the type 2 edge connect a non–
leaf node (not the root) with the no–leaf node or lower level node of different branch. For each tree
new n–1 edges are added while the generation of bi–connected graph.
To pretend a network in which a switch has many ports, we define a ratio r. This means each node
in the tree is connected to at least r edges. In each test graph, from the generated bi–connected
graph, we create three more trees with ratio r15 = n/15, r10 = n/10 and r5 = n/5 (where n = no. of
nodes).
3.5.4 The FAT Tree:
Figure shown below depicts the Fat Tree – another topology for DCNs proposed in [35] It is called
Fat Tree because it is not a

The Provider And Patient Attributes
Provider and Patient Attributes
We collected a set of attributes for providers and patients from the EDW. For providers, we
extracted employee ID, employee role, and a physician index (a Boolean value; 1 if provider is a
type of physician, 0 if not). For patients, we extracted age, encounter type (all inpatient in this data
set), admission and discharge times, primary diagnosis, discharge location, length of stay, med
service (department to which the patient was admitted), discharge disposition (where the patient was
discharged to), and an index noting whether or not the patient had expired.
Network Visualization
We created two types of networks in this study. The first is a directed bipartite network and
represents interactions between providers and patient records (Figure 2). The second network is
undirected and depicts shared patient record access between providers (Figure 3). Visualization for
both networks was performed using Gephi. [59] Further description of these networks follows.
Provider–patient Network
EDW data indicating provider access to a patients EHR was depicted as a directed bipartite graph
(see Figure 2 for a one–patient example). The source node designates a provider of type physician,
nurse, pharmacist, etc. The target node designates a patient with a diagnosis of heart failure who was
admitted to NMH in 2012. An edge between them is an indication that the provider has accessed the
patient record. The complete bipartite graph included all providers as

What Is Graph Theoretical Analysis
1.3.4. Introduction to graph theoretical analysis. The case of brain perfusion SPECT.
In the field of quantitative neuroimaging, graph theoretical analysis is one of the methods to study
brain connectivity [93–95, 100, 101]. A key concept of this method is the notion of topology. This
concept can be illustrated with a simple idea which is used when we travel in the subway of any
large city. In figure 3 two maps of the London subway appear, the first map shows a precise spatial
description of the railways (or lines) through which trains travel (i.e., the subway topography),
whereas the second one is only concerned with the relative locations of subway stations and
connecting lines (i.e., the subway topology). These two maps do not coincide with regards to the
relative position of the stations, neither in the distances nor in the location of the lines. However, the
topological map simplifies the problem for the traveler. For example, two stations may be physically
(topographically) ... Show more content on Helpwriting.net ...
By simply inspecting the topological maps, it is not easy to know if one subway is better organized
than the other (e.g., subway efficiency). One way to simplify this problem is to use metrics that
quantify or analyze the subway network using graph theory [94, 101]. Hence the name of graph
theoretical analysis.
A first aspect to measure could be how easy it is to travel between any two stations (e.g. the number
of stations on average, between the start and end of the trip). This aspect is relevant, especially if the
traveler wants to visit different parts of the city on the same day. This example illustrates the concept
of global efficiency of a graph [94, 101]. The metric of global efficiency is a way to quantify the
global connectivity (integration) of the network. In this example, it is assumed that the number of
stations (nodes) and lines (connectors) are the same in the two subways that are

Definition Of Subjectivity Score And Objectivity Score ( Os )
namely, Subjectivity Score (SS) and Objectivity Score (OS) corresponding to Kleinberg's71 hub and
authority scores respectively for the WWW graph. Kleinberg not only takes into account the number
of links to and from a node, but also considers the relevance of linked nodes. Accordingly, if a
resource in RDF is pointed to by a resource with high SS, its OS increases. On the other hand, if a
resource points to a resource with a high OS, its SS is increased. Another important feature of this
method is contextualized weights added into the graph properties. For instance, RDF graphs are
complex with varying importance of properties which in turn depend on the subject and object it is
associated with. The study assigns distinct weights to different types of properties, based on the type
of the property and the nodes it's connecting to. Each property is assigned with a subjectivity weight
(weight that depends on the subject of the property) and an objectivity weight (weight that depends
on the object of the property). These weights play a critical role to calculate the centrality of genes.
The feasibility of this approach in candidate gene prioritization was validated by using to 60
randomly selected diseases from a total of about 420 cardiovascular disorders with each of the
diseases having clinical synopsis and at least one implicated gene. For validation purposes, no
information about any explicit links between target gene and the disease were part of the input to the

Price Control Research Paper
Use economic theory and supporting material to discuss whether house rents in big cities should be
regulated and if a price limit to rents would be beneficial
The issue of introducing regulations and limits to the prices at which rents are set has been long
debated by economists and policymakers. Morally considered, price caps and rent regulation seem
an effective strategy in allowing lower to middle income families and individuals rent out a home,
however, economists generally believe that such regulations negatively impact the housing market
and the supply of housing. In this essay, the issue of price regulations within the housing market will
be discussed from a microeconomic standpoint, with brief acknowledgement to the social effects ...
Show more content on Helpwriting.net ...
With these circumstances, it is hard to see how price capping would alleviate the supply gap in
rental properties, even with external factors such as land–use regulations playing a part in keeping
rent prices high; capping any sort of price increases in rent simply gives landlords an impetus to sell
property that they may have instead rented out to homeowners. This suggests that price caps prove
little help in alleviating issues in rental property supply for those who need it.
From a historical standpoint, rent control has had few positive effects, particularly for Britain, who
has frequently experimented with such endeavours. Rent control was introduced in 1915 for wartime
Britain, far from a temporary solution, rent control of some form existed until the 1990s. The Rent
Act of 1939 reintroduced full rent control, likely in anticipation for World War 2, for practically all
rented housing regardless of circumstance. The 1939 act largely made it so that tenants of rented
property could not legally be required to vacate their rented property, this left almost every landlord
with practically no volition to maintain their properties given the lack of competition. Furthermore,
tenants had basically no incentive to leave their properties on their own accord due to the very low
prices of rent, even when family and economic situations may have otherwise pushed said families
to relocate. There were

Leonard Euler And The Application Of The Graph Theory, (E....
DRAFT ONE
Mathematics IA
To investigate Leonard Euler and his application of the graph theory and 'e'
Caitlin McFarlane
10/14/2015
Table of Contents
Introduction
Leonhard Euler was a Swiss Mathematician and physicist during the 1700s. He was born in 1707 in
Basel, Switzerland. He is known to be a pioneer of mathematics contributing to trigonometry,
calculus and geometry. The principle that he came up with and investigated was the foundation of
modern day mathematics. His most famous was 'The Graph Theory', using mathematic to
investigate graphs. The aim of this Mathematics IA is to investigate Leonhard Euler and the
application of his 'graph theory and 'e' (Euler's identity) in real life situations. I ... Show more
content on Helpwriting.net ...
This question was the basis for Leonard Euler's investigation into graph theory. He observed when
answering the question that some graphs could be drawn in different way, and some with multiple
possibilities and other don't have any. Being able to answer this question is depends on the number
of vertices with the odd edges. In the example below display. When it refers to two odd veracities
refers to the connection between the line and the nodes. The example above is one that you are able
to draw without lifting your pencil off. This graph has two odd veracities what agrees with Euler's
observation.
However this example has 6 odd vertices making this graph impossible to solve. Knowing this rule
is important when solving the seven bridges of Konigsberg problem.
Seven bridge of Konigsberg problem
Leonard Euler used graph theory to solve the 18th century problem seven bridges of Konigsberg.
The problem states:
Königsberg is divided into four parts by the river Pregel, and connected by seven bridges. Is it

possible to tour Königsberg along a path that crosses every bridge once, and at most once? You can
start and finish wherever you want, not necessarily in the same

Edge

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