There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Thank you for downloading using multivariate statistics. As you may know, people have look hundreds times for their favorite novels like this using multivariate statistics, but end up in infectious downloads. Rather than reading a good book with a cup of tea in the afternoon, instead they juggled with some harmful bugs inside their laptop. using multivariate statistics is available in our digital library an online access to it is set as public so you can download it instantly. Our books collection saves in multiple locations, allowing you to get the most less latency time to download any of our books like this one. Merely said, the using multivariate statistics is universally compatible with any devices to read.

Using Multivariate Statistics

The modern science of networks has brought significant advances to our understanding of complex systems. One of the most relevant features of graphs representing real systems is community structure, or clustering, i. e. the organization of vertices in clusters, with many edges joining vertices of the same cluster and comparatively few edges joining vertices of different clusters. Such clusters, or communities, can be considered as fairly independent compartments of a graph, playing a similar role like, e. g., the tissues or the organs in the human body. Detecting communities is of great importance in sociology, biology and computer science, disciplines where systems are often represented as graphs. This problem is very hard and not yet satisfactorily solved, despite the huge effort of a large interdisciplinary community of scientists working on it over the past few years. We will attempt a thorough exposition of the topic, from the definition of the main elements of the problem, to the presentation of most methods developed, with a special focus on techniques designed by statistical physicists, from the discussion of crucial issues like the significance of clustering and how methods should be tested and compared against each other, to the description of applications to real networks.

/pdf/community-detection-in-graphs-34rogm3r6p.pdf

Community detection in graphs

Twitter, a microblogging service less than three years old, commands more than 41 million users as of July 2009 and is growing fast. Twitter users tweet about any topic within the 140-character limit and follow others to receive their tweets. The goal of this paper is to study the topological characteristics of Twitter and its power as a new medium of information sharing.We have crawled the entire Twitter site and obtained 41.7 million user profiles, 1.47 billion social relations, 4,262 trending topics, and 106 million tweets. In its follower-following topology analysis we have found a non-power-law follower distribution, a short effective diameter, and low reciprocity, which all mark a deviation from known characteristics of human social networks [28]. In order to identify influentials on Twitter, we have ranked users by the number of followers and by PageRank and found two rankings to be similar. Ranking by retweets differs from the previous two rankings, indicating a gap in influence inferred from the number of followers and that from the popularity of one's tweets. We have analyzed the tweets of top trending topics and reported on their temporal behavior and user participation. We have classified the trending topics based on the active period and the tweets and show that the majority (over 85%) of topics are headline news or persistent news in nature. A closer look at retweets reveals that any retweeted tweet is to reach an average of 1,000 users no matter what the number of followers is of the original tweet. Once retweeted, a tweet gets retweeted almost instantly on next hops, signifying fast diffusion of information after the 1st retweet.To the best of our knowledge this work is the first quantitative study on the entire Twittersphere and information diffusion on it.

https://ink.library.smu.edu.sg/cgi/viewcontent.cgi?article=7104&context=sis_research

What is Twitter, a social network or a news media?

Proactive measurement of the delay in communication networks aims to detect congestion as early as possible and find links on which the traffic flow is obstructed. There is, however, a tradeoff between detection time and cost (e.g., bandwidth utilization). Adaptive measurement adjusts the inspection rate per each link, for effective monitoring with reduced costs. In this paper we present SDProber---a tool for proactive measurement of delays in SDN. SDProber uses probe packets that are routed by adding tailored rules to the vSwitches. It adjusts the forwarding rules to route probe packets more frequently to areas where congestion tends to occur. To increase efficiency, SDProber uses a novel approach of probing by a random walk. Adaptation is achieved by changing the probabilities that govern the random walk. Our experimental results show that SDProber provides control over the probe rates per each link and that it reduces measurement costs in comparison to baseline methods that send probe packets via shortest paths.

SDProber: A Software Defined Prober for SDN

Phishing is an increasingly prevalent social-engineering attack that attempts identity theft using spoofed Web pages of legitimate organizations. Unfortunately, current phishing detection methods are neither complete nor responsive because they rely on user reports, and many also require clientside software. Anti-phishing techniques could be more effective if they (1) could detect phishing attacks automatically from the network traffic; (2) could operate without cooperation from end-users. This paper performs a preliminary study to determine the feasibility of detecting phishing attacks in real-time, from the network traffic stream itself. We develop a model to identify the stages where in-network phishing detection is feasible and the data sources that can be analyzed to provide relevant information at each stage. Based on this model, we develop and evaluate a detection method based on features that exist in the network traffic itself and are correlated with confirmed phishing attacks.

/pdf/fishing-for-phishing-from-the-network-stream-317i191h8z.pdf

Fishing for Phishing from the Network Stream

Disclosed is a method and system for determining one or more performance characteristics of a target server. A command is transmitted from a coordinator to a plurality of clients. The command instructs the plurality of clients to each transmit a request targeting a sub-system of said target server. A response time is then received from each client and a performance characteristic is determined from the received response times.

System and method for profiling resource constraints of web servers

In embodiments of the disclosed technology, a plurality of ratings of, for example, websites is received, wherein each rating is associated with a category and a rater, and each rater is associated with at least one group. A selection of a category is received from the user, wherein the user is associated with at least one group. One website location, or a plurality of website locations, is provided in the category to the user, based on at least one rating of the plurality of ratings provided by at least one of the raters, wherein at least one group associated with the rater and at least one group associated with the user are the same group.

Method and Device to Provide Trusted Recommendations of Websites

Disclosed is a method and apparatus for compensating for a performance degradation of an application session in a plurality of application sessions associated with a network link. The performance of each application session in the plurality of application sessions associated with the network link is determined. The performance of each application session in the plurality is then compared. From this comparison, a lowest performance application session in the plurality of application sessions is identified. Corrective action is performed on packets scheduled to be transmitted over the lowest performance application session.

Balachander Krishnamurthy

Papers

SDProber: A Software Defined Prober for SDN

Fishing for Phishing from the Network Stream

System and method for profiling resource constraints of web servers

Method and Device to Provide Trusted Recommendations of Websites

Method and apparatus for compensating for performance degradation of an application session