A hybrid method for sag source location in power network

The work presented in this paper belongs to the power quality knowledge area and deals with the voltage sags in power transmission and distribution systems. Propagating throughout the power network, voltage sags can cause plenty of problems for domestic and industrial loads that can financially cost a lot. To impose penalties to responsible party and to improve monitoring and mitigation strategies, sags must be located in the power network. With such a worthwhile objective, this paper comes up with a new method for associating a sag waveform with its origin in transmission and distribution networks. It solves this problem through developing hybrid methods which hire multiway principal component analysis (MPCA) as a dimension reduction tool. MPCA reexpresses sag waveforms in a new subspace just in a few scores. We train some well-known classifiers with these scores and exploit them for classification of future sags. The capabilities of the proposed method for dimension reduction and classification are examined using the real data gathered from three substations in Catalonia, Spain. The obtained classification rates certify the goodness and powerfulness of the developed hybrid methods as brand-new tools for sag classification

Renssellaer Institute. Jim Hendler. CSCI 4964/COMM 49652 – Web Science. Social Network

Social Networks on the World Wide Web - lecture by Dr. Jennifer Golbeck

TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 6: Network Evolution and Process

In this class, we will discuss the nature of network evolution and some selected network processes. We will discuss graph generation algorithms that generate networks with different interesting characteristics. Optional : The Structure and Function of Complex Networks (chapter 8), M.E.J. Newman, SIAM Review 45 167--256 (2003); Optional: Emergence of Scaling in Random Networks, A.L. Barabasi and R. Albert, Science 286, 509 (1999)

TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 3: Network Theory and Terminology

In this class, we will discuss network theory fundamentals, including concepts such as diameter, distance, clustering coefficient and others. We will also discuss different types of networks, such as scale-free networks, random networks etc. Readings: Graph structure in the Web, A. Broder and R. Kumar and F. Maghoul and P. Raghavan and S. Rajagopalan and R. Stata and A. Tomkins and J. Wiener Computer Networks 33 309--320 (2000) [Web link, Alternative Link] Optional: The Structure and Function of Complex Networks, M.E.J. Newman, SIAM Review 45 167--256 (2003) [Web link] Original course at: http://kmi.tugraz.at/staff/markus/courses/SS2008/707.000_web-science/

TU Graz: Course: 707.000 Web Science and Web Technology: Lecture 4: Social Network Analysis

What are fundamental entities in social networks and what information is contained in social graphs? We will discuss some selected concepts in social network analysis, such as one- and two mode networks, prestige and centrality, and cliques, clans and clubs. Readings: Web tool predicts election results and stock prices, J. Palmer, New Scientist, 07 February (2008) [Protected Access] Optional: Social Network Analysis, Methods and Applications, S. Wasserman and K. Faust (1994)

Research on Social Network Sites

A bibliography of research on Social Network web sites. The research contained below is focused specifically on social network sites (or "social networking" sites). Some of this is connected to social media, social software, Web2.0, social bookmarking, educational technologies, communities research, etc. but this is not the organizing focus and not everything related to these other topics is included here. This list is not methodologically or disciplinarily organized. There is work here from communications, information science, anthropology, sociology, economics, political science, cultural studies, computer science, etc.

Introduction to Network Mathematics

Introduction to Network Mathematics provides college students with basic graph theory to better understand the Internet

Creative Commons network

My profile page on creative commons network

Improving social capital : a social network monitoring system. 'Mejorar el capital social : un sistema de red de control social'.

Resumen tomado del autor

Simple Analysis of Network Datasets

Linux commands that are generally useful for analyzing data; it is very easy to reduce phenomena such as links, nodes, URLs or downloads, to multiply repeating identifiers and then sorting and counting appearances.

Curriculum Innovation Network Conference - 18th & 19th January 2011

Presentations from the Curriculum Innovation Network Conference that took place on 18th & 19th January 2011 at the University of Southampton. The ambition was to bring together a global network of universities who are engaged in institution-wide curriculum innovation. The focus of the network is to share learning and practice in a collaborative way, to identify best practice and to explore practical solutions to the challenges we face. Keynote speakers from across the world and colleagues from leading universities came together to share their experience on approaches to transforming their curricula and the overall learning experience of their students. The challenges of doing this are significant, and there is much that we can learn from each other as we seek to transform the learning environment of our institutions. We hope that all who attend found these two days of great value in starting and enhancing a global dialogue about education transformation. Additional presentations will be uploaded in due course. Please note the copy right of these presentations remains with the author.

Increasing Rail's Mode Share Within The Constraints of The Existing Network

This file contains the results of application of the model (4.6) and (4.8)

SB.TV's successful yet unconventional establishment of a Brand based solely on Social Network Success may present a problem in long-term survival

Research Proposal in SB.TV case study. New dimension to brand model for Web 2.0 success