Most of virtual communities are built on the client/server system. There are some limitations on the client/server system such as the maintenance cost and the personal attribute protection. The peer-to-peer system has some strengths to overcome the limitations of client/server system. Therefore, we are willing to export the virtual community on the peer-to-peer system. There are two main team formation approaches in the current virtual community collaboration. Either one of these approaches alone has its limitations. In this study, we adopt the social network concept to design a team formation mechanism in order to overcome the limitations of current approaches. Besides, because of the natural of peer-to-peer system, the exchange of messages is sending and receiving on the network. The mechanism proposed in this research can also reduce the traffic cost of the team formation process. Furthermore, it maintains the fitness of members who are chosen in the same team.

Intelligent Transport Systems (ITS) are becoming a part of our daily lives in various forms of application. Their success depends highly on the accuracy of the digital data they use. In networks where characteristics change by time, time-based network analysis algorithms provide results that are more accurate. However, these analyses require time-based travel speed data to provide accurate results. Conventionally, traffic data are usually obtained using the data provided from loop-detectors. These detectors usually exist on main arteries, freeways and highways / they rarely exist on back roads, secondary roads and streets due to their deployment costs. Today, telematics systems offer fleet operators to track their fleet remotely from a central system. Those systems provide data about the behaviors of vehicles with time information. Therefore, a tracking system can be used as an alternative to detector-based systems on estimating travel speeds on networks. This study aims to provide methods to estimate network characteristics using the data collected directly from fleets consisting of global positioning system (GPS) receiver equipped vehicles. GIS technology is used to process the collected GPS data spatially to match digital road maps. After matching, time-dependent characteristics of roads on which tracked vehicles traveled are estimated. This estimation provides data to perform a time-dependent network analysis. The methods proposed in this study are tested on traffic network of Middle East Technical University campus. The results showed that the proposed methods are capable of measuring time-dependent link-travel times on the network. Peak hours through the network are clearly detected.

This research is to explore the decision-making process of new policy of working hours and its influence on the industrial relations network? This study uses the texts of political discourse that legislators interrogated with government officials in Taiwan Legislative Yuan. This text is focused on Article 30 of the Labor Standards Act. The main research methods of this study include quantitative study, and qualitative analysis. The process of policy making is constructed from industrial of ideology, policy of interest, and the opinion about industrial relations. The main results of the study are as follows: 1.) On the industrial relations network, the new working hours policy has main influence on the labors than on the employers. 2.) On the content of political discourse: the labors concern for the right and equality, with as the employers concern for economical perspective. 3.) Labors and employers have different strategies to respond the change of working hours policy.

In the context of a DFG research project, scientists of Prof. Helbing’s chair at the Institute of Transport & Economics deal with the dynamics of disasters, being experienced in the modelling of complex systems and in the simulation of emergency scenarios. The analyses of systems and their behaviour in extraordinary events are based on the latest results of network sciences and on numerous empirical investigations. The results shall be used for precaution measures and innovations in disaster recovery. / Im Rahmen eines Projekts der Deutschen Forschungsgemeinschaft (DFG-Projekt He 2789/6-1) befassen sich Wissenschaftler unter Leitung von Professor Dirk Helbing an der Fakultät Verkehrswissenschaften „Friedrich List“ mit der Dynamik von Katastrophen. Aus der Simulation von Fußgängerströmen, des Panikverhaltens von Menschen sowie der Verkehrsmodellierung verfügen die Wissenschaftler bereits über einschlägige Erfahrungen auf dem Gebiet der Modellierung komplexer Systeme sowie auf dem Gebiet der Simulation und Auswertung von Notfallszenarien. Auf Basis der jüngsten Ergebnisse der Netzwerkforschung und umfangreicher empirischer Untersuchungen von Katastrophenereignissen werden im Rahmen des aktuellen Forschungsprojekts anthropogene Systeme auf ihr Verhalten bei außergewöhnlichen Schadensereignissen untersucht. Die Projektergebnisse (Laufzeit bis 2007) sollen als Basis für weitere Verbesserungen in der Vorsorge und im Management von Katastrophen dienen.

<p>The aim of this essay was to describe the power elite of the Swedish town Karlshamn, and its influences on the local political process before the realization of the narrow-gauge railway Karlshamn-Wislanda-Jernväg. During the mid 19th century, a revolutionary period began in the Swedish pre-industrial epoch. The political and institutional regulatory frameworks were disassembled and restructured, away from protectionism and centrally controlled administration, for the benefit of free trade, local self-government and liberalism. The changes were carried through during times marked by a drastic increasing native population and upcoming demands for adjustments to meet the growth of the industrial-, trade- and labour markets. An essential industrial development factor was the building of the national railway network, which started after some important decisions in the Swedish Riksdag during the 1850´s. In close connection with governmental initiatives to build national trunk lines, processes on the local political arenas were initiated to rapidly obtain connections to these planned main lines. Focus in this study was put on the town Karlshamn 1855-1874 and the main document sources that were examined consisted of protocols and petitions from errands on the local political arenas, f.e. the town council. The material was methodically revised by means of a network- and field analysis. Through this analytical method it was possible to confirm the power elite actors, their potential networks and reproduced groups. The results point to the importance of the formal networks an their contributions to the accumulation of social capital. Above all, this was significant for the most important individuals in the process, the local wholesale dealers Edvard Ferdinand Meyer and Carl Gustaf Berg. The process also resulted in a reproduction of local political power, and the dominance on the political field was continued. All through the twenty-year lasting process, the railway issue became a possibility for the local elite, with representatives from the trading companies, to mobilize the political decisions in the direction of continuous economic development, and enlargement of the town´s commercial area. In the town of Karlshamn, with a stagnating economy, the new infrastructure, beside the connection to the main national lines, constituted a lifeline towards continuous financial expansion and competitiveness.</p>

Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references. Available also from Dissertation Abstracts.

With the exponential growth of Facebook users worldwide, this platform for social network online has become a powerful tool to connect individuals and share information with each other. This study explores the phenomenal trend of utilizing a Facebook application called Causes to help users organize into online communities for a specific cause and mobilize their resources for disaster relief during the Haiti earthquake disaster. Two separate samples of 100 joiners each from the American Red Cross (ARC) Cause on Facebook were randomly selected before and after the Haiti earthquake disaster to examine the differences of the composition (i.e., attributes) and structure (i.e., relational ties) of each social network. The social network analysis performed for this thesis research intends to fill the gap of historical research literature on recruitment to activism and support provision following a disaster in the digital age of the 21 st century. The results of this study show how understanding the membership size of online communities, salient identity for the cause through organizational affiliations, interpersonal ties among the joiners, density of the network as well as gender diversity can be crucial recruitment factors to leverage for disaster relief efforts. The findings reveal a beneficial partnership between disaster relief organizations and online social networks in mobilizing their resources for a speedy response to disasters.

From 1961 to 1971 the United States and the Republic of South Vietnam used chemicals to defoliate the coastal and upload forest areas of Viet Nam. The most notorious of these chemicals was named Agent Orange, a weaponized herbicide made up of two chemicals that, when combined, produced a toxic byproduct called TCDD-dioxin. Studied suggest that TCDD-dioxin causes significant human health problems in exposed American and Vietnamese veterans, and possibly their children (Agency, U.S. Environmental Protection, 2011). In the years since the end of the Vietnam War, volumes of discourse about Agent Orange has been generated, much of which is now digitally archived and machine-readable, providing rich sites of study ideal for “big data” text mining, extraction and computation. This study uses a combination of tools and text mining scripts developed in Python to study the descriptive phrases four discourse communities used across 45 years of discourse to talk about key issues in the debates over Agent Orange. Findings suggests these stakeholders describe and frame in significantly different ways, with Congress focused on taking action, the New York Times article and editorial corpus focused on controversy, and the Vietnamese News Agency focused on victimization. Findings also suggest that while new tools and methods make lighter work of mining large sets of corpora, a mixed-methods approach yields the most reliable insights. Though fully automated text analysis is still a distant reality, this method was designed to study potential effects of rhetoric on public policy and advocacy initiatives across large corpora of texts and spans of time.

Coalitions are widely associated with collective or collaborative attempts to influence organizational members, decisions, policies and events. Yet, surprisingly, relatively little is known about how coalitions develop within organizations. Employing an exploratory case study design and using social network analysis, the Rokeach Value Survey, and semi-structured interviews, this research demonstrated that it is possible to identify and study coalitions in a real organizational setting. I suggest that the inclusion and investigation of member relationships may advance the state of the art in organizational coalition research. A benefit of this study, and contrary to most coalition research, is that it used multiple forms of data, including demographic, historical, values-based and interaction patterns for work and social relationships.Two coalitions were identified in the organization studied. Formation centered on a single issue and each coalition followed a strategy designed to influence a possible change in structure and operation. Coalition members exhibited similarities across several factors, including tenure within the organization, education, race, age, and previous experiences. Analyses showed some similarity in member values within and between coalitions. The coalition attempting to maintain the current work structure demonstrated higher value similarity with non-coalition members. Social network analysis revealed that coalition members tended to be structurally similar to each other, more centrally located in the work network, and had higher correlation between coalition interactions and existing social relationships.

Brain decoding involves the determination of a subject’s cognitive state or an associated stimulus from functional neuroimaging data measuring brain activity. In this setting the cognitive state is typically characterized by an element of a finite set, and the neuroimaging data comprise voluminous amounts of spatiotemporal data measuring some aspect of the neural signal. The associated statistical problem is one of classification from high-dimensional data. We explore the use of functional principal component analysis, mutual information networks, and persistent homology for examining the data through exploratory analysis and for constructing features characterizing the neural signal for brain decoding. We review each approach from this perspective, and we incorporate the features into a classifier based on symmetric multinomial logistic regression with elastic net regularization. The approaches are illustrated in an application where the task is to infer from brain activity measured with magnetoencephalography (MEG) the type of video stimulus shown to a subject. / Graduate