1,306 research outputs found
Understanding digital intelligence and the norms that might govern it
Abstract: This paper describes the nature of digital intelligence and provides context for the material published as a result of the actions of National Security Agency contractor Edward Snowden. It looks at the dynamic interaction between demands from government and law enforcement for digital intelligence, and at the new possibilities that digital technology has opened up for meeting such demands. The adequacy of previous regimes of legal powers and governance arrangements is seriously challenged just at a time when the objective need for intelligence on the serious threats facing civil society is apparent. This paper suggests areas where it might be possible to derive international norms, regarded as promoting standards of accepted behaviour that might gain widespread, if not universal, international acceptance, for the safe practice of digital intelligence
Social Network Dynamics
This thesis focuses on the analysis of structural and topological network problems. In particular, in this work the privileged subjects of investigation will be both static and dynamic social networks. Nowadays, the constantly growing availability of Big Data describing human behaviors (i.e., the ones provided by online social networks, telco companies, insurances, airline companies. . . ) offers the chance to evaluate and validate, on large scale realities, the performances of algorithmic approaches and the soundness of sociological theories. In this scenario, exploiting data-driven methodologies enables for a more careful modeling and thorough understanding of observed phenomena. In the last decade, graph theory has lived a second youth: the scientific community has extensively adopted, and sharpened, its tools to shape the so called Network Science. Within this highly active field of research, it is recently emerged the need to extend classic network analytical methodologies in order to cope with a very important, previously underestimated, semantic information: time. Such awareness has been the linchpin for recent works that have started to redefine form scratch well known network problems in order to better understand the evolving nature of human interactions. Indeed, social networks are highly dynamic realities: nodes and edges appear and disappear as time goes by describing the natural lives of social ties: for this reason. it is mandatory to assess the impact that time-aware approaches have on the solution of network problems. Moving from the analysis of the strength of social ties, passing through node ranking and link prediction till reaching community discovery, this thesis aims to discuss data-driven methodologies specifically tailored to approach social network issues in semantic enriched scenarios. To this end, both static and dynamic analytical processes will be introduced and tested on real world data
Northern Periphery Programme Preparatory Project - Arctic Collaboration Mechanism
This final report of the âNorthern Periphery Programme Preparatory Project â Arctic Collaboration Mechanismâ details project progress and results to date and sets out the final steps for the project. The report draws on a synthesis of past project outputs and new research and consultation. The overall aims of the project are to consider the need for improved collaboration across regional economic development programmes in the Arctic and High North, and how a collaboration mechanism can be optimally structured and delivered
Ranking to Learn and Learning to Rank: On the Role of Ranking in Pattern Recognition Applications
The last decade has seen a revolution in the theory and application of
machine learning and pattern recognition. Through these advancements, variable
ranking has emerged as an active and growing research area and it is now
beginning to be applied to many new problems. The rationale behind this fact is
that many pattern recognition problems are by nature ranking problems. The main
objective of a ranking algorithm is to sort objects according to some criteria,
so that, the most relevant items will appear early in the produced result list.
Ranking methods can be analyzed from two different methodological perspectives:
ranking to learn and learning to rank. The former aims at studying methods and
techniques to sort objects for improving the accuracy of a machine learning
model. Enhancing a model performance can be challenging at times. For example,
in pattern classification tasks, different data representations can complicate
and hide the different explanatory factors of variation behind the data. In
particular, hand-crafted features contain many cues that are either redundant
or irrelevant, which turn out to reduce the overall accuracy of the classifier.
In such a case feature selection is used, that, by producing ranked lists of
features, helps to filter out the unwanted information. Moreover, in real-time
systems (e.g., visual trackers) ranking approaches are used as optimization
procedures which improve the robustness of the system that deals with the high
variability of the image streams that change over time. The other way around,
learning to rank is necessary in the construction of ranking models for
information retrieval, biometric authentication, re-identification, and
recommender systems. In this context, the ranking model's purpose is to sort
objects according to their degrees of relevance, importance, or preference as
defined in the specific application.Comment: European PhD Thesis. arXiv admin note: text overlap with
arXiv:1601.06615, arXiv:1505.06821, arXiv:1704.02665 by other author
Ranking to Learn and Learning to Rank: On the Role of Ranking in Pattern Recognition Applications
The last decade has seen a revolution in the theory and application of
machine learning and pattern recognition. Through these advancements, variable
ranking has emerged as an active and growing research area and it is now
beginning to be applied to many new problems. The rationale behind this fact is
that many pattern recognition problems are by nature ranking problems. The main
objective of a ranking algorithm is to sort objects according to some criteria,
so that, the most relevant items will appear early in the produced result list.
Ranking methods can be analyzed from two different methodological perspectives:
ranking to learn and learning to rank. The former aims at studying methods and
techniques to sort objects for improving the accuracy of a machine learning
model. Enhancing a model performance can be challenging at times. For example,
in pattern classification tasks, different data representations can complicate
and hide the different explanatory factors of variation behind the data. In
particular, hand-crafted features contain many cues that are either redundant
or irrelevant, which turn out to reduce the overall accuracy of the classifier.
In such a case feature selection is used, that, by producing ranked lists of
features, helps to filter out the unwanted information. Moreover, in real-time
systems (e.g., visual trackers) ranking approaches are used as optimization
procedures which improve the robustness of the system that deals with the high
variability of the image streams that change over time. The other way around,
learning to rank is necessary in the construction of ranking models for
information retrieval, biometric authentication, re-identification, and
recommender systems. In this context, the ranking model's purpose is to sort
objects according to their degrees of relevance, importance, or preference as
defined in the specific application.Comment: European PhD Thesis. arXiv admin note: text overlap with
arXiv:1601.06615, arXiv:1505.06821, arXiv:1704.02665 by other author
User-Centric Quality of Service Provisioning in IP Networks
The Internet has become the preferred transport medium for almost every type of communication, continuing to grow, both in terms of the number of users and delivered services. Efforts have been made to ensure that time sensitive applications receive sufficient resources and subsequently receive an acceptable Quality of Service (QoS). However, typical Internet users no longer use a single service at a given point in time, as they are instead engaged in a multimedia-rich experience, comprising of many different concurrent services. Given the scalability problems raised by the diversity of the users and traffic, in conjunction with their increasing expectations, the task of QoS provisioning can no longer be approached from the perspective of providing priority to specific traffic types over coexisting services; either through explicit resource reservation, or traffic classification using static policies, as is the case with the current approach to QoS provisioning, Differentiated Services (Diffserv). This current use of static resource allocation and traffic shaping methods reveals a distinct lack of synergy between current QoS practices and user activities, thus highlighting a need for a QoS solution reflecting the user services.
The aim of this thesis is to investigate and propose a novel QoS architecture, which considers the activities of the user and manages resources from a user-centric perspective. The research begins with a comprehensive examination of existing QoS technologies and mechanisms, arguing that current QoS practises are too static in their configuration and typically give priority to specific individual services rather than considering the user experience. The analysis also reveals the potential threat that unresponsive application traffic presents to coexisting Internet services and QoS efforts, and introduces the requirement for a balance between application QoS and fairness.
This thesis proposes a novel architecture, the Congestion Aware Packet Scheduler (CAPS), which manages and controls traffic at the point of service aggregation, in order to optimise the overall QoS of the user experience. The CAPS architecture, in contrast to traditional QoS alternatives, places no predetermined precedence on a specific traffic; instead, it adapts QoS policies to each individualâs Internet traffic profile and dynamically controls the ratio of user services to maintain an optimised QoS experience. The rationale behind this approach was to enable a QoS optimised experience to each Internet user and not just those using preferred services. Furthermore, unresponsive bandwidth intensive applications, such as Peer-to-Peer, are managed fairly while minimising their impact on coexisting services.
The CAPS architecture has been validated through extensive simulations with the topologies used replicating the complexity and scale of real-network ISP infrastructures. The results show that for a number of different user-traffic profiles, the proposed approach achieves an improved aggregate QoS for each user when compared with Best effort Internet, Traditional Diffserv and Weighted-RED configurations. Furthermore, the results demonstrate that the proposed architecture not only provides an optimised QoS to the user, irrespective of their traffic profile, but through the avoidance of static resource allocation, can adapt with the Internet user as their use of services change.France Teleco
THE INVOLVEMENT OF ENTREPRENERâS NETWORKS IN OPPORTUNITIES EXPLORATION AND EXPLOITATION OF INTERNATIONAL NEW VENTURES. A case study of two Vietnamese International New Ventures
The role and importance of entrepreneurâs network for International New Ventures (INVs) are highlighted in much research. However, there is a lack of more profound studies on how different perspectives of network influence INVs. Therefore, this thesis aims to develop a deeper understanding of the multiple aspects of entrepreneursâ networks involvement in INVs with regard to opportunity development process. Theoretical framework constitutes of three aspects of entrepreneurâs networks: type, strength and functions of relationships, put in the context of entrepreneurial opportunityâs exploration and exploitation. The theoretical framework is empirically examined through two cases study of two prominent business models in Vietnam economy: State-owned company and Private-owned company. Lastly, empirical part validates and contributes to a better understanding of the framework, hence, answers the research question.
It is found that entrepreneurs utilize social network as the most efficient means of rapid internationalization. While entrepreneursâ weak relationships positively impact business opportunities exploration, strong relationships greatly affect business opportunities exploitation. This study also uncovers more clearly the functions of networks in various critical activities related to opportunity exploration and exploitation.fi=OpinnĂ€ytetyö kokotekstinĂ€ PDF-muodossa.|en=Thesis fulltext in PDF format.|sv=LĂ€rdomsprov tillgĂ€ngligt som fulltext i PDF-format
âYou are warmly invited.â Exploring knowledge exchange seminars as sites of productive interactions and social networking
This thesis examines Knowledge Exchange (KE) seminars and the wider social,
political, and economic environment in which they are situated
Two-way interactive exchanges between academics and Non-Academic
Professionals (NAPs) have been identified as an important factor in explaining why
some academic research is used by NAPs, or not (Meagher et al, 2008; Mitton et al,
2007; Lavis et al, 2003; Hanney et al, 2003). Despite this, very little research has
examined the social occasions where such exchanges occur. This thesis aims to fill
this lacuna by examining the process of knowledge exchange through one specific
type of intervention (Walter et al, 2003) â that of KE seminars.
KE seminars are a common, almost canonical, strategy for academics wishing to
engage with non-academic audiences, yet are relatively unexplored within the KE
literature. If âsharing research findings with a non-academic audienceâ is the sole
purpose of KE seminars, then the goal could have been achieved more cheaply
through a mail-shot of a briefing paper to a targeted audience (Percy-Smith et al,
2002). By comparison, KE seminars require a considerable investment in resources
in terms of time and money. These factors make them theoretically and
substantively interesting. This thesis explores the rationale for hosting and
attending KE seminars, what benefits participants feel that they gain from
attending, and provides insights into how best to facilitate those benefits.
Conceptually this thesis draws on Spaapen and van Drooge (2011) & Molas-Gallart
and Tangâs (2011) concept of âproductive interactions.â The thesis research examines
what makes interactions between academics and NAPs âproductiveâ in the context
of KE seminars, and the wider social network, economic and political environment
in which those interactions emerge and are shaped.
This thesis is based on a case study of the ESRC Centre for Population Change
(CPC). The empirical evidence comes from 27 semi-structured interviews conducted
with CPC academics & administrators (13), and NAPs who attended at least 1 CPC-organised
KE seminar (14); and an online questionnaire of 48 CPC staff members
(representing 75% of the Centre). The interviews were analysed thematically and the
online questionnaire was analysed using Social Network Analysis (SNA). The
research design was devised to collect data on the motivations, experiences, and
understandings of interactions between academics and NAP within the CPCâs KE
seminars. The social network analysis was designed to reveal the CPCâs KE social
networks which are pertinent to understanding how the CPC engages with NAPs.
This thesis documents ways in which KE seminars are sites of âknowledge
interactionâ (Davies et al, 2008) where multiple actors from multiple organisations
with different knowledges come together to engage in a topic of mutual interest. It
finds that KE seminars are worthwhile for participants despite being resource-intensive
because they fulfil multiple functions which cannot easily be replicated
through non-dialogical and non-corporeal interventions. The academic research
being presented on these social occasions is just one source of knowledge among
many others (ibid). KE seminars are also opportunities for participants to create new
informal contacts and strengthen existing ones. In other words, they help develop
informal professional networks which is an important component for successful KE
(Olmos-Peñuela, 2014b; Grimshaw et al, 2012; Kramer and Wells, 2005; Greenhalgh
et al, 2004; Philip et al, 2003; Molas-Gallart et al, 2000).
This thesis makes three original contributions. It shows: how KE seminars fill a
number of functions that cannot easily be replicated by indirect forms of nonacademic
engagement, which makes the investment of resources for hosting and
attending them not only desirable but often necessary; how corporeal co-presence is
important for facilitating productive interactions (Goffman, 1966; Urry, 2002; 2003);
and the major factors which help facilitate âproductive interactionsâ within KE
seminars. It is a contribution to the KE field generally, and will also be helpful to KE
practitioners and academics that are tasked with organising and hosting KE
seminars
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