To what extent has research conducted by the GaWC Research Network aided our understanding of large EU law firm geography?

This thesis explores whether a specific group of large EU law firms exhibited multiple common behaviours regarding their EU geographies between 1998 and 2009. These potentially common behaviours included their preferences for trading in certain EU locations, their usage of law firm alliances, and the specific reasons why they opened or closed EU branch offices. If my hypothesis is confirmed, this may indicate that certain aspects of large law firm geography are predictable – a finding potentially of interest to various stakeholders globally, including legal regulators, academics and law firms. In testing my hypothesis, I have drawn on research conducted by the Globalization and World Cities (GaWC) Research Network to assist me. Between 1999 and 2010, the GaWC published seven research papers exploring the geographies of large US and UK law firms. Several of the GaWC’s observations arising from these studies were evidence-based; others were speculative – including a novel approach for explaining legal practice branch office change, not adopted in research conducted previously or subsequently. By distilling the GaWC’s key observations these papers into a series of “sub-hypotheses”, I been able to test whether the geographical behaviours of my novel cohort of large EU law firms reflect those suggested by the GaWC. The more the GaWC’s suggested behaviours are observed among my cohort, the more my hypothesis will be supported. In conducting this exercise, I will additionally evaluate the extent to which the GaWC’s research has aided our understanding of large EU law firm geography. Ultimately, my findings broadly support most of the GaWC’s observations, notwithstanding our cohort differences and the speculative nature of several of the GaWC’s propositions. My investigation has also allowed me to refine several of the GaWC’s observations regarding commonly-observable large law firm geographical behaviours, while also addressing a key omission from the group’s research output.

D6.3 – Semantic Content Annotation Support

The Semantic Annotation component is a software application that provides support for automated text classification, a process grounded in a cohesion-centered representation of discourse that facilitates topic extraction. The component enables the semantic meta-annotation of text resources, including automated classification, thus facilitating information retrieval within the RAGE ecosystem. It is available in the ReaderBench framework (http://readerbench.com/) which integrates advanced Natural Language Processing (NLP) techniques. The component makes use of Cohesion Network Analysis (CNA) in order to ensure an in-depth representation of discourse, useful for mining keywords and performing automated text categorization. Our component automatically classifies documents into the categories provided by the ACM Computing Classification System (http://dl.acm.org/ccs_flat.cfm), but also into the categories from a high level serious games categorization provisionally developed by RAGE. English and French languages are already covered by the provided web service, whereas the entire framework can be extended in order to support additional languages.

Audit of mathematics learning support in Ireland in 2015 – the key findings

In 2015 the Irish Mathematics Learning Support Network (IMLSN) commissioned a comprehensive audit of the extent and nature of mathematics learning support (MLS) provision on the island of Ireland. An online survey was sent to 32 institutions, including universities, institutes of technology, further education and teacher training colleges, and a 97% response rate was achieved. While the headline figure – 84% of institutions that responded to the survey provide MLS – sounds good, deeper analysis reveals that the true state of MLS is not so solid. For example, in 25% of institutions offering MLS, only five hours per week (at most) of physical MLS are available, while in 20% of institutions the service is provided by only one or two staff members. Furthermore, training of tutors is minimal or non-existent in at least half of the institutions offering MLS. The results provide an illuminating picture, however, identifying the true state of MLS in Ireland is beneficial only if it informs developments in the years ahead. This talk will present some of the findings of the survey in more depth along with conclusions and recommendations. Key among these is the need for institutions to recognise MLS as a vital element of mathematics teaching and learning strategy at third level and devote the necessary resources to facilitate the provision of a service which can grow and adapt to meet student requirements.

Effective network security monitoring: from attribution to target-centric monitoring

Network security monitoring remains a challenge. As global networks scale up, in terms of traffic, volume and speed, effective attribution of cyber attacks is increasingly difficult. The problem is compounded by a combination of other factors, including the architecture of the Internet, multi-stage attacks and increasing volumes of nonproductive traffic. This paper proposes to shift the focus of security monitoring from the source to the target. Simply put, resources devoted to detection and attribution should be redeployed to efficiently monitor for targeting and prevention of attacks. The effort of detection should aim to determine whether a node is under attack, and if so, effectively prevent the attack. This paper contributes by systematically reviewing the structural, operational and legal reasons underlying this argument, and presents empirical evidence to support a shift away from attribution to favour of a target-centric monitoring approach. A carefully deployed set of experiments are presented and a detailed analysis of the results is achieved.

Fruit and vegetable intake and risk of incident of type 2 diabetes: results from the consortium on health and ageing network of cohorts in Europe and the United States (CHANCES)

BACKGROUND/OBJECTIVES: There is limited information to support definitive recommendations concerning the role of diet in the development of type 2 Diabetes mellitus (T2DM). The results of the latest meta-analyses suggest that an increased consumption of green leafy vegetables may reduce the incidence of diabetes, with either no association or weak associations demonstrated for total fruit and vegetable intake. Few studies have, however, focused on older subjects.

SUBJECTS/METHODS: The relationship between T2DM and fruit and vegetable intake was investigated using data from the NIH-AARP study and the EPIC Elderly study. All participants below the age of 50 and/or with a history of cancer, diabetes or coronary heart disease were excluded from the analysis. Multivariate logistic regression analysis was used to calculate the odds ratio of T2DM comparing the highest with the lowest estimated portions of fruit, vegetable, green leafy vegetables and cabbage intake.

RESULTS: Comparing people with the highest and lowest estimated portions of fruit, vegetable or green leafy vegetable intake indicated no association with the risk of T2DM. However, although the pooled OR across all studies showed no effect overall, there was significant heterogeneity across cohorts and independent results from the NIH-AARP study showed that fruit and green leafy vegetable intake was associated with a reduced risk of T2DM OR 0.95 (95% CI 0.91,0.99) and OR 0.87 (95% CI 0.87,0.90) respectively.

CONCLUSIONS: Fruit and vegetable intake was not shown to be related to incident T2DM in older subjects. Summary analysis also found no associations between green leafy vegetable and cabbage intake and the onset of T2DM. Future dietary pattern studies may shed light on the origin of the heterogeneity across populations.European Journal of Clinical Nutrition advance online publication, 17 August 2016; 

Model-driven development of sensor network applications with optimization of non-functional constraints

Wireless sensor networks (WSNs) differ from conventional distributed systems in many aspects. The resource limitation of sensor nodes, the ad-hoc communication and topology of the network, coupled with an unpredictable deployment environment are difficult non-functional constraints that must be carefully taken into account when developing software systems for a WSN. Thus, more research needs to be done on designing, implementing and maintaining software for WSNs. This thesis aims to contribute to research being done in this area by presenting an approach to WSN application development that will improve the reusability, flexibility, and maintainability of the software. Firstly, we present a programming model and software architecture aimed at describing WSN applications, independently of the underlying operating system and hardware. The proposed architecture is described and realized using the Model-Driven Architecture (MDA) standard in order to achieve satisfactory levels of encapsulation and abstraction when programming sensor nodes. Besides, we study different non-functional constrains of WSN application and propose two approaches to optimize the application to satisfy these constrains. A real prototype framework was built to demonstrate the developed solutions in the thesis. The framework implemented the programming model and the multi-layered software architecture as components. A graphical interface, code generation components and supporting tools were also included to help developers design, implement, optimize, and test the WSN software. Finally, we evaluate and critically assess the proposed concepts. Two case studies are provided to support the evaluation. The first case study, a framework evaluation, is designed to assess the ease at which novice and intermediate users can develop correct and power efficient WSN applications, the portability level achieved by developing applications at a high-level of abstraction, and the estimated overhead due to usage of the framework in terms of the footprint and executable code size of the application. In the second case study, we discuss the design, implementation and optimization of a real-world application named TempSense, where a sensor network is used to monitor the temperature within an area.

Predictive Analytics and Decision Support for Heart Failure patients

Thesis (Master's)--University of Washington, 2016-08

DEVELOPMENT OF A DECISION/DEPLOYMENT SUPPORT TOOL FOR VARIABLE SPEED LIMITS IN RECURRENT CONGESTION

Traffic demand increases are pushing aging ground transportation infrastructures to their theoretical capacity. The result of this demand is traffic bottlenecks that are a major cause of delay on urban freeways. In addition, the queues associated with those bottlenecks increase the probability of a crash while adversely affecting environmental measures such as emissions and fuel consumption. With limited resources available for network expansion, traffic professionals have developed active traffic management systems (ATMS) in an attempt to mitigate the negative consequences of traffic bottlenecks. Among these ATMS strategies, variable speed limits (VSL) and ramp metering (RM) have been gaining international interests for their potential to improve safety, mobility, and environmental measures at freeway bottlenecks. Though previous studies have shown the tremendous potential of variable speed limit (VSL) and VSL paired with ramp metering (VSLRM) control, little guidance has been developed to assist decision makers in the planning phase of a congestion mitigation project that is considering VSL or VSLRM control. To address this need, this study has developed a comprehensive decision/deployment support tool for the application of VSL and VSLRM control in recurrently congested environments. The decision tool will assist practitioners in deciding the most appropriate control strategy at a candidate site, which candidate sites have the most potential to benefit from the suggested control strategy, and how to most effectively design the field deployment of the suggested control strategy at each implementation site. To do so, the tool is comprised of three key modules, (1) Decision Module, (2) Benefits Module, and (3) Deployment Guidelines Module. Each module uses commonly known traffic flow and geometric parameters as inputs to statistical models and empirically based procedures to provide guidance on the application of VSL and VSLRM at each candidate site. These models and procedures were developed from the outputs of simulated experiments, calibrated with field data. To demonstrate the application of the tool, a list of real-world candidate sites were selected from the Maryland State Highway Administration Mobility Report. Here, field data from each candidate site was input into the tool to illustrate the step-by-step process required for efficient planning of VSL or VSLRM control. The output of the tool includes the suggested control system at each site, a ranking of the sites based on the expected benefit-to-cost ratio, and guidelines on how to deploy the VSL signs, ramp meters, and detectors at the deployment site(s). This research has the potential to assist traffic engineers in the planning of VSL and VSLRM control, thus enhancing the procedure for allocating limited resources for mobility and safety improvements on highways plagued by recurrent congestion.

A Recommender System based on the Immune Network

Abstract-The immune system is a complex biological system with a highly distributed, adaptive and self-organising nature. This paper presents an artificial immune system (AIS) that exploits some of these characteristics and is applied to the task of film recommendation by collaborative filtering (CF). Natural evolution and in particular the immune system have not been designed for classical optimisation. However, for this problem, we are not interested in finding a single optimum. Rather we intend to identify a sub-set of good matches on which recommendations can be based. It is our hypothesis that an AIS built on two central aspects of the biological immune system will be an ideal candidate to achieve this: Antigen - antibody interaction for matching and antibody - antibody interaction for diversity. Computational results are presented in support of this conjecture and compared to those found by other CF techniques.

Approximation Algorithms for Network Design and Orienteering

This thesis presents approximation algorithms for some NP-Hard combinatorial optimization problems on graphs and networks; in particular, we study problems related to Network Design. Under the widely-believed complexity-theoretic assumption that P is not equal to NP, there are no efficient (i.e., polynomial-time) algorithms that solve these problems exactly. Hence, if one desires efficient algorithms for such problems, it is necessary to consider approximate solutions: An approximation algorithm for an NP-Hard problem is a polynomial time algorithm which, for any instance of the problem, finds a solution whose value is guaranteed to be within a multiplicative factor of the value of an optimal solution to that instance. We attempt to design algorithms for which this factor, referred to as the approximation ratio of the algorithm, is as small as possible. The field of Network Design comprises a large class of problems that deal with constructing networks of low cost and/or high capacity, routing data through existing networks, and many related issues. In this thesis, we focus chiefly on designing fault-tolerant networks. Two vertices u,v in a network are said to be k-edge-connected if deleting any set of k − 1 edges leaves u and v connected; similarly, they are k-vertex connected if deleting any set of k − 1 other vertices or edges leaves u and v connected. We focus on building networks that are highly connected, meaning that even if a small number of edges and nodes fail, the remaining nodes will still be able to communicate. A brief description of some of our results is given below. We study the problem of building 2-vertex-connected networks that are large and have low cost. Given an n-node graph with costs on its edges and any integer k, we give an O(log n log k) approximation for the problem of finding a minimum-cost 2-vertex-connected subgraph containing at least k nodes. We also give an algorithm of similar approximation ratio for maximizing the number of nodes in a 2-vertex-connected subgraph subject to a budget constraint on the total cost of its edges. Our algorithms are based on a pruning process that, given a 2-vertex-connected graph, finds a 2-vertex-connected subgraph of any desired size and of density comparable to the input graph, where the density of a graph is the ratio of its cost to the number of vertices it contains. This pruning algorithm is simple and efficient, and is likely to find additional applications. Recent breakthroughs on vertex-connectivity have made use of algorithms for element-connectivity problems. We develop an algorithm that, given a graph with some vertices marked as terminals, significantly simplifies the graph while preserving the pairwise element-connectivity of all terminals; in fact, the resulting graph is bipartite. We believe that our simplification/reduction algorithm will be a useful tool in many settings. We illustrate its applicability by giving algorithms to find many trees that each span a given terminal set, while being disjoint on edges and non-terminal vertices; such problems have applications in VLSI design and other areas. We also use this reduction algorithm to analyze simple algorithms for single-sink network design problems with high vertex-connectivity requirements; we give an O(k log n)-approximation for the problem of k-connecting a given set of terminals to a common sink. We study similar problems in which different types of links, of varying capacities and costs, can be used to connect nodes; assuming there are economies of scale, we give algorithms to construct low-cost networks with sufficient capacity or bandwidth to simultaneously support flow from each terminal to the common sink along many vertex-disjoint paths. We further investigate capacitated network design, where edges may have arbitrary costs and capacities. Given a connectivity requirement R_uv for each pair of vertices u,v, the goal is to find a low-cost network which, for each uv, can support a flow of R_uv units of traffic between u and v. We study several special cases of this problem, giving both algorithmic and hardness results. In addition to Network Design, we consider certain Traveling Salesperson-like problems, where the goal is to find short walks that visit many distinct vertices. We give a (2 + epsilon)-approximation for Orienteering in undirected graphs, achieving the best known approximation ratio, and the first approximation algorithm for Orienteering in directed graphs. We also give improved algorithms for Orienteering with time windows, in which vertices must be visited between specified release times and deadlines, and other related problems. These problems are motivated by applications in the fields of vehicle routing, delivery and transportation of goods, and robot path planning.

Street lighting mesh network protocol

The digital revolution of the 21st century contributed to stem the Internet of Things (IoT). Trillions of embedded devices using the Internet Protocol (IP), also called smart objects, will be an integral part of the Internet. In order to support such an extremely large address space, a new Internet Protocol, called Internet Protocol Version 6 (IPv6) is being adopted. The IPv6 over Low Power Wireless Personal Area Networks (6LoWPAN) has accelerated the integration of WSNs into the Internet. At the same time, the Constrained Application Protocol (CoAP) has made it possible to provide resource constrained devices with RESTful Web services functionalities. This work builds upon previous experience in street lighting networks, for which a proprietary protocol, devised by the Lighting Living Lab, was implemented and used for several years. The proprietary protocol runs on a broad range of lighting control boards. In order to support heterogeneous applications with more demanding communication requirements and to improve the application development process, it was decided to port the Contiki OS to the four channel LED driver (4LD) board from Globaltronic. This thesis describes the work done to adapt the Contiki OS to support the Microchip TM PIC24FJ128GA308 microprocessor and presents an IP based solution to integrate sensors and actuators in smart lighting applications. Besides detailing the system’s architecture and implementation, this thesis presents multiple results showing that the performance of CoAP based resource retrievals in constrained nodes is adequate for supporting networking services in street lighting networks.

Credible Commitments and Post-Conflict Refugee Return: A Statistical and Network Analysis

I examine determinants of refugee return after conflicts. I argue that institutional constraints placed on the executive provide a credible commitment that signals to refugees that the conditions required for durable return will be created. This results in increased return flows for refugees. Further, when credible commitments are stronger in the country of origin than in the country of asylum, the level of return increases. Finally, I find that specific commitments made to refugees in the peace agreement do not lead to increased return because they are not credible without institutional constraints. Using data on returnees that has only recently been made available, along with network analysis and an original coding of the provisions in refugee agreements, statistical results are found to support this theory. An examination of cases in Djibouti, Sierra Leone, and Liberia provides additional support for this argument.

A longitudinal qualitative exploration of healthcare and informal support needs among survivors of critical illness: the RELINQUISH protocol.

Introduction and background: Survival following critical illness is associated with a significant burden of physical, emotional and psychosocial morbidity. Recovery can be protracted and incomplete, with important and sustained effects upon everyday life, including family life, social participation and return to work. In stark contrast with other critically ill patient groups (eg, those following cardiothoracic surgery), there are comparatively few interventional studies of rehabilitation among the general intensive care unit patient population. This paper outlines the protocol for a sub study of the RECOVER study: a randomised controlled trial evaluating a complex intervention of enhanced ward-based rehabilitation for patients following discharge from intensive care. Methods and analysis: The RELINQUISH study is a nested longitudinal, qualitative study of family support and perceived healthcare needs among RECOVER participants at key stages of the recovery process and at up to 1 year following hospital discharge. Its central premise is that recovery is a dynamic process wherein patients’ needs evolve over time. RELINQUISH is novel in that we will incorporate two parallel strategies into our data analysis: (1) a pragmatic health services-oriented approach, using an a priori analytical construct, the ‘Timing it Right’ framework and (2) a constructivist grounded theory approach which allows the emergence of new themes and theoretical understandings from the data. We will subsequently use Qualitative Health Needs Assessment methodology to inform the development of timely and responsive healthcare interventions throughout the recovery process. Ethics and dissemination: The protocol has been approved by the Lothian Research Ethics Committee (protocol number HSRU011). The study has been added to the UK Clinical Research Network Database (study ID. 9986). The authors will disseminate the findings in peer reviewed publications and to relevant critical care stakeholder groups.

D3M: multicast listener mobility support mechanisms over distributed mobility anchoring architectures

The explosion in mobile data traffic is a driver for future network operator technologies, given its large potential to affect both network performance and generated revenue. The concept of distributed mobility management (DMM) has emerged in order to overcome efficiency-wise limitations in centralized mobility approaches, proposing not only the distribution of anchoring functions but also dynamic mobility activation sensitive to the applications needs. Nevertheless, there is not an acceptable solution for IP multicast in DMM environments, as the first proposals based on MLD Proxy are prone to tunnel replication problem or service disruption. We propose the application of PIM-SM in mobility entities as an alternative solution for multicast support in DMM, and introduce an architecture enabling mobile multicast listeners support over distributed anchoring frameworks in a network-efficient way. The architecture aims at providing operators with flexible options to provide multicast mobility, supporting three modes: the first one introduces basic IP multicast support in DMM; the second improves subscription time through extensions to the mobility protocol, obliterating the dependence on MLD protocol; and the third enables fast listener mobility by avoiding potentially slow multicast tree convergence latency in larger infrastructures, by benefiting from mobility tunnels. The different modes were evaluated by mathematical analysis regarding disruption time and packet loss during handoff against several parameters, total and tunneling packet delivery cost, and regarding packet and signaling overhead.