On the Marginal Utility of Deploying Measurement Infrastructure

The cost and complexity of deploying measurement infrastructure in the Internet for the purpose of analyzing its structure and behavior is considerable. Basic questions about the utility of increasing the number of measurements and/or measurement sites have not yet been addressed which has lead to a "more is better" approach to wide-area measurements. In this paper, we quantify the marginal utility of performing wide-area measurements in the context of Internet topology discovery. We characterize topology in terms of nodes, links, node degree distribution, and end-to-end flows using statistical and information-theoretic techniques. We classify nodes discovered on the routes between a set of 8 sources and 1277 destinations to differentiate nodes which make up the so called "backbone" from those which border the backbone and those on links between the border nodes and destination nodes. This process includes reducing nodes that advertise multiple interfaces to single IP addresses. We show that the utility of adding sources goes down significantly after 2 from the perspective of interface, node, link and node degree discovery. We show that the utility of adding destinations is constant for interfaces, nodes, links and node degree indicating that it is more important to add destinations than sources. Finally, we analyze paths through the backbone and show that shared link distributions approximate a power law indicating that a small number of backbone links in our study are very heavily utilized.

Information Fusion and Hierarchical Knowledge Discovery by ARTMAP Neural Networks

Mapping novel terrain from sparse, complex data often requires the resolution of conflicting information from sensors working at different times, locations, and scales, and from experts with different goals and situations. Information fusion methods help resolve inconsistencies in order to distinguish correct from incorrect answers, as when evidence variously suggests that an object's class is car, truck, or airplane. The methods developed here consider a complementary problem, supposing that information from sensors and experts is reliable though inconsistent, as when evidence suggests that an objects class is car, vehicle, or man-made. Underlying relationships among objects are assumed to be unknown to the automated system of the human user. The ARTMAP information fusion system uses distributed code representations that exploit the neural network's capacity for one-to-many learning in order to produce self-organizing expert systems that discover hierarchial knowledge structures. The system infers multi-level relationships among groups of output classes, without any supervised labeling of these relationships. The procedure is illustrated with two image examples.

Self-Organizing Hierarchical Knowledge Discovery by an ARTMAP Image Fusion System

Classifying novel terrain or objects front sparse, complex data may require the resolution of conflicting information from sensors working at different times, locations, and scales, and from sources with different goals and situations. Information fusion methods can help resolve inconsistencies, as when evidence variously suggests that an object's class is car, truck, or airplane. The methods described here consider a complementary problem, supposing that information from sensors and experts is reliable though inconsistent, as when evidence suggests that an object's class is car, vehicle, and man-made. Underlying relationships among objects are assumed to be unknown to the automated system or the human user. The ARTMAP information fusion system used distributed code representations that exploit the neural network's capacity for one-to-many learning in order to produce self-organizing expert systems that discover hierarchical knowledge structures. The system infers multi-level relationships among groups of output classes, without any supervised labeling of these relationships.

Self-Organizing Information Fusion and Hierarchical Knowledge Discovery: A New Framework Using Artmap Neural Networks

Classifying novel terrain or objects from sparse, complex data may require the resolution of conflicting information from sensors woring at different times, locations, and scales, and from sources with different goals and situations. Information fusion methods can help resolve inconsistencies, as when eveidence variously suggests that and object's class is car, truck, or airplane. The methods described her address a complementary problem, supposing that information from sensors and experts is reliable though inconsistent, as when evidence suggests that an object's class is car, vehicle, and man-made. Underlying relationships among classes are assumed to be unknown to the autonomated system or the human user. The ARTMAP information fusion system uses distributed code representations that exploit the neural network's capacity for one-to-many learning in order to produce self-organizing expert systems that discover hierachical knowlege structures. The fusion system infers multi-level relationships among groups of output classes, without any supervised labeling of these relationships. The procedure is illustrated with two image examples, but is not limited to image domain.

Women's help seeking behaviour and the associated influencing factors on self discovery of a breast symptom

To investigate women’s help seeking behavior (HSB) following self discovery of a breast symptom and determine the associated influencing factors. A descriptive correlation design was used to ascertain the help seeking behavior (HSB) and the associated influencing factors of a sample of women (n = 449) with self discovered breast symptoms. The study was guided by the ‘Help Seeking Behaviour and Influencing Factors” conceptual framework (Facione et al., 2002; Meechan et al., 2003, 2002; Leventhal, Brissette and Leventhal, 2003 and O’Mahony and Hegarty, 2009b). Data was collected using a researcher developed multi-scale questionnaire package to ascertain women’s help seeking behavior on self discovery of a breast symptom and determine the factors most associated with HSB. Factors examined include: socio-demographics, knowledge and beliefs (regarding breast symptom; breast changes associated with breast cancer; use of alternative help seeking behaviours and presence or absence of a family history of breast cancer),emotional responses, social factors, health seeking habits and health service system utilization and help seeking behavior. A convenience sample (n = 449 was obtained by the researcher from amongst women attending the breast clinics of two large urban hospitals within the Republic of Ireland. All participants had self-discovered breast symptoms and no previous history of breast cancer. The study identified that while the majority of women (69.9%; n=314) sought help within one month, 30.1% (n=135) delayed help seeking for more than one month following self discovery of their breast symptom. The factors most significantly associated with HSB were the presenting symptom of ‘nipple indrawn/changes’ (p = 0.005), ‘ignoring the symptom and hoping it would go away’ (p < 0.001), the emotional response of being ‘afraid@ on symptom discovery (p = 0.005) and the perception/belief in longer symptom duration (p = 0.023). It was found that women who presented with an indrawn/changed nipple were more likely to delay (OR = 4.81) as were women who ‘ignored the symptoms and hoped it would go away’ (OR = 10.717). Additionally, the longer women perceived that their symptom would last, they more likely they were to delay (OR = 1.18). Conversely, being afraid following symptom discovery was associated with less delay (OR = 0.37; p=0.005). This study provides further insight into the HSB of women who self discovered breast symptoms. It highlights the complexity of the help seeking process, indicating that is not a linear event but is influenced by multiple factors which can have a significant impact on the outcomes in terms of whether women delay or seek help promptly. The study further demonstrates that delayed HSB persists amongst women with self discovered breast symptoms. This has important implications for continued emphasis on the promotion of breast awareness, prompt help seeking for self discovered breast symptoms and early detection and treatment of breast cancer, amongst women of all ages.

Legislative policy, law and competitiveness: a mysterious and difficult relationship in the EU

The Lisbon Agenda places Europe in a uniquely difficult position globally, most particularly as an example of a social and regulatory experiment which many consider to be doomed to failure. The drive towards economic competitiveness has led to a focus on regulation and its effect on entrepreneurship, productivity and business growth but assessing this relationship is complex for a number of reasons. First, not all regulatory effects can be predicted precisely in relation to behavioural outcomes. Path-dependency scholars have also demonstrated that the regulation will have varying effects depending on context. Second, theoretically it is clear that many non-regulatory factors may contribute to economic and competitive success. Third, there is evidence of internal conflict within the Commission as to the relative importance of the Lisbon goals. Finally, the experience of distinct Member States presents challenges both for assessment and prescriptive remedies. The Commission has estimated that the cost of regulatory compliance obligations on businesses in the EU is between 4% and 6% of gross domestic product and that 15% of this figure is avoidable 'red tape' (the term used specifically to signify unnecessary compliance burdens). This article proposes to assess the likely outcomes of de-regulation as we rapidly approach 2010, the year for attainment of the Lisbon goals.

The corporate social responsibility movement and law's empire: Is there a conflict?

At the heart of corporate governance and social responsibility discourse is recognition of the fact that the modern corporation is primarily governed by the profit maximisation imperative coupled with moral and ethical concerns that such a limited imperative drives the actions of large and wealthy corporations which have the ability to act in influential and significant ways, shaping how our social world is experienced. The actions of the corporation and its management will have a wide sphere of impact over all of its stakeholders whether these are employees, shareholders, consumers or the community in which the corporation is located. As globalisation has become central to the way we think it is also clear that ‘community’ has an ever expanding meaning which may include workers and communities living very far away from Corporate HQ. In recent years academic commentators have become increasingly concerned about the emphasis on what can be called short-term profit maximisation and the perception that this extremist interpretation of the profit imperative results in morally and ethically unacceptable outcomes.1 Hence demands for more corporate social responsibility. Following Cadbury’s2 classification of corporate social responsibility into three distinct areas, this paper will argue that once the legally regulated tier is left aside corporate responsibility can become so nebulous as to be relatively meaningless. The argument is not that corporations should not be required to act in socially responsible ways but that unless supported by regulation, which either demands high standards, or at the very least incentivises the attainment of such standards such initiatives are doomed to failure. The paper will illustrate by reference to various chosen cases that law’s discourse has already signposted ways to consider and resolve corporate governance problems in the broader social responsibility context.3 It will also illustrate how corporate responsibility can and must be supported by legal measures. Secondly, this paper will consider the potential conflict between an emphasis on corporate social responsibility and the regulatory approach.4 Finally, this paper will place the current interest in corporate social responsibility within the broader debate on the relationship between law and non-legally enforceable norms and will present some reflections on the norm debate arising from this consideration of the CSR movement.

Non-product related environmental process and production methods (NPR-PPMs): a view from international trade law and international environmental governance

The primary aim of this thesis is to analyse legal and governance issues in the use of Environmental NPR-PPMs, particularly those aiming to promote sustainable practices or to protect natural resources. NPR-PPMs have traditionally been thought of as being incompatible with the rules of the World Trade Organization (WTO). However, the issue remains untouched by WTO adjudicatory bodies. One can suggest that WTO adjudicatory bodies may want to leave this issue to the Members, but the analysis of the case law also seems to indicate that the question of legality of NPR-PPMs has not been brought ‘as such’ in dispute settlement. This thesis advances the argument that despite the fact that the legal status of NPR-PPMs remains unsettled, during the last decades adjudicatory bodies have been scrutinising environmental measures based on NPR-PPMs just as another expression of the regulatory autonomy of the Members. Though NPR-PPMs are regulatory choices associated with a wide range of environmental concerns, trade disputes giving rise to questions related to the legality of process-based measures have been mainly associated with the protection of marine wildlife (i.e., fishing techniques threatening or affecting animal species). This thesis argues that environmental objectives articulated as NPR-PPMs can indeed qualify as legitimate objectives both under the GATT and the TBT Agreement. However, an important challenge for the their compatibility with WTO law relate to aspects associated with arbitrary or unjustifiable discrimination. In the assessment of discrimination procedural issues play an important role. This thesis also elucidates other important dimensions to the issue from the perspective of global governance. One of the arguments advanced in this thesis is that a comprehensive analysis of environmental NPR-PPMs should consider not only their role in what is regarded as trade barriers (governmental and market-driven), but also their significance in global objectives such as the transition towards a green economy and sustainable patterns of consumption and production.

A study of the extent to which Irish law, policy and practice allow for Ireland's application of the United Nations Convention on the Rights of the Child, 1989 to pre-natal children

The central research question of this thesis asks the extent to which Irish law, policy and practice allow for the application of the United Nations Convention on the Rights of the Child (CRC) to pre-natal children. First, it is demonstrated that pre-natal children can fall within the definition of ‘child’ under the Convention and so the possibility of applying the Convention to children before birth is opened. Many State Parties to the CRC have interpreted it as applicable to pre-natal children, while others have expressed that it only applies from birth. Ireland has not clarified whether or not it interprets it as being applicable from conception, birth, or some other point. The remainder of the thesis examines the extent to which Ireland interprets the CRC as applicable to the pre-natal child. First, the question of whether Ireland affords to the pre-natal child the right to life under Article 6(1) of the Convention is analysed. Given the importance of the indivisibility of rights under the Convention, the extent to which Ireland applies other CRC rights to pre-natal children is examined. The rights analysed are the right to protection from harm, the right to the provision of health care and the procedural right to representation. It is concluded that Ireland’s laws, policies and practices require urgent clarification on the issue of the extent to which rights such as protection, health care and representation apply to children before birth. In general, there are mixed and ad hoc approaches to these issues in Ireland and there exists a great deal of confusion amongst those working on the frontline with such children, such as health care professionals and social workers. The thesis calls for significant reform in this area in terms of law and policy, which will inform practice.

Narratives in early Irish law tracts

This thesis presents a study of the 112 narratives collected from the Corpus Iuris Hibernici. The selection of narratives is based on criteria informed by modern narratological theories. The significant presence of narratives in early Irish law tracts appears at odds with the normal conception of law texts as consisting solely of provisions, and therefore needs to be accounted for. Since no systematic study has been conducted of these legal narratives, this thesis serves as an introduction by giving firstly an index of narratives and secondly a categorisation of them in terms of distribution, dates and functions. It then carries out a general analysis of the relationship between legal narratives and early Irish literature, and a selected case study of the relationship between legal narratives and the legal institutions in the context of which the narratives are located. It has become clearer, with the progress of argument, that the use of narratives was an integral part of legal writing in medieval Ireland; and the narratives, though having many idiosyncratic features of themselves, are profoundly connected with the learned tradition at large. The legal narratives reveal the intellectual background and compositional concerns of medieval Irish jurists, and they formed a crucial part of the effort to accommodate law tracts into the dynamic tradition of senchas. Two appendices are included at the end: one consists of translations of 34 narratives from the index, and the other is a critical edition of one of the narratives discussed in detail, together with translations of some relevant passages.

The accountability of transnational armed groups under international law

Terrorist attacks by transnational armed groups cause on average 15,000 deaths every year worldwide, with the law enforcement agencies of some states facing many challenges in bringing those responsible to justice. Despite various attempts to codify the law on transnational terrorism since the 1930s, a crime of transnational terrorism under International Law remains contested, reflecting concerns regarding the relative importance of prosecuting members of transnational armed groups before the International Criminal Court. However, a study of the emerging jurisprudence of the International Criminal Court suggests that terrorist attacks cannot be classified as a war crime or a crime against humanity. Therefore, using organisational network theory, this thesis will probe the limits of international criminal law in bringing members of transnational armed groups to justice in the context of changing methods of warfare. Determining the organisational structure of transnational armed groups, provides a powerful analytical framework for examining the challenges in holding members of transnational armed groups accountable before the International Criminal Court, in the context of the relationship between the commanders and the subordinate members of the group.

Delivering mobile cloud services to the user: description, discovery, and consumption

The mobile cloud computing paradigm can offer relevant and useful services to the users of smart mobile devices. Such public services already exist on the web and in cloud deployments, by implementing common web service standards. However, these services are described by mark-up languages, such as XML, that cannot be comprehended by non-specialists. Furthermore, the lack of common interfaces for related services makes discovery and consumption difficult for both users and software. The problem of service description, discovery, and consumption for the mobile cloud must be addressed to allow users to benefit from these services on mobile devices. This paper introduces our work on a mobile cloud service discovery solution, which is utilised by our mobile cloud middleware, Context Aware Mobile Cloud Services (CAMCS). The aim of our approach is to remove complex mark-up languages from the description and discovery process. By means of the Cloud Personal Assistant (CPA) assigned to each user of CAMCS, relevant mobile cloud services can be discovered and consumed easily by the end user from the mobile device. We present the discovery process, the architecture of our own service registry, and service description structure. CAMCS allows services to be used from the mobile device through a user's CPA, by means of user defined tasks. We present the task model of the CPA enabled by our solution, including automatic tasks, which can perform work for the user without an explicit request.

Real-Time and Data-Driven Operation Optimization and Knowledge Discovery for an Enterprise Information System

An enterprise information system (EIS) is an integrated data-applications platform characterized by diverse, heterogeneous, and distributed data sources. For many enterprises, a number of business processes still depend heavily on static rule-based methods and extensive human expertise. Enterprises are faced with the need for optimizing operation scheduling, improving resource utilization, discovering useful knowledge, and making data-driven decisions.

This thesis research is focused on real-time optimization and knowledge discovery that addresses workflow optimization, resource allocation, as well as data-driven predictions of process-execution times, order fulfillment, and enterprise service-level performance. In contrast to prior work on data analytics techniques for enterprise performance optimization, the emphasis here is on realizing scalable and real-time enterprise intelligence based on a combination of heterogeneous system simulation, combinatorial optimization, machine-learning algorithms, and statistical methods.

On-demand digital-print service is a representative enterprise requiring a powerful EIS.We use real-life data from Reischling Press, Inc. (RPI), a digit-print-service provider (PSP), to evaluate our optimization algorithms.

In order to handle the increase in volume and diversity of demands, we first present a high-performance, scalable, and real-time production scheduling algorithm for production automation based on an incremental genetic algorithm (IGA). The objective of this algorithm is to optimize the order dispatching sequence and balance resource utilization. Compared to prior work, this solution is scalable for a high volume of orders and it provides fast scheduling solutions for orders that require complex fulfillment procedures. Experimental results highlight its potential benefit in reducing production inefficiencies and enhancing the productivity of an enterprise.

We next discuss analysis and prediction of different attributes involved in hierarchical components of an enterprise. We start from a study of the fundamental processes related to real-time prediction. Our process-execution time and process status prediction models integrate statistical methods with machine-learning algorithms. In addition to improved prediction accuracy compared to stand-alone machine-learning algorithms, it also performs a probabilistic estimation of the predicted status. An order generally consists of multiple series and parallel processes. We next introduce an order-fulfillment prediction model that combines advantages of multiple classification models by incorporating flexible decision-integration mechanisms. Experimental results show that adopting due dates recommended by the model can significantly reduce enterprise late-delivery ratio. Finally, we investigate service-level attributes that reflect the overall performance of an enterprise. We analyze and decompose time-series data into different components according to their hierarchical periodic nature, perform correlation analysis,

and develop univariate prediction models for each component as well as multivariate models for correlated components. Predictions for the original time series are aggregated from the predictions of its components. In addition to a significant increase in mid-term prediction accuracy, this distributed modeling strategy also improves short-term time-series prediction accuracy.

In summary, this thesis research has led to a set of characterization, optimization, and prediction tools for an EIS to derive insightful knowledge from data and use them as guidance for production management. It is expected to provide solutions for enterprises to increase reconfigurability, accomplish more automated procedures, and obtain data-driven recommendations or effective decisions.

Component-wise gradient boosting and false discovery control in survival analysis with high-dimensional covariates.

MOTIVATION: Technological advances that allow routine identification of high-dimensional risk factors have led to high demand for statistical techniques that enable full utilization of these rich sources of information for genetics studies. Variable selection for censored outcome data as well as control of false discoveries (i.e. inclusion of irrelevant variables) in the presence of high-dimensional predictors present serious challenges. This article develops a computationally feasible method based on boosting and stability selection. Specifically, we modified the component-wise gradient boosting to improve the computational feasibility and introduced random permutation in stability selection for controlling false discoveries. RESULTS: We have proposed a high-dimensional variable selection method by incorporating stability selection to control false discovery. Comparisons between the proposed method and the commonly used univariate and Lasso approaches for variable selection reveal that the proposed method yields fewer false discoveries. The proposed method is applied to study the associations of 2339 common single-nucleotide polymorphisms (SNPs) with overall survival among cutaneous melanoma (CM) patients. The results have confirmed that BRCA2 pathway SNPs are likely to be associated with overall survival, as reported by previous literature. Moreover, we have identified several new Fanconi anemia (FA) pathway SNPs that are likely to modulate survival of CM patients. AVAILABILITY AND IMPLEMENTATION: The related source code and documents are freely available at https://sites.google.com/site/bestumich/issues. CONTACT: yili@umich.edu.

Interrogation of individual intratumoral B lymphocytes from lung cancer patients for molecular target discovery.

Intratumoral B lymphocytes are an integral part of the lung tumor microenvironment. Interrogation of the antibodies they express may improve our understanding of the host response to cancer and could be useful in elucidating novel molecular targets. We used two strategies to explore the repertoire of intratumoral B cell antibodies. First, we cloned VH and VL genes from single intratumoral B lymphocytes isolated from one lung tumor, expressed the genes as recombinant mAbs, and used the mAbs to identify the cognate tumor antigens. The Igs derived from intratumoral B cells demonstrated class switching, with a mean VH mutation frequency of 4%. Although there was no evidence for clonal expansion, these data are consistent with antigen-driven somatic hypermutation. Individual recombinant antibodies were polyreactive, although one clone demonstrated preferential immunoreactivity with tropomyosin 4 (TPM4). We found that higher levels of TPM4 antibodies were more common in cancer patients, but measurement of TPM4 antibody levels was not a sensitive test for detecting cancer. Second, in an effort to focus our recombinant antibody expression efforts on those B cells that displayed evidence of clonal expansion driven by antigen stimulation, we performed deep sequencing of the Ig genes of B cells collected from seven different tumors. Deep sequencing demonstrated somatic hypermutation but no dominant clones. These strategies may be useful for the study of B cell antibody expression, although identification of a dominant clone and unique therapeutic targets may require extensive investigation.