Attributes of Identity Document Credibility: A Synthesis of Expert Knowledge

In broad terms — including a thief's use of existing credit card, bank, or other accounts — the number of identity fraud victims in the United States ranges 9-10 million per year, or roughly 4% of the US adult population. The average annual theft per stolen identity was estimated at $6,383 in 2006, up approximately 22% from $5,248 in 2003; an increase in estimated total theft from $53.2 billion in 2003 to $56.6 billion in 2006. About three million Americans each year fall victim to the worst kind of identity fraud: new account fraud. Names, Social Security numbers, dates of birth, and other data are acquired fraudulently from the issuing organization, or from the victim then these data are used to create fraudulent identity documents. In turn, these are presented to other organizations as evidence of identity, used to open new lines of credit, secure loans, “flip” property, or otherwise turn a profit in a victim's name. This is much more time consuming — and typically more costly — to repair than fraudulent use of existing accounts. This research borrows from well-established theoretical backgrounds, in an effort to answer the question – what is it that makes identity documents credible? Most importantly, identification of the components of credibility draws upon personal construct psychology, the underpinning for the repertory grid technique, a form of structured interviewing that arrives at a description of the interviewee’s constructs on a given topic, such as credibility of identity documents. This represents substantial contribution to theory, being the first research to use the repertory grid technique to elicit from experts, their mental constructs used to evaluate credibility of different types of identity documents reviewed in the course of opening new accounts. The research identified twenty-one characteristics, different ones of which are present on different types of identity documents. Expert evaluations of these documents in different scenarios suggest that visual characteristics are most important for a physical document, while authenticated personal data are most important for a digital document.

Leader's reflections on knowledge, knowing and not knowing: an analysis of change over time

One commonality across the leadership and knowledge related literature is the apparent neglect of the leaders own knowledge. This thesis sought to address this issue through conducting exploratory research into the content of leader’s personal knowledge and the process of knowing it. The empirical inquiry adopted a longitudinal approach, with interviews conducted at two separate time periods with an extended time-interval between each. The findings from this research contrast with images of leadership which suggest leaders are in control of what they know, that they own their own knowledge. The picture that emerges is one of individuals struggling to keep abreast of the knowledge required to deal with the dynamics and uncertainties of organisational life. Much knowledge is tacit, provisional and perishable and the related process of knowing more organic, evolutionary and informal than any structured or orchestrated approach. The collective nature of knowing is a central feature, with these leaders embedded in networks of uncontrollable relationships. In view of the indeterminate nature of knowing, the boundary between what is known and what one needs to know is both amorphous and ephemeral, and the likelihood of knowledge-absences is escalated. A significant finding in this regard is the identification of two critical points where not-knowing is most likely (entry and exit from role) and the differing implications of each. Overtime the knowledge that is legitimised or prioritised is significantly altered as these leaders replace the dogmas that were previously held in high esteem with the lessons from their own experience. This experience brings increased self-knowledge and a deeper appreciation of the values and morals instilled in their early lives. In view of the above findings, this study makes theoretical contribution to a number of core literatures: authentic leadership, role transition and knowledge-absences. In terms of leadership development, the findings point to the necessity to prepare leaders for the challenges they will encounter at the pivotal stages of the leadership role.

An Examination of Current Approaches to Integrative Indigenous and Western Knowledge System Implementation in Water Research and Management: A Case Study Encompassing the Colonized Geographies of Canada, Australia, New Zealand, and the United States

The commodification of natural resources and the pursuit of continuous growth has resulted in environmental degradation, depletion, and disparity in access to these life-sustaining resources, including water. Utility-based objectification and exploitation of water in some societies has brought us to the brink of crisis through an apathetic disregard for present and future generations. The ongoing depletion and degradation of the world’s water sources, coupled with a reliance on Western knowledge and the continued omission of Indigenous knowledge to manage our relationship with water has unduly burdened many, but particularly so for Indigenous communities. The goal of my thesis research is to call attention to and advance the value and validity of using both Indigenous and Western knowledge systems (also known as Two-Eyed Seeing) in water research and management to better care for water. To achieve this goal, I used a combined systematic and realist review method to identify and synthesize the peer-reviewed, integrative water literature, followed by semi-structured interviews with first authors of the exemplars from the included literature to identify the challenges and insights that researchers have experienced in conducting integrative water research. Findings suggest that these authors recognize that many previous attempts to integrate Indigenous knowledges have been tokenistic rather than meaningful, and that new methods for knowledge implementation are needed. Community-based participatory research methods, and the associated tenets of balancing power, fostering trust, and community ownership over the research process, emerged as a pathway towards the meaningful implementation of Indigenous and Western knowledge systems. Data also indicate that engagement and collaborative governance structures developed from a position of mutual respect are integral to the realization of a given project. The recommendations generated from these findings offer support for future Indigenous-led research and partnerships through the identification and examination of approaches that facilitate the meaningful implementation of Indigenous and Western knowledge systems in water research and management. Asking Western science questions and seeking Indigenous science solutions does not appear to be working; instead, the co-design of research projects and asking questions directed at the problem rather than the solution better lends itself to the strengths of Indigenous science.

Identification and bioactivity evaluation of two novel temporins from the skin secretion of the European edible frog, Pelophylax kl. Esculentus

The amphibian temporins, amongst the smallest antimicrobial peptides (AMPs), are α-helical, amphipathic, hydrophobic and cationic and are active mainly against Gram-positive bacteria but inactive or weakly active against Gram-negative bacteria. Here, we report two novel members of the temporin family, named temporin-1Ee (FLPVIAGVLSKLFamide) and temporin-1Re (FLPGLLAGLLamide), whose biosynthetic precursor structures were deduced from clones obtained from skin secretion-derived cDNA libraries of the European edible frog, Pelophylax kl. esculentus, by ‘shotgun’ cloning. Deduction of the molecular masses of each mature processed peptide from respective cloned cDNAs was used to locate respective molecules in reverse-phase HPLC fractions of secretion. Temporin-1Ee (MIC = 10 μM) and temporin-1Re (MIC = 60 μM) were both found to be active against Gram-positive Staphylococcus aureus, but retaining a weak haemolytic activity. To our knowledge, Single-site substitutions can dramatically change the spectrum of activity of a given temporin. Compared with temporine-1Ec, just one chemically-conservative substitution (Val8 instead of Leu8), temporin-1Ee bearing a net charge of +2 displays broad-spectrum activity with particularly high potency on the clinically relevant Gram-negative strains, Escherichia coli (MIC = 40 μM). These factors bode well for translating temporins to be potential drug candidates for the design of new and valuable anti-infective agents.

Détection, reconstruction 3D et identification des êtres vivants du règne animal

L’automatisation de la détection et de l’identification des animaux est une tâche qui a de l’intérêt dans plusieurs domaines de recherche en biologie ainsi que dans le développement de systèmes de surveillance électronique. L’auteur présente un système de détection et d’identification basé sur la vision stéréo par ordinateur. Plusieurs critères sont utilisés pour identifier les animaux, mais l’accent a été mis sur l’analyse harmonique de la reconstruction en temps réel de la forme en 3D des animaux. Le résultat de l’analyse est comparé avec d’autres qui sont contenus dans une base évolutive de connaissances.

Knowledge Exchange Institutional Repository Workshop

The workshop took place on 16-17 January in Utrecht, with Seventy experts from eight European countries in attendance. The workshop was structured in six sessions: usage statistics research paper metadata exchanging information author identification Open Archives Initiative eTheses Following the workshop, the discussion groups were asked to continue their collaboration and to produce a report for circulation to all participants. The results can be downloaded below. The recommendations contained in the reports above have been reviewed by the Knowledge Exchange partner organisations and formed the basis for new proposals and the next steps in Knowledge Exchange work with institutional repositories. Institutional Repository Workshop - Next steps During April and May 2007 Knowledge Exchange had expert reviewers from the partner organisations go though the workshop strand reports and make their recommendations about the best way to move forward, to set priorities, and find possibilities for furthering the institutional repository cause. The KE partner representatives reviewed the reviews and consulted with their partner organisation management to get an indication of support and funding for the latest ideas and proposals, as follows: Pragmatic interoperability During a review meeting at JISC offices in London on 31 May, the expert reviewers and the KE partner representatives agreed that ‘pragmatic interoperability' is the primary area of interest. It was also agreed that the most relevant and beneficial choice for a Knowledge Exchange approach would be to aim for CRIS-OAR interoperability as a step towards integrated services. Within this context, interlinked joint projects could be undertaken by the partner organisations regarding the areas that most interested them. Interlinked projects The proposed Knowledge Exchange activities involve interlinked joint projects on metadata, persistent author identifiers, and eTheses which are intended to connect to and build on projects such as ISPI, Jisc NAMES and the Digital Author Identifier (DAI) developed by SURF. It is important to stress that the projects are not intended to overlap, but rather to supplement the DRIVER 2 (EU project) approaches. Focus on CRIS and OAR It is believed that the focus on practical interoperability between Current Research Information Systems and Open Access Repository systems will be of genuine benefit to research scientists, research administrators and librarian communities in the Knowledge Exchange countries; accommodating the specific needs of each group. Timing June 2007: Write the draft proposal by KE Working Group members July 2007: Final proposal to be sent to partner organisations by KE Group August 2007: Decision by Knowledge Exchange partner organisations.

Probabilistic Models for Scalable Knowledge Graph Construction

In the past decade, systems that extract information from millions of Internet documents have become commonplace. Knowledge graphs -- structured knowledge bases that describe entities, their attributes and the relationships between them -- are a powerful tool for understanding and organizing this vast amount of information. However, a significant obstacle to knowledge graph construction is the unreliability of the extracted information, due to noise and ambiguity in the underlying data or errors made by the extraction system and the complexity of reasoning about the dependencies between these noisy extractions. My dissertation addresses these challenges by exploiting the interdependencies between facts to improve the quality of the knowledge graph in a scalable framework. I introduce a new approach called knowledge graph identification (KGI), which resolves the entities, attributes and relationships in the knowledge graph by incorporating uncertain extractions from multiple sources, entity co-references, and ontological constraints. I define a probability distribution over possible knowledge graphs and infer the most probable knowledge graph using a combination of probabilistic and logical reasoning. Such probabilistic models are frequently dismissed due to scalability concerns, but my implementation of KGI maintains tractable performance on large problems through the use of hinge-loss Markov random fields, which have a convex inference objective. This allows the inference of large knowledge graphs using 4M facts and 20M ground constraints in 2 hours. To further scale the solution, I develop a distributed approach to the KGI problem which runs in parallel across multiple machines, reducing inference time by 90%. Finally, I extend my model to the streaming setting, where a knowledge graph is continuously updated by incorporating newly extracted facts. I devise a general approach for approximately updating inference in convex probabilistic models, and quantify the approximation error by defining and bounding inference regret for online models. Together, my work retains the attractive features of probabilistic models while providing the scalability necessary for large-scale knowledge graph construction. These models have been applied on a number of real-world knowledge graph projects, including the NELL project at Carnegie Mellon and the Google Knowledge Graph.

Defining a management strategy for the azorean natural thermal resources : valuing criteria identification

Dissertação de Mestrado, Gestão de Empresas (MBA), 23 de Maio de 2016, Universidade dos Açores.

Knowledge sharing networks and performance

The present investigation aims to analyse the relationship between knowledge sharing behaviours and performance. The former behaviours were studied using Social Network Analysis, in an attempt to characterise knowledge sharing networks. Through identification of central individuals in these networks, we made analysis of the association between this centrality and individual performance. A questionnaire was developed and applied to a sample of workers in a Portuguese organisation (N=244). The final conclusions point to a positive association between these behaviours and individual performance.

Swedish-speaking Finns: a multi-method qualitative study of belonging and identification

The Swedish-speaking minority in Finland, often described as an ‘elite minority’, holds a special position in the country. With linguistic rights protected by the constitution of Finland, Swedish-speakers, as a minority of only 5.3%, are often described in public discourse and in academic and statistical studies as happier, healthier and more well off economically than the Finnish-speaking majority. As such, the minority is a unique example of language minorities in Europe. Knowledge derived from qualitatively grounded studies on the topic is however lacking, meaning that there is a gap in understanding of the nature and complexity of the minority. Drawing on ethnographic research conducted in four different locations in Finland over a period of 12 months, this thesis provides a theoretically grounded and empirically informed rich account of the identifications and sites of belonging of this diverse minority. The thesis makes a contribution to theoretical, methodological and empirical research on the Swedish-speaking minority, debates around identity and belonging, and ethnographic methodological approaches. Making use of novel methodology in studying Swedish-speaking Finns, this thesis moves beyond generalisations and simplifications on its nature and character. Drawing on rich ethnographic empirical material, the thesis interrogates various aspects of the lived experience of Swedish-speaking Finns by combining the concepts of belonging and identification. Some of the issues explored are the way in which belonging can be regionally specific, how Swedish-speakers create Swedish-spaces, how language use is situational and variable and acts as a marker of identity, and finally how identifications and sites of belonging among the minority are extremely varied and complex. The thesis concludes that there are various sites of belonging and identification available to Swedish-speakers, and these need to be studied and considered in order to gain an accurate picture of the lived experience of the minority. It also argues that while identifications are based on collective imagery, this imagery can vary among Swedish-speakers and identifications are multiple and situational. Finally, while language is a key commonality for the minority, the meanings attached to it are not only concerned with ‘Finland Swedishness’, but connected to various other factors, such as the context a person grew up in and the region one lives in. The complex issues affecting the lived experience of Swedish-speaking Finns cannot be understood without the contribution of findings from qualitative research. This thesis therefore points towards a new kind of understanding of Swedish-speaking Finns, moving away from stereotypes and simplifications, shifting our gaze towards a richer perception of the minority.

On The Use of Genetic Algorithms for Parameter Identification in Anaerobic Digestion Modelling

Anaerobic digestion (AD) of wastewater is a very interesting option for waste valorization, energy production and environment protection. It is a complex, naturally occurring process that can take place inside bioreactors. The capability of predicting the operation of such bioreactors is important to optimize the design and the operation conditions of the reactors, which, in part, justifies the numerous AD models presently available. The existing AD models are not universal, have to be inferred from prior knowledge and rely on existing experimental data. Among the tasks involved in the process of developing a dynamical model for AD, the estimation of parameters is one of the most challenging. This paper presents the identifiability analysis of a nonlinear dynamical model for a batch reactor. Particular attention is given to the structural identifiability of the model, which considers the uniqueness of the estimated parameters. To perform this analysis, the GenSSI toolbox was used. The estimation of the model parameters is achieved with genetic algorithms (GA) which have already been used in the context of AD modelling, although not commonly. The paper discusses its advantages and disadvantages.

Experiments on identification of argumentative sentences

The main purpose of this study is to evaluate the best set of features that automatically enables the identification of argumentative sentences from unstructured text. As corpus, we use case laws from the European Court of Human Rights (ECHR). Three kinds of experiments are conducted: Basic Experiments, Multi Feature Experiments and Tree Kernel Experiments. These experiments are basically categorized according to the type of features available in the corpus. The features are extracted from the corpus and Support Vector Machine (SVM) and Random Forest are the used as Machine learning algorithms. We achieved F1 score of 0.705 for identifying the argumentative sentences which is quite promising result and can be used as the basis for a general argument-mining framework.