Understanding Contradictions in Times of Change: A CHAT Analysis in an Art Museum

Thesis (Ph.D.)--University of Washington, 2016-08

Threat analysis of IoT networks using artificial neural network intrusion detection system

The Internet of things (IoT) is still in its infancy and has attracted much interest in many industrial sectors including medical fields, logistics tracking, smart cities and automobiles. However, as a paradigm, it is susceptible to a range of significant intrusion threats. This paper presents a threat analysis of the IoT and uses an Artificial Neural Network (ANN) to combat these threats. A multi-level perceptron, a type of supervised ANN, is trained using internet packet traces, then is assessed on its ability to thwart Distributed Denial of Service (DDoS/DoS) attacks. This paper focuses on the classification of normal and threat patterns on an IoT Network. The ANN procedure is validated against a simulated IoT network. The experimental results demonstrate 99.4% accuracy and can successfully detect various DDoS/DoS attacks.

Oceans of energy? The non-linear trajectory of the emerging wave energy technology

This paper addresses the construction and structuring of a technological niche – i.e. a protected space where promising but still underperforming technologies are stabilized and articulated with societal needs – and discusses the processes that influence niche development and may enable niche breakout. In theoretical terms the paper is grounded on the multi-level approach to sustainability transitions, and particularly on the niche literature. But it also attempts to address the limitations of this literature in what concerns the spatial dimension of niche development. It is argued that technological niches can transcend the narrow territorial boundaries to which they are often confined, and encompass communities and actions that span several spatial levels, without losing some territorial embeddedness. It is further proposed that these features shape the niche trajectory and, therefore, need to be explicitly considered by the niche theoretical framework. To address this problem the paper builds on and extends the socio-cognitive perspective to technology development, introducing a further dimension – space – which broadens the concept of technological niche and permits to better capture the complexity of niche behaviour. This extended framework is applied to the case of an emerging renewable energy technology – wave energy - which exhibits a particularly slow and non-linear development trajectory. The empirical analysis starts by examining how an “overall niche space” in wave energy was spatially constructed over time. Then it investigates in greater detail the niche development processes that took place in Portugal, a country that was among the pioneers in the field, and whose actors have been, from very early stages, engaged in the activities conducted at various spatial levels. Through this combined analysis, the paper seeks to understand whether and how niche development is shaped by processes taking place at different spatial levels. More specifically it investigates the interplay between territorial and relational elements in niche development, and how these different dynamics influence the performance of the niche processes and impact on the overall niche trajectory. The results confirm the niche multi-spatial dynamics, showing that it is shaped by the interplay between a niche relational space constructed by actors’ actions and interactions on/across levels, and the territorial effects introduced by these actors’ embeddedness in particular geographical and institutional settings. They contribute to a more precise understanding of the processes that can accelerate or slow down the trajectory of a technological niche. In addition, the results shed some light into the niche activities conducted in/originating from a specific territorial setting - Portugal - offering some insights into the behaviour of key actors and its implications for the positioning of the country in the emerging field, which can be relevant for the formulation of strategies and policies for this area.

Effects of exposure to Bovine viral diarrhoea virus 1 on risk of bovine respiratory disease in Australian feedlot cattle

Viruses play a key role in the complex aetiology of bovine respiratory disease (BRD). Bovine viral diarrhoea virus 1 (BVDV-1) is widespread in Australia and has been shown to contribute to BRD occurrence. As part of a prospective longitudinal study on BRD, effects of exposure to BVDV-1 on risk of BRD in Australian feedlot cattle were investigated. A total of 35,160 animals were enrolled at induction (when animals were identified and characteristics recorded), held in feedlot pens with other cattle (cohorts) and monitored for occurrence of BRD over the first 50 days following induction. Biological samples collected from all animals were tested to determine which animals were persistently infected (PI) with BVDV-1. Data obtained from the Australian National Livestock Identification System database were used to determine which groups of animals that were together at the farm of origin and at 28 days prior to induction (and were enrolled in the study) contained a PI animal and hence to identify animals that had probably been exposed to a PI animal prior to induction. Multi-level Bayesian logistic regression models were fitted to estimate the effects of exposure to BVDV-1 on the risk of occurrence of BRD.Although only a total of 85 study animals (0.24%) were identified as being PI with BVDV-1, BVDV-1 was detected on quantitative polymerase chain reaction in 59% of cohorts. The PI animals were at moderately increased risk of BRD (OR 1.9; 95% credible interval 1.0-3.2). Exposure to BVDV-1 in the cohort was also associated with a moderately increased risk of BRD (OR 1.7; 95% credible interval 1.1-2.5) regardless of whether or not a PI animal was identified within the cohort. Additional analyses indicated that a single quantitative real-time PCR test is useful for distinguishing PI animals from transiently infected animals.The results of the study suggest that removal of PI animals and/or vaccination, both before feedlot entry, would reduce the impact of BVDV-1 on BRD risk in cattle in Australian feedlots. Economic assessment of these strategies under Australian conditions is required. © 2016 Elsevier B.V.

Klasseneffekte oder individuelle Einflussgrößen. Was bestimmt die Teilnahme am Instrumentallernen im Grundschulalter

In den vergangenen Jahren hat die Diskussion um kulturelle Teilhabe im Rahmen der Ergebnisse großer Bildungsstudien zugenommen. Diese hatten eine hochgradige Abhängigkeit des Bildungserfolgs und des Kompetenzerwerbs vom sozialen Hintergrund der Kinder und ihrer Familien konstatiert (u.a. Ehmke & Jude 2010, S. 250). Auch für den Teilaspekt der kulturellen Teilhabe ließen sich in Studien soziale Disparitäten feststellen: Die rezeptive Nutzung kultureller Angebote durch Kinder und Jugendliche unterliegt einer deutlichen sozialen Selektivität (Autorengruppe Bildungsberichterstattung 2012, S. 165). Gleichzeitig ist mit dem Programm Jedem Kind ein Instrument eine große Initiative zur Förderung frühen Instrumentallernens in der Grundschulzeit angelaufen. Die Initiatoren verfolgen dabei explizit das Ziel, die Kluft „zwischen kulturaffinen Elternhäusern und bildungsfernen Schichten" (Kulturstiftung des Bundes, 2012) in Bezug auf kulturelle Bildung zu verringern, eine „Grundversorgung" (ebd.) sicherzustellen und im demokratischen Sinne niemanden von der Alphabetisierung in Sachen Kunst auszuschließen (Völckers, 2007). Die Teilnahme von Kindern an Instrumentalunterricht während der Grundschulzeit wird hier also als ein Aspekt aktiver kultureller Teilhabe gedeutet und wird im Folgenden einer Analyse unterzogen. (DIPF/Orig.)

Les stratégies syndicales face aux restructurations d’entreprises : une étude comparative des contre-pouvoirs syndicaux dans le secteur des équipementiers automobiles en France et au Canada

Cette thèse tente de comprendre l’impact des restructurations des entreprises multinationales sur les stratégies syndicales. Les acteurs syndicaux locaux sont-ils déterminés par l’appartenance à des régimes nationaux et à des contingences organisationnelles ou peuvent-ils influencer des décisions objectives comme les restructurations ? Cette recherche s’insère dans une problématique large qui fait la jonction entre la mondialisation économique sur une base continentale, la réorganisation productive des entreprises multinationales et l’action syndicale. Au plan théorique, nous confrontons trois grandes approches analytiques, à savoir : le néo-institutionnalisme et les structures d’opportunités ; l’économie politique critique et la question du pouvoir syndical ; la géographie économique critique mettant de l’avant les contingences, l’encastrement et l’espace concurrentiel. Sur la base de ces trois familles, nous présentons un modèle d’analyse multidisciplinaire. Au plan méthodologique, cette thèse est structurée autour de quatre études de cas locales qui ont subi des menaces de restructurations. Cette collecte a été effectuée dans deux pays (la France et le Canada) et dans un secteur particulier (les équipementiers automobiles). Trois sources qualitatives forment le cœur empirique de cette thèse : des statistiques descriptives, des documents de sources secondaires et des entretiens semi-dirigés (44), principalement avec des acteurs syndicaux. L’analyse intra et inter régime national éclaire plusieurs aspects de la question des stratégies syndicales en contexte de restructurations. Les principales contributions de cette thèse touchent : 1. l’impact des facteurs relationnels et des ressources de pouvoir développées par les syndicats locaux sur les structures d’opportunités institutionnelles; 2. l’importance des aspects « cognitifs » et d’envisager le pouvoir de manière multi-niveaux; 3. l’importance de l’encastrement social et des dynamiques relationnelles entre syndicats et patronats; 4. l’influence de la concurrence internationale/nationale/régionale/locale dans le secteur des équipementiers automobiles; et 5. l’importance des arbitrages et des relations entre les acteurs de l’entreprise par rapport à la théorie de la contingence pour comprendre les marges structurelles des syndicats locaux. Notre recherche invite les acteurs sociaux à repenser leur action dans le cadre des restructurations. En particulier, les syndicats locaux se doivent d’explorer de nouveaux répertoires stratégiques pour répondre aux nombreux défis que posent le changement économique et les restructurations.

Information fusion in the immune system

Biologically-inspired methods such as evolutionary algorithms and neural networks are proving useful in the field of information fusion. Artificial immune systems (AISs) are a biologically-inspired approach which take inspiration from the biological immune system. Interestingly, recent research has shown how AISs which use multi-level information sources as input data can be used to build effective algorithms for realtime computer intrusion detection. This research is based on biological information fusion mechanisms used by the human immune system and as such might be of interest to the information fusion community. The aim of this paper is to present a summary of some of the biological information fusion mechanisms seen in the human immune system, and of how these mechanisms have been implemented as AISs.

Gestão de políticas públicas intersetoriais : uma análise da política nacional de promoção da saúde

Mestrado (dissertação)—Universidade de Brasília, Faculdade de Ciências da Saúde, Programa de Pós-Graduação em Saúde Coletiva, 2015.

A Retrospective-Longitudinal Examination of the Relationship between Apportionment of Seat Time in Community-College Algebra Courses and Student Academic Performance

During the past decade, there has been a dramatic increase by postsecondary institutions in providing academic programs and course offerings in a multitude of formats and venues (Biemiller, 2009; Kucsera & Zimmaro, 2010; Lang, 2009; Mangan, 2008). Strategies pertaining to reapportionment of course-delivery seat time have been a major facet of these institutional initiatives; most notably, within many open-door 2-year colleges. Often, these enrollment-management decisions are driven by the desire to increase market-share, optimize the usage of finite facility capacity, and contain costs, especially during these economically turbulent times. So, while enrollments have surged to the point where nearly one in three 18-to-24 year-old U.S. undergraduates are community college students (Pew Research Center, 2009), graduation rates, on average, still remain distressingly low (Complete College America, 2011). Among the learning-theory constructs related to seat-time reapportionment efforts is the cognitive phenomenon commonly referred to as the spacing effect, the degree to which learning is enhanced by a series of shorter, separated sessions as opposed to fewer, more massed episodes. This ex post facto study explored whether seat time in a postsecondary developmental-level algebra course is significantly related to: course success; course-enrollment persistence; and, longitudinally, the time to successfully complete a general-education-level mathematics course. Hierarchical logistic regression and discrete-time survival analysis were used to perform a multi-level, multivariable analysis of a student cohort (N = 3,284) enrolled at a large, multi-campus, urban community college. The subjects were retrospectively tracked over a 2-year longitudinal period. The study found that students in long seat-time classes tended to withdraw earlier and more often than did their peers in short seat-time classes (p < .05). Additionally, a model comprised of nine statistically significant covariates (all with p-values less than .01) was constructed. However, no longitudinal seat-time group differences were detected nor was there sufficient statistical evidence to conclude that seat time was predictive of developmental-level course success. A principal aim of this study was to demonstrate—to educational leaders, researchers, and institutional-research/business-intelligence professionals—the advantages and computational practicability of survival analysis, an underused but more powerful way to investigate changes in students over time.

Network Construction and Graph Theoretical Analysis of Functional Language Networks in Pediatric Epilepsy

This dissertation introduces a new approach for assessing the effects of pediatric epilepsy on the language connectome. Two novel data-driven network construction approaches are presented. These methods rely on connecting different brain regions using either extent or intensity of language related activations as identified by independent component analysis of fMRI data. An auditory description decision task (ADDT) paradigm was used to activate the language network for 29 patients and 30 controls recruited from three major pediatric hospitals. Empirical evaluations illustrated that pediatric epilepsy can cause, or is associated with, a network efficiency reduction. Patients showed a propensity to inefficiently employ the whole brain network to perform the ADDT language task; on the contrary, controls seemed to efficiently use smaller segregated network components to achieve the same task. To explain the causes of the decreased efficiency, graph theoretical analysis was carried out. The analysis revealed no substantial global network feature differences between the patient and control groups. It also showed that for both subject groups the language network exhibited small-world characteristics; however, the patient’s extent of activation network showed a tendency towards more random networks. It was also shown that the intensity of activation network displayed ipsilateral hub reorganization on the local level. The left hemispheric hubs displayed greater centrality values for patients, whereas the right hemispheric hubs displayed greater centrality values for controls. This hub hemispheric disparity was not correlated with a right atypical language laterality found in six patients. Finally it was shown that a multi-level unsupervised clustering scheme based on self-organizing maps, a type of artificial neural network, and k-means was able to fairly and blindly separate the subjects into their respective patient or control groups. The clustering was initiated using the local nodal centrality measurements only. Compared to the extent of activation network, the intensity of activation network clustering demonstrated better precision. This outcome supports the assertion that the local centrality differences presented by the intensity of activation network can be associated with focal epilepsy.