Contributions to Time Series Classification: Meta-Learning and Explainability

This thesis includes 3 contributions of different types to the area of supervised time series classification, a growing field of research due to the amount of time series collected daily in a wide variety of domains. In this context, the number of methods available for classifying time series is increasing, and the classifiers are becoming more and more competitive and varied. Thus, the first contribution of the thesis consists of proposing a taxonomy of distance-based time series classifiers, where an exhaustive review of the existing methods and their computational costs is made. Moreover, from the point of view of a non-expert user (even from that of an expert), choosing a suitable classifier for a given problem is a difficult task. The second contribution, therefore, deals with the recommendation of time series classifiers, for which we will use a meta-learning approach. Finally, the third contribution consists of proposing a method to explain the prediction of time series classifiers, in which we calculate the relevance of each region of a series in the prediction. This method of explanation is based on perturbations, for which we will consider specific and realistic transformations for the time series.BES-2016-07689

Knowledge modelling of emerging technologies for sustainable building development

In the quest for improved performance of buildings and mitigation of climate change, governments are encouraging the use of innovative sustainable building technologies. Consequently, there is now a large amount of information and knowledge on sustainable building technologies over the web. However, internet searches often overwhelm practitioners with millions of pages that they browse to identify suitable innovations to use on their projects. It has been widely acknowledged that the solution to this problem is the use of a machine-understandable language with rich semantics - the semantic web technology. This research investigates the extent to which semantic web technologies can be exploited to represent knowledge about sustainable building technologies, and to facilitate system decision-making in recommending appropriate choices for use in different situations. To achieve this aim, an exploratory study on sustainable building and semantic web technologies was conducted. This led to the use of two most popular knowledge engineering methodologies - the CommonKADS and "Ontology Development 101" in modelling knowledge about sustainable building technology and PV -system domains. A prototype system - Photo Voltaic Technology ONtology System (PV -TONS) - that employed sustainable building technology and PV -system domain knowledge models was developed and validated with a case study. While the sustainable building technology ontology and PV -TONS can both be used as generic knowledge models, PV -TONS is extended to include applications for the design and selection of PV -systems and components. Although its focus was on PV -systems, the application of semantic web technologies can be extended to cover other areas of sustainable building technologies. The major challenges encountered in this study are two-fold. First, many semantic web technologies are still under development and very unstable, thus hindering their full exploitation. Second, the lack of learning resources in this field steepen the learning curve and is a potential set-back in using semantic web technologies

Impact on soil chemistry of atmospheric sulfur fallout near Arnot coal-fired power station, in the Eastern Transvaal highveld region, South Africa

Includes bibliographical references.The objective of the study was to evaluate the potential impact of atmospheric sulfur deposition on the soils surrounding Arnot power station. In particular, the study focused on the relationship between sulfur and organic carbon (OC) and on the various pools of sulfur in the soil. A representative selection of collected soil samples was characterized both physically and chemically in the laboratory. In addition to the representative soils sampled in 2000, archived soils sampled in 1996 and 1999 from the same area were included in some of the chemical analyses

Drug Resistance in Mycobacterium Tuberculosis: An Investigation of Drug Transporter P-glycoprotein and an Evaluation of Improved Diagnosis of Drug Resistant Tuber- culosis in Cameroonian Pulmonary Tuberculosis Patients.

Ph.D. Thesis. University of Hawaiʻi at Mānoa 2017

Contributions to Time Series Classification: Meta-Learning and Explainability

141 p.La presente tesis incluye 3 contribuciones de diferentes tipos al área de la clasificación supervisada de series temporales, un campo en auge por la cantidad de series temporales recolectadas día a día en una gran variedad en ámbitos. En este contexto, la cantidad de métodos disponibles para clasificar series temporales es cada vez más grande, siendo los clasificadores cada vez más competitivos y variados. De esta manera, la primera contribución de la tesis consiste en proponer una taxonomía de los clasificadores de series temporales basados en distancias, donde se hace una revisión exhaustiva de los métodos existentes y sus costes computacionales. Además, desde el punto de vista de un/a usuario/a no experto/a (incluso desde la de un/a experto/a), elegir un clasificador adecuado para un problema concreto es una tarea difícil. En la segunda contribución, por tanto, se aborda la recomendación de clasificadores de series temporales, para lo que usaremos un enfoque basado en el meta-aprendizaje. Por último, la tercera contribución consiste en proponer un método para explicar la predicción de los clasificadores de series temporales, en el que calculamos la relevancia de cada región de una serie en la predicción. Este método de explicación está basado en perturbaciones, para lo que consideraremos transformaciones específicas y realistas para las series temporales

Tick-borne pathogens in African cattle – novel molecular tools for diagnostics in epizootiology and the genetics of resistance

Zecken-übertragene Pathogene gehören zu den schädlichsten Mikroorganismen, die für Verluste bei der Tierhaltung verantwortlich sind, mit einer erheblichen Bedrohung für die menschliche Bevölkerung. Ihr Nachweis mittels Blutausstrich oder Serologie erlaubt eher die Bestimmung einzelner Arten, während Ko-infektionen eher die Regel sind. Einschränkungen ergeben sich insbesondere in Laboren mit begrenzten Ressourcen und ohne nachhaltige Kapazität. Die vorliegende Arbeit beschäftigt sich mit der Identifizierung von 4 Gruppen von TBPs in Nordkamerun (Ehrlichien, Rickettsien, Spirochäten und Piroplasmen), wobei sieben Erstnachweise von Krankheitserregern in Rinderpopulationen (Borrelia theileri, Theileria mutans, T. velifera, Anaplasma platys, Anaplasma sp. ‘Hadesa’) in Kamerun sind, einschließlich den weltweiten Erstnachweisen von Rickettsia felis und Ehrlichia canis im Rind. Bei mehr als 80% (1123/1260, 89.1%) der untersuchten infizierten Rinder wurden mindestens zwei der vier untersuchten Genusgruppen (903/1123, 80.4%) von Krankheitserregern nachgewiesen, was die Einschränkung konventioneller Methoden unterstreicht. Über die Plattform eines kommerziellen Biochip-Anbieters (Chipron® in Berlin) wurde ein neuartiges Chip-basiertes Diagnostik-Array entwickelt. Dieses PCR-basierte Tool ermöglicht die gleichzeitige Identifizierung von fünf Erreger-Gattungen, einschließlich neuer Arten, im Blut mehrfach befallener Rinder. Deutlich mehr Krankheitserreger ließen sich so bei einer erhöhten Spezifität und Sensitivität nachweisen. Das LCD-Array kann problemlos in kleinen Veterinärlaboratorien in endemischen Ländern einschließlich Afrikas eingesetzt werden. Die häufigen Mischinfektionen mit je nach Region und Rinderrasse unterschiedlicher Zusammensetzung von Erregern werden zusätzlich von Umweltfaktoren beeinflusst (χ2, regression, p< 0,05). Unterschiedliche Reaktionen zwischen Individuen und Rassen aus derselben Umgebung motivierten den Test auf Heritabilität. Niedrige bis moderate (h_(obs.)^2=0.1 and h_(liab.)^2=0.6) Erbanlagen beobachtet, was eine genomische Grundlage für das Merkmal der Resistenz gegen Zecken-übertragene Pathogene darstellt. Dieses Ergebnis bestätigt die Möglichkeit einer Verbesserung der Resistenz durch Züchtung. Die genomweite Analyse erwies die quantitative Natur der Merkmale und verwies auf potentiell assoziierte genomische Regionen, von denen eine noch nicht in der Literatur beschrieben wurde. Erweiterte Analysen und eine größere Stichprobengröße wären nötig, um die Rinder Rassen besser zu charakterisieren (Feinkartierung von Lozi unter natürlicher Selektion und Allel-Fixierung).Les agents pathogènes transmis par les tiques comptent parmi les micro-organismes les plus nocifs responsables des pertes et de la détérioration des élevages, avec une menace importante pour la population humaine. Leur détection par frottis sanguin ou sérologie est plus susceptible de permettre l'identification d'espèces individuelle, alors que les co-infections sont plus fréquentes. Les contraintes sont tangibles dans les laboratoires aux ressources limitées et aux capacités non-durables. La présente thèse fait état de l'identification de sept agents pathogènes décris pour la première fois dans le cheptel bovin du Cameroun (Borrelia theileri, Theileria mutans, T. velifera, Anaplasma platys, Anaplasma sp. ‘Hadesa’) y compris ceux identifiés pour la première fois dans l'hôte bovin (Rickettsia felis et Ehrlichia canis). Plus de 80% de (1123/1260, 89.1%) la population infectée étudiée était co-infectée par au moins deux groupes des genres (903/1123, 80.4%) des agents pathogènes étudiés, ce qui souligne les limites des méthodes d'identification d'un seul agent pathogène précédemment utilisées. Sur la base de ces contraintes, une nouvelle matrice de diagnostic a été mise au point, grâce à la plate-forme du fournisseur commercial de biochip Chipron® à Berlin, en Allemagne. L'outil (LCD-array) basé sur la PCR a permis l'identification simultanée d'échantillons co-infectés, y compris les nouvelles espèces. Il a également permis d'identifier un plus grand nombre de microorganismes en état de co-infection avec une spécificité et une sensibilité accrues. Cet outil peut facilement être utilisé dans des laboratoires vétérinaires à capacité réduite dans les pays endémiques d'Afrique et d’ailleurs. Il a été démontré que la co-infection ainsi que la combinaison de pathogènes responsables diffèrent selon les zones climatiques et les populations bovines, influencées par des facteurs environnementaux (χ2, régression). Des réponses différentes entre individus et espèces (p< 0.05) d'un même environnement ont motivé le test des valeurs d'héritabilité. Des héritabilités faibles à modérées ont été décelées (h_(obs.)^2=0.1 and h_(liab.)^2=0.6), impliquant un fondement génétique du caractère de résistance. Ce résultat confirme la possibilité d'amélioration des facultés d’adaptation du bétail par gestion du système de production animale. Les analyses génétiques ont révélé les portions du génome responsables des phénotypes variés. Des analyses approfondies sur un plus grand échantillon seront nécessaires pour une différenciation des populations par représentation précise des loci sous sélection naturelle.Tick-borne pathogens are among the most harmful micro-organisms responsible for losses in animal husbandry, with a significant threat to the human population. Their detection by blood smear or serology is more likely to allow the identification of individual species, whereas co-infections are more common. Limitations arise especially in laboratories with limited resources and without sustainable capacities. The present thesis presents the identification of seven organisms in the cattle population from Cameroon for the first time (Borrelia theileri, Theileria mutans, T. velifera, Anaplasma platys, Anaplasma sp. ‘Hadesa’) including the first published reports of Rickettsia felis and Ehrlichia canis in cattle worldwide. More than 80% of the infected studied population (1123/1260, 89.1%) were found being co-infected with at least two of the four studied groups of genera (903/1123, 80.4%), highlighting the caveats of the predominating single pathogen identification approach. Based on those observed limitations, a novel chip-based diagnostic array was developed through the platform of the commercial biochip manufacturer Chipron® in Berlin, Germany. The PCR-based tool allowed the simultaneous identification of co-infected samples of five genera, including novel species. Moreover, the array allowed the identification of significantly more pathogens in co-infection with increased specificity and sensitivity compared to traditional Sanger sequencing. This LCD-array can be easily implemented in small veterinary laboratories in endemic countries of Africa and elsewhere. The co-infection status and pathogen combinations was proven to differ between climatic zones and cattle populations, and being influenced by environmental factors (χ2, regression). Different responses between individuals and breeds (p< 0.05) from the same environment motivated the test for heritability values. The observed low to moderate heritability based on genotyping dataset (h_(obs.)^2=0.1 and h_(liab.)^2=0.6) implied a genomic foundation of the trait of resistance to tick pathogens. More importantly, this result confirmed the possibility of improvement by breeding, which may be implemented as a control measure. The genome-wide analysis revealed the quantitative nature of the traits of resistance, exposing putative associated genomic regions with one of them not yet reported in the literature. Extended analyses and larger sample size will be advantageous for population differentiation and breed improvement through fine mapping of loci under natural selection and allele fixation related to resistance and susceptibility traits

Dynamical Evolution of the Coffee Berry Borer, Hypothenemus Hampei

In this paper, we propose a mathematical delay model that can describe the dynamics of the co?ee berry borer, Hypothenemus hampei. We propose a model include di?erent delays which are important for the life cycle of Hypothenemus hampei. The obtained model is completely analysed and we present a numerical simulation in order to validate the theoretical results

A state-of-the-art review of built environment information modelling (BeIM)

Elements that constitute the built environment are vast and so are the independent systems developed to model its various aspects. Many of these systems have been developed under various assumptions and approaches to execute functions that are distinct, complementary or sometimes similar. Also, these systems are ever increasing in number and often assume similar nomenclatures and acronyms thereby exacerbating the challenges of understanding their peculiar functions, definitions and differences. The current societal demand to improve sustainability performance through collaboration, whole-systems and through-life thinking, is driving the need to integrate independent systems associated with different aspects and scales of the built environment to deliver smart solutions and services that improve the wellbeing of citizens. The contemporary object-oriented digitization of real world elements appears to provide a leeway for amalgamating modelling systems of various domains in the built environment which we termed as built environment information modelling (BeIM). These domains included Architecture, Engineering, Construction and Urban Planning and Design. Applications such as Building Information Modelling, Geographic Information Systems and 3D City Modelling systems are now being integrated for city modelling purposes. The various works directed at integrating these systems are examined revealing that current research efforts on integration fall into three categories: (1) data/file conversion systems, (2) semantic mapping systems and (3) the hybrid of both. The review outcome suggests that a good knowledge of these domains and how their respective systems operate is vital to pursuing holistic systems integration in the built environment