Learning representations for Information Retrieval

La recherche d'informations s'intéresse, entre autres, à répondre à des questions comme: est-ce qu'un document est pertinent à une requête ? Est-ce que deux requêtes ou deux documents sont similaires ? Comment la similarité entre deux requêtes ou documents peut être utilisée pour améliorer l'estimation de la pertinence ? Pour donner réponse à ces questions, il est nécessaire d'associer chaque document et requête à des représentations interprétables par ordinateur. Une fois ces représentations estimées, la similarité peut correspondre, par exemple, à une distance ou une divergence qui opère dans l'espace de représentation. On admet généralement que la qualité d'une représentation a un impact direct sur l'erreur d'estimation par rapport à la vraie pertinence, jugée par un humain. Estimer de bonnes représentations des documents et des requêtes a longtemps été un problème central de la recherche d'informations. Le but de cette thèse est de proposer des nouvelles méthodes pour estimer les représentations des documents et des requêtes, la relation de pertinence entre eux et ainsi modestement avancer l'état de l'art du domaine. Nous présentons quatre articles publiés dans des conférences internationales et un article publié dans un forum d'évaluation. Les deux premiers articles concernent des méthodes qui créent l'espace de représentation selon une connaissance à priori sur les caractéristiques qui sont importantes pour la tâche à accomplir. Ceux-ci nous amènent à présenter un nouveau modèle de recherche d'informations qui diffère des modèles existants sur le plan théorique et de l'efficacité expérimentale. Les deux derniers articles marquent un changement fondamental dans l'approche de construction des représentations. Ils bénéficient notamment de l'intérêt de recherche dont les techniques d'apprentissage profond par réseaux de neurones, ou deep learning, ont fait récemment l'objet. Ces modèles d'apprentissage élicitent automatiquement les caractéristiques importantes pour la tâche demandée à partir d'une quantité importante de données. Nous nous intéressons à la modélisation des relations sémantiques entre documents et requêtes ainsi qu'entre deux ou plusieurs requêtes. Ces derniers articles marquent les premières applications de l'apprentissage de représentations par réseaux de neurones à la recherche d'informations. Les modèles proposés ont aussi produit une performance améliorée sur des collections de test standard. Nos travaux nous mènent à la conclusion générale suivante: la performance en recherche d'informations pourrait drastiquement être améliorée en se basant sur les approches d'apprentissage de représentations.

Learning representations for Information Retrieval

La recherche d'informations s'intéresse, entre autres, à répondre à des questions comme: est-ce qu'un document est pertinent à une requête ? Est-ce que deux requêtes ou deux documents sont similaires ? Comment la similarité entre deux requêtes ou documents peut être utilisée pour améliorer l'estimation de la pertinence ? Pour donner réponse à ces questions, il est nécessaire d'associer chaque document et requête à des représentations interprétables par ordinateur. Une fois ces représentations estimées, la similarité peut correspondre, par exemple, à une distance ou une divergence qui opère dans l'espace de représentation. On admet généralement que la qualité d'une représentation a un impact direct sur l'erreur d'estimation par rapport à la vraie pertinence, jugée par un humain. Estimer de bonnes représentations des documents et des requêtes a longtemps été un problème central de la recherche d'informations. Le but de cette thèse est de proposer des nouvelles méthodes pour estimer les représentations des documents et des requêtes, la relation de pertinence entre eux et ainsi modestement avancer l'état de l'art du domaine. Nous présentons quatre articles publiés dans des conférences internationales et un article publié dans un forum d'évaluation. Les deux premiers articles concernent des méthodes qui créent l'espace de représentation selon une connaissance à priori sur les caractéristiques qui sont importantes pour la tâche à accomplir. Ceux-ci nous amènent à présenter un nouveau modèle de recherche d'informations qui diffère des modèles existants sur le plan théorique et de l'efficacité expérimentale. Les deux derniers articles marquent un changement fondamental dans l'approche de construction des représentations. Ils bénéficient notamment de l'intérêt de recherche dont les techniques d'apprentissage profond par réseaux de neurones, ou deep learning, ont fait récemment l'objet. Ces modèles d'apprentissage élicitent automatiquement les caractéristiques importantes pour la tâche demandée à partir d'une quantité importante de données. Nous nous intéressons à la modélisation des relations sémantiques entre documents et requêtes ainsi qu'entre deux ou plusieurs requêtes. Ces derniers articles marquent les premières applications de l'apprentissage de représentations par réseaux de neurones à la recherche d'informations. Les modèles proposés ont aussi produit une performance améliorée sur des collections de test standard. Nos travaux nous mènent à la conclusion générale suivante: la performance en recherche d'informations pourrait drastiquement être améliorée en se basant sur les approches d'apprentissage de représentations.

Investigation of factors driving the costs of operating the 2020 Irish power system with large-scale wind generation

The main goal of this work is to determine the true cost incurred by the Republic of Ireland and Northern Ireland in order to meet their EU renewable electricity targets. The primary all-island of Ireland policy goal is that 40% of electricity will come from renewable sources in 2020. From this it is expected that wind generation on the Irish electricity system will be in the region of 32-37% of total generation. This leads to issues resulting from wind energy being a non-synchronous, unpredictable and variable source of energy use on a scale never seen before for a single synchronous system. If changes are not made to traditional operational practices, the efficient running of the electricity system will be directly affected by these issues in the coming years. Using models of the electricity system for the all-island grid of Ireland, the effects of high wind energy penetration expected to be present in 2020 are examined. These models were developed using a unit commitment, economic dispatch tool called PLEXOS which allows for a detailed representation of the electricity system to be achieved down to individual generator level. These models replicate the true running of the electricity system through use of day-ahead scheduling and semi-relaxed use of these schedules that reflects the Transmission System Operator's of real time decision making on dispatch. In addition, it carefully considers other non-wind priority dispatch generation technologies that have an effect on the overall system. In the models developed, three main issues associated with wind energy integration were selected to be examined in detail to determine the sensitivity of assumptions presented in other studies. These three issues include wind energy's non-synchronous nature, its variability and spatial correlation, and its unpredictability. This leads to an examination of the effects in three areas: the need for system operation constraints required for system security; different onshore to offshore ratios of installed wind energy; and the degrees of accuracy in wind energy forecasting. Each of these areas directly impact the way in which the electricity system is run as they address each of the three issues associated with wind energy stated above, respectively. It is shown that assumptions in these three areas have a large effect on the results in terms of total generation costs, wind curtailment and generator technology type dispatch. In particular accounting for these issues has resulted in wind curtailment being predicted in much larger quantities than had been previously reported. This would have a large effect on wind energy companies because it is already a very low profit margin industry. Results from this work have shown that the relaxation of system operation constraints is crucial to the economic running of the electricity system with large improvements shown in the reduction of wind curtailment and system generation costs. There are clear benefits in having a proportion of the wind installed offshore in Ireland which would help to reduce variability of wind energy generation on the system and therefore reduce wind curtailment. With envisaged future improvements in day-ahead wind forecasting from 8% to 4% mean absolute error, there are potential reductions in wind curtailment system costs and open cycle gas turbine usage. This work illustrates the consequences of assumptions in the areas of system operation constraints, onshore/offshore installed wind capacities and accuracy in wind forecasting to better inform the true costs associated with running Ireland's changing electricity system as it continues to decarbonise into the near future. This work also proposes to illustrate, through the use of Ireland as a case study, the effects that will become ever more prevalent in other synchronous systems as they pursue a path of increasing renewable energy generation.

Systematic evaluation of patient-reported outcome (PRO) protocol content and reporting in UK cancer clinical trials: the EPiC study protocol

Introduction Emerging evidence suggests that patient-reported outcome (PRO)-specific information may be omitted in trial protocols and that PRO results are poorly reported, limiting the use of PRO data to inform cancer care. This study aims to evaluate the standards of PRO-specific content in UK cancer trial protocols and their arising publications and to highlight examples of best-practice PRO protocol content and reporting where they occur. The objective of this study is to determine if these early findings are generalisable to UK cancer trials, and if so, how best we can bring about future improvements in clinical trials methodology to enhance the way PROs are assessed, managed and reported. Hypothesis: Trials in which the primary end point is based on a PRO will have more complete PRO protocol and publication components than trials in which PROs are secondary end points.

Methods and analysis Completed National Institute for Health Research (NIHR) Portfolio Cancer clinical trials (all cancer specialities/age-groups) will be included if they contain a primary/secondary PRO end point. The NIHR portfolio includes cancer trials, supported by a range of funders, adjudged as high-quality clinical research studies. The sample will be drawn from studies completed between 31 December 2000 and 1 March 2014 (n=1141) to allow sufficient time for completion of the final trial report and publication. Two reviewers will then review the protocols and arising publications of included trials to: (1) determine the completeness of their PRO-specific protocol content; (2) determine the proportion and completeness of PRO reporting in UK Cancer trials and (3) model factors associated with PRO protocol and reporting completeness and with PRO reporting proportion.

Ethics and dissemination The study was approved by the ethics committee at University of Birmingham (ERN_15-0311). Trial findings will be disseminated via presentations at local, national and international conferences, peer-reviewed journals and social media including the CPROR twitter account and UOB departmental website (http://www.birmingham.ac.uk/cpro0r).

Coupling of Chemical Kinetics with Computational Fluid Dynamics in a Three-Dimensional Engine Model

The role of computer modeling has grown recently to integrate itself as an inseparable tool to experimental studies for the optimization of automotive engines and the development of future fuels. Traditionally, computer models rely on simplified global reaction steps to simulate the combustion and pollutant formation inside the internal combustion engine. With the current interest in advanced combustion modes and injection strategies, this approach depends on arbitrary adjustment of model parameters that could reduce credibility of the predictions. The purpose of this study is to enhance the combustion model of KIVA, a computational fluid dynamics code, by coupling its fluid mechanics solution with detailed kinetic reactions solved by the chemistry solver, CHEMKIN. As a result, an engine-friendly reaction mechanism for n-heptane was selected to simulate diesel oxidation. Each cell in the computational domain is considered as a perfectly-stirred reactor which undergoes adiabatic constant- volume combustion. The model was applied to an ideally-prepared homogeneous- charge compression-ignition combustion (HCCI) and direct injection (DI) diesel combustion. Ignition and combustion results show that the code successfully simulates the premixed HCCI scenario when compared to traditional combustion models. Direct injection cases, on the other hand, do not offer a reliable prediction mainly due to the lack of turbulent-mixing model, inherent in the perfectly-stirred reactor formulation. In addition, the model is sensitive to intake conditions and experimental uncertainties which require implementation of enhanced predictive tools. It is recommended that future improvements consider turbulent-mixing effects as well as optimization techniques to accurately simulate actual in-cylinder process with reduced computational cost. Furthermore, the model requires the extension of existing fuel oxidation mechanisms to include pollutant formation kinetics for emission control studies.

Probabilistic verification of satellite systems for mission critical applications

In this thesis, we present a quantitative approach using probabilistic verification techniques for the analysis of reliability, availability, maintainability, and safety (RAMS) properties of satellite systems. The subject of our research is satellites used in mission critical industrial applications. A strong case for using probabilistic model checking to support RAMS analysis of satellite systems is made by our verification results. This study is intended to build a foundation to help reliability engineers with a basic background in model checking to apply probabilistic model checking to small satellite systems. We make two major contributions. One of these is the approach of RAMS analysis to satellite systems. In the past, RAMS analysis has been extensively applied to the field of electrical and electronics engineering. It allows system designers and reliability engineers to predict the likelihood of failures from the indication of historical or current operational data. There is a high potential for the application of RAMS analysis in the field of space science and engineering. However, there is a lack of standardisation and suitable procedures for the correct study of RAMS characteristics for satellite systems. This thesis considers the promising application of RAMS analysis to the case of satellite design, use, and maintenance, focusing on its system segments. Data collection and verification procedures are discussed, and a number of considerations are also presented on how to predict the probability of failure. Our second contribution is leveraging the power of probabilistic model checking to analyse satellite systems. We present techniques for analysing satellite systems that differ from the more common quantitative approaches based on traditional simulation and testing. These techniques have not been applied in this context before. We present the use of probabilistic techniques via a suite of detailed examples, together with their analysis. Our presentation is done in an incremental manner: in terms of complexity of application domains and system models, and a detailed PRISM model of each scenario. We also provide results from practical work together with a discussion about future improvements.

Apprendre à être un Leader dans un Programme de Leadership: Perceptions, Éxpérience Préalable en Leadership et Sexe de l’Étudiant

The purpose of this study was to examine whether leadership can be learned through the Community Recreation and Leadership Training (CRLT) program and how effective the program is in terms of changing the perceptions and abilities of the students. The intentions of the researcher were to discover crucial learning moments as perceived by students and to gain insights that could lead to future improvements to enhance and enrich learning in a leadership program. To continue to be a viable program and to keep step with the demands of the recreation/leisure industry and society's wide-ranging needs, this study may help to inform the program's 'action plan' for continued success. This study employed a mixed method approach to determine how college students develop effective leadership ability in a three-year Community Recreation and Leadership Training (CRLT) college career program. First, a number of statistical tests were carried out to examine the four research questions used to guide the study. The SPSS software was used to analyze the data collected. The first research question asked how perceptions of leadership change as a result of being in a three-year leadership program. This study, using the Student Leadership Practice Inventory (SLPI), compared the five SLPI leadership dimensions by year. The SLPI was administered to all the first, second, and third year CRLT students ( N = 84). A one-way analysis of variance in participants' scores was conducted. No significant differences were revealed in any of the five dimensions of the SLPI among the first, second, and third year students at p < .05. However, two dimensions (model and encourage) approached significance and may hint at a possible influence the program is having on its students as they progress into the third year. The second research question asked whether perceptions of leadership vary by gender. Comparing the mean scores between the males and females on the five dimensions of the SLPI, no significant differences were found. The third research question asked whether prior leadership experience results in better academic performance for CRLT students in their 1st term. A one-way analysis of variance was conducted to evaluate the relationship between prior leadership experience and mean scores on academic performance. No significant correlations were found between grades and low, medium, or high levels of prior leadership experience F(2,79) = 2.67, p = .08. A correlation coefficient was also computed to determine whether there was a relationship between the Recreation Leadership I course grade and prior leadership experience. The correlation coefficient (.02) was statistically significant, r(80) = .24, p < .05. However, further studies with a larger sample size would be necessary to help determine this. The fourth question asked whether there was a correlation between students' first semester grades and their scores on the Student Leadership Practice Inventory (SLPI). Bivariate correlations (Pearson) were computed for the five SLPI dimensions with academic performance. None of the correlations using the five SLPI indicators was significant. Qualitative data was examined to discover what factors and experiences help students to assert a more effective leadership role. The study relied on content analysis of personal statements, and focus groups. Student perceptions of an effective leader, students' perceptions of their own abilities, and the strengths of the program were explored. A content analysis of the 'Personal Statements' was carried out to determine how students defined leadership prior to their having had any formal teaching in a college program. The result of the analysis of personal statements provided eight leadership categories used as an initial baseline for the study. Six focus groups (totaling N = 30) were conducted. Students responded to four key questions: how they define leadership. What is the single most effective quality of a leader? What leadership skills did they feel they had gained? How had the program helped them obtain their skills? Students credited the CRLT program with helping them develop a variety of leadership skills. Students revealed that they had gained skills such as confidence, knowledge and understanding of people's needs, and becoming more self-directed. They attributed their skill development to such things as good course design, intensive outdoor education and fieldwork courses, "hands on" learning approaches, group work, skill practice, the support they received from teachers, and encouragement they were given by their peers. A common finding among genders was defining an effective leader as someone who is "confident". However, the definition of the most important quality of a leader varied by gender. While males showed a tendency to prefer a leader being "confident," females preferred a leader being a "teacher".

Regulating Vertical Agreements: A Comparative Law & Economics analysis of Brazil and Europe

This PhD thesis discusses antitrust enforcement of anti-competitive vertical agreements in Europe and in Brazil from an institutional perspective. It considers both the evolution of the legal framework and the application of the existing policies, with the analysis of case studies. The research highlights the main challenges of the current approaches adopted by the competition authorities in these jurisdictions and formulates specific proposals for future improvements. Because the Brazilian competition rules were originally inspired by the European legal framework, this thesis also summarizes the contemporary discussions regarding comparative law and the efficiency of transplanting laws and good practices. In a Law & Economics perspective, vertical agreements have always been a paradoxical topic and constitute one of the most dynamic disputes for antitrust enforcement. The reason for that concern is the fact that those contracts among companies are complex in nature. Taking into account this background, the thesis provides an original analysis of the pro- and anti-competitive effects of vertical agreements, based on the classical literature of Law & Economics. One of the novelties of the research is the extension of the economic analysis of vertical agreements to also consider new forms of contractual abuses in the context of digital markets, such as the contractual restrictions that are being put I practice in e-commerce platforms. The international comparative approach focuses on the Brazilian and European experiences, and opens up a reflection about the policy recommendations applied to several countries with similar economic and institutional realities.

Real-time anomaly detection of gamma-ray bursts for the Cherenkov Telescope Array using deep learning

The Cherenkov Telescope Array (CTA) will be the next-generation ground-based observatory to study the universe in the very-high-energy domain. The observatory will rely on a Science Alert Generation (SAG) system to analyze the real-time data from the telescopes and generate science alerts. The SAG system will play a crucial role in the search and follow-up of transients from external alerts, enabling multi-wavelength and multi-messenger collaborations. It will maximize the potential for the detection of the rarest phenomena, such as gamma-ray bursts (GRBs), which are the science case for this study. This study presents an anomaly detection method based on deep learning for detecting gamma-ray burst events in real-time. The performance of the proposed method is evaluated and compared against the Li&Ma standard technique in two use cases of serendipitous discoveries and follow-up observations, using short exposure times. The method shows promising results in detecting GRBs and is flexible enough to allow real-time search for transient events on multiple time scales. The method does not assume background nor source models and doe not require a minimum number of photon counts to perform analysis, making it well-suited for real-time analysis. Future improvements involve further tests, relaxing some of the assumptions made in this study as well as post-trials correction of the detection significance. Moreover, the ability to detect other transient classes in different scenarios must be investigated for completeness. The system can be integrated within the SAG system of CTA and deployed on the onsite computing clusters. This would provide valuable insights into the method's performance in a real-world setting and be another valuable tool for discovering new transient events in real-time. Overall, this study makes a significant contribution to the field of astrophysics by demonstrating the effectiveness of deep learning-based anomaly detection techniques for real-time source detection in gamma-ray astronomy.

Study of the activity and enantioselectivity of alginate-based catalysts in Friedel-Crafts reactions

This thesis is part of a long-term project which aims to demonstrate for the first time that alginate gel beads can be used as chiral heterogeneous catalysts for enantioselective reactions. Alginate barium beads were prepared as previously optimized and applied to the Friedel-Crafts reaction between indoles and nitroalkenes. New substrates were tested, showing that the reaction can accommodate different nitroalkenes and indoles, affording the corresponding products with moderate yields and good enantioselectivities. However, aliphatic nitroalkenes cannot be used as they degrade under the catalytic reaction conditions. Preliminary study on the recyclability of the heterogeneous catalyst indicated a moderate stability of the catalyst, which can be used for few cycles with a slight erosion of enantioinducing power. Some directions for future improvements (storage and work-up solvent, use of ultrasonic bath) have been suggested.

Container logistic innovations in forest-energy sector: Markets, future service concepts and technical improvements

The report presents the results of the commercialization project called the Container logistic services for forest bioenergy. The project promotes new business that is emerging around overall container logistic services in the bioenergy sector. The results assess the European markets of the container logistics for biomass, enablers for new business creation and required service bundles for the concept. We also demonstrate the customer value of the container logistic services for different market segments. The concept analysis is based on concept mapping, quality function deployment process (QFD) and business network analysis. The business network analysis assesses key shareholders and their mutual connections. The performance of the roadside chipping chain is analysed by the logistic cost simulation, RFID system demonstration and freezing tests. The EU has set the renewable energy target to 20 % in 2020 of which Biomass could account for two-thirds. In the Europe, the production of wood fuels was 132.9 million solid-m3 in 2012 and production of wood chips and particles was 69.0 million solidm3. The wood-based chips and particle flows are suitable for container transportation providing market of 180.6 million loose- m3 which mean 4.5 million container loads per year. The intermodal logistics of trucks and trains are promising for the composite containers because the biomass does not freeze onto the inner surfaces in the unloading situations. The overall service concept includes several packages: container rental, container maintenance, terminal services, RFID-tracking service, and simulation and ERP-integration service. The container rental and maintenance would provide transportation entrepreneurs a way to increase the capacity without high investment costs. The RFID-concept would lead to better work planning improving profitability throughout the logistic chain and simulation supports fuel supply optimization.

Performance Analysis and Improvements for the Future Aeronautical Mobile Airport Communications System (AeroMACS)

This thesis deals with the development of the upcoming aeronautical mobile airport communications system (AeroMACS) system. We analyzed the performance of AeroMACS and we investigated potential solutions for enhancing its performance. Since the most critical results correspond to the channel scenario having less diversity1, we tackled this problem investigating potential solutions for increasing the diversity of the system and therefore improving its performance. We accounted different forms of diversity as space diversity and time diversity. More specifically, space (antenna and cooperative) diversity and time diversity are analyzed as countermeasures for the harsh fading conditions that are typical of airport environments. Among the analyzed techniques, two novel concepts are introduced, namely unequal diversity coding and flexible packet level codes. The proposed techniques have been analyzed on a novel airport channel model, derived from a measurement campaign at the airport of Munich (Germany). The introduced techniques largely improve the performance of the conventional AeroMACS link; representing thus appealing solutions for the long term evolution of the system.

An encyclopædia of agriculture : comprising the theory and practice of the valuation, transfer, laying out, improvement, and management of landed property : and the cultivation and economy of the animal and vegetable productions of agriculture, including all the latest improvements : a general history of agriculture in all countries : and a statistical view of its present state, with suggestions for its future progress in the British Isles /

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An encyclopaedia of gardening; comprising the theory and practice of horticulture, floriculture, arboriculture, and landscape-gardening, including all the latest improvements; a general history of gardening in all countries; and a statistical view of its present stat, with suggestions for its future progress, in the British Isles.

Mode of access: Internet.

Future Dementia Care in Ireland: Sharing the Evidence to Mobilise Action

A major challenge facing societies across the world today is population ageing. The fact that people are living longer and the notable improvements in the overall quality of life and well-being of older people today needs to be celebrated. However, population ageing will inevitably result in an increase in disability and a very significant increase in the incidence of age-related health problems especially Alzheimer's disease and the related dementias. Click here to download PDF 2.5mb