The information age and the information society have become dominant features in the newm illennium.H owever,t heset ermsa reo ften referredt o with the youngerg enerations in mind,n eglectingth e older andm oree xperiencemd emberso f our society. This thesis focuses on the 'Grey Market' (travellers over the age of 50) who use the Internet on a regular basis - therefore also referred to as 'Silver Surfers' - and in particularf or their travel and tourism decision-makingI.t aims to identify experiences andp rocesseosf travel decision-makinga,n alyseth e impacto n the useo f the Interneta s an informations earcha s well as evaluateth e effectivenesos f the Interneti n providing informationf or particulara ndn ot mainstreamm arkets egments. The methodologye mployedi n this particularp iece of researchb uilds on positivisma s most consumerb ehaviourt heoriesd o; howevera more inductivea pproachw as taken. While relying on existingt heoriesn ewera nd lessw ell testedm ethodso f datac ollection were put to use.T he methodsw ere triangulatedu, tilising bothq uantitativea ndq ualitative research methods which complement each other in the results. An initial pilot study questionnairwe asf ollowedu p with semi-structureidn -depthi nterviewsw hich thenl edt o the completiono f the final survey,t hat was administeredb y 'e-surveying'u sing both conveniencea nd snowballs amplinga nd resultedi n 517 valid responsesfr om 'Silver Surfers' around the United Kingdom. Main findings of this thesiss how a distinct patterno f behaviourin the travel decisionmaking process of this particular market segment as well as what kind of information they were researchingo n the Internet.M ost importantly,t he respondentdso not consider themselvesto o different from other (younger)a geg roupsa nde vent houghs omeo f their informationr equirementsa re distinctive,t hey do not want to be consideredju st as 'the older consumers'.

Online decision making is a kind of machine learning problems where decisions are made in a sequential manner so as to accumulate as many rewards as possible. Typical examples include multi-armed bandit (MAB) problems where an agent needs to decide which arm to pull in each round, and network routing problems where each router needs to decide the next hop for each packet. Thompson sampling (TS) is an efficient and effective algorithm for online decision making problems. Although TS has been proposed for a long time, it was not until recent years that the theoretical guarantees for TS in the standard MAB were given. In this thesis, we first analyze the performance of TS both theoretically and practically in a special MAB called combinatorial MAB with sleeping arms and long-term fairness constraints (CSMAB-F). Then, we apply TS to a novel reactive network routing problem, called \emph{opportunistic routing without link metrics known a priori}, and use the proof techniques we developed for CSMAB-F to analyze the performance. / Graduate

The goal of this study was to build a more holistic and comprehensive look of the effects of search and decision tools (collectively known as decision aids) on the traditional consumer decision process. Specifically, how it affects the information search and alternative evaluation stages. It combined multiple models and concepts from different areas of consumer decision behavior, decision support systems, technology acceptance and task-technology fit theory. It explores how consumers use five different decision aids that are commonly found in today’s marketplace: consumer reviews, social media and electronic-word-of-mouth, comparison matrices, filter agents, and virtual assistants. The effects of these different decision aids were compared in both the information search stage and alternative evaluation stage. In information search, a 5x2 within-subject factorial study was used to determine the effects of decision aids over time (present vs. ten years ago). Two-way repeated ANOVA found that the effects of decision aids in terms of perceived usage across all decision aids have increased from that of ten years ago. Also, consistent with task-technology fit theory usage between each decision aid differed based on how well the decision aid’s capabilities matched the stage’s need. In the alternative evaluation stage, three treatments were manipulated: decision aids, task complexity (high vs. low) and step within the alternative evaluation stage of the consumer decision process (screening vs. evaluation step) in a 5x2x2 within-subject factorial design. The treatments were compared by measuring its effects on four dependent variables proposed in technology acceptance literature: perceived ease of use, perceived usefulness, trusting beliefs and intention to use. Three-way repeated ANOVA showed that consumers rely on a two-step process when faced with high task complexity, screening out alternatives based on a simple non-compensatory rule before more detailed evaluation of the remaining alternatives are evaluated. The results were also consistent with task-fit theory with decision aids differing based on how well their capabilities matched each stage. The study however couldn’t provide definitive proof of differences in the two steps within the alternative evaluation as the significance of the results varied.

Introduction : La prise de décision concernant la préservation de la fertilité dans un contexte de prise en charge urgente de cancer du sein est complexe. Les objectifs de ce travail étaient de définir les attentes et les besoins des patientes en matière d’information, de concevoir un outil d’aide à la décision en ligne et d’évaluer sa validité apparente et son influence sur le choix éclairé des patientes.Méthodologie : Trois méthodes de recherche ont été menées pour répondre aux hypothèses : un focus group de cinq patientes pour l’étude qualitative, l’élaboration d’un outil d’aide à la décision selon la méthode d’Ottawa et une étude randomisée monocentrique. Cette dernière a été menée auprès de patientes âgées de 18 à 40 ans, adressées pour préservation de la fertilité dans un contexte de cancer du sein, randomisées au sein du groupe IRIS (information standard) ou du groupe DECISIF (avec outil d’aide à la décision en ligne). La mesure du choix éclairé était évaluée selon trois critères, à l’aide d’un questionnaire : les connaissances, l’attitude, et la mise en place ou non de techniques de préservation de la fertilité.Résultats : L’étude qualitative a permis de mettre en évidence que l’information transmise aux femmes et l’annonce de l’infertilité potentielle était à parfaire. L’outil d’aide à la décision en ligne a été élaboré suivant les recommandations des patientes et des professionnels de santé impliqués qui ont confirmé sa validité apparente. En ce qui concerne l’étude quantitative, au total 125 patientes ont été inclues et randomisées dans le groupe IRIS (n=65) ou DECISIF (n=60). Il a été mis en évidence une amélioration des connaissances dans le groupe DECISIF (8.6/10 (±1.34)) par rapport au groupe IRIS (6.49/10 (±1.89)). Dans les deux groupes, les patientes ont une attitude favorable envers la préservation de la fertilité (96 %). La décision finale n’est pas influencée par l’appartenance à un groupe ou un autre. Ainsi, à l’issue de la consultation de préservation de la fertilité, 73.6 % (92/125), soit 69.2 % (45/65) des patientes du groupe IRIS et 78.3 % (47/60) des patientes du groupe DECISIF vont choisir de conserver leurs ovocytes, embryons et/ou tissu ovarien. La proportion de choix éclairé était statistiquement plus élevée dans le groupe DECISIF que dans le groupe IRIS (respectivement 75 % versus 38.5 %, p<0.001). Par ailleurs, le niveau de conflit décisionnel chez les patientes du groupe DECISIF était moins élevé que chez celles du groupe IRIS (respectivement 14.4 (±2.94) versus 15.1 (±2.18), p=0.13).Conclusion : Nous avons conçu un outil d’aide à la décision en ligne pour accompagner les femmes atteintes d’un cancer du sein dans leur prise de décision concernant la préservation de la fertilité. Notre travail de recherche a permis de valider scientifiquement cet outil qui améliore les connaissances des patientes et leur autonomie de décision sans influencer leur attitude envers la préservation de la fertilité. / Introduction: Decision-making regarding fertility preservation in the context of urgent breast cancer management is complex. The objectives of this study were to define patients' expectations and information needs, develop an online decision support tool, and assess its apparent validity and influence on patients' informed choice.Methodology: Three research methods were used to address the hypotheses: a focus group of five patients for the qualitative study, the development of a decision support tool using the Ottawa method and a randomized, single-centre study. The latter was conducted with patients aged 18 to 40 years referred for fertility preservation in the context of breast cancer, randomized to the IRIS group (standard information) or the DECISIF group (with online decision support tool). The measurement of informed choice was evaluated according to three criteria using a questionnaire: knowledge, attitude, and whether fertility preservation techniques were available.Results: The qualitative study revealed that the information provided to women and the announcement of potential infertility needed to be improved. The online decision support tool was developed based on recommendations from the patients and health professionals involved, who confirmed its apparent validity. For the quantitative study, a total of 125 patients were included and randomized to the IRIS (n=65) or DECISIF (n=60) group. Better knowledge was found in the DECISIF group (8.6/10 (±1.34)) compared to the IRIS group (6.49/10 (±1.89)). In both groups, patients had a positive attitude towards fertility preservation (96%). The final decision was not influenced by membership in one group or another. Thus, at the end of the fertility preservation consultation, 73.6% (92/125), i.e. 69.2% (45/65) of patients in the IRIS group and 78.3% (47/60) of patients in the DECISIF group, chose to keep their oocytes, embryos and/or ovarian tissue. The proportion of informed choice was statistically higher in the DECISIF group than in the IRIS group (respectively 75% versus 38.5%, p<0.001). In addition, the level of decision-making conflict among patients in the DECISIF group was lower than in the IRIS group (respectively 14.4 (±2.94) versus 15.1 (±2.18), p=0.13).Conclusion: We have developed an online decision support tool to assist women with breast cancer in making decisions about fertility preservation. We have now validated this tool, which improves patients' knowledge and decision-making autonomy without influencing their attitude towards fertility preservation.

Cette thèse s'intéresse aux architectures contenant des FPGAs reconfigurables dynamiquement et partiellement. Dans ces architectures, la complexité et la difficulté de portage des applications sont principalement dues aux connections étroites entre la gestion de la reconfiguration et le calcul lui-même. Nous proposons 1) un nouveau niveau d'abstraction, appelé gestionnaire de composants matériels (HCM) et 2) un mécanisme de communication scalable (SCM), qui permettent une séparation claire entre l'allocation d'une fonction matérielle et la procédure de reconfiguration. Cela réduit l'impact de la gestion de la reconfiguration dynamique sur le code de l'application, ce qui simplifie grandement l'utilisation des plateformes FPGA. Les application utilisant le HCM et le SCM peuvent aussi être portées de manière transparentes à des systèmes multi-FPGA et/ou multi-utilisateurs. L'implémentation de cette couche HCM et du mécanisme SCM sur des plateformes réalistes de prototypage virtuel démontre leur capacité à faciliter la gestion du FPGA tout en préservant les performances d'une gestion manuelle, et en garantissant la protection des fonctions matérielles. L'implémentation du HCM et du mécanisme SCM ainsi que leur environnement de simulation sont open-source dans l'espoir d'une réutilisation par la communauté. / This thesis shows that in FPGA-based dynamic reconfigurable architectures, the complexity and low portability of application developments are mainly due to the tight connections between reconfiguration management and computation. By proposing 1) a new abstraction layer, called Hardware Component Manager (HCM) and 2) a Scalable Communication Mechanism (SCM), we clearly separate the allocation of a hardware function from the control of a reconfiguration procedure. This reduces the dynamic reconfiguration management impact on the application code, which greatly simplifies the use of FPGA platforms. Applications using the HCM and the SCM can also be transparently ported to multi-user and/or multi-FPGA systems. The implementation of this HCM layer and the SCM mechanism on realistic simulation platforms demonstrates their ability to ease the management of FPGA flexibility while preserving performance and ensuring hardware function protection. The HCM and SCM implementations and their simulation environment are open-source in the hope of reuse by the community.

<p dir="ltr">We propose a fully online procedure to conduct statistical inference with adaptively collected data. The low-rank structure of the model parameter and the adaptivity nature of the data collection process make this task challenging: standard low-rank estimators are biased and cannot be obtained in a sequential manner while existing inference approaches in sequential decision-making algorithms fail to account for the low-rankness and are also biased. To tackle the challenges previously outlined, we first develop an online low-rank estimation process employing Stochastic Gradient Descent with noisy observations. Subsequently, to facilitate statistical inference using the online low-rank estimator, we introduced a novel online debiasing technique designed to address both sources of bias simultaneously. This method yields an unbiased estimator suitable for parameter inference. Finally, we developed an inferential framework capable of establishing an online estimator for performing inference on the optimal policy value. In theory, we establish the asymptotic normality of the proposed online debiased estimators and prove the validity of the constructed confidence intervals for both inference tasks. Our inference results are built upon a newly developed low-rank stochastic gradient descent estimator and its non-asymptotic convergence result, which is also of independent interest.</p>