In contrast to large-scale earthquakes which are caused when energy is released as a result of rock failure along a fault, microseismic events are caused when human activities, such as mining or oil and gas production, change the stress distribution or the volume of a rockmass. During such processes, microseismic event location, which aims at estimating source locations accurately, is a vital component of observing, diagnosing and acting upon the dynamic indications in reservoir performance by tracking the fracturing properly. Conventional methods for microseismic event location face considerable drawbacks. For example, traveltime based methods require manual labor in traveltime picking and thus suffer from the heavy workload of human interactions and manmade errors. Migration based and waveform inversion based location methods demand large computational memory and time for simulating the wavefields, especially in face of tens of thousands of microseismic events recorded. In this thesis research, we developed an approach based on a deep CNN for the purpose of microseismic event location, which is completely automatic with no human interactions like traveltime picking and also computationally friendly due to no requirement of wavefield simulations. An example in which the network is well-trained on the synthetic data from the smooth SEAM model and tested on the true SEAM model has shown its accuracy and efficiency. Moreover, we have proved that this approach is not only feasible for the cases with a uniform receiver distribution, but also applicable to cases where the passive seismic data are acquired with an irregular spacing geometry of sensors, which makes this approach more practical in reality.

Le 16 mars 1978, à Rome, les Brigades Rouges enlèvent l’ancien président du Conseil Aldo Moro, qui sera assassiné par les terroristes après une longue séquestration. Cet épisode a fortement marqué l’histoire récente de l’Italie, mais sa lecture reste controversée en raison des zones d’ombre qui entourent les faits aujourd’hui encore, suscitant un réel besoin de compréhension des évènements. En réponse à ce besoin, des écrivains et artistes provenant de milieux différents se sont emparés au fil du temps de l’histoire d’Aldo Moro pour en donner leur propre lecture et proposer ainsi une « autre » interprétation, qui pose un regard nouveau sur les faits. Ainsi l’affaire Moro a été transformée en objet narratif au croisement entre l’histoire et la fiction. Dans cette thèse nous étudions la transformation de l’enlèvement et de l’assassinat d’Aldo Moro en événements et en récit de ces événements. Par ailleurs, nous réfléchissons au potentiel heuristique de ces réécritures en nous interrogeant sur leurs implications mémorielles. Le premier apport critique de notre travail consiste à donner une systématisation aux narrations de l’affaire Moro produites de 1978, au lendemain des événements, à 2013, trente-cinquième anniversaire de la mort de l’homme politique : romans divers et variés, pamphlets, autobiographies, livres de mémoires, pièces de théâtre, films. Ce corpus extrêmement composite constitue désormais une « macronarration transmédiatique » organique et mérite de ce fait d’être considéré dans son ensemble. Pour définir les caractéristiques de la macronarration, nous conduisons une analyse approfondie ainsi qu’un examen comparatif des textes : en ayant recours aux apports multiples de la narratologie, nous évaluons les aspects formels des réécritures de l’affaire Moro, observons la transformation d’Aldo Moro de figure historique en personnage de fiction et étudions le dialogue transmédiatique, intra- et interdisciplinaire entre les œuvres de fiction et, le cas échéant, entre ces œuvres et les discours historiographiques et journalistiques, ainsi qu’avec les témoignages de quelques-uns des protagonistes des événements. En faisant référence aux apports théoriques de l’esthétique de la réception, nous interprétons également les relations entre l’auteur, l’œuvre et le public avec l’objectif d’approfondir et de mettre à jour la question des influences réciproques entre réécritures de l’affaire Moro et imaginaire collectif. / On March 16, 1978, the Red Brigades kidnap the former President of the Council of Ministers Aldo Moro, who will be assassinated by the terrorists after a long sequestration. This episode has strongly marked the recent history of Italy, but its interpretation remains controversial because of the gray areas that still surround the facts that need clarifications. In response to this need, writers and artists from different backgrounds have looked into the history of Aldo Moro in order to cast a new light on it and give "further" interpretations. Thus the Moro case has been transformed into a narrative object at the crossroads between history and fiction. In this thesis we study the transformation of the abduction and murder of Aldo Moro into events and their narration. In addition, we reflect on the heuristic potential of these rewritings by asking about their memory implications. Our first critical contribution is to give a systematization to the narratives of the kidnap and murder of Aldo Moro produced starting from 1978, in the aftermath of events, up to 2013, the thirty-fifth anniversary of the death of the politician: novels, pamphlets, autobiographies, memoir books, plays, movies. This extremely composite corpus is by now an organic "transmediatic macro-narration" and it deserves to be considered as a whole. To define the characteristics of this macro-narration, we conduct an in-depth analysis but also a comparative examination of the texts. By resorting to the multiple contributions of narratology, we evaluate the formal aspects of the rewrites of the Moro case and, at the same time, we observe the transformation of Aldo Moro from an historical figure to a fictional character. In addition, we study the intra and interdisciplinary dialogue between works of fiction and, where appropriate, between these works and historiographical and journalistic discourses. With regard to the theoretical contributions of the aesthetics of reception, we also interpret the connections between the author, the work and the audience with the aim of deepening and updating the question of the reciprocal influences between the rewritings of the Moro case and the collective imagination.

Objectives: The study objectives were to (1) determine the types and frequency of off-label (OL) or unlicensed (UL) medications used in a pediatric emergency department (PED) and before admission, (2) describe OL/UL-associated adverse drug events (ADEs) resulting in admission to the PED and those occurring during patient care in PED, and (3) determine the outcomes of these ADEs. Methods: Medical records of patients 18 years or younger admitted to the PED over a 5-month period were reviewed. Off-label/UL use of medications was determined based on Food and Drug Administration-approved labeling. The Adverse Drug Reaction Probability Scale was used to determine ADE causality. Data were analyzed using descriptive statistics. Results: A total of 2191 patients with 6675 medication orders were evaluated. About 26.2% (n = 1712) of medication orders were considered as OL/ UL use; 70.5% (n = 1208) of these medications were ordered as part of treatment in the PED, and the remaining 29.5% (n = 504) were home medications before their PED evaluation. Inhaled bronchodilators (30.4%), antimicrobials (14.8%), and antihistamines/antiemetics (9.1%) were the most common OL/UL medication classes. The frequency of ADEs among licensed medication use was greater compared with OL/UL use by 2-fold. Reported overall rate of ADEs was 0.6% (n = 40). Of these 40 ADEs, 5 resulted from the use of an OL/UL medication, 3 from home medication use, and 2 from PED-prescribed medications. Conclusions: The frequency of reported ADEs associated with OL/UL medications was less than the frequency of ADEs from licensed medication use, with overall ADE frequency of less than 1%.

The purpose of this study was to investigate the nation branding process deployed by a host country organizing committee. Three research questions helped guide this study: (1) How does the organizing committee see the opportunity of hosting a sport-mega event (SME) as a nation branding tool? (2) What aspects of the FIFA World Cup (FWC) do people working with the organizing committee believe, create such nation branding opportunities? (3) How do event organizers leverage a nation branding legacy from the FWC? A single case study was built using 1,669 document pages, and nine semi-structured interviews and data were thematically analyzed. The study investigated relevant organizational documents and the event organizers’ perspectives to determine the nation branding processes. Results revealed the organization's approach to nation branding involved assessing their external image, creating a country narrative based on the population's characteristics and values, and depicting a unique identity by showcasing their cultural heritage to increase the attraction of the nation brand. Findings highlight that nation branding through the FWC requires the LOC’s strategic coordination through nation brand stakeholders, nation brand ambassadors, important organizations as well as the leadership of the nation in order to build brand equity.

Research shows that in a system model, when the production rate is adjusted based on the number of items in queue, the nature of the model changes from an open-loop queueing system to a closed-loop feedback control system. Service-rate adjustment can be implemented in a discrete event simulation model, but the effect of this adjustment has not been thoroughly analyzed in the literature. This research considers the design of feedback signals to generate realistic simulation models of production system behavior. A series of simulation experiments is conducted to provide practical guidance for simulation modelers on how adding a service-rate adjustment feedback loop to a queueing system affects system performance.

Headwater watersheds initiate material export to downstream environments. A nested headwater study examined the flux and source of dissolved constituents and water from a perennial stream and four ephemeral/intermittent streams in the Upper Gulf Coastal Plain, Mississippi. Water was collected during storm and baseflow conditions. Multiple linear regression was used to model constituent concentration and calculate flux. Source of water was determined using principle components analysis and end-member mixing analysis. Rain was the major source of water discharged from the ephemeral and intermittent streams, while groundwater was the major source for water discharged by the perennial stream during events. Baseflow from both stream types was dominated by groundwater sources. The perennial stream had an area weighted average yields of 10.1, 0.01, 1.0, 0.6, and 0.03 kg-1 ha-1 yr-1 of DON, NO3--N, NH4+-N, PO4-3, and DOC,respectively. This research highlights the interaction of source water and dissolved constituent flux.

No description available.

This dissertation focuses on identifying various types of anomalous information pattern in social media and news outlets. We focus on three types of anomalous information, including (1) media censorship in news outlets, which is information that should be published but is actually missing, (2) fake news in social media, which is unreliable information shown to the public, and (3) media propaganda in news outlets, which is trustworthy information but being over-populated. For the first problem, existing approaches on censorship detection mostly rely on monitoring posts in social media. However, media censorship in news outlets has not received nearly as much attention, mostly because it is difficult to systematically detect. The contributions of our work include: (1) a hypothesis testing framework to identify and evaluate censored clusters of keywords, (2) a near-linear-time algorithm to identify the highest scoring clusters as indicators of censorship, and (3) extensive experiments on six Latin American countries for performance evaluation. For the second problem, existing approaches studying fake news in social media primarily focus on topic-level modeling or prediction based on a set of aggregated features from a col- lection of posts. However, the credibility of various information components within the same topic can be quite different. The contributions of our work in this space include: (1) a new benchmark dataset for fake news research, (2) a cluster-based approach to improve instance- level prediction of information credibility, and (3) extensive experiments for performance evaluations. For the last problem, existing approaches to media propaganda detection primarily focus on investigating the pattern of information shared over social media or evaluation from domain experts. However, these approaches cannot be generalized to a large-scale analysis of media propaganda in news outlets. The contributions of our work include: (1) non- parametric scan statistics to identify clusters of over-populated keywords, (2) a near-linear-time algorithm to identify the highest scoring clusters as indicators of propaganda, and (3) extensive experiments on two Latin American countries for performance evaluation. / Doctor of Philosophy / Nowadays, massive information is available through a variety of social media platforms. However, the information accessed by the audience might be not exactly correct in different ways. In order for the audience being able to get access to the correct information, we develop various machine learning algorithms to uncover the anomalous information pattern in social media and explain the reason behind this behavior. Our algorithms can be used to learn what different information patterns can exist in the open data source.

In this Thesis I will examine technology adoption by analyzing how different organizations come to interpret a technology as a specific kind of innovation based on a certain set of criteria. The kind of innovation an organization interprets a technology to be effects how quickly the organization will adopt that technology. To analyze how organizations come to interpret technologies as a specific kind of innovation I will construct a model. I will utilize the Actor-Network Theory from Science and Technology Studies as the framework to combined theories regarding technology adoption from other disciplines. This new model of technology adoption will be able to address the individual weakness of each theory that I use, and at the same time build on the strengths of the Actor-Network Theory. I will conclude my thesis by testing my new model using an event study from econometrics. Using the surrogate measure of the stock market to represent consumers, the event study will allow me to gauge if the kind of innovation a technology is interpreted as affects the rate of its adoption. / Master of Science

Event detection is a critical challenge in many fields like video surveillance, social graph analysis, and multimedia processing. Furthermore, events are “structured” objects involv ing multiple components like the event type, the participants with their roles, and the atomic events in which it decomposes. Therefore, the recognition of an event is not only limited to recognize the type of the event and when it happened, but it involves solving a set of simple tasks. Exploiting background knowledge about events and their relations could then be beneficial for event detection. In the last years, neuro-symbolic integration has been proposed to merge the strengths and overcome the drawbacks of both symbolic and neural worlds. As a consequence, different neuro-symbolic frameworks, which com bine low-level perception of neural networks with a symbolic layer, encoding prior domain knowledge (usually defined in terms of logical rules), have been applied to solve different atemporal tasks. In this thesis, we want to investigate the application of the neuro-symbolic paradigm for event detection. This would also provide a better insight into the strengths and limitations of neuro-symbolic towards tasks involving time.