57 research outputs found
Subsidia: Tools and Resources for Speech Sciences
Este libro, resultado de la colaboración de investigadores expertos en sus respectivas áreas, pretende ser una ayuda a la comunidad cientÃfica en tanto en cuanto recopila y describe una serie de materiales de gran utilidad para seguir avanzando en la investigació
Top 10 technology opportunities : tips and tools
https://egrove.olemiss.edu/aicpa_guides/1610/thumbnail.jp
Storytelling and mobile media: narratives for the mobile phone
The mobile phone epitomises the ability of media convergence to promote a synthesis of multiple digital technologies within the body of one portable device. In order to develop a methodology for the design and production of mobile narratives, it is necessary to examine and identify factors that may influence the creative possibilities for artists working in mobile media. The mobile phone is a ubiquitous portable device capable of generating and displaying narrative content in the form of voice communications, text, images and video. It could be said that hybrid devices such as the mobile phone can create hybrid narratives. It is the aim of this exegesis to outline the theories, concepts and artistic practices that inform the design, production and display of narrative content that utilizes the potential of the mobile phone as a tool for storytelling. Over the course of this exegesis I will examine examples of media projects that exploit the creative potential of portable networked media devices. I will also look to contemporary narrative theory, in particular Mieke Bal’s theories on reframing and narrative gaps as a reference point for the design of my mobile phone narratives. A critical reflection on each of my narrative experiments that accompany this exegesis will outline the key concepts and creative strategies employed in the planning and production of my narrative experiments. This research is a contribution towards the existing body of research in the area of developing narratives for mobile media devices and will potentially act as a guide for future research
Research reports: 1985 NASA/ASEE Summer Faculty Fellowship Program
A compilation of 40 technical reports on research conducted by participants in the 1985 NASA/ASEE Summer Faculty Fellowship Program at Marshall Space Flight Center (MSFC) is given. Weibull density functions, reliability analysis, directional solidification, space stations, jet stream, fracture mechanics, composite materials, orbital maneuvering vehicles, stellar winds and gamma ray bursts are among the topics discussed
PhysioSim – A Full Hard- And Software Physiological Simulation Environment Applying A Hybrid Approach Based On Hierarchical Modeling Using Algebraic And Differential Systems and Dynamic Bayesian Networks
A system for physiological modeling and simulation is presented. The architecture is considering hardware and software support for real-time physiological simulators, which are very important for medical education and risk management. In contrary to other modeling methods, in this work the focus is to provide maximal modeling flexibility and extensibility. This is provided on the one hand by a hierarchical modeling notation in XML and on other hand by extending current methods by dynamic stochastic system modeling. Dynamic Bayesian Networks as well as deterministic system modeling by systems of algebraic and differential equations lead towards a sophisticated environment for medical simulation. Specific simulations of haemodynamics and physiological based pharmacokinetics and pharmacodynamics are performed by the proposed methods, demonstrating the applicability of the approaches. In contrary to physiological modeling and analysis tools, for an educational simulator, the models have to be computed in real-time, which requires extensive design of the hardware and software architecture. For this purpose generic and extensible frameworks have been suggested and realized. All the components together lead to a novel physiological simulator environment, including a dummy, which emulates ECG, SaO2 and IBP vital signals in addition to software signal simulation. The modeling approaches with DBN are furthermore analyzed in the domains of psychological and physiological reasoning, which should be integrated into a common basis for medical consideration. Furthermore the system is used to show new concepts for dependable medical data monitoring, which are strongly related to physiological and psychological simulations
Tuning of boundary conditions parameters for hemodynamics simulation using patient data
This thesis describes an engineering workflow, which allows specification of boundary conditions and 3D simulation based on clinically available patient-specific data. A review of numerical models used to describe the cardiovascular system is provided, with a particular focus on the clinical target disease chosen for the toolkit, aortic coarctation. Aorta coarctation is the fifth most common congenital heart disease, characterized by a localized stenosis of the descending thoracic aorta. Current diagnosis uses invasive pressure measurement with rare but potential complications. The principal objective of this work was to develop a tool that can be translated into the clinic, requiring minimum operator input and time, capable of returning meaningful results from data typically acquired in clinical practice.
Linear and nonlinear 1D modelling approaches are described, tested against full 3D solutions derived for idealized geometries of increasing complexityand for a patient-specific aortic coarctation. The 1D linear implementation is able to represent the fluid dynamic in simple idealized benchmarks with a limited effort in terms of computational time, but in a more complex case, such as a mild aortic coarctation, it is unable to predict well 3D fluid dynamic features. On the other side, the 1D nonlinear implementation showed a good agreement when compared to 3D pressure and flow waveforms, making it suitable to estimate outflow boundary conditions for subject-specific models.
A cohort of 11 coarctation patients was initially used for a preliminary analysis using 0D models of increasing complexity to examine parameters derived when tuning models of the peripheral circulation. The first circuit represents the aortic coarctation as a nonlinear resistance, using the Bernoulli pressure drop equation, without considering the effect of downstream circulation. The second circuit include a peripheral resistance and compliance, and separate ascending and descending aortic pressure responses. In the third circuit a supra-aortic Windkessel model was added in order to include the supra-aortic circulation. The analysis detailed represents a first attempt to assess the interaction between local aortic haemodynamics and subject-specific parameterization of windkessel representations of the peripheral and supra-aortic circulation using clinically measured data. From the analysis of these 0D models, it is clear that the significance of the coarctation becomes less from the simple two resistance model to the inclusion of both the peripheral and supra-aortic circulation. These results provide a context within which to interpret outcomes of the tuning process reported for a more complex model of aortic haemodynamics using 1D and 3D model approaches.
Earlier developments are combined to enable a multi-scale modelling approach to simulate fluid-dynamics. This includes non-linear 1D models to derive patient-specific parameters for the peripheral and supra-aortic circulation followed by transient analysis of a coupled 3D/0D system to estimate the coarctation pressure augmentation. These predictions are compared with invasively measured catheter data and the influence of uncertainty in measured data on the tuning process is discussed. This study has demonstrated the feasibility of constructing a workflow using non-invasive routinely collected clinical data to predict the pressure gradient in coarctation patients using patient specific CFD simulation, with relatively low levels of user interaction required. The results showed that the model is not suitable for the clinical use at this stage, thus further work is required to enhance the tuning process to improve agreement with measured catheter data.
Finally, a preliminary approach for the assessment of change in haemodynamics following coarctation repair, where the coarctation region is enlarged through a virtual intervention process. The CFD approach reported can be expanded to explore the sensitivity of the peak ascending aortic pressure and descending aortic flow to the aortic diameter achieved following intervention, such an analysis would provide guidance for surgical intervention to target the optimal diameter to restore peripheral perfusion and reduce cerebral hypertension
RRS Discovery Cruise DY111, 2 December 2019 – 9 January 2020. Punta Arenas, Chile – Punta Arenas, Chile. CUSTARD: Carbon Uptake and Seasonal Traits in Antarctic Remineralisation Depth
The CUSTARD project examines how seasonal changes in nutrient availability for phytoplankton, at a key junction of the global ocean circulation, influence how long carbon is trapped in the ocean rather than escaping to the atmosphere as carbon dioxide.
If we want to understand the role of the Southern Ocean in regulating global climate we need to understand both how much carbon is used to make phytoplankton at the ocean surface and how deep this material penetrates into the ocean interior; the ‘remineralisation depth’. The objective of CUSTARD is to make new observations of the remineralisation depth and its controls in an important, yet remote, region of the Southern Ocean, using a combination of gliders, a mooring, sophisticated new sensors and a process cruise. The observations will be combined with modelling to determine the key processes regulating carbon uptake in the Southern Ocean.
CUSTARD fieldwork began with DY096 in Nov-Dec 2019. A surface mooring and two gliders were deployed at the OOI site (54.42 S 89 W) to make observations throughout the year. One glider was lost early on and the second had to be recovered in November 2019 after it became trapped at the surface. The mooring was recovered on DY112.
DY111 was a process cruise immediately prior to the mooring recovery cruise (DY112), to allow a more detailed study of the biogeochemistry of the site at the key spring bloom period. Objectives were: to deploy two other gliders (just for the duration of the cruise); to deploy 6 BGC ARGO floats on behalf of the SOCCOM project; to do multiple visits to 3 sites along 89 W (OOI, TN at 57S and TS at 60S); and to carry out a full depth CTD transect between OOI and TS at 1 degree latitude resolution. All objectives were met, though one glider had to be recovered immediately after deployment due to a leak. Additionally, a modest spatial survey was carried out collecting underway data and samples along a grid-pattern extending 90km west of 89W, to assess upstream properties and gradients.
The cruise was exceptionally fortunate both in weather and in coinciding strongly with the spring bloom spanning the area.
CUSTARD (NE/K015613/1) is part of the NERC Role of the Southern Ocean in the Earth System (RoSES) programme. Additional work was funded by the NERC Bridging International Activity and Related Research Into the Twilight Zone (NE/ S00842X/1)
ECG Classification with an Adaptive Neuro-Fuzzy Inference System
Heart signals allow for a comprehensive analysis of the heart. Electrocardiography (ECG or EKG) uses electrodes to measure the electrical activity of the heart. Extracting ECG signals is a non-invasive process that opens the door to new possibilities for the application of advanced signal processing and data analysis techniques in the diagnosis of heart diseases. With the help of today’s large database of ECG signals, a computationally intelligent system can learn and take the place of a cardiologist. Detection of various abnormalities in the patient’s heart to identify various heart diseases can be made through an Adaptive Neuro-Fuzzy Inference System (ANFIS) preprocessed by subtractive clustering. Six types of heartbeats are classified: normal sinus rhythm, premature ventricular contraction (PVC), atrial premature contraction (APC), left bundle branch block (LBBB), right bundle branch block (RBBB), and paced beats. The goal is to detect important characteristics of an ECG signal to determine if the patient’s heartbeat is normal or irregular. The results from three trials indicate an average accuracy of 98.10%, average sensitivity of 94.99%, and average specificity of 98.87%. These results are comparable to two artificial neural network (ANN) algorithms: gradient descent and Levenberg Marquardt, as well as the ANFIS preprocessed by grid partitioning
Data-Driven, Personalized Usable Privacy
We live in the "inverse-privacy" world, where service providers derive insights from users' data that the users do not even know about. This has been fueled by the advancements in machine learning technologies, which allowed providers to go beyond the superficial analysis of users' transactions to the deep inspection of users' content. Users themselves have been facing several problems in coping with this widening information discrepancy. Although the interfaces of apps and websites are generally equipped with privacy indicators (e.g., permissions, policies, ...), this has not been enough to create the counter-effect. We particularly identify three of the gaps that hindered the effectiveness and usability of privacy indicators: - Scale Adaptation: The scale at which service providers are collecting data has been growing on multiple fronts. Users, on the other hand, have limited time, effort, and technological resources to cope with this scale. - Risk Communication: Although providers utilize privacy indicators to announce what and (less often) why they need particular pieces of information, they rarely relay what can be potentially inferred from this data. Without this knowledge, users are less equipped to make informed decisions when they sign in to a site or install an application. - Language Complexity: The information practices of service providers are buried in complex, long privacy policies. Generally, users do not have the time and sometimes the skills to decipher such policies, even when they are interested in knowing particular pieces of it. In this thesis, we approach usable privacy from a data perspective. Instead of static privacy interfaces that are obscure, recurring, or unreadable, we develop techniques that bridge the understanding gap between users and service providers. Towards that, we make the following contributions: - Crowdsourced, data-driven privacy decision-making: In an effort to combat the growing scale of data exposure, we consider the context of files uploaded to cloud services. We propose C3P, a framework for automatically assessing the sensitivity of files, thus enabling realtime, fine-grained policy enforcement on top of unstructured data. - Data-driven app privacy indicators: We introduce PrivySeal, which involves a new paradigm of dynamic, personalized app privacy indicators that bridge the risk under- standing gap between users and providers. Through PrivySeal's online platform, we also study the emerging problem of interdependent privacy in the context of cloud apps and provide a usable privacy indicator to mitigate it. - Automated question answering about privacy practices: We introduce PriBot, the first automated question-answering system for privacy policies, which allows users to pose their questions about the privacy practices of any company with their own language. Through a user study, we show its effectiveness at achieving high accuracy and relevance for users, thus narrowing the complexity gap in navigating privacy policies. A core aim of this thesis is paving the road for a future where privacy indicators are not bound by a specific medium or pre-scripted wording. We design and develop techniques that enable privacy to be communicated effectively in an interface that is approachable to the user. For that, we go beyond textual interfaces to enable dynamic, visual, and hands-free privacy interfaces that are fit for the variety of emerging technologies
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