Revolutions Without Revolutionaries? Social Media Networks and Regime Response in Egypt

Does the Internet change the balance of power between authoritarian regimes and their domestic opponents? The results of this case study of Egyptian digital activism suggest that the Internet has important effects on authoritarian politics, though not necessarily the kind we have come to expect from popular accounts of online activism. In this dissertation, I argue that what I call Social Media Networks can trigger informational cascades through their interaction effects with independent media outlets and on-the-ground organizers. They do so primarily through the reduction of certain costs of collective action, the transmission capabilities of certain elite nodes in social and online networks, and through changing the diffusion dynamics of information across social networks. An important secondary argument is that while states, including Egypt, have become more adept at surveillance and filtering of online activities, SMNs make it impossible for authoritarian countries to control their media environments in the way that such regimes have typically done so in the past. Case studies of media events in Egypt between 2006 and 2008 explain how SMNs undermine the process of authoritarian media control and why the independent press is critical for claims-making and the building of shared meaning. However, the power of SMNs is not capable of challenging the entrenched repressive capacity of determined states, nor can SMNs be substituted for the difficult work of grassroots organizing. I arrive at this conclusion through a case study of the April 6th Youth Movement, which staged nearly identical strikes on April 6th, 2008, and April 6th, 2009, with divergent results. Therefore, the dissertation concludes that even though SMNs may lead to richer information environments with increased capacity for organizing, the technologies themselves are not determinative of political outcomes. Finally, by studying the use of digital tools by Muslim Brothers and Baha’is, the dissertation argues that SMNs can provide critical public space and create discursive focal points for political and religious minorities

Multi-View Region Adaptive Multi-temporal DMM and RGB Action Recognition

Human action recognition remains an important yet challenging task. This work proposes a novel action recognition system. It uses a novel Multiple View Region Adaptive Multi-resolution in time Depth Motion Map (MV-RAMDMM) formulation combined with appearance information. Multiple stream 3D Convolutional Neural Networks (CNNs) are trained on the different views and time resolutions of the region adaptive Depth Motion Maps. Multiple views are synthesised to enhance the view invariance. The region adaptive weights, based on localised motion, accentuate and differentiate parts of actions possessing faster motion. Dedicated 3D CNN streams for multi-time resolution appearance information (RGB) are also included. These help to identify and differentiate between small object interactions. A pre-trained 3D-CNN is used here with fine-tuning for each stream along with multiple class Support Vector Machines (SVM)s. Average score fusion is used on the output. The developed approach is capable of recognising both human action and human-object interaction. Three public domain datasets including: MSR 3D Action,Northwestern UCLA multi-view actions and MSR 3D daily activity are used to evaluate the proposed solution. The experimental results demonstrate the robustness of this approach compared with state-of-the-art algorithms.Comment: 14 pages, 6 figures, 13 tables. Submitte

Condition Monitoring Philosophy for Tidal Turbines

Renewable energy is currently considered as the main solution to reduce greenhouse gas emission. This has led to great developments in the use of renewable energy for electricity generation. Among many renewable energy resources, tidal energy has the advantage of being predictable, particularly when compared to wind energy. Currently the UK is the world leader in extracting energy from the tide; an estimation shows a potential of 67 TWh per year. In order to ensure safe operation and prolonged life for tidal turbines, condition monitoring is essential. The technology for power generation using tidal turbines is new therefore the condition monitoring concept for these devices is yet to be established. Also, there is a lack of understanding of techniques suitable for health monitoring of the turbine components and support structure given their unique operating environment.In this paper the condition monitoring of a tidal turbine is investigated. The objective is to highlight the need for condition monitoring and establish procedures to decide the condition monitoring techniques required, in addition to highlighting the impact and benefits of applying condition based maintenance. A model for failure analysis is developed to assess the needs for condition monitoring and identify critical components, after which a ‘symptoms analysis’ was performed to decide the appropriate condition monitoring techniques. Finally, the impact of condition monitoring on system reliability is considered

Prognosis of a Wind Turbine Gearbox Bearing Using Supervised Machine Learning

Deployment of large-scale wind turbines requires sophisticated operation and maintenance strategies to ensure the devices are safe, profitable and cost-effective. Prognostics aims to predict the remaining useful life (RUL) of physical systems based on condition measurements. Analyzing condition monitoring data, implementing diagnostic techniques and using machinery prognostic algorithms will bring about accurate estimation of the remaining life and possible failures that may occur. This paper proposes to combine two supervised machine learning techniques, namely, regression model and multilayer artificial neural network model, to predict the RUL of an operational wind turbine gearbox using vibration measurements. Root Mean Square (RMS), Kurtosis (KU) and Energy Index (EI) were analysed to define the bearing failure stages. The proposed methodology was evaluated through a case study involving vibration measurements of a high-speed shaft bearing used in a wind turbine gearbox

Acute small bowel obstruction secondary to intestinal endometriosis, an elusive condition: a case report

<p>Abstract</p> <p>Background</p> <p>Endometriosis is a benign condition affecting females of reproductive age. Although intestinal endometriosis is common it is rare for the condition to manifest as an acute bowel obstruction secondary to ileocaecal and appendicular endometriosis. This case is important to report as it highlights the diagnostic difficulty this particular condition presents to an emergency surgeon.</p> <p>Case presentation</p> <p>We present the case of a 33 year old female of Asian origin who presented with symptoms and signs of an acute small bowel obstruction. A right hemicolectomy for suspected malignancy was performed with an ileocolic anastomosis. Histological examination demonstrated extensive endometriosis of the appendix and ileocaecal junction.</p> <p>Conclusion</p> <p>Enteric endometriosis should be considered as a differential diagnosis when assessing females of reproductive age with acute small bowel obstruction. A high index of suspicion is required to arrive at a diagnosis of this elusive condition.</p