Electron, ion and neutral heating in hollow cathode plasma thrusters

This thesis demonstrates the capability to control the particle heating mechanisms in radio-frequency (rf) hollow cathode electrothermal micropropulsion sources via the application of multi-harmonic `tailored' voltage waveforms. Modulation of the electrical asymmetry of such waveforms, through varying the phase offset between successive harmonics, results in a direct variation of the phase-resolved sheath dynamics. This enables the preferential deposition of power into either electrons or ion species, selectively enhancing the ionisation rate or neutral gas heating efficiency, respectively. Further, by considering the neutral depletion arising from neutral gas heating, this work predicts the formation of collisionless ion populations within otherwise collisional plasmas. These outcomes are achieved in tandem through the use of 2D fluid/Monte-Carlo numerical simulations with comparison to experimental measurements of the lab-based prototype Pocket Rocket hollow cathode microthruster. Application of these electrical control schemes to plasma sources for spacecraft propulsion enables the prospect of variable thrust and variable specific impulse operation, significantly increasing the in-mission versatility of electric thrusters

Blended e-learning skeleton of conversation: improving formative assessment in undergraduate dissertation supervision

The supervision of undergraduate student dissertations is an area in need of research. Although some studies have already addressed this, these are primarily based on academic staff responses. This study contributes to knowledge by gathering the responses of students and focusing on formative electronic assessment. Data was collected using a student focus group and student questionnaire. The findings suggest that good supervisor-student communication is crucial to the supervision process and a number of students felt unhappy with this aspect. It is suggested that to improve the undergraduate student dissertation experience, a combination of face-to-face and electronic formative assessment is used. In addition, the Blended E-learning Skeleton of Conversation model provides a sound theoretical framework that could guide supervisors and students in the supervision process. This model is advocated for use in dissertation module design and in supervisor development

Developing the Quantitative Histopathology Image Ontology : A case study using the hot spot detection problem

Interoperability across data sets is a key challenge for quantitative histopathological imaging. There is a need for an ontology that can support effective merging of pathological image data with associated clinical and demographic data. To foster organized, cross-disciplinary, information-driven collaborations in the pathological imaging field, we propose to develop an ontology to represent imaging data and methods used in pathological imaging and analysis, and call it Quantitative Histopathological Imaging Ontology – QHIO. We apply QHIO to breast cancer hot-spot detection with the goal of enhancing reliability of detection by promoting the sharing of data between image analysts

Intelligent assistance in scientific data preparation

Scientific data preparation is the process of extracting usable scientific data from raw instrument data. This task involves noise detection (and subsequent noise classification and flagging or removal), extracting data from compressed forms, and construction of derivative or aggregate data (e.g. spectral densities or running averages). A software system called PIPE provides intelligent assistance to users developing scientific data preparation plans using a programming language called Master Plumber. PIPE provides this assistance capability by using a process description to create a dependency model of the scientific data preparation plan. This dependency model can then be used to verify syntactic and semantic constraints on processing steps to perform limited plan validation. PIPE also provides capabilities for using this model to assist in debugging faulty data preparation plans. In this case, the process model is used to focus the developer's attention upon those processing steps and data elements that were used in computing the faulty output values. Finally, the dependency model of a plan can be used to perform plan optimization and run time estimation. These capabilities allow scientists to spend less time developing data preparation procedures and more time on scientific analysis tasks

Una entrevista con Luis Murillo Fort, traductor de Cormac McCarthy

Una entrevista con Luis Murillo Fort, traductor de Cormac McCarth

Cleaning Up East Potomac Park

In this project, we investigated the causes, impacts and approaches to the trash problem in East Potomac Park. We interviewed National Park Service staff, conducted a site assessment of the park, and reviewed literature on visitor behavior and waste management approaches to compare various infrastructural, informational, educational, and enforcement practices of parks in and around D.C. Based on this research, we created recommendations for the implementation of new approaches and created deliverables to supplement them: maps of proposed locations for more trash bins and fishing line containers; anti-littering signage created using the theory of planned behavior, and an education program local teachers can use to increase students\u27 awareness of the impacts of trash