Generalizing and Transferring Mathematical Definitions from Euclidean to Taxicab Geometry

Research shows that by observing properties of figures and making conjectures in non-Euclidean geometries, students can better develop their understanding of concepts in Euclidean geometry. It is also known that definitions in mathematics are an integral part of understanding concepts and are often not used correctly in proof or logic courses by students. To further investigate student understanding of mathematical definitions, this dissertation studied students’ uses of dynamic geometry software and group work to generalize their understanding of definitions as they completed activities in Taxicab geometry. As a result of the analysis from the group work and use of Geometer’s Sketchpad by 18 students in a College Geometry class, suggestions are provided to implement cooperative learning and technology in the classroom. In addition, results are provided from the data analysis of responses to questions pertaining to the definition of circle (and its relevant concepts) of 15 students enrolled in the course who volunteered to participate in semi-structured interviews. This dissertation specifically utilizes APOS Theory (Arnon et al., 2014) and the interaction of schema framework provided by Baker et al. (2000) to determine what components of the circle schema were evoked by these participating students during these interviews. By adapting and transferring their knowledge of concepts back and forth between Euclidean and Taxicab geometry, these students provided evidence for the relationships they had formed between the components of their circle schema. Further, they demonstrated a variety of levels of schema interaction of their evoked Euclidean geometry schema and Taxicab geometry schema. As a result, a model of schema interaction and suggested pedagogical activities were developed to help facilitate student understanding of the definition of a circle and other relevant concepts

The sharing economy in the global South: Uber’s precarious labour force in Johannesburg

Submitted in the partial fulfilment for the Degree of Master of Arts in Development Studies Faculty of Humanities University of the Witwatersrand, March 2017The precarious existence of Uber drivers operating within Johannesburg’s metropolitan area is the primary area of study in which this dissertation has undertaken. Driver precarity, defined in the study as the loss of labour market security in various forms, is argued to stem from Uber’s sharing economy-inspired business model. The analysis of Uber’s business model, substantively focuses on the service’s dynamic pricing model of fare price setting, the implementation of a ‘rating’ system in which to evaluate driver performance and the use of ‘independent contractor’ labour. It is argued that each of these three Uber business practices place drivers in a position of precarity in the realm of their income, employment, work and job security. The study mobilises a qualitative research methodology, enlisting the methods of unstructured interviews on eight active Uber drivers, four autoethnographical observations on real-time work behaviour and document analysis to generate data for analysis. The prevailing argument made regarding Uber’s precarity-creation, is aided through a consultation of Guy Standing’s theorisation on precarity (2011), with Harvey’s flexible Accumulation theory (1990), Foucault’s Panopticism thesis (1975) and Hochschild’s emotional labour theory (1983) broadening the scope of the analysis.XL201

A New Insight into Land Use Classification Based on Aggregated Mobile Phone Data

Land use classification is essential for urban planning. Urban land use types can be differentiated either by their physical characteristics (such as reflectivity and texture) or social functions. Remote sensing techniques have been recognized as a vital method for urban land use classification because of their ability to capture the physical characteristics of land use. Although significant progress has been achieved in remote sensing methods designed for urban land use classification, most techniques focus on physical characteristics, whereas knowledge of social functions is not adequately used. Owing to the wide usage of mobile phones, the activities of residents, which can be retrieved from the mobile phone data, can be determined in order to indicate the social function of land use. This could bring about the opportunity to derive land use information from mobile phone data. To verify the application of this new data source to urban land use classification, we first construct a time series of aggregated mobile phone data to characterize land use types. This time series is composed of two aspects: the hourly relative pattern, and the total call volume. A semi-supervised fuzzy c-means clustering approach is then applied to infer the land use types. The method is validated using mobile phone data collected in Singapore. Land use is determined with a detection rate of 58.03%. An analysis of the land use classification results shows that the accuracy decreases as the heterogeneity of land use increases, and increases as the density of cell phone towers increases.Comment: 35 pages, 7 figure

Data from mobile phone operators: A tool for smarter cities?

Abstract The use of mobile phone data provides new spatio-temporal tools for improving urban planning, and for reducing inefficiencies in present-day urban systems. Data from mobile phones, originally intended as a communication tool, are increasingly used as innovative tools in geography and social sciences research. Empirical studies on complex city systems from human-centred and urban dynamics perspectives provide new insights to develop promising applications for supporting smart city initiatives. This paper provides a comprehensive review and a typology of spatial studies on mobile phone data, and highlights the applicability of such digital data to develop innovative applications for enhanced urban management

A Service Oriented Architecture Approach for Global Positioning System Quality of Service Monitoring

This research focuses on the development of a Service Oriented Architecture (SOA) for monitoring the Global Positioning System (GPS) Standard Positioning Service (SPS) in near real time utilizing a Mobile Crowd Sensing (MCS) technique. A unique approach to developing the MCS SOA was developed that utilized both the Depart- ment of Defense Architecture Framework (DoDAF) and the SOA Modeling Language (SoaML) guidance. The combination of these two frameworks resulted in generation of all the architecture products required to evaluate the SOA through the use of Model Based System Engineering (MBSE) techniques. Ultimately this research provides a feasibility analysis for utilization of mobile distributed sensors to provide situational awareness of the GPS Quality of Service (QoS). First this research provides justification for development of a new monitoring architecture and defines the scope of the SOA. Then an exploration of current SOA, MBSE, and Geospatial System Information (GIS) research was conducted. Next a Discrete Event Simulation (DES) of the MCS participant interactions was developed and simulated within AGI\u27s Systems Toolkit. The architecture performance analysis was executed using a GIS software package known as ArcMap. Finally, this research concludes with a suitability analysis of the proposed architecture for detecting sources of GPS interference within an Area of Interest (AoI)