Modeling random and non-random decision uncertainty in ratings data: A fuzzy beta model

Modeling human ratings data subject to raters' decision uncertainty is an attractive problem in applied statistics. In view of the complex interplay between emotion and decision making in rating processes, final raters' choices seldom reflect the true underlying raters' responses. Rather, they are imprecisely observed in the sense that they are subject to a non-random component of uncertainty, namely the decision uncertainty. The purpose of this article is to illustrate a statistical approach to analyse ratings data which integrates both random and non-random components of the rating process. In particular, beta fuzzy numbers are used to model raters' non-random decision uncertainty and a variable dispersion beta linear model is instead adopted to model the random counterpart of rating responses. The main idea is to quantify characteristics of latent and non-fuzzy rating responses by means of random observations subject to fuzziness. To do so, a fuzzy version of the Expectation-Maximization algorithm is adopted to both estimate model's parameters and compute their standard errors. Finally, the characteristics of the proposed fuzzy beta model are investigated by means of a simulation study as well as two case studies from behavioral and social contexts.Comment: 24 pages, 0 figures, 5 table

Strategies for online personalised nutrition advice employed in the development of the eNutri web app

The internet has considerable potential to improve health-related food choice at low-cost. Online solutions in this field can be deployed quickly and at very low cost, especially if they are not dependent on bespoke devices or offline processes such as the provision and analysis of biological samples. One key challenge is the automated delivery of personalised dietary advice in a replicable, scalable and inexpensive way, using valid nutrition assessment methods and effective recommendations. We have developed a web-based personalised nutrition system (eNutri) which assesses dietary intake using a validated graphical FFQ and provides personalised food-based dietary advice automatically. Its effectiveness was evaluated during an online randomised controlled trial dietary intervention (EatWellUK study) in which personalised dietary advice was compared with general population recommendations (control) delivered online. The present paper presents a review of literature relevant to this work, and describes the strategies used during the development of the eNutri app. Its design and source code have been made publicly available under a permissive open source license, so that other researchers and organisations can benefit from this work. In a context where personalised diet advice has great potential for health promotion and disease prevention at-scale and yet is not currently being offered in the most popular mobile apps, the strategies and approaches described in the present paper can help to inform and advance the design and development of technologies for personalised nutrition

User Controlled Privacy Protection in Location-Based Services

The rapid development of location-determining technologies has enabled tracking of people or objects more accurately than ever before and the volume and extent of tracking has increased dramatically over time. Within the broader domain of tracking technologies, location-based services (LBS) are a subset of capabilities that allow users to access information relative to their own physical location. However, the personal location information generated by such technologies is at risk of being misused or abused unless protection capabilities are built into the design of such systems. These concerns may ultimately prevent society from achieving the broad range of benefits that otherwise would be available to consumers. The assumption of the emerging location-based industry is that corporations will own and control location and other information about individuals. Traditionally, privacy has been addressed through minimum standard approaches. However, regulatory and technological approaches focused on one size fits all standards are ill equipped to accommodate the interests of individuals or broad groups of users. This research explores the possibility of developing an approach for protecting privacy in the use of location-based services that supports the autonomy of an individual through a combined technological and legal model that places the power to protect location privacy in the hands of consumers. A proof of concept user interface to illustrate how personal information privacy could be protected in the conceptual model is demonstrated. A major goal of this project is to create an operational vision supporting user controlled protection of privacy that can help direct technological efforts along appropriate paths

Porto Maphazardly - Representation of Place in Graphic Design

This project, Porto Maphazardly, examines the role of a graphic designer in exploring alternate means of mapping a location. A square in the Portuguese city of Porto was mapped through five sensory approaches: sound, smell, taste, activity, and color perception. The data that was gathered was translated into visuals to create a generated, but totally unique, graphic portrait of a place. The portmanteau maphazardly in the title combines the word ‘map’ with the adverb, ‘haphazardly,’ which means to do something determined by accident rather than design, without a clear plan or at the mercy of chance. The coining of the word is meant to evoke the extent to which the illustrations developed in response to observations, encounters and circumstance, rather than a client brief or a designer’s pre-decided aesthetic. In this report, the project is contextualized between the theory of critical cartography in the field of sociology, and the mapping works which already exist in the graphic design field, including the works of Paula Scher, Pedro Pina, Jeremy Wood, Alison Barnes and Kate McLean. The report presents a synthesized definition of ‘map’ for use in a visual, graphic analysis. A limited survey of the principles of information design is discussed, in its relation to traditional cartography, infographics, and our cognitive interpretations of maps. Finally, a brief analysis of changes in the nature of maps (smart-maps) is included, focusing on how user-centered maps have changed how one interacts with a city. The project endeavors to work in the realm of ‘designer as researcher,’ and is influenced by the writing of Russell Bestley and Ian Noble on visual research, in which the experiential nature of the data collection influences the design process. The methodology was developed through a series of test projects and by the application of ‘walking as method,’ and the report introduces the generative systems which were used to transform data— notes, photographs, and recordings—into illustrations. The final mappings are presented along with an analysis of successes and failures

Doctor of Philosophy

dissertationMany nutritional assessment techniques, including food frequency questionnaires (FFQs) and 24-hour dietary recalls have innate limitations such as expensive protocols, high respondent burden, and self-reporting biases. Supermarket sales data have shown promise as a new, indirect, inexpensive nutritional assessment method in recent studies. The goals of the research in this dissertation were to link nutritional content to supermarket sales data and to determine the relationship between supermarket purchases and traditional nutritional measures through correlation and regression analyses. Nutritional data was mapped to sales data at the nutrient and food group levels. One year retrospective supermarket sales data, household food inventory data, and FFQ results were then obtained for 50 households recruited for the study. A correlation analysis was completed to compare percentage of food groups purchased over 52 weeks against food groups in the household inventory and in the FFQ results. Additionally, stepwise regression models were created to predict BMI, energy intake, fat intake, and saturated fat intake based on supermarket sales data. Nutritional content was mapped to 100% of the supermarket sales data at the food group level and at 69% for the nutrient level. The correlation coefficients between the household inventory and sales data over the course of 52 weeks ranged from -0.13 to 0.83 with an average value of 0.23 at week 32, while correlation for the comparison between the FFQ and sales data ranged from -0.17 to 0.47 with an average of 0.23 at 32 weeks. 5 The regression models to predict BMI, energy intake, fat intake, and saturated fat intake each yielded significant results for several food group purchases from the sales data. Mapping nutritional content to sales data was successful, given that there are potential strategies to increase the linkage for nutrient data. The correlation results are in line with other studies comparing nutritional assessment methods against each other and the regression models produced many significant food groups that are substantiated by multiple studies. Overall, the work presented gives an excellent starting point for further informatics research into the untapped potential of supermarket sales data as a nutritional assessment method and public health tool