2,003 research outputs found

    Spartan Daily February 16, 2011

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    Volume 136, Issue 11https://scholarworks.sjsu.edu/spartandaily/1118/thumbnail.jp

    How predictable : patterns of human economic behavior in the wild

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    Thesis (S.M.)--Massachusetts Institute of Technology, School of Architecture and Planning, Program in Media Arts and Sciences, 2010.Cataloged from PDF version of thesis.Includes bibliographical references (p. 40-41).Shopping is driven by needs (to eat, to socialize, to work), but it is also a driver of where we go. I examine the transaction records of 80 million customers and find that while our economic choices predict mobility patterns overall, at the small scale we transact unpredictably. In particular, we bundle together multiple store visits, and interleave the order in which we frequent those stores. Individual predictability also varies with income level. I end with a description of how merchant composition emerges in US cities, as seen through the lens of credit card swipes.by Katherine (Coco) Krumme.S.M

    Protecting privacy of semantic trajectory

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    The growing ubiquity of GPS-enabled devices in everyday life has made large-scale collection of trajectories feasible, providing ever-growing opportunities for human movement analysis. However, publishing this vulnerable data is accompanied by increasing concerns about individuals’ geoprivacy. This thesis has two objectives: (1) propose a privacy protection framework for semantic trajectories and (2) develop a Python toolbox in ArcGIS Pro environment for non-expert users to enable them to anonymize trajectory data. The former aims to prevent users’ re-identification when knowing the important locations or any random spatiotemporal points of users by swapping their important locations to new locations with the same semantics and unlinking the users from their trajectories. This is accomplished by converting GPS points into sequences of visited meaningful locations and moves and integrating several anonymization techniques. The second component of this thesis implements privacy protection in a way that even users without deep knowledge of anonymization and coding skills can anonymize their data by offering an all-in-one toolbox. By proposing and implementing this framework and toolbox, we hope that trajectory privacy is better protected in research

    'One media – three screens' – Convergence and interactivity at its full potential? ARTE: French-German experiments in 'crossing the borders'

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    This contribution is aimed at discussing different current policies of convergence as well as questioning whether these exploit the opportunities of digital media to their full potential, especially with regard to transmedia storytelling, interactivity, participation and networking.Taking the portfolio of the ‘European Culture Channel’ ARTE as an example, I draw a sketch of existing and emerging industrial strategies as well as of new formats and user practices. In the second part of the article, I examine one specific genre within this context I look at the collaborative, networked transmedia documentary Prison Valley to consider transformations at both the macro and the micro level. Last but not least, I question whether ARTE fulfils its promise to be the first “100% bi-medial channel” (according to ARTE’s mission statement), or whether it promotes an ‘extended side-by sideness’ of devices and practices, which would constitute the first steps towards the synergetic potential of media convergence

    Data mining in the development of mobile health apps : assessing in-app navigation through Markov chain analysis

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    Background: Mobile apps generate vast amounts of user data. In the mobile health (mHealth) domain, researchers are increasingly discovering the opportunities of log data to assess the usage of their mobile apps. To date, however, the analysis of these data are often limited to descriptive statistics. Using data mining techniques, log data can offer significantly deeper insights. Objective: The purpose of this study was to assess how Markov Chain and sequence clustering analysis can be used to find meaningful usage patterns of mHealth apps. Methods: Using the data of a 25-day field trial (n=22) of the Start2Cycle app, an app developed to encourage recreational cycling in adults, a transition matrix between the different pages of the app was composed. From this matrix, a Markov Chain was constructed, enabling intuitive user behavior analysis. Results: Through visual inspection of the transitions, 3 types of app use could be distinguished (route tracking, gamification, and bug reporting). Markov Chain-based sequence clustering was subsequently used to demonstrate how clusters of session types can otherwise be obtained. Conclusions: Using Markov Chains to assess in-app navigation presents a sound method to evaluate use of mHealth interventions. The insights can be used to evaluate app use and improve user experience

    The cognitive representation of the large-scale environment

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    This thesis is concerned with the processes involved in the acquisition and use of cognitive representations of the large-scale environment, or 'cognitive mapping'. The first half of the thesis reviews relevant literature in three main sections. Firstly, the historical roots of the subject are described in chapters on early investigations of wayfinding and orientation, theoretical models of behaviour incorporating the concept of subjective knowledge and multidisciplinary studies of environmental images. Secondly, studies of group differences in cognitive mapping and initial theoretical frameworks are reviewed. Finally, the current state of research evidence is assessed in relation to four research areas. These concern methodological issues, the structure of internal representations, the process of acquiring new representations and individual differences in cognitive mapping.The remainder of the thesis reports and discusses four experimental studies of issues which were judged to be inadequately researched on the basis of the literature review. The first compared the utility of freehand sketch-mapping and three-dimensional modelling with educated, adult subjects. The second investigated the rate of acquisition of cognitive maps, particularly during the first days of environmental experience; using a structured mapping task. Objective accuracy, subjective ratings of accuracy and recall order were examined in relation to building usage and spatial experience. The third experiment compared artificial map learning with spatial relations ability, visual imagery ratings and everyday map usage. Additionally, the effect upon learning of stimulus mode (map or verbal list), response mode and stimulus-response mode compatibility was measured. The final experiment compared performance upon the 'real-life' mapping task of the second study with the map learning and spatial ability measures used in the third study. Evidence was found that cognitive mapping. spatial ability and attitudes to navigational problems are positively related. It was concluded that future work should emphasize the process of cognitive mapping and the relationship between map form and practical needs

    Knowledge discovery from trajectories

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    Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial TechnologiesAs a newly proliferating study area, knowledge discovery from trajectories has attracted more and more researchers from different background. However, there is, until now, no theoretical framework for researchers gaining a systematic view of the researches going on. The complexity of spatial and temporal information along with their combination is producing numerous spatio-temporal patterns. In addition, it is very probable that a pattern may have different definition and mining methodology for researchers from different background, such as Geographic Information Science, Data Mining, Database, and Computational Geometry. How to systematically define these patterns, so that the whole community can make better use of previous research? This paper is trying to tackle with this challenge by three steps. First, the input trajectory data is classified; second, taxonomy of spatio-temporal patterns is developed from data mining point of view; lastly, the spatio-temporal patterns appeared on the previous publications are discussed and put into the theoretical framework. In this way, researchers can easily find needed methodology to mining specific pattern in this framework; also the algorithms needing to be developed can be identified for further research. Under the guidance of this framework, an application to a real data set from Starkey Project is performed. Two questions are answers by applying data mining algorithms. First is where the elks would like to stay in the whole range, and the second is whether there are corridors among these regions of interest

    Small Forgotten Places in the Hearth of Cities

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    This book is the result of a research project designed and carried out at the Department of Architecture, University of Florence. This book discusses urban public spaces and, more specifically, run-down, inactive micro-spaces that are barely used due to their location, dimensions, morphology or semantic characteristics. In literature, these spaces are often defined as “residual urban spaces.” A large abandoned industrial area on the outskirts of a town or a small interstitial space in a historical centre can be residual. With respect to such a broad subject matter, the book seeks to radically limit the field, concentrating on public residual spaces found in the oldest parts of cities. The book reflects on this theme and introduces a method for reading and assessment of the residuality of public spaces in historical contexts (Residuality Assessment Process) which was tested in the historical centre of Florence. It is the authors’ view that residual spaces, above all if designed according to a system logic, can go from being problems to potential activators of urban and social regeneration processes, offering a useful contribution to improve city life

    Kinetic and Statistical Mechanical Modeling of DNA Unzipping and Kinesin Mechanochemistry

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    This thesis explores two topics. The first is shotgun DNA mapping (SDM). Ability to map polymerases and nucleosomes on chromatin is important for understanding the impact of chromatin remodeling on key cellular processes. Current methods have produced a wealth of information that demonstrates this importance, but key information is elusive in these methods. We are pursuing a new single-molecule chromatin mapping method based on unzipping native chromatin molecules with optical tweezers. The first step we are taking towards this ability is SDM. This is the ability to identify the genomic location of a random DNA fragment based on its naked DNA unzipping forces compared with simulated unzipping forces of a published genome. We show that ~32 separate experimental unzipping curves for pBR322 were correctly matched to their simulated unzipping curves hidden in a background of the ~2700 sequences neighboring XhoI sites in the S. cerevisiae (yeast) genome. We describe this method and characterize its robustness as well as discuss future applications. The second topic is a discrete state model for kinesin-1\u27s processivity. Kinesin-1 is a homodimeric molecular motor protein that uses ATP and a hand-over-hand motion to transport cargo along microtubules. Minimal kinetic models are often developed to both explain kinesin\u27s hand-over-hand forward-stepping behavior and to infer important kinetic rate constants from experimental data. These minimal models are often limited to a handful of two-headed states on a core cycle. However, it is not always clear how to evolve these core-cycle models to explain more complex behavior. We have developed a kinetic model without a predefined core cycle. Our model includes 80 two-headed states and permits transitions between any two states that differ by a single catalytic or binding event. We constrain the rate constants as much as possible by published rates and mechanical strain in the kinesin neck linkers and their docking state. We present a model for neck-linker modulation of head and nucleotide binding and unbinding rates. We show that our model reproduces generally-accepted experimental results. The core cycles that emerge are slightly different than those seen in previous experiments. We also explore how processivity and speed change with neck linker length
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