1,983 research outputs found

    Fault Tolerance in Cellular Automata at High Fault Rates

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    A commonly used model for fault-tolerant computation is that of cellular automata. The essential difficulty of fault-tolerant computation is present in the special case of simply remembering a bit in the presence of faults, and that is the case we treat in this paper. We are concerned with the degree (the number of neighboring cells on which the state transition function depends) needed to achieve fault tolerance when the fault rate is high (nearly 1/2). We consider both the traditional transient fault model (where faults occur independently in time and space) and a recently introduced combined fault model which also includes manufacturing faults (which occur independently in space, but which affect cells for all time). We also consider both a purely probabilistic fault model (in which the states of cells are perturbed at exactly the fault rate) and an adversarial model (in which the occurrence of a fault gives control of the state to an omniscient adversary). We show that there are cellular automata that can tolerate a fault rate 1/2ξ1/2 - \xi (with ξ>0\xi>0) with degree O((1/ξ2)log(1/ξ))O((1/\xi^2)\log(1/\xi)), even with adversarial combined faults. The simplest such automata are based on infinite regular trees, but our results also apply to other structures (such as hyperbolic tessellations) that contain infinite regular trees. We also obtain a lower bound of Ω(1/ξ2)\Omega(1/\xi^2), even with purely probabilistic transient faults only

    Capturing personal health data from wearable sensors

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    Recently, there has been a significant growth in pervasive computing and ubiquitous sensing which strives to develop and deploy sensing technology all around us. We are also seeing the emergence of applications such as environmental and personal health monitoring to leverage data from a physical world. Most of the developments in this area have been concerned with either developing the sensing technologies, or the infrastructure (middleware) to gather this data and the issues which have been addressed include power consumption on the devices, security of data transmission, networking challenges in gathering and storing the data and fault tolerance in the event of network and/or device failure. Research is focusing on harvesting and managing data and providing query capabilities

    HealthSense: an application for querying raw sensor data

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    New sensing technologies and the decreasing cost of Information and Communication Technologies (ICTs) make possible the development of electronic Health (eHealth) monitoring systems. The challenges of such systems include the representation of data extracted from various sensor devices by knowledge workers through semantic enrichment and integration. Also, the data must be stored in a format suitable for querying and further analysis. This paper describes the demonstration of the HealthSense system which captures and queries personal health data extracted from wearable sensors

    Tracking internet interest in anabolic-androgenic steroids using Google Trends

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    Background: There is a perception that the prevalence of anabolic-androgenic steroid (AAS) use is increasing in the UK, with consequent individual and public health risks. Nevertheless, there is a lack of real-time surveillance data to support the development of effective policy. This paper explores the potential of Google Trends to complement existing surveillance methods by analysing user generated search term data. Methods: The Google Trends web tool was used to identify patterns of UK online interest in 15 AAS from January 2011 to December 2015, with 10 ultimately suitable for further analysis. Time series analysis was applied to the data. Results: 10 steroids were ranked from most to least popular. All compounds had peaks in interest between April to July, potentially indicating a consumer driven desire to attain a desired physique in time for summer. Oral steroids were among the most searched for drugs which may have relevance for current service provision to steroid users. Conclusion: Alternative data sources such Google Trends may provide useful additional information to supplement existing surveillance data. The limitations of this method however makes cautious interpretation and triangulation with other data sources essential

    Integrating sensor streams in pHealth networks

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    Personal Health (pHealth) sensor networks are generally used to monitor the wellbeing of both athletes and the general public to inform health specialists of future and often serious ailments. The problem facing these domain experts is the scale and quality of data they must search in order to extract meaningful results. By using peer-to-peer sensor architectures and a mechanism for reducing the search space, we can, to some extent, address the scalability issue. However, synchronisation and normalisation of distributed sensor streams remains a problem in many networks. In the case of pHealth sensor networks, it is crucial for experts to align multiple sensor readings before query or data mining activities can take place. This paper presents a system for clustering and synchronising sensor streams in preparation for user queries

    The Lady from the Sea by Henrik Ibsen : A Production Thesis in Scene Design

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    The Lady From The Sea by Henrik Ibsen was selected as a thesis project in design in the spring semester, 1981. This thesis is a written record of the design aspect of the project. It includes an analysis of the script as it relates to the design, a discussion of the concept for the production, a description of the execution of the design and a post-production evaluation of the design. The thesis also includes pertinent drawings and photographs of the setting

    A century of the evolution of the urban system in Brazil

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    In this paper, we study the hitherto unexplored evolution of the size distribution of 185 urban areas in Brazil between 1907 and 2008. We find that the power law parameter of the size distribution of the 100 largest urban areas increases from 0.63 in 1907 to 0.89 in 2008, which confirms an agglomeration process in which the size distribution has become more unequal. A panel fixed effects model pooling the same range of urban size distributions provides a power law parameter equal to 0.53, smaller than those from cross-sectional estimation. Clearly, Zipf’s Law is rejected. The lognormal distribution fits the city size distribution quite well until the 1940s, but since then applies to small and medium size cities only. These results are consistent with our understanding of historical-political and socio-economic processes that have shaped the development of Brazilian cities

    Agglomeration externalities and 1981-2006 regional growth in Brazil

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    This paper focuses on manufacturing employment growth across the 26 states of Brazil. We employ the Glaeser et al. (1992) approach to identify the role played by knowledge externalities in growth and convergence. To assess robustness of the results, we compare cross-section models, dynamic panel models and pooled-periods fixed-effect models. We find that cross-section models confirm the positive impact of Porter’s and Jacobs’ competition externalities on growth, whereas dynamic panel models and pooled-periods fixed-effect models are consistent with the predictions of Marshall-Arrow-Romer and Porter regarding the role of specialisation in manufacturing vis-à-vis other employment. The results provide new insights into the rapid growth since 1981 in particularly the North and Centre West of Brazil

    SRT Division Algorithms As Dynamical Systems

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    Sweeney--Robertson--Tocher (SRT) division, as it was discovered in the late 1950s, represented an important improvement in the speed of division algorithms for computers at the time. A variant of SRT division is still commonly implemented in computers today. Although some bounds on the performance of the original SRT division method were obtained, a great many questions remained unanswered. In this paper, the original version of SRT division is described as a dynamical system. This enables us to bring modern dynamical systems theory, a relatively new development in mathematics, to bear on an older problem. In doing so, we are able to show that SRT division is ergodic, and is even Bernoulli, for all real divisors and dividends. With the Bernoulli property, we are able to use entropy to prove that the natural extensions of SRT division are isomorphic by way of the Kolmogorov--Ornstein theorem. We demonstrate how our methods and results can be applied to a much larger class of division algorithms

    Fault Tolerance in Cellular Automata at Low Fault Rates

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    A commonly used model for fault-tolerant computation is that of cellular automata. The essential difficulty of fault-tolerant computation is present in the special case of simply remembering a bit in the presence of faults, and that is the case we treat in this paper. The conceptually simplest mechanism for correcting errors in a cellular automaton is to determine the next state of a cell by taking a majority vote among its neighbors (including the cell itself, if necessary to break ties). We are interested in which regular two-dimensional tessellations can tolerate faults using this mechanism, when the fault rate is sufficiently low. We consider both the traditional transient fault model (where faults occur independently in time and space) and a recently introduced combined fault model which also includes manufacturing faults (which occur independently in space, but which affect cells for all time). We completely classify regular two-dimensional tessellations as to whether they can tolerate combined transient and manufacturing faults, transient faults but not manufacturing faults, or not even transient faults.Comment: i+26 p
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