51,929 research outputs found

    Enjoy the Joy of Copulas: With a Package copula

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    Copulas have become a popular tool in multivariate modeling successfully applied in many fields. A good open-source implementation of copulas is much needed for more practitioners to enjoy the joy of copulas. This article presents the design, features, and some implementation details of the R package copula. The package provides a carefully designed and easily extensible platform for multivariate modeling with copulas in R. S4 classes for most frequently used elliptical copulas and Archimedean copulas are implemented, with methods for density/distribution evaluation, random number generation, and graphical display. Fitting copula-based models with maximum likelihood method is provided as template examples. With the classes and methods in the package, the package can be easily extended by user-defined copulas and margins to solve problems.

    The State Of Play: A Notional Machine for Learning Programming

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    Comprehension of programming and programs is known to be a difficult task for many beginning students, with many computing courses showing significant drop out and failure rates. In this paper, we present a new notional machine de- sign and implementation to help with understanding of pro- gramming and its dynamics for beginning learners. The no- tional machine offers an abstraction of the physical machine designed for comprehension and learning purposes. We in- troduce the notional machine and a graphical notation for its representation. We also present Novis, an implementation of a dynamic real-time visualiser of this notional machine, integrated into BlueJ

    Man and Machine: Questions of Risk, Trust and Accountability in Today's AI Technology

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    Artificial Intelligence began as a field probing some of the most fundamental questions of science - the nature of intelligence and the design of intelligent artifacts. But it has grown into a discipline that is deeply entwined with commerce and society. Today's AI technology, such as expert systems and intelligent assistants, pose some difficult questions of risk, trust and accountability. In this paper, we present these concerns, examining them in the context of historical developments that have shaped the nature and direction of AI research. We also suggest the exploration and further development of two paradigms, human intelligence-machine cooperation, and a sociological view of intelligence, which might help address some of these concerns.Comment: Preprin

    Imaging the Sunyaev-Zel'dovich Effect

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    We report on results of interferometric imaging of the Sunyaev-Zel'dovich Effect (SZE) with the OVRO and BIMA mm-arrays. Using low-noise cm-wave receivers on the arrays, we have obtained high quality images for 27 distant galaxy clusters. We review the use of the SZE as a cosmological tool. Gas mass fractions derived from the SZE data are given for 18 of the clusters, as well as the implied constraint on the matter density of the universe, ΩM\Omega_M. We find ΩMh1000.220.03+0.05\Omega_M h_{100} \le 0.22 ^{+0.05}_{-0.03}. A best guess for the matter density obtained by assuming a reasonable value for the Hubble constant and also by attempting to account for the baryons contained in the galaxies as well as those lost during the cluster formation process gives ΩM0.25\Omega_M \sim 0.25. We also give preliminary results for the Hubble constant. Lastly, the power for investigating the high redshift universe with a non-targeted high sensitivity SZE survey is discussed and an interferometric survey is proposed.Comment: 14 pages, 7 figures, latex, contribution to Nobel Symposium "Particle Physics and the Universe" to appear in Physica Scripta and World Scientific, eds L. Bergstrom, P. Carlson and C. Fransso

    Drivers’ behaviour modelling for virtual worlds

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    In this paper we present a study that looks at modelling drivers’ behaviour with a view to contribute to the problem of road rage. The approach we adopt is based on agent technology, particularly multi-agent systems. Each driver is represented by a software agent. A virtual environment is used to simulate drivers’ behaviour, thus enabling us to observe the conditions leading to road rage. The simulated model is then used to suggest possible ways of alleviating this societal problem. Our agents are equipped with an emotional module which will make their behaviours more human-like. For this, we propose a computational emotion model based on the OCC model and probabilistic cognitive maps. The key influencing factors that are included in the model are personality, emotions and some social/personal attributes

    Novis: A notional machine implementation for teaching introductory programming

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    Comprehension of programming and programs is known to be a difficult task for many beginning students, with many computing courses showing significant drop out and failure rates. In this paper, we present a notional machine imple- mentation, Novis, to help with understanding of program- ming and its dynamics for beginning learners. The notional machine offers an abstraction of the physical machine de- signed for comprehension and learning purposes. Novis pro- vides a real-time visualisation of this notional machine, and is integrated into BlueJ

    On properties of modeling control software for embedded control applications with CSP/CT framework

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    This PROGRESS project (TES.5224) traces a design framework for implementing embedded real-time software for control applications by exploiting its natural concurrency. The paper illustrates the stage of yielded automation in the process of structuring complex control software architectures, modeling controlled mechatronic systems and designing corresponding control laws, simulating them, generating control code out of simulated control strategy and implementing the software system on a (embedded) computer. The gap between the development of control strategies and the procedures of implementing them on chosen hardware targets is going to be overcome

    Virtual Reality Games for Motor Rehabilitation

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    This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion
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