93,692 research outputs found

    Relation of SiO maser emission to IR radiation in evolved stars based on the MSX observation

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    Based on the space MSX observation in bands A(8μ\mum), C(12μ\mum), D(15μ\mum) and E(21μ\mum), and the ground SiO maser observation of evolved stars by the Nobeyama 45-m telescope in the v=1 and v=2 J=1-0 transitions, the relation between SiO maser emission and mid-IR continuum radiation is analyzed. The relation between SiO maser emission and the IR radiation in the MSX bands A, C, D and E is all clearly correlated. The SiO maser emission can be explained by a radiative pumping mechanism according to its correlation with infrared radiation in the MSX band A.Comment: 11 pages, 4 figures, to appear in ApJ

    Multi-agent simulation: new approaches to exploring space-time dynamics in GIS

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    As part of the long term quest to develop more disaggregate, temporally dynamic models of spatial behaviour, micro-simulation has evolved to the point where the actions of many individuals can be computed. These multi-agent systems/simulation(MAS) models are a consequence of much better micro data, more powerful and user-friendly computer environments often based on parallel processing, and the generally recognised need in spatial science for modelling temporal process. In this paper, we develop a series of multi-agent models which operate in cellular space.These demonstrate the well-known principle that local action can give rise to global pattern but also how such pattern emerges as the consequence of positive feedback and learned behaviour. We first summarise the way cellular representation is important in adding new process functionality to GIS, and the way this is effected through ideas from cellular automata (CA) modelling. We then outline the key ideas of multi-agent simulation and this sets the scene for three applications to problems involving the use of agents to explore geographic space. We first illustrate how agents can be programmed to search route networks, finding shortest routes in adhoc as well as structured ways equivalent to the operation of the Bellman-Dijkstra algorithm. We then demonstrate how the agent-based approach can be used to simulate the dynamics of water flow, implying that such models can be used to effectively model the evolution of river systems. Finally we show how agents can detect the geometric properties of space, generating powerful results that are notpossible using conventional geometry, and we illustrate these ideas by computing the visual fields or isovists associated with different viewpoints within the Tate Gallery.Our forays into MAS are all based on developing reactive agent models with minimal interaction and we conclude with suggestions for how these models might incorporate cognition, planning, and stronger positive feedbacks between agents

    Mapping cyberspace: visualising, analysing and exploring virtual worlds

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    In the past years, with the development of computer networks such as the Internet and world wide web (WWW), cyberspace has been increasingly studied by researchers in various disciplines such as computer sciences, sociology, geography, and cartography as well. Cyberspace is mainly rooted in two computer technologies: network and virtual reality. Cybermaps, as special maps for cyberspace, have been used as a tool for understanding various aspects of cyberspace. As recognised, cyberspace as a virtual space can be distinguished from the earth we live on in many ways. Because of these distinctions, mapping it implies a big challenge for cartographers with their long tradition of mapping things in clear ways. This paper, by comparing it to traditional maps, addresses various cybermap issues such as visualising, analysing and exploring cyberspace from different aspects

    Optimal Hour-Ahead Bidding in the Real-Time Electricity Market with Battery Storage using Approximate Dynamic Programming

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    There is growing interest in the use of grid-level storage to smooth variations in supply that are likely to arise with increased use of wind and solar energy. Energy arbitrage, the process of buying, storing, and selling electricity to exploit variations in electricity spot prices, is becoming an important way of paying for expensive investments into grid-level storage. Independent system operators such as the NYISO (New York Independent System Operator) require that battery storage operators place bids into an hour-ahead market (although settlements may occur in increments as small as 5 minutes, which is considered near "real-time"). The operator has to place these bids without knowing the energy level in the battery at the beginning of the hour, while simultaneously accounting for the value of leftover energy at the end of the hour. The problem is formulated as a dynamic program. We describe and employ a convergent approximate dynamic programming (ADP) algorithm that exploits monotonicity of the value function to find a revenue-generating bidding policy; using optimal benchmarks, we empirically show the computational benefits of the algorithm. Furthermore, we propose a distribution-free variant of the ADP algorithm that does not require any knowledge of the distribution of the price process (and makes no assumptions regarding a specific real-time price model). We demonstrate that a policy trained on historical real-time price data from the NYISO using this distribution-free approach is indeed effective.Comment: 28 pages, 11 figure
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