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<link>http://hdl.handle.net/10453/214</link>
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<pubDate>Sun, 19 May 2013 07:13:10 GMT</pubDate>
<dc:date>2013-05-19T07:13:10Z</dc:date>
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<title>MODIS vegetation indices</title>
<link>http://hdl.handle.net/10453/17756</link>
<description>MODIS vegetation indices
Huete Alfredo; Didan Kamel; Van Leeuwen Willem
Ramachandran, B., Justice, C.O., and Abrams, M.
Assessments of vegetation condition, cover, change, and processes are major components of global change research programs, and are topics of considerable societal relevance. Spectral vegetation indices are among the most widely used satellite data products, which provide key measurements for climate, hydrologic, and biogeochemical studies; phenology, land cover, and land cover change detection; natural resource management and sustainable development. Vegetation indices (VI) are robust and seamless data products computed similarly across all pixels in time and space, regardless of biome type, land cover condition, and soil type, and thus represent true surface  measurements. The simplicity of VIs enables their amalgamation across sensor systems, which facilitates an ensured continuity of critical datasets for long-term land surface modeling and climate change studies. Currently, a more than two decades long NOAA Advanced Very High Resolution Radiometer (AVHRR)-derived consistent global normalized difference vegetation index (NDVI) land record exists, which has contributed significantly to global biome, ecosystem, and agricultural studies.
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<pubDate>Sat, 01 Jan 2011 00:00:00 GMT</pubDate>
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<dc:date>2011-01-01T00:00:00Z</dc:date>
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<title>Decentralized Model Predictive Control of Time-varying Splitting Parallel Systems</title>
<link>http://hdl.handle.net/10453/17757</link>
<description>Decentralized Model Predictive Control of Time-varying Splitting Parallel Systems
Tran Tri; Tuan H; Ha Quang; Nguyen Hung
Mohammadpour, Javad; Scherer, Carsten W.
This chapter is devoted to the development of a decentralised model predictive control (MPC) strategy for splitting parallel systems that have timevarying and unknown splitting ratios. The large-scale system in consideration consists of several dynamically-coupled modular subsystems. Each subsystem is regulated by a dedicated multivariable controller employing the open-loop MPC algorithms in conjunction with stability constraints. The connection topology of the large-scale systems includes serial, parallel and recirculated configurations. The solution to splitting parallel systems in this chapter is not only an alternative to the hybrid approach for duty-standby modes, but also a novel approach that accommodates the concurrent operations of splitting parallel systems. The effectiveness of this approach rests on the newly introduced asymptotically positive real constraint (APRC) which prescribes an approaching characteristic towards a positive real property of the system under control. The asymptotic attribute of APRC smooths out all significant wind-up actions in the control trajectories. The APRCs are developed into a one-time-step quadratic constraint on the local control vectors, which plays the role of a stability constraint for the decentralised MPC. The recursive feasibility is assured by characterizing the APRC with dynamicmultiplier matrices. Numerical simulations for two typical modular systems in an alumina refinery are provided to illustrate the theoretical results.
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<pubDate>Sun, 01 Jan 2012 00:00:00 GMT</pubDate>
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<dc:date>2012-01-01T00:00:00Z</dc:date>
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<title>Stochastic Nature of Flow Turbulence and Sediment Particle Entrainment over the Ripples at the Bed of Open Channel Using Image Processing Technique</title>
<link>http://hdl.handle.net/10453/17758</link>
<description>Stochastic Nature of Flow Turbulence and Sediment Particle Entrainment over the Ripples at the Bed of Open Channel Using Image Processing Technique
Keshavarzy Alireza; Ball James
Faruk Bhuiyan

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<pubDate>Sat, 01 Jan 2011 00:00:00 GMT</pubDate>
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<dc:date>2011-01-01T00:00:00Z</dc:date>
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<title>Empirical Evaluation of an Autonomous Vehicle in an Urban Environment</title>
<link>http://hdl.handle.net/10453/17753</link>
<description>Empirical Evaluation of an Autonomous Vehicle in an Urban Environment
Upcroft Ben; Makarenko Alexei; Brooks Alex; Moser Michael; Alempijevic Alen; Donikian Ashod; Sprinkle Jonathan; Uther William; Fitch Robert
Rouff, Christopher; Hinchey, Michael
Experience from the DARPA Urban Challenge provides details of the types of systems, software and processes that were used to develop the complex unmanned vehicles that participated in the DARPA Urban Challenge. The vehicle developers explain how autonomous vehicle software in this race was designed and implemented. The chapters range from system and software architecture, navigation, path planning, steering, perception, engineering autonomous systems, and testing and performance evaluation.
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<pubDate>Sat, 01 Jan 2011 00:00:00 GMT</pubDate>
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<dc:date>2011-01-01T00:00:00Z</dc:date>
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