117 research outputs found

    Advanced Automation for Space Missions

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    The feasibility of using machine intelligence, including automation and robotics, in future space missions was studied

    Flood Forecasting Using Machine Learning Methods

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    This book is a printed edition of the Special Issue Flood Forecasting Using Machine Learning Methods that was published in Wate

    The occurrence and origin of salinity in non-coastal groundwater in the Waikato region

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    Aims The aims of this project are to describe the occurrence, and determine the origin of non-coastal saline groundwater in the Waikato region. High salinity limits the use of the water for supply and agricultural use. Understanding the origin and distribution of non-coastal salinity will assist with development and management of groundwater resources in the Waikato. Method The occurrence of non-coastal groundwater salinity was investigated by examining driller’s records and regional council groundwater quality information. Selected wells were sampled for water quality analyses and temperatures were profiled where possible. Water quality analyses include halogens such as chloride, fluoride, iodide and bromide. Ratios of these ions are useful to differentiate between geothermal and seawater origins of salinity (Hem, 1992). Other ionic ratio approaches for differentiating sources and influences on salinity such as those developed by Alcala and Emilio (2008) and Sanchez-Martos et al., (2002), may also be applied. Potential sources of salinity include seawater, connate water, geothermal and anthropogenic influences. The hydrogeologic settings of saline occurrence were also investigated, to explore the potential to predict further occurrence. Results Numerous occurrences of non-coastal saline groundwater have been observed in the Waikato region. Where possible, wells with relatively high total dissolved solids (TDS) were selected for further investigation. Several groundwater samples are moderately saline and exceed the TDS drinking water aesthetic guideline of 1,000 g m-3 (Ministry of Health, 2008). Selected ion ratios (predominantly halogens) were used to assist in differentiating between influences on salinity such as seawater and geothermal. Bromide to iodide ratios, in particular, infer a greater geothermal influence on salinity, although other ratios are not definitive. The anomalously elevated salinity observed appears natural but nevertheless has constrained localised groundwater resource development for dairy factory, industrial and prison water supply use. Further work may show some relationship with geology or tectonics, which could assist prediction of inland saline groundwater occurrence

    The Data Science Design Manual

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    NASA SBIR abstracts of 1990 phase 1 projects

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    The research objectives of the 280 projects placed under contract in the National Aeronautics and Space Administration (NASA) 1990 Small Business Innovation Research (SBIR) Phase 1 program are described. The basic document consists of edited, non-proprietary abstracts of the winning proposals submitted by small businesses in response to NASA's 1990 SBIR Phase 1 Program Solicitation. The abstracts are presented under the 15 technical topics within which Phase 1 proposals were solicited. Each project was assigned a sequential identifying number from 001 to 280, in order of its appearance in the body of the report. The document also includes Appendixes to provide additional information about the SBIR program and permit cross-reference in the 1990 Phase 1 projects by company name, location by state, principal investigator, NASA field center responsible for management of each project, and NASA contract number

    Gauged mini-bucket elimination for approximate inference

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    Computing the partition function Z of a discrete graphical model is a fundamental inference challenge. Since this is computationally intractable, variational approximations are often used in practice. Recently, so-called gauge transformations were used to improve variational lower bounds on Z. In this paper, we propose a new gauge-variational approach, termed WMBE-G, which combines gauge transformations with the weighted mini-bucket elimination (WMBE) method. WMBE-G can provide both upper and lower bounds on Z, and is easier to optimize than the prior gauge-variational algorithm. We show that WMBE-G strictly improves the earlier WMBE approximation for symmetric models including Ising models with no magnetic field. Our experimental results demonstrate the effectiveness of WMBE-G even for generic, non-symmetric models.1
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