89 resultados para Data mining and knowledge discovery


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The long-term stability, high accuracy, all-weather capability, high vertical resolution, and global coverage of Global Navigation Satellite System (GNSS) radio occultation (RO) suggests it as a promising tool for global monitoring of atmospheric temperature change. With the aim to investigate and quantify how well a GNSS RO observing system is able to detect climate trends, we are currently performing an (climate) observing system simulation experiment over the 25-year period 2001 to 2025, which involves quasi-realistic modeling of the neutral atmosphere and the ionosphere. We carried out two climate simulations with the general circulation model MAECHAM5 (Middle Atmosphere European Centre/Hamburg Model Version 5) of the MPI-M Hamburg, covering the period 2001–2025: One control run with natural variability only and one run also including anthropogenic forcings due to greenhouse gases, sulfate aerosols, and tropospheric ozone. On the basis of this, we perform quasi-realistic simulations of RO observables for a small GNSS receiver constellation (six satellites), state-of-the-art data processing for atmospheric profiles retrieval, and a statistical analysis of temperature trends in both the “observed” climatology and the “true” climatology. Here we describe the setup of the experiment and results from a test bed study conducted to obtain a basic set of realistic estimates of observational errors (instrument- and retrieval processing-related errors) and sampling errors (due to spatial-temporal undersampling). The test bed results, obtained for a typical summer season and compared to the climatic 2001–2025 trends from the MAECHAM5 simulation including anthropogenic forcing, were found encouraging for performing the full 25-year experiment. They indicated that observational and sampling errors (both contributing about 0.2 K) are consistent with recent estimates of these errors from real RO data and that they should be sufficiently small for monitoring expected temperature trends in the global atmosphere over the next 10 to 20 years in most regions of the upper troposphere and lower stratosphere (UTLS). Inspection of the MAECHAM5 trends in different RO-accessible atmospheric parameters (microwave refractivity and pressure/geopotential height in addition to temperature) indicates complementary climate change sensitivity in different regions of the UTLS so that optimized climate monitoring shall combine information from all climatic key variables retrievable from GNSS RO data.

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Trace elements may present an environmental hazard in the vicinity of mining and smelting activities. However, the factors controlling their distribution and transfer within the soil and vegetation systems are not always well defined. Total concentrations of up to 15,195 mg center dot kg (-1) As, 6,690 mg center dot kg(-1) Cu, 24,820 mg center dot kg(-1) Pb and 9,810 mg center dot kg(-1) Zn in soils, and 62 mg center dot kg(-1) As, 1,765 mg center dot kg(-1) Cu, 280 mg center dot kg(-1) Pb and 3,460 mg center dot kg (-1) Zn in vegetation were measured. However, unusually for smelters and mines of a similar size, the elevated trace element concentrations in soils were found to be restricted to the immediate vicinity of the mines and smelters (maximum 2-3 km). Parent material, prevailing wind direction, and soil physical and chemical characteristics were found to correlate poorly with the restricted trace element distributions in soils. Hypotheses are given for this unusual distribution: (1) the contaminated soils were removed by erosion or (2) mines and smelters released large heavy particles that could not have been transported long distances. Analyses of the accumulation of trace elements in vegetation (median ratios: As 0.06, Cu 0.19, Pb 0.54 and Zn 1.07) and the percentage of total trace elements being DTPA extractable in soils (median percentages: As 0.06%, Cu 15%, Pb 7% and Zn 4%) indicated higher relative trace element mobility in soils with low total concentrations than in soils with elevated concentrations.

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Trace elements may present an environmental hazard in the vicinity of mining and smelting activities. However, the factors controlling trace element distribution in soils around ancient and modem mining and smelting areas are not always clear. Tharsis, Riotinto and Huelva are located in the Iberian Pyrite Belt in SW Spain. Tharsis and Riotinto mines have been exploited since 2500 B.C., with intensive smelting taking place. Huelva, established in 1970 and using the Flash Furnace Outokumpu process, is currently one of the largest smelter in the world. Pyrite and chalcopyrite ore have been intensively smelted for Cu. However, unusually for smelters and mines of a similar size, the elevated trace element concentrations in soils were found to be restricted to the immediate vicinity of the mines and smelters, being found up to a maximum of 2 kin from the mines and smelters at Tharsis, Riotinto and Huelva. Trace element partitioning (over 2/3 of trace elements found in the residual immobile fraction of soils at Tharsis) and soil particles examination by SEM-EDX showed that trace elements were not adsorbed onto soil particles, but were included within the matrix of large trace element-rich Fe silicate slag particles (i.e. 1 min circle divide at least 1 wt.% As, Cu and Zn, and 2 wt.% Pb). Slag particle large size (I mm 0) was found to control the geographically restricted trace element distribution in soils at Tharsis, Riotinto and Huelva, since large heavy particles could not have been transported long distances. Distribution and partitioning indicated that impacts to the environment as a result of mining and smelting should remain minimal in the region. (c) 2006 Elsevier B.V. All rights reserved.

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Toxic trace elements present an environmental hazard in the vicinity of mining and smelting activities. However. the processes of transfer of these elements to groundwater and to plants are not always clear. Tharsis mine. in the Iberian pyrite belt (SW Spain), has been exploited since 2500 BC, with extensive smelting, taking place front the 1850S until the 1920s. Sixty four soil (mainly topsoils) and vegetation samples were collected in February 2001 and analysed by ICP-AES for 23 elements. Concentrations are 6-6300 mg kg(-1) As and 14-24800 mg kg(-1) Pb in soils, and 0.20-9 mg kg(-1) As and 2-195 mg Pb in vegetation. Trace element concentrations decrease rapidly away from the mine. with As and Pb concentrations in the range 6-1850 mg kg(-1) (median 22 mg kg(-1)) and 14-31 mg, kg(-1) (median 43 mg, kg(-1)), respectively, 1 km away from the mine. These concentrations are low when compared to other well-studied mining and smelting areas (e.g. 600 mg kg(-1) As at 8 km from Yellowknife smelter, Canada; >100 mg kg(-1) Pb over 270 km(2) around the Pb-Zn Port Pirie smelter. South Australia: mean of 1419 mg kg(-1) Pb around Aberystwyth smelter, Wales, UK). The high metal content of the vegetation and the low soil pH (mean pH 4.93) indicate the potential for trace element mobility which Could explain the relatively low concentration of metals in Tharsis topsoils and cause threats to plans to redevelop the Tharsis area as an orange plantation.

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In real world applications sequential algorithms of data mining and data exploration are often unsuitable for datasets with enormous size, high-dimensionality and complex data structure. Grid computing promises unprecedented opportunities for unlimited computing and storage resources. In this context there is the necessity to develop high performance distributed data mining algorithms. However, the computational complexity of the problem and the large amount of data to be explored often make the design of large scale applications particularly challenging. In this paper we present the first distributed formulation of a frequent subgraph mining algorithm for discriminative fragments of molecular compounds. Two distributed approaches have been developed and compared on the well known National Cancer Institute’s HIV-screening dataset. We present experimental results on a small-scale computing environment.

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In a cross-sectional study of 400 randomly selected smallholder dairy farms in the Tanga and Iringa regions of Tanzania, 14.2% (95% confidence interval (CI) = 11.6-17.3) of cows had developed clinical mastitis during the previous year. The point prevalence of subclinical mastitis, defined as a quarter positive by the California Mastitis Test (CMT) or by bacteriological culture, was 46.2% (95% Cl = 43.6-48.8) and 24.3% (95% Cl = 22.2-26.6), respectively. In a longitudinal disease study in Iringa, the incidence of clinical mastitis was 31.7 cases per 100 cow-years. A randomised intervention trial indicated that intramammary antibiotics significantly reduced the proportion of bacteriologically positive quarters in the short-term (14 days post-infusion) but teat dipping had no detectable effect on bacteriological infection and CMT positive quarters. Other risk and protective factors were identified from both the cross-sectional and longitudinal included animals with Boran breeding (odds ratio (OR) = 3,40, 95% CI = 1.00-11.57, P < 0.05 for clinical mastitis, and OR = 3.51, 95% CI = 1.299.55, P < 0.01 for a CMT positive quarter), while the practice of residual calf suckling was protective for a bacteriologically positive quarter (OR = 0.63, 95% Cl = 0.48-0.81, P <= 0.001) and for a CMT positive quarter (OR = 0.69, 95% Cl = 0.63-0.75, P < 0.001). A mastitis training course for farmers and extension officers was held, and the knowledge gained and use of different methods of dissemination were assessed over time. In a subsequent randomised controlled trial, there were strong associations between knowledge gained and both the individual question asked and the combination of dissemination methods (village meeting, video and handout) used. This study demonstrated that both clinical and subclinical mastitis is common in smallholder dairying in Tanzania, and that some of the risk and protective factors for mastitis can be addressed by practical management of dairy cows following effective knowledge transfer. (c) 2006 Elsevier B.V. All rights reserved.

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In a cross-sectional study of 400 randomly selected smallholder dairy farms in the Tanga and Iringa regions of Tanzania, 14.2% (95% confidence interval (CI) = 11.6-17.3) of cows had developed clinical mastitis during the previous year. The point prevalence of subclinical mastitis, defined as a quarter positive by the California Mastitis Test (CMT) or by bacteriological culture, was 46.2% (95% Cl = 43.6-48.8) and 24.3% (95% Cl = 22.2-26.6), respectively. In a longitudinal disease study in Iringa, the incidence of clinical mastitis was 31.7 cases per 100 cow-years. A randomised intervention trial indicated that intramammary antibiotics significantly reduced the proportion of bacteriologically positive quarters in the short-term (14 days post-infusion) but teat dipping had no detectable effect on bacteriological infection and CMT positive quarters. Other risk and protective factors were identified from both the cross-sectional and longitudinal included animals with Boran breeding (odds ratio (OR) = 3,40, 95% CI = 1.00-11.57, P < 0.05 for clinical mastitis, and OR = 3.51, 95% CI = 1.299.55, P < 0.01 for a CMT positive quarter), while the practice of residual calf suckling was protective for a bacteriologically positive quarter (OR = 0.63, 95% Cl = 0.48-0.81, P <= 0.001) and for a CMT positive quarter (OR = 0.69, 95% Cl = 0.63-0.75, P < 0.001). A mastitis training course for farmers and extension officers was held, and the knowledge gained and use of different methods of dissemination were assessed over time. In a subsequent randomised controlled trial, there were strong associations between knowledge gained and both the individual question asked and the combination of dissemination methods (village meeting, video and handout) used. This study demonstrated that both clinical and subclinical mastitis is common in smallholder dairying in Tanzania, and that some of the risk and protective factors for mastitis can be addressed by practical management of dairy cows following effective knowledge transfer. (c) 2006 Elsevier B.V. All rights reserved.

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Physiological parameters measured by an embedded body sensor system were demonstrated to respond to changes of the air temperature in an office environment. The thermal parameters were monitored with the use of a wireless sensor system that made possible to turn any existing room into a field laboratory. Two human subjects were monitored over daily activities and at various steady-state thermal conditions when the air temperature of the room was altered from 22-23°C to 25-28°C. The subjects indicated their thermal feeling on questionnaires. The measured skin temperature was distributed close to the calculated mean skin temperature corresponding to the given activity level. The variation of Galvanic Skin Response (GSR) reflected the evaporative heat loss through the body surfaces and indicated whether sweating occurred on the subjects. Further investigations are needed to fully evaluate the influence of thermal and other factors on the output given by the investigated body sensor system.

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This paper proposes a new iterative algorithm for OFDM joint data detection and phase noise (PHN) cancellation based on minimum mean square prediction error. We particularly highlight the problem of "overfitting" such that the iterative approach may converge to a trivial solution. Although it is essential for this joint approach, the overfitting problem was relatively less studied in existing algorithms. In this paper, specifically, we apply a hard decision procedure at every iterative step to overcome the overfitting. Moreover, compared with existing algorithms, a more accurate Pade approximation is used to represent the phase noise, and finally a more robust and compact fast process based on Givens rotation is proposed to reduce the complexity to a practical level. Numerical simulations are also given to verify the proposed algorithm.

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This paper proposes a new iterative algorithm for orthogonal frequency division multiplexing (OFDM) joint data detection and phase noise (PHN) cancellation based on minimum mean square prediction error. We particularly highlight the relatively less studied problem of "overfitting" such that the iterative approach may converge to a trivial solution. Specifically, we apply a hard-decision procedure at every iterative step to overcome the overfitting. Moreover, compared with existing algorithms, a more accurate Pade approximation is used to represent the PHN, and finally a more robust and compact fast process based on Givens rotation is proposed to reduce the complexity to a practical level. Numerical Simulations are also given to verify the proposed algorithm. (C) 2008 Elsevier B.V. All rights reserved.