967 resultados para Web Mining


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Develop a web-based tool to assist farmers and consultants make strategic and tactical irrigation decisions.

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The existing internet computing resource, Biomolecules Segment Display Device (BSDD), has been updated with several additional useful features. An advanced option is provided to superpose the structural motifs obtained from a search on the Protein Data Bank (PDB) in order to see if the three-dimensional structures adopted by identical or similar sequence motifs are the same. Furthermore, the options to display structural aspects like inter- and intra-molecular interactions, ion-pairs, disulphide bonds, etc. have been provided.The updated resource is interfaced with an up-to-date copy of the public domain PDB as well as 25 and 90% non-redundant protein structures. Further, users can upload the three-dimensional atomic coordinates (PDB format) from the client machine. A free molecular graphics program, JMol, is interfaced with it to display the three-dimensional structures.

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Cat's claw creeper, Dolichandra unguis-cati (L.) L.G. Lohman (syn: Macfadyena unguis-cati (L.) A.H. Gentry) (Bignoniaceae), a major environmental weed in Queensland and New South Wales, is a Weed of National Significance and an approved target for biological control. A leaf-mining jewel beetle, Hylaeogena jureceki Obenberger (Coleoptera: Buprestidae), first collected in 2002 from D. unguis-cati in Brazil and Argentina, was imported from South Africa into a quarantine facility in Brisbane in 2009 for host-specificity testing. H. jureceki adults chew holes in leaves and lay eggs on leaf margins and the emerging larvae mine within the leaves of D. unguis-cati. The generation time (egg to adult) of H. jureceki under quarantine conditions was 55.4 ± 0.2 days. Host-specificity trials conducted in Australia on 38 plant species from 11 families supplement and support South African studies which indicated that H. jureceki is highly host-specific and does not pose a risk to any non-target plant species in Australia. In no-choice tests, adults survived significantly longer (>32 weeks) on D. unguis-cati than on non-target test plant species (<3 weeks). Oviposition occurred on D. unguis-cati and one non-target test plant species, Citharexylum spinosum (Verbenaceae), but no larval development occurred on the latter species. In choice tests involving D. unguis-cati, C. spinosum and Avicennia marina (Avicenniaceae), feeding and oviposition were evident only on D. unguis-cati. The insect was approved for field release in Australia in May 2012.

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Peanut (Arachis hypogaea L.) is an economically important legume crop in irrigated production areas of northern Australia. Although the potential pod yield of the crop in these areas is about 8 t ha(-1), most growers generally obtain around 5 t ha(-1), partly due to poor irrigation management. Better information and tools that are easy to use, accurate, and cost-effective are therefore needed to help local peanut growers improve irrigation management. This paper introduces a new web-based decision support system called AQUAMAN that was developed to assist Australian peanut growers schedule irrigations. It simulates the timing and depth of future irrigations by combining procedures from the food and agriculture organization (FAO) guidelines for irrigation scheduling (FAO-56) with those of the agricultural production systems simulator (APSIM) modeling framework. Here, we present a description of AQUAMAN and results of a series of activities (i.e., extension activities, case studies, and a survey) that were conducted to assess its level of acceptance among Australian peanut growers, obtain feedback for future improvements, and evaluate its performance. Application of the tool for scheduling irrigations of commercial peanut farms since its release in 2004-2005 has shown good acceptance by local peanuts growers and potential for significantly improving yield. Limited comparison with the farmer practice of matching the pan evaporation demand during rain-free periods in 2006-2007 and 2008-2009 suggested that AQUAMAN enabled irrigation water savings of up to 50% and the realization of enhanced water and irrigation use efficiencies.

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High levels of hydrological connectivity during seasonal flooding provide significant opportunities for movements of fish between rivers and their floodplains, estuaries and the sea, possibly mediating food web subsidies among habitats. To determine the degree of utilisation of food sources from different habitats in a tropical river with a short floodplain inundation duration (similar to 2 months), stable isotope ratios in fishes and their available food were measured from three habitats (inundated floodplain, dry season freshwater, coastal marine) in the lower reaches of the Mitchell River, Queensland (Australia). Floodplain food sources constituted the majority of the diet of large-bodied fishes (barramundi Lates calcarifer, catfish Neoarius graeffei) captured on the floodplain in the wet season and for gonadal tissues of a common herbivorous fish (gizzard shad Nematalosa come), the latter suggesting that critical reproductive phases are fuelled by floodplain production. Floodplain food sources also subsidised barramundi from the recreational fishery in adjacent coastal and estuarine areas, and the broader fish community from a freshwater lagoon. These findings highlight the importance of the floodplain in supporting the production of large fishes in spite of the episodic nature and relatively short duration of inundation compared to large river floodplains of humid tropical regions. They also illustrate the high degree of food web connectivity mediated by mobile fish in this system in the absence of human modification, and point to the potential consequences of water resource development that may reduce or eliminate hydrological connectivity between the river and its floodplain.

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Precipitation-induced runoff and leaching from milled peat mining mires by peat types: a comparative method for estimating the loading of water bodies during peat production. This research project in environmental geology has arisen out of an observed need to be able to predict more accurately the loading of watercourses with detrimental organic substances and nutrients from already existing and planned peat production areas, since the authorities capacity for insisting on such predictions covering the whole duration of peat production in connection with evaluations of environmental impact is at present highly limited. National and international decisions regarding monitoring of the condition of watercourses and their improvement and restoration require more sophisticated evaluation methods in order to be able to forecast watercourse loading and its environmental impacts at the stage of land-use planning and preparations for peat production.The present project thus set out from the premise that it would be possible on the basis of existing mire and peat data properties to construct estimates for the typical loading from production mires over the whole duration of their exploitation. Finland has some 10 million hectares of peatland, accounting for almost a third of its total area. Macroclimatic conditions have varied in the course of the Holocene growth and development of this peatland, and with them the habitats of the peat-forming plants. Temperatures and moisture conditions have played a significant role in determining the dominant species of mire plants growing there at any particular time, the resulting mire types and the accumulation and deposition of plant remains to form the peat. The above climatic, environmental and mire development factors, together with ditching, have contributed, and continue to contribute, to the existence of peat horizons that differ in their physical and chemical properties, leading to differences in material transport between peatlands in a natural state and mires that have been ditched or prepared for forestry and peat production. Watercourse loading from the ditching of mires or their use for peat production can have detrimental effects on river and lake environments and their recreational use, especially where oxygen-consuming organic solids and soluble organic substances and nutrients are concerned. It has not previously been possible, however, to estimate in advance the watercourse loading likely to arise from ditching and peat production on the basis of the characteristics of the peat in a mire, although earlier observations have indicated that watercourse loading from peat production can vary greatly and it has been suggested that differences in peat properties may be of significance in this. Sprinkling is used here in combination with simulations of conditions in a milled peat production area to determine the influence of the physical and chemical properties of milled peats in production mires on surface runoff into the drainage ditches and the concentrations of material in the runoff water. Sprinkling and extraction experiments were carried out on 25 samples of milled Carex (C) and Sphagnum (S) peat of humification grades H 2.5 8.5 with moisture content in the range 23.4 89% on commencement of the first sprinkling, which was followed by a second sprinkling 24 hours later. The water retention capacity of the peat was best, and surface runoff lowest, with Sphagnum and Carex peat samples of humification grades H 2.5 6 in the moisture content class 56 75%. On account of the hydrophobicity of dry peat, runoff increased in a fairly regular manner with drying of the sample from 55% to 24 30%. Runoff from the samples with an original moisture content over 55% increased by 63% in the second round of sprinkling relative to the first, as they had practically reached saturation point on the first occasion, while those with an original moisture content below 55% retained their high runoff in the second round, due to continued hydrophobicity. The well-humified samples (H 6.5 8.5) with a moisture content over 80% showed a low water retention capacity and high runoff in both rounds of sprinkling. Loading of the runoff water with suspended solids, total phosphorus and total nitrogen, and also the chemical oxygen demand (CODMn O2), varied greatly in the sprinkling experiment, depending on the peat type and degree of humification, but concentrations of the same substances in the two sprinklings were closely or moderately closely correlated and these correlations were significant. The concentrations of suspended solids in the runoff water observed in the simulations of a peat production area and the direct surface runoff from it into the drainage ditch system in response to rain (sprinkling intensity 1.27 mm/min) varied c. 60-fold between the degrees of humification in the case of the Carex peats and c. 150-fold for the Sphagnum peats, while chemical oxygen demand varied c. 30-fold and c. 50-fold, respectively, total phosphorus c. 60-fold and c. 66-fold, total nitrogen c. 65-fold and c. 195-fold and ammonium nitrogen c. 90-fold and c. 30-fold. The increases in concentrations in the runoff water were very closely correlated with increases in humification of the peat. The correlations of the concentrations measured in extraction experiments (48 h) with peat type and degree of humification corresponded to those observed in the sprinkler experiments. The resulting figures for the surface runoff from a peat production area into the drainage ditches simulated by means of sprinkling and material concentrations in the runoff water were combined with statistics on the mean extent of daily rainfall (0 67 mm) during the frost-free period of the year (May October) over an observation period of 30 years to yield typical annual loading figures (kg/ha) for suspended solids (SS), chemical oxygen demand of organic matter (CODmn O2), total phosphorus (tot. P) and total nitrogen (tot. N) entering the ditches with respect to milled Carex (C) and Sphagnum (S) peats of humification grades H 2.5 8.5. In order to calculate the loading of drainage ditches from a milled peat production mire with the aid of these annual comparative values (in kg/ha), information is required on the properties of the intended production mire and its peat. Once data are available on the area of the mire, its peat depth, peat types and their degrees of humification, dry matter content, calorific value and corresponding energy content, it is possible to produce mutually comparable estimates for individual mires with respect to the annual loading of the drainage ditch system and the surrounding watercourse for the whole service life of the production area, the duration of this service life, determinations of energy content and the amount of loading per unit of energy generated (kg/MWh). In the 8 mires in the Köyhäjoki basin, Central Ostrobothnia, taken as an example, the loading of suspended solids (SS) in the drainage ditch networks calculated on the basis of the typical values obtained here and existing mire and peat data and expressed per unit of energy generated varied between the mires and horizons in the range 0.9 16.5 kg/MWh. One of the aims of this work was to develop means of making better use of existing mire and peat data and the results of corings and other field investigations. In this respect combination of the typical loading values (kg/ha) obtained here for S, SC, CS and C peats and the various degrees of humification (H 2.5 8.5) with the above mire and peat data by means of a computer program for the acquisition and handling of such data would enable all the information currently available and that deposited in the system in the future to be used for defining watercourse loading estimates for mires and comparing them with the corresponding estimates of energy content. The intention behind this work has been to respond to the challenge facing the energy generation industry to find larger peat production areas that exert less loading on the environment and to that facing the environmental authorities to improve the means available for estimating watercourse loading from peat production and its environmental impacts in advance. The results conform well to the initial hypothesis and to the goals laid down for the research and should enable watercourse loading from existing and planned peat production to be evaluated better in the future and the resulting impacts to be taken into account when planning land use and energy generation. The advance loading information available in this way would be of value in the selection of individual peat production areas, the planning of their exploitation, the introduction of water protection measures and the planning of loading inspections, in order to achieve controlled peat production that pays due attention to environmental considerations.

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User generated information such as product reviews have been booming due to the advent of web 2.0. In particular, rich information associated with reviewed products has been buried in such big data. In order to facilitate identifying useful information from product (e.g., cameras) reviews, opinion mining has been proposed and widely used in recent years. In detail, as the most critical step of opinion mining, feature extraction aims to extract significant product features from review texts. However, most existing approaches only find individual features rather than identifying the hierarchical relationships between the product features. In this paper, we propose an approach which finds both features and feature relationships, structured as a feature hierarchy which is referred to as feature taxonomy in the remainder of the paper. Specifically, by making use of frequent patterns and association rules, we construct the feature taxonomy to profile the product at multiple levels instead of single level, which provides more detailed information about the product. The experiment which has been conducted based upon some real world review datasets shows that our proposed method is capable of identifying product features and relations effectively.

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Telecommunications network management is based on huge amounts of data that are continuously collected from elements and devices from all around the network. The data is monitored and analysed to provide information for decision making in all operation functions. Knowledge discovery and data mining methods can support fast-pace decision making in network operations. In this thesis, I analyse decision making on different levels of network operations. I identify the requirements decision-making sets for knowledge discovery and data mining tools and methods, and I study resources that are available to them. I then propose two methods for augmenting and applying frequent sets to support everyday decision making. The proposed methods are Comprehensive Log Compression for log data summarisation and Queryable Log Compression for semantic compression of log data. Finally I suggest a model for a continuous knowledge discovery process and outline how it can be implemented and integrated to the existing network operations infrastructure.

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Segmentation is a data mining technique yielding simplified representations of sequences of ordered points. A sequence is divided into some number of homogeneous blocks, and all points within a segment are described by a single value. The focus in this thesis is on piecewise-constant segments, where the most likely description for each segment and the most likely segmentation into some number of blocks can be computed efficiently. Representing sequences as segmentations is useful in, e.g., storage and indexing tasks in sequence databases, and segmentation can be used as a tool in learning about the structure of a given sequence. The discussion in this thesis begins with basic questions related to segmentation analysis, such as choosing the number of segments, and evaluating the obtained segmentations. Standard model selection techniques are shown to perform well for the sequence segmentation task. Segmentation evaluation is proposed with respect to a known segmentation structure. Applying segmentation on certain features of a sequence is shown to yield segmentations that are significantly close to the known underlying structure. Two extensions to the basic segmentation framework are introduced: unimodal segmentation and basis segmentation. The former is concerned with segmentations where the segment descriptions first increase and then decrease, and the latter with the interplay between different dimensions and segments in the sequence. These problems are formally defined and algorithms for solving them are provided and analyzed. Practical applications for segmentation techniques include time series and data stream analysis, text analysis, and biological sequence analysis. In this thesis segmentation applications are demonstrated in analyzing genomic sequences.

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Matrix decompositions, where a given matrix is represented as a product of two other matrices, are regularly used in data mining. Most matrix decompositions have their roots in linear algebra, but the needs of data mining are not always those of linear algebra. In data mining one needs to have results that are interpretable -- and what is considered interpretable in data mining can be very different to what is considered interpretable in linear algebra. --- The purpose of this thesis is to study matrix decompositions that directly address the issue of interpretability. An example is a decomposition of binary matrices where the factor matrices are assumed to be binary and the matrix multiplication is Boolean. The restriction to binary factor matrices increases interpretability -- factor matrices are of the same type as the original matrix -- and allows the use of Boolean matrix multiplication, which is often more intuitive than normal matrix multiplication with binary matrices. Also several other decomposition methods are described, and the computational complexity of computing them is studied together with the hardness of approximating the related optimization problems. Based on these studies, algorithms for constructing the decompositions are proposed. Constructing the decompositions turns out to be computationally hard, and the proposed algorithms are mostly based on various heuristics. Nevertheless, the algorithms are shown to be capable of finding good results in empirical experiments conducted with both synthetic and real-world data.