22 resultados para Recursive Partitioning and Regression Trees (RPART)

em Indian Institute of Science - Bangalore - Índia


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The problem of scheduling divisible loads in distributed computing systems, in presence of processor release time is considered. The objective is to find the optimal sequence of load distribution and the optimal load fractions assigned to each processor in the system such that the processing time of the entire processing load is a minimum. This is a difficult combinatorial optimization problem and hence genetic algorithms approach is presented for its solution.

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The present work presents the results of experimental investigation of semi-solid rheocasting of A356 Al alloy using a cooling slope. The experiments have been carried out following Taguchi method of parameter design (orthogonal array of L-9 experiments). Four key process variables (slope angle, pouring temperature, wall temperature, and length of travel of the melt) at three different levels have been considered for the present experimentation. Regression analysis and analysis of variance (ANOVA) has also been performed to develop a mathematical model for degree of sphericity evolution of primary alpha-Al phase and to find the significance and percentage contribution of each process variable towards the final outcome of degree of sphericity, respectively. The best processing condition has been identified for optimum degree of sphericity (0.83) as A(3), B-3, C-2, D-1 i.e., slope angle of 60 degrees, pouring temperature of 650 degrees C, wall temperature 60 degrees C, and 500 mm length of travel of the melt, based on mean response and signal to noise ratio (SNR). ANOVA results shows that the length of travel has maximum impact on degree of sphericity evolution. The predicted sphericity obtained from the developed regression model and the values obtained experimentally are found to be in good agreement with each other. The sphericity values obtained from confirmation experiment, performed at 95% confidence level, ensures that the optimum result is correct and also the confirmation experiment values are within permissible limits. (c) 2014 Elsevier Ltd. All rights reserved.

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How similar species co-exist in nature is a fundamental question in community ecology. Resource partitioning has been studied in desert lizard communities across four continents, but data from South Asia is lacking. We used area-constrained visual encounter surveys to study community composition and spatial and temporal resource partitioning in a lizard community during summer in the Thar Desert, western India, addressing an important biogeographic gap in knowledge. Twelve one-hectare grids divided into 25 m x 25 m plots were placed across four habitats barren dunes, stabilized dunes, grassland, and rocky hills. We recorded 1039 sightings of 12 species during 84 sampling sessions. Lizard abundance decreased in the order stabilized dunes > grassland > barren dunes > rocky hills; richness was in roughly the opposite order. Resource partitioning was examined for the seven commonest species. Overall spatial overlap was low (<0.6) between species pairs. Overlap was higher within habitats, but species showed finer separation through use of different microhabitat categories and specific spatial resources, as well as by positioning at different distances to vegetation. Diurnal species were also separated by peak time of activity. Space appears to be an important resource dimension facilitating coexistence in this desert lizard community. (C) 2015 Elsevier Ltd. All rights reserved.

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In the nursery pollination system of figs (Ficus, Moraceae), flower-bearing receptacles called syconia breed pollinating wasps and are units of both pollination and seed dispersal. Pollinators and mammalian seed dispersers are attracted to syconia by volatile organic compounds (VOCs). In monoecious figs, syconia produce both wasps and seeds, while in (gyno)dioecious figs, male (gall) fig trees produce wasps and female (seed) fig trees produce seeds. VOCs were collected using dynamic headspace adsorption methods on freshly collected figs from different trees using Super Q® collection traps. VOC profiles were determined using gas chromatography–mass spectrometry (GC–MS).The VOC profile of receptive and dispersal phase figs were clearly different only in the dioecious mammal-dispersed Ficus hispida but not in dioecious bird-dispersed F. exasperata and monoecious bird-dispersed F. tsjahela. The VOC profile of dispersal phase female figs was clearly different from that of male figs only in F. hispida but not in F. exasperata, as predicted from the phenology of syconium production which only in F. hispida overlaps between male and female trees. Greater difference in VOC profile in F. hispida might ensure preferential removal of seed figs by dispersal agents when gall figs are simultaneously available.The VOC profile of only mammal-dispersed female figs of F. hispida had high levels of fatty acid derivatives such as amyl-acetates and 2-heptanone, while monoterpenes, sesquiterpenes and shikimic acid derivatives were predominant in the other syconial types. A bird- and mammal-repellent compound methyl anthranilate occurred only in gall figs of both dioecious species, as expected, since gall figs containing wasp pollinators should not be consumed by dispersal agents.

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Nanotechnology is a new technology which is generating a lot of interest among academicians, practitioners and scientists. Critical research is being carried out in this area all over the world.Governments are creating policy initiatives to promote developments it the nanoscale science and technology developments. Private investment is also seeing a rising trend. Large number of academic institutions and national laboratories has set up research centers that are workingon the multiple applications of nanotechnology. Wide ranges of applications are claimed for nanotechnology. This consists of materials, chemicals, textiles, semiconductors, to wonder drug delivery systems and diagnostics. Nanotechnology is considered to be a next big wave of technology after information technology and biotechnology. In fact, nanotechnology holds the promise of advances that exceed those achieved in recent decades in computers and biotechnology. Much interest in nanotechnology also could be because of the fact that enormous monetary benefits are expected from nanotechnology based products. According to NSF, revenues from nanotechnology could touch $ 1 trillion by 2015. However much of the benefits are projected ones. Realizing claimed benefits require successful development of nanoscience andv nanotechnology research efforts. That is the journey of invention to innovation has to be completed. For this to happen the technology has to flow from laboratory to market. Nanoscience and nanotechnology research efforts have to come out in the form of new products, new processes, and new platforms.India has also started its Nanoscience and Nanotechnology development program in under its 10(th) Five Year Plan and funds worth Rs. One billion have been allocated for Nanoscience and Nanotechnology Research and Development. The aim of the paper is to assess Nanoscience and Nanotechnology initiatives in India. We propose a conceptual model derived from theresource based view of the innovation. We have developed a structured questionnaire to measure the constructs in the conceptual model. Responses have been collected from 115 scientists and engineers working in the field of Nanoscience and Nanotechnology. The responses have been analyzed further by using Principal Component Analysis, Cluster Analysis and Regression Analysis.

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We propose a novel second order cone programming formulation for designing robust classifiers which can handle uncertainty in observations. Similar formulations are also derived for designing regression functions which are robust to uncertainties in the regression setting. The proposed formulations are independent of the underlying distribution, requiring only the existence of second order moments. These formulations are then specialized to the case of missing values in observations for both classification and regression problems. Experiments show that the proposed formulations outperform imputation.

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Gaussian Processes (GPs) are promising Bayesian methods for classification and regression problems. They have also been used for semi-supervised learning tasks. In this paper, we propose a new algorithm for solving semi-supervised binary classification problem using sparse GP regression (GPR) models. It is closely related to semi-supervised learning based on support vector regression (SVR) and maximum margin clustering. The proposed algorithm is simple and easy to implement. It gives a sparse solution directly unlike the SVR based algorithm. Also, the hyperparameters are estimated easily without resorting to expensive cross-validation technique. Use of sparse GPR model helps in making the proposed algorithm scalable. Preliminary results on synthetic and real-world data sets demonstrate the efficacy of the new algorithm.

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The status of the tree biomass resource was investigated in Ungra, a semi-arid village ecosystem in South India. There were 57 tree species with 12 trees capita−1 and 35 trees ha−1. Multiple benefit yielding local tree species dominated the village ecosystem, while fuel only or single end use trees accounted for a small proportion of trees. The standing tree biomass is adequate to meet the requirement of biomass fuels for cooking only for about two years. Village tree biomass is presently being depleted largely for export to urban areas. Tree regeneration is now characterized by transformation from multiple-use local tree species to a few single-use species. A large potential exists for tree biomass production along field boundaries (bunds), stream banks and roadsides. Biomass estimation equations were developed for 10 species.

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Detecting and quantifying the presence of human-induced climate change in regional hydrology is important for studying the impacts of such changes on the water resources systems as well as for reliable future projections and policy making for adaptation. In this article a formal fingerprint-based detection and attribution analysis has been attempted to study the changes in the observed monsoon precipitation and streamflow in the rain-fed Mahanadi River Basin in India, considering the variability across different climate models. This is achieved through the use of observations, several climate model runs, a principal component analysis and regression based statistical downscaling technique, and a Genetic Programming based rainfall-runoff model. It is found that the decreases in observed hydrological variables across the second half of the 20th century lie outside the range that is expected from natural internal variability of climate alone at 95% statistical confidence level, for most of the climate models considered. For several climate models, such changes are consistent with those expected from anthropogenic emissions of greenhouse gases. However, unequivocal attribution to human-induced climate change cannot be claimed across all the climate models and uncertainties in our detection procedure, arising out of various sources including the use of models, cannot be ruled out. Changes in solar irradiance and volcanic activities are considered as other plausible natural external causes of climate change. Time evolution of the anthropogenic climate change ``signal'' in the hydrological observations, above the natural internal climate variability ``noise'' shows that the detection of the signal is achieved earlier in streamflow as compared to precipitation for most of the climate models, suggesting larger impacts of human-induced climate change on streamflow than precipitation at the river basin scale.

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Luteal insufficiency affects fertility and hence study of mechanisms that regulate corpus luteum (CL) function is of prime importance to overcome infertility problems. Exploration of human genome sequence has helped to study the frequency of single nucleotide polymorphisms (SNPs). Clinical benefits of screening SNPs in infertility are being recognized well in recent times. Examining SNPs in genes associated with maintenance and regression of CL may help to understand unexplained luteal insufficiency and related infertility. Publicly available microarray gene expression databases reveal the global gene expression patterns in primate CL during the different functional state. We intend to explore computationally the deleterious SNPs of human genes reported to be common targets of luteolysin and luteotropin in primate CL Different computational algorithms were used to dissect out the functional significance of SNPs in the luteinizing hormone sensitive genes. The results raise the possibility that screening for SNPs might be integrated to evaluate luteal insufficiency associated with human female infertility for future studies. (C) 2012 Elsevier B.V. All rights reserved,

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Video decoders used in emerging applications need to be flexible to handle a large variety of video formats and deliver scalable performance to handle wide variations in workloads. In this paper we propose a unified software and hardware architecture for video decoding to achieve scalable performance with flexibility. The light weight processor tiles and the reconfigurable hardware tiles in our architecture enable software and hardware implementations to co-exist, while a programmable interconnect enables dynamic interconnection of the tiles. Our process network oriented compilation flow achieves realization agnostic application partitioning and enables seamless migration across uniprocessor, multi-processor, semi hardware and full hardware implementations of a video decoder. An application quality of service aware scheduler monitors and controls the operation of the entire system. We prove the concept through a prototype of the architecture on an off-the-shelf FPGA. The FPGA prototype shows a scaling in performance from QCIF to 1080p resolutions in four discrete steps. We also demonstrate that the reconfiguration time is short enough to allow migration from one configuration to the other without any frame loss.

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Gaussian processes (GPs) are promising Bayesian methods for classification and regression problems. Design of a GP classifier and making predictions using it is, however, computationally demanding, especially when the training set size is large. Sparse GP classifiers are known to overcome this limitation. In this letter, we propose and study a validation-based method for sparse GP classifier design. The proposed method uses a negative log predictive (NLP) loss measure, which is easy to compute for GP models. We use this measure for both basis vector selection and hyperparameter adaptation. The experimental results on several real-world benchmark data sets show better orcomparable generalization performance over existing methods.

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1. Whether life-history traits can determine community composition and structure is an important question that has been well explored theoretically, but has received scant empirical attention. Life-history traits of a seven-member community of galler and parasitoid fig wasp species (Chalcidoidea), developing within the inflorescences (syconia) of Ficus racemosa (Moraceae) in India, were determined and used to examine community structure and ecology. 2. Gallers were pro-ovigenic (all eggs are mature upon adult emergence) whereas parasitoids were synovigenic (eggs mature progressively during adult lifespan). Initial egg load was correlated with body size for some species, and there was a trade-off between egg number and egg size across all species. Although all species completed their development and left the syconium concurrently, they differed in their adult and pre-adult lifespans. Providing sucrose solutions increased parasitoid lifespan but had no effect on the longevity of some galler species. While feeding regimes and body size affected longevity in most species, an interaction effect between these variables was detected for only one species. 3. Life-history traits of wasp species exhibited a continuum in relation to their arrival sequence at syconia for oviposition during syconium development, and therefore reflected their ecology. The largest number of eggs, smallest egg sizes, and shortest longevities were characteristic of the earliest-arriving galling wasps at the smallest, immature syconia; the converse characterised the later-arriving parasitoids at the larger, already parasitised syconia. Thus life history is an important correlate of community resource partitioning and can be used to understand community structure. 4. This is the first comprehensive study of life-history traits in a fig wasp community. The comparative approach revealed constraints and flexibility in trait evolution.

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Condensation from the vapor state is an important technique for the preparation of nanopowders. Levitational gas condensation is one such technique that has a unique ability of attaining steady state. Here, we present the results of applying this technique to an iron-copper alloy (96Fe-4Cu). A qualitative model of the process is proposed to understand the process and the characteristics of resultant powder. A phase diagram of the alloy system in the liquid-vapor region was calculated to help understand the course of condensation, especially partitioning and coring during processing. The phase diagram could not explain coring in view of the simultaneous occurrence of solidification and the fast homogenization through diffusion in the nanoparticles; however, it could predict the very low levels of copper observed in the levitated drop. The enrichment of copper observed near the surface of the powder was considered to be a manifestation of the lower surface energy of copper compared with that of iron. Heat transfer calculations indicated that most condensed particles can undergo solidification even when they are still in the proximity of the levitated drop. It helped us to predict the temperature and the cooling rate of the powder particles as they move away from the levitated drop. The particles formed by the process seem to be single domain, single crystals that are magnetic in nature. They, thus, can agglomerate by forming a chain-like structure, which manifests as a three-dimensional network enclosing a large unoccupied space, as noticed in scanning electron microscopy and transmission electron microscopy studies. This also explains the observed low packing density of the nanopowders.

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Taking the various values ascribed to biodiversity as its point of departure rather many years ago, the present study aims at deriving a conservation strategy for Uttara Kannada. This hilly district, with the highest proportion of its area under forests in South India, is divided into five ecological zones: coastal, northern evergreen, southern evergreen, moist deciduous, and dry deciduous. The heavily-populated coastal zone includes mangrove forests and estuarine wetlands. The evergreen forests are particularly rich in the diversity of plant species which they support - including wild relatives of a number of cultivated plants. They also serve a vital function in watershed conservation. The moist deciduous forests are rich in bird species; both moist and dry deciduous forests include a number of freshwater ponds and lakes that support a high diversity of aquatic birds.Reviewing the overall distribution of biodiversity, we identify specific localities - including estuaries, evergreen forests, and moist deciduous forests - which should be set aside as Nature reserves. These larger reserves must be complemented by a network of traditionally-protected sacred groves and sacred trees that are distributed throughout the district and that protect today, for instance, the finest surviving stand of dipterocarp trees.We also spell out the necessary policy-changes in overall development strategy that should stem the ongoing decimation of biodiversity. These include (1) revitalizing community-based systems of sustainable management of village forests and protection of sacred groves and trees; (2) reorienting the usage-pattern of reserve forests from production of a limited variety of timber and softwood species for industrial consumers, to production of a larger diversity of non-wood forest produce of commercial value to support the rural economy; (3) utilizing marginal lands under private ownership for generating industrial wood supplies; and (4) provision of incentives for in situ maintenance of land-races of cultivated plants - especially evergreen, fruit-yielding trees - by the local people.It is proposed that this broad framework be now taken to the local communities, and that an action-plan be developed on the basis of inputs provided - and initiatives taken - by them.