Fast adaptive real-time classification for data streams with concept drift

An important application of Big Data Analytics is the real-time analysis of streaming data. Streaming data imposes unique challenges to data mining algorithms, such as concept drifts, the need to analyse the data on the fly due to unbounded data streams and scalable algorithms due to potentially high throughput of data. Real-time classification algorithms that are adaptive to concept drifts and fast exist, however, most approaches are not naturally parallel and are thus limited in their scalability. This paper presents work on the Micro-Cluster Nearest Neighbour (MC-NN) classifier. MC-NN is based on an adaptive statistical data summary based on Micro-Clusters. MC-NN is very fast and adaptive to concept drift whilst maintaining the parallel properties of the base KNN classifier. Also MC-NN is competitive compared with existing data stream classifiers in terms of accuracy and speed.

Contrasting fast precipitation responses to tropospheric and stratospheric ozone forcing

The precipitation response to radiative forcing (RF) can be decomposed into a fast precipitation response (FPR), which depends on the atmospheric component of RF, and a slow response, which depends on surface temperature change. We present the first detailed climate model study of the FPR due to tropospheric and stratospheric ozone changes. The FPR depends strongly on the altitude of ozone change. Increases below about 3 km cause a positive FPR; increases above cause a negative FPR. The FPR due to stratospheric ozone change is, per unit RF, about 3 times larger than that due to tropospheric ozone. As historical ozone trends in the troposphere and stratosphere are opposite in sign, so too are the FPRs. Simple climate model calculations of the time-dependent total (fast and slow) precipitation change, indicate that ozone's contribution to precipitation change in 2011, compared to 1765, could exceed 50% of that due to CO2 change.

Preconditioning 2D integer data for fast convex hull computations

In order to accelerate computing the convex hull on a set of n points, a heuristic procedure is often applied to reduce the number of points to a set of s points, s ≤ n, which also contains the same hull. We present an algorithm to precondition 2D data with integer coordinates bounded by a box of size p × q before building a 2D convex hull, with three distinct advantages. First, we prove that under the condition min(p, q) ≤ n the algorithm executes in time within O(n); second, no explicit sorting of data is required; and third, the reduced set of s points forms a simple polygonal chain and thus can be directly pipelined into an O(n) time convex hull algorithm. This paper empirically evaluates and quantifies the speed up gained by preconditioning a set of points by a method based on the proposed algorithm before using common convex hull algorithms to build the final hull. A speedup factor of at least four is consistently found from experiments on various datasets when the condition min(p, q) ≤ n holds; the smaller the ratio min(p, q)/n is in the dataset, the greater the speedup factor achieved.

Fast and slow precipitation responses to individual climate forcers: a PDRMIP multi-model study

Precipitation is expected to respond differently to various drivers of anthropogenic climate change. We present the first results from the Precipitation Driver and Response Model Intercomparison Project (PDRMIP), where nine global climate models have perturbed CO2, CH4, black carbon, sulfate, and solar insolation. We divide the resulting changes to global mean and regional precipitation into fast responses that scale with changes in atmospheric absorption and slow responses scaling with surface temperature change. While the overall features are broadly similar between models, we find significant regional intermodel variability, especially over land. Black carbon stands out as a component that may cause significant model diversity in predicted precipitation change. Processes linked to atmospheric absorption are less consistently modeled than those linked to top-of-atmosphere radiative forcing. We identify a number of land regions where the model ensemble consistently predicts that fast precipitation responses to climate perturbations dominate over the slow, temperature-driven responses.

Fast and slow responses of Southern Ocean sea surface temperature to SAM in coupled climate models

We investigate how sea surface temperatures (SSTs) around Antarctica respond to the Southern An- nular Mode (SAM) on multiple timescales. To that end we examine the relationship between SAM and SST within unperturbed preindustrial control simulations of coupled general circulation models (GCMs) included in the Climate Modeling Intercomparison Project phase 5 (CMIP5). We develop a technique to extract the re- sponse of the Southern Ocean SST (55◦S−70◦S) to a hypothetical step increase in the SAM index. We demonstrate that in many GCMs, the expected SST step re- sponse function is nonmonotonic in time. Following a shift to a positive SAM anomaly, an initial cooling regime can transition into surface warming around Antarctica. However, there are large differences across the CMIP5 ensemble. In some models the step response function never changes sign and cooling persists, while in other GCMs the SST anomaly crosses over from negative to positive values only three years after a step increase in the SAM. This intermodel diversity can be related to differences in the models’ climatological thermal ocean stratification in the region of seasonal sea ice around Antarctica. Exploiting this relationship, we use obser- vational data for the time-mean meridional and vertical temperature gradients to constrain the real Southern Ocean response to SAM on fast and slow timescales.

Design and analysis of a haptic device design for large and fast movements

Haptic devices tend to be kept small as it is easier to achieve a large change of stiffness with a low associated apparent mass. If large movements are required there is a usually a reduction in the quality of the haptic sensations which can be displayed. The typical measure of haptic device performance is impedance-width (z-width) but this does not account for actuator saturation, usable workspace or the ability to do rapid movements. This paper presents the analysis and evaluation of a haptic device design, utilizing a variant of redundant kinematics, sometimes referred to as a macro-micro configuration, intended to allow large and fast movements without loss of impedance-width. A brief mathematical analysis of the design constraints is given and a prototype system is described where the effects of different elements of the control scheme can be examined to better understand the potential benefits and trade-offs in the design. Finally, the performance of the system is evaluated using a Fitts’ Law test and found to compare favourably with similar evaluations of smaller workspace devices.

A fast adaptive tunable RBF network for nonstationary systems

This paper describes a novel on-line learning approach for radial basis function (RBF) neural network. Based on an RBF network with individually tunable nodes and a fixed small model size, the weight vector is adjusted using the multi-innovation recursive least square algorithm on-line. When the residual error of the RBF network becomes large despite of the weight adaptation, an insignificant node with little contribution to the overall system is replaced by a new node. Structural parameters of the new node are optimized by proposed fast algorithms in order to significantly improve the modeling performance. The proposed scheme describes a novel, flexible, and fast way for on-line system identification problems. Simulation results show that the proposed approach can significantly outperform existing ones for nonstationary systems in particular.

Effect of enzymatic pretreatment and increasing the organic loading rate of lipid-rich wastewater treated in a hybrid UASB reactor

This study aimed at evaluating the effect of increasing organic loading rates and of enzyme pretreatment on the stability and efficiency of a hybrid upflow anaerobic sludge blanket reactor (UASBh) treating dairy effluent. The UASBh was submitted to the following average organic loading rates (OLR) 0.98 Kg.m(-3).d(-1), 4.58 Kg.m(-3).d(-1), 8.89 Kg.m(-3).d(-1) and 15.73 Kg.m(-3).d(-1), and with the higher value, the reactor was fed with effluent with and without an enzymatic pretreatment to hydrolyze fats. The hydraulic detention time was 24 h, and the temperature was 30 +/- 2 degrees C. The reactor was equipped with a superior foam bed and showed good efficiency and stability until an OLR of 8.89 Kg.m(-3).d(-1). The foam bed was efficient for solid retention and residual volatile acid concentration consumption. The enzymatic pretreatment did not contribute to the process stability, propitiating loss in both biomass and system efficiency. Specific methanogenic activity tests indicated the presence of inhibition after the sludge had been submitted to the pretreated effluent It was concluded that continuous exposure to the hydrolysis products or to the enzyme caused a dramatic drop in the efficiency and stability of the process, and the single exposure of the biomass to this condition did not inhibit methane formation. (C) 2011 Elsevier B.V. All rights reserved.

Effect of agitation on the performance of an anaerobic sequencing batch biofilm reactor in the treatment of dairy effluents

Agitation rate is an important parameter in the operation of Anaerobic Sequencing Biofilm Batch Reactors (ASBBRs), and a proper agitation rate guarantees good mixing, improves mass transfer, and enhances the solubility of the particulate organic matter. Dairy effluents have a high amount of particulate organic matter, and their anaerobic digestion presents inhibitory intermediates (e. g., long-chain fatty acids). The importance of studying agitation in such batch systems is clear. The present study aimed to evaluate how agitation frequency influences the anaerobic treatment of dairy effluents. The ASBBR was fed with wastewater from milk pasteurisation process and cheese manufacture with no whey segregation. The organic matter concentration, measured as chemical oxygen demand (COD), was maintained at approximately 8,000 mg/L. The reactor was operated with four agitation frequencies: 500 rpm, 350 rpm, 200 rpm, and no agitation. In terms of COD removal efficiency, similar results were observed for 500 rpm and 350 rpm (around 90%) and for 200 rpm and no agitation (around 80%). Increasing the system`s agitation thus not only improved the global efficiency of organic matter removal but also influenced volatile acid production and consumption and clearly modified this balance in each experimental condition.

Fast magnetic reconnection and energetic particle acceleration

Our numerical simulations show that the reconnection of magnetic field becomes fast in the presence of weak turbulence in the way consistent with the Lazarian and Vishniac (1999) model of fast reconnection. We trace particles within our numerical simulations and show that the particles can be efficiently accelerated via the first order Fermi acceleration. We discuss the acceleration arising from reconnection as a possible origin of the anomalous cosmic rays measured by Voyagers. (C) 2010 Elsevier Ltd. All rights reserved.

Imprints of fast-rotating massive stars in the Galactic Bulge

The first stars that formed after the Big Bang were probably massive(1), and they provided the Universe with the first elements heavier than helium (`metals`), which were incorporated into low-mass stars that have survived to the present(2,3). Eight stars in the oldest globular cluster in the Galaxy, NGC 6522, were found to have surface abundances consistent with the gas from which they formed being enriched by massive stars(4) (that is, with higher alpha-element/Fe and Eu/Fe ratios than those of the Sun). However, the same stars have anomalously high abundances of Ba and La with respect to Fe(4), which usually arises through nucleosynthesis in low-mass stars(5) (via the slow-neutron-capture process, or s-process). Recent theory suggests that metal-poor fast-rotating massive stars are able to boost the s-process yields by up to four orders of magnitude(6), which might provide a solution to this contradiction. Here we report a reanalysis of the earlier spectra, which reveals that Y and Sr are also over-abundant with respect to Fe, showing a large scatter similar to that observed in extremely metal-poor stars(7), whereas C abundances are not enhanced. This pattern is best explained as originating in metal-poor fast-rotating massive stars, which might point to a common property of the first stellar generations and even of the `first stars`.

Fast or slow melting of the Marinoan snowball Earth? The cap dolostone record

The end of the Neoproterozoic era is punctuated by two global glacial events marked by the presence of glacial deposits overlaid by cap carbonates. Duration of glacial intervals is now consistently constrained to 3-12 million years but the duration of the post-glacial transition is more controversial due to the uncertainty in cap dolostone sedimentation rates. Indeed, the presence of several stratabound magnetic reversals in Brazilian cap dolostones recently questioned the short sedimentation duration (a few thousand years at most) that was initially suggested for these rocks. Here, we present new detailed magnetostratigraphic data of the Mirassol d`Oeste cap dolostones (Mato Grosso, Brazil) and ""bomb-spike"" calibrated AMS (14)C data of microbial mats from the Lagoa Vermelha (Rio de Janeiro, Brazil). We also compile sedimentary, isotopic and microbiological data from post-Marinoan outcrops and/or recent depositional analogues in order to discuss the deposition rate of Marinoan cap dolostones and to infer an estimation of the deglaciation duration in the snowball Earth aftermath. Taken together, the various data point to a sedimentation duration in the range of a few 10(5) years. (C) 2010 Elsevier B.V. All rights reserved.

Effect of Short-term High-Dose Creatine Supplementation on Measured GFR in a Young Man With a Single Kidney

It currently is unknown whether creatine supplementation is safe for people with or at risk of kidney disease. We report on the short-term effects of creatine supplementation on kidney function in a young man with a single kidney and mildly decreased glomerular filtration rate (GFR). A 20-year-old man who had undergone unilateral nephrectomy and presented with mildly decreased GFR without kidney damage underwent a trial with 35 days of creatine supplementation (20 g/d for 5 days followed by 5 g/d for the next 30 days) and had his kidney function monitored. After the intervention, (51)Cr-EDTA clearance (pre, 81.6 mL/min/1.73 m(2); post, 82.0 mL/min/1.73 m(2)), proteinuria (protein excretion: pre, 130 mg/d; post, 120 mg/d), and electrolyte levels were unchanged. Albuminuria, serum urea level, and estimated creatinine clearance were decreased (pre, 4.6 mg/d; post, 2.9 mg/d; pre, 37 mg/d; post, 28 mg/dL; and pre, 88 mL/min/1.73 m(2); post, 71 mL/min/1.73 m(2), respectively), whereas serum creatinine level was slightly increased (pre, 1.03 mg/dL; post, 1.27 mg/dL), falsely suggesting kidney function impairment. This prospective report suggests that short-term creatine supplementation may not affect kidney function in an individual with a single kidney, mild decreased GFR, and ingesting a high-protein diet (ie, 2.8 g/kg/d). This finding has great relevance considering that creatine-induced kidney disease has been a growing concern, even for healthy people. Am J Kidney Dis 55: e7-e9. (C) 2010 by the National Kidney Foundation, Inc.

Least square projection: A fast high-precision multidimensional projection technique and its application to document mapping

The problem of projecting multidimensional data into lower dimensions has been pursued by many researchers due to its potential application to data analyses of various kinds. This paper presents a novel multidimensional projection technique based on least square approximations. The approximations compute the coordinates of a set of projected points based on the coordinates of a reduced number of control points with defined geometry. We name the technique Least Square Projections ( LSP). From an initial projection of the control points, LSP defines the positioning of their neighboring points through a numerical solution that aims at preserving a similarity relationship between the points given by a metric in mD. In order to perform the projection, a small number of distance calculations are necessary, and no repositioning of the points is required to obtain a final solution with satisfactory precision. The results show the capability of the technique to form groups of points by degree of similarity in 2D. We illustrate that capability through its application to mapping collections of textual documents from varied sources, a strategic yet difficult application. LSP is faster and more accurate than other existing high-quality methods, particularly where it was mostly tested, that is, for mapping text sets.