Classification in e-procurement

Three coupled knowledge transfer partnerships used pattern recognition techniques to produce an e-procurement system which, the National Audit Office reports, could save the National Health Service £500 m per annum. An extension to the system, GreenInsight, allows the environmental impact of procurements to be assessed and savings made. Both systems require suitable products to be discovered and equivalent products recognised, for which classification is a key component. This paper describes the innovative work done for product classification, feature selection and reducing the impact of mislabelled data.

Application of complex extreme learning machine to multiclass classification problems with high dimensionality: a THz spectra classification problem

We extend extreme learning machine (ELM) classifiers to complex Reproducing Kernel Hilbert Spaces (RKHS) where the input/output variables as well as the optimization variables are complex-valued. A new family of classifiers, called complex-valued ELM (CELM) suitable for complex-valued multiple-input–multiple-output processing is introduced. In the proposed method, the associated Lagrangian is computed using induced RKHS kernels, adopting a Wirtinger calculus approach formulated as a constrained optimization problem similarly to the conventional ELM classifier formulation. When training the CELM, the Karush–Khun–Tuker (KKT) theorem is used to solve the dual optimization problem that consists of satisfying simultaneously smallest training error as well as smallest norm of output weights criteria. The proposed formulation also addresses aspects of quaternary classification within a Clifford algebra context. For 2D complex-valued inputs, user-defined complex-coupled hyper-planes divide the classifier input space into four partitions. For 3D complex-valued inputs, the formulation generates three pairs of complex-coupled hyper-planes through orthogonal projections. The six hyper-planes then divide the 3D space into eight partitions. It is shown that the CELM problem formulation is equivalent to solving six real-valued ELM tasks, which are induced by projecting the chosen complex kernel across the different user-defined coordinate planes. A classification example of powdered samples on the basis of their terahertz spectral signatures is used to demonstrate the advantages of the CELM classifiers compared to their SVM counterparts. The proposed classifiers retain the advantages of their ELM counterparts, in that they can perform multiclass classification with lower computational complexity than SVM classifiers. Furthermore, because of their ability to perform classification tasks fast, the proposed formulations are of interest to real-time applications.

Vegetation and soils feedbacks on the response of the African monsoon response to orbital forcing in early to middle Holocene

Fossil pollen, ancient lake sediments and archaeological evidence from Africa indicate that the Sahel and Sahara regions were considerably wetter than today during the early to middle Holocene period, about 12,000 to 5,000 years ago1–4. Vegetation associated with the modern Sahara/Sahel boundary was about 5° farther north, and there were more and larger lakes between 15 and 30° N. Simulations with climate models have shown that these wetter conditions were probably caused by changes in Earth's orbital parameters that increased the amplitude of the seasonal cycle of solar radiation in the Northern Hemisphere, enhanced the land-ocean temperature contrast, and thereby strengthened the African summer monsoon5–7. However, these simulations underestimated the consequent monsoon enhancement as inferred from palaeorecords4. Here we use a climate model to show that changes in vegetation and soil may have increased the climate response to orbital forcing. We find that replacing today's orbital forcing with that of the mid-Holocene increases summer precipitation by 12% between 15 and 22° N. Replacing desert with grassland, and desert soil with more loamy soil, further enhances the summer precipitation (by 6 and 10% respectively), giving a total precipitation increase of 28%. When the simulated climate changes are applied to a biome model, vegetation becomes established north of the current Sahara/Sahel boundary, thereby shrinking the area of the Sahara by 11% owing to orbital forcing alone, and by 20% owing to the combined influence of orbital forcing and the prescribed vegetation and soil changes. The inclusion of the vegetation and soil feedbacks thus brings the model simulations and palaeovegetation observations into closer agreement.

Potential role of vegetation feedback in the climate sensitivity of high-latitude regions: a case study at 6000 years B.P.

Previous climate model simulations have shown that the configuration of the Earth's orbit during the early to mid-Holocene (approximately 10–5 kyr) can account for the generally warmer-than-present conditions experienced by the high latitudes of the northern hemisphere. New simulations for 6 kyr with two atmospheric/mixed-layer ocean models (Community Climate Model, version 1, CCMl, and Global ENvironmental and Ecological Simulation of Interactive Systems, version 2, GENESIS 2) are presented here and compared with results from two previous simulations with GENESIS 1 that were obtained with and without the albedo feedback due to climate-induced poleward expansion of the boreal forest. The climate model results are summarized in the form of potential vegetation maps obtained with the global BIOME model, which facilitates visual comparisons both among models and with pollen and plant macrofossil data recording shifts of the forest-tundra boundary. A preliminary synthesis shows that the forest limit was shifted 100–200 km north in most sectors. Both CCMl and GENESIS 2 produced a shift of this magnitude. GENESIS 1 however produced too small a shift, except when the boreal forest albedo feedback was included. The feedback in this case was estimated to have amplified forest expansion by approximately 50%. The forest limit changes also show meridional patterns (greatest expansion in central Siberia and little or none in Alaska and Labrador) which have yet to be reproduced by models. Further progress in understanding of the processes involved in the response of climate and vegetation to orbital forcing will require both the deployment of coupled atmosphere-biosphere-ocean models and the development of more comprehensive observational data sets

The response of northern hemisphere extratropical climate and vegetation to orbitally-induced changes in insolation during the last interglaciation

The last interglaciation (substage 5e) provides an opportunity to examine the effects of extreme orbital changes on regional climates. We have made two atmospheric general circulation model experiments: P+T+ approximated the northern hemisphere seasonality maximum near the beginning of 5e; P-T- approximated the minimum near the end of 5e. Simulated regional climate changes have been translated into biome changes using a physiologically based model of global vegetation types. Major climatic and vegetational changes were simulated for the northern hemisphere extratropics, due to radiational effects that were both amplified and modified by atmospheric circulation changes and sea-ice feedback. P+T+ showed mid-continental summers up to 8°C warmer than present. Mid-latitude winters were 2-4°C cooler than present but in the Arctic, summer warmth reduced sea-ice extent and thickness, producing winters 2-8°C warmer than present. The tundra and taiga biomes were displaced poleward, while warm-summer steppes expanded in the mid latitudes due to drought. P-T- showed summers up to 5°C cooler than present, especially in mid latitudes. Sea ice and snowpack were thicker and lasted longer; polar desert, tundra, and taiga biomes were displaced equatorward, while cool-summer steppes and semideserts expanded due to the cooling. A slight winter warming in mid latitudes, however, caused warm-temperate evergreen forests and scrub to expand poleward. Such qualitative contrasts in the direction of climate and vegetation change during 5e should be identifiable in the paleorecord

Improved simulation of fire–vegetation interactions in the Land surface Processes and eXchanges dynamic global vegetation model (LPX-Mv1)

The Land surface Processes and eXchanges (LPX) model is a fire-enabled dynamic global vegetation model that performs well globally but has problems representing fire regimes and vegetative mix in savannas. Here we focus on improving the fire module. To improve the representation of ignitions, we introduced a reatment of lightning that allows the fraction of ground strikes to vary spatially and seasonally, realistically partitions strike distribution between wet and dry days, and varies the number of dry days with strikes. Fuel availability and moisture content were improved by implementing decomposition rates specific to individual plant functional types and litter classes, and litter drying rates driven by atmospheric water content. To improve water extraction by grasses, we use realistic plant-specific treatments of deep roots. To improve fire responses, we introduced adaptive bark thickness and post-fire resprouting for tropical and temperate broadleaf trees. All improvements are based on extensive analyses of relevant observational data sets. We test model performance for Australia, first evaluating parameterisations separately and then measuring overall behaviour against standard benchmarks. Changes to the lightning parameterisation produce a more realistic simulation of fires in southeastern and central Australia. Implementation of PFT-specific decomposition rates enhances performance in central Australia. Changes in fuel drying improve fire in northern Australia, while changes in rooting depth produce a more realistic simulation of fuel availability and structure in central and northern Australia. The introduction of adaptive bark thickness and resprouting produces more realistic fire regimes in Australian savannas. We also show that the model simulates biomass recovery rates consistent with observations from several different regions of the world characterised by resprouting vegetation. The new model (LPX-Mv1) produces an improved simulation of observed vegetation composition and mean annual burnt area, by 33 and 18% respectively compared to LPX.

Vegetation and environmental changes in Northern Anatolia between 134 and 119ka recorded in Black Sea sediments

This multiproxy study on SE Black Sea sediments provides the first detailed reconstruction of vegetation and environmental history of Northern Anatolia between 134 and 119 ka. Here, the glacial–interglacial transition is characterized by several short-lived alternating cold and warm events preceding a meltwater pulse (~ 130.4–131.7 ka). The latter is reconstructed as a cold arid period correlated to Heinrich event 11. The initial warming is evidenced at ~ 130.4 ka by increased primary productivity in the Black Sea, disappearance of ice-rafted detritus, and spreading of oaks in Anatolia. A Younger Dryas-type event is not identifiable. The Eemian vegetation succession corresponds to the main climatic phases in Europe: i) the Quercus–Juniperus phase (128.7–126.4 ka) indicates a dry continental climate; ii) the Ostrya–Corylus–Quercus–Carpinus phase (126.4–122.9 ka) suggests warm summers, mild winters, and high year-round precipitation; iii) the Fagus–Carpinus phase (122.9–119.5 ka) indicates cooling and high precipitation; and iv) increasing Pinus at ~ 121 ka marks the onset of cooler/drier conditions. Generally, pollen reconstructions suggest altitudinal/latitudinal migrations of vegetation belts in Northern Anatolia during the Eemian caused by increased transport of moisture. The evidence for the wide distribution of Fagus around the Black Sea contrasts with the European records and is likely related to climatic and genetic factors

The classification of involuntary musical imagery: the case for earworms

Involuntary musical imagery (INMI) is the subject of much recent research interest. INMI covers a number of experience types such as musical obsessions and musical hallucinations. One type of experience has been called earworms, for which the literature provides a number of definitions. In this paper we consider the origins of the term earworm in the German language literature and compare that usage with the English language literature. We consider the published literature on earworms and conclude that there is merit in distinguishing between earworms and other types of types of involuntary musical imagery described in the scientific literature: e.g. musical hallucinations, musical obsessions. We also describe other experiences that can be considered under the term INMI. The aim of future research could be to ascertain similarities and differences between types of INMI with a view to refining the classification scheme proposed here.

Effects of past climate variability on fire and vegetation in the cerrãdo savanna of the Huanchaca Mesetta, NE Bolivia

Cerrãdo savannas have the greatest fire activity of all major global land-cover types and play a significant role in the global carbon cycle. During the 21st century, temperatures are projected to increase by ∼ 3 ◦C coupled with a precipitation decrease of ∼ 20 %. Although these conditions could potentially intensify drought stress, it is unknown how that might alter vegetation composition and fire regimes. To assess how Neotropical savannas responded to past climate changes, a 14 500-year, high-resolution, sedimentary record from Huanchaca Mesetta, a palm swamp located in the cerrãdo savanna in northeastern Bolivia, was analyzed with phytoliths, stable isotopes, and charcoal. A nonanalogue, cold-adapted vegetation community dominated the Lateglacial–early Holocene period (14 500–9000 cal yr BP, which included trees and C3 Pooideae and C4 Panicoideae grasses. The Lateglacial vegetation was fire-sensitive and fire activity during this period was low, likely responding to fuel availability and limitation. Although similar vegetation characterized the early Holocene, the warming conditions associated with the onset of the Holocene led to an initial increase in fire activity. Huanchaca Mesetta became increasingly firedependent during the middle Holocene with the expansion of C4 fire-adapted grasses. However, as warm, dry conditions, characterized by increased length and severity of the dry season, continued, fuel availability decreased. The establishment of the modern palm swamp vegetation occurred at 5000 cal yr BP. Edaphic factors are the first-order control on vegetation on the rocky quartzite mesetta. Where soils are sufficiently thick, climate is the second-order control of vegetation on the mesetta. The presence of the modern palm swamp is attributed to two factors: (1) increased precipitation that increased water table levels and (2) decreased frequency and duration of surazos (cold wind incursions from Patagonia) leading to increased temperature minima. Natural (soil, climate, fire) drivers rather than anthropogenic drivers control the vegetation and fire activity at Huanchaca Mesetta. Thus the cerrãdo savanna ecosystem of the Huanchaca Plateau has exhibited ecosystem resilience to major climatic changes in both temperature and precipitation since the Lateglacial period.

An evaluation of the pedestrian classification in a multi-domain multi-modality setup

The objective of this article is to study the problem of pedestrian classification across different light spectrum domains (visible and far-infrared (FIR)) and modalities (intensity, depth and motion). In recent years, there has been a number of approaches for classifying and detecting pedestrians in both FIR and visible images, but the methods are difficult to compare, because either the datasets are not publicly available or they do not offer a comparison between the two domains. Our two primary contributions are the following: (1) we propose a public dataset, named RIFIR , containing both FIR and visible images collected in an urban environment from a moving vehicle during daytime; and (2) we compare the state-of-the-art features in a multi-modality setup: intensity, depth and flow, in far-infrared over visible domains. The experiments show that features families, intensity self-similarity (ISS), local binary patterns (LBP), local gradient patterns (LGP) and histogram of oriented gradients (HOG), computed from FIR and visible domains are highly complementary, but their relative performance varies across different modalities. In our experiments, the FIR domain has proven superior to the visible one for the task of pedestrian classification, but the overall best results are obtained by a multi-domain multi-modality multi-feature fusion.

Vegetation history, human impact and climate change during prehistory: an island perspective of the isles of Tiree, Coll and north-west Mull

Results of extensive site reconnaissance on the Isles of Tiree, Coll and north-west Mull, Inner Hebrides are presented. Pollen-stratigraphic records were compiled from a profile from Glen Aros, north-west Mull and from two profiles on Coll located at Loch an t-Sagairt and Caolas an Eilean. Quantification of microscopic charcoal provided records that were used to facilitate a preliminary evaluation of the causal driving mechanisms of vegetation change. Bayesian modelling of radiocarbon dates was used to construct preliminary chronological frameworks for these records. Basal sedimentary deposits at Glen Aros contain pollen records that correspond with vegetation succession typical of the early Holocene dating to c. 11,370 cal BP. Woodland development is a key feature of the pollen records dating to the early Holocene, while records from Loch an t-Sagairt show that blanket mire communities were widespread in north-west Coll by c. 9800 cal BP. The Corylus-rise is dated to c. 10,710 cal BP at Glen Aros and c. 9905 cal BP at Loch an t-Sagairt, with records indicating extensive cover of hazel woodland with birch. All of the major arboreal taxa were recorded, though Quercus and Ulmus were nowhere widespread. Analysis of wood charcoal remains from a Mesolithic site at Fiskary Bay, Coll indicate that Salix and Populus are likely to be under-represented in the pollen records. Reconstructed isopoll maps appear to underplay the importance of alder in western Scotland during the mid-Holocene. Alder-rise expansions in microscopic charcoal dating to c. 7300 cal BP at Glen Aros and c. 6510 to 5830 cal BP on Coll provide records of significance to the issue of human-induced burning related to the expansion of alder in Britain. Increasing frequencies in microscopic charcoal are correlated with mid-Holocene records of increasing aridity in western Scotland after c. 7490 cal BP at Glen Aros, 6760 cal BP at Loch an t-Sagairt and 6590 cal BP at Caolas an Eilean, while several phases of increasing bog surface wetness were detected in the Loch an t-Sagairt archive during the Holocene. At least five phases of small-scale woodland disturbance during the Mesolithic period were identified in the Glen Aros profile dating to c. 11,650 cal BP, 9300 cal BP, 7840 cal BP, 7040 cal BP and 6100 cal BP. The timing of the third phase is coincident with evidence of Mesolithic settlement at Creit Dhu, north-west Mull. Three phases of small-scale woodland disturbance were detected at Loch an t-Sagairt dating to c. 9270 cal BP, 8770 cal BP and 8270 cal BP, all of which overlap chronologically with evidence of Mesolithic activity at Fiskary Bay, Coll. A number of these episodes are aligned chronologically with phases of Holocene climate variability such as the 8.2 K event.

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.