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.

Sequential hydrocarbon biodegradation of a soil from arid coastal Australia oil-treated under laboratory controlled conditions

A general consistency in the sequential order of petroleum hydrocarbon reduction in previous biodegradation studies has led to the proposal of several molecularly based biodegradation scales. Few studies have investigated the biodegradation susceptibility of petroleum hydrocarbon products in soil media, however, and metabolic preferences can change with habitat type. A laboratory based study comprising gas chromatography–mass spectrometry (GC–MS) analysis of extracts of oil-treated soil samples incubated for up to 161 days was conducted to investigate the biodegradation of crude oil exposed to sandy soils of Barrow Island, home to both a Class ‘‘A” nature reserve and Australia’s largest on-shore oil field. Biodegradation trends of the hydrocarbon-treated soils were largely consistent with previous reports but some unusual behaviour was recognised both between and within hydrocarbon classes. For example, the n-alkanes persisted at trace levels from day 86 to 161 following the removal of typically more stable dimethyl naphthalenes and methyl phenanthrenes. The relative susceptibility to biodegradation of different di- tri- and tetramethylnaphthalene isomers also showed several features distinct from previous reports. The unique biodegradation behaviour of Barrow Is. soil likely reflects difference in microbial functioning with physiochemical variation in the environment. Correlation of molecular parameters, reduction rates of selected alkyl naphthalene isomers and CO2 respiration values with a delayed (61 d) oil-treated soil identified a slowing of biodegradation with microcosm incubation; a reduced function or population of incubated soil flora might also influence the biodegradation patterns observed.

Production and on-line comprehension of definiteness in English and Dutch by monolingual and sequential bilingual children

The present article examines production and on-line processing of definite articles in Turkish-speaking sequential bilingual children acquiring English and Dutch as second languages (L2) in the UK and in the Netherlands, respectively. Thirty-nine 6–8-year-old L2 children and 48 monolingual (L1) age-matched children participated in two separate studies examining the production of definite articles in English and Dutch in conditions manipulating semantic context, that is, the anaphoric and the bridging contexts. Sensitivity to article omission was examined in the same groups of children using an on-line processing task involving article use in the same semantic contexts as in the production task. The results indicate that both L2 children and L1 controls are less accurate when definiteness is established by keeping track of the discourse referents (anaphoric) than when it is established via world knowledge (bridging). Moreover, despite variable production, all groups of children were sensitive to the omission of definite articles in the on-line comprehension task. This suggests that the errors of omission are not due to the lack of abstract syntactic representations, but could result from processes implicated in the spell-out of definite articles. The findings are in line with the idea that variable production in child L2 learners does not necessarily indicate lack of abstract representations (Haznedar and Schwartz, 1997).

Resting tremor classification and detection in Parkinson's disease patients

Parkinson is a neurodegenerative disease, in which tremor is the main symptom. This paper investigates the use of different classification methods to identify tremors experienced by Parkinsonian patients.Some previous research has focussed tremor analysis on external body signals (e.g., electromyography, accelerometer signals, etc.). Our advantage is that we have access to sub-cortical data, which facilitates the applicability of the obtained results into real medical devices since we are dealing with brain signals directly. Local field potentials (LFP) were recorded in the subthalamic nucleus of 7 Parkinsonian patients through the implanted electrodes of a deep brain stimulation (DBS) device prior to its internalization. Measured LFP signals were preprocessed by means of splinting, down sampling, filtering, normalization and rec-tification. Then, feature extraction was conducted through a multi-level decomposition via a wavelettrans form. Finally, artificial intelligence techniques were applied to feature selection, clustering of tremor types, and tremor detection.The key contribution of this paper is to present initial results which indicate, to a high degree of certainty, that there appear to be two distinct subgroups of patients within the group-1 of patients according to the Consensus Statement of the Movement Disorder Society on Tremor. Such results may well lead to different resultant treatments for the patients involved, depending on how their tremor has been classified. Moreover, we propose a new approach for demand driven stimulation, in which tremor detection is also based on the subtype of tremor the patient has. Applying this knowledge to the tremor detection problem, it can be concluded that the results improve when patient clustering is applied prior to detection.

An investigation of the shortcomings of the CONSORT 2010 statement for the reporting of group sequential randomised controlled trials: a methodological systematic review

Background It can be argued that adaptive designs are underused in clinical research. We have explored concerns related to inadequate reporting of such trials, which may influence their uptake. Through a careful examination of the literature, we evaluated the standards of reporting of group sequential (GS) randomised controlled trials, one form of a confirmatory adaptive design. Methods We undertook a systematic review, by searching Ovid MEDLINE from the 1st January 2001 to 23rd September 2014, supplemented with trials from an audit study. We included parallel group, confirmatory, GS trials that were prospectively designed using a Frequentist approach. Eligible trials were examined for compliance in their reporting against the CONSORT 2010 checklist. In addition, as part of our evaluation, we developed a supplementary checklist to explicitly capture group sequential specific reporting aspects, and investigated how these are currently being reported. Results Of the 284 screened trials, 68(24%) were eligible. Most trials were published in “high impact” peer-reviewed journals. Examination of trials established that 46(68%) were stopped early, predominantly either for futility or efficacy. Suboptimal reporting compliance was found in general items relating to: access to full trials protocols; methods to generate randomisation list(s); details of randomisation concealment, and its implementation. Benchmarking against the supplementary checklist, GS aspects were largely inadequately reported. Only 3(7%) trials which stopped early reported use of statistical bias correction. Moreover, 52(76%) trials failed to disclose methods used to minimise the risk of operational bias, due to the knowledge or leakage of interim results. Occurrence of changes to trial methods and outcomes could not be determined in most trials, due to inaccessible protocols and amendments. Discussion and Conclusions There are issues with the reporting of GS trials, particularly those specific to the conduct of interim analyses. Suboptimal reporting of bias correction methods could potentially imply most GS trials stopping early are giving biased results of treatment effects. As a result, research consumers may question credibility of findings to change practice when trials are stopped early. These issues could be alleviated through a CONSORT extension. Assurance of scientific rigour through transparent adequate reporting is paramount to the credibility of findings from adaptive trials. Our systematic literature search was restricted to one database due to resource constraints.

A Genetic Algorithm for the selection of structural MRI features for classification of Mild Cognitive Impairment and Alzheimer's Disease

This work investigates the problem of feature selection in neuroimaging features from structural MRI brain images for the classification of subjects as healthy controls, suffering from Mild Cognitive Impairment or Alzheimer’s Disease. A Genetic Algorithm wrapper method for feature selection is adopted in conjunction with a Support Vector Machine classifier. In very large feature sets, feature selection is found to be redundant as the accuracy is often worsened when compared to an Support Vector Machine with no feature selection. However, when just the hippocampal subfields are used, feature selection shows a significant improvement of the classification accuracy. Three-class Support Vector Machines and two-class Support Vector Machines combined with weighted voting are also compared with the former and found more useful. The highest accuracy achieved at classifying the test data was 65.5% using a genetic algorithm for feature selection with a three-class Support Vector Machine classifier.

Interim analyses and sequential designs in phase III studies

Recruitment of patients to a clinical trial usually occurs over a period of time, resulting in the steady accumulation of data throughout the trial's duration. Yet, according to traditional statistical methods, the sample size of the trial should be determined in advance, and data collected on all subjects before analysis proceeds. For ethical and economic reasons, the technique of sequential testing has been developed to enable the examination of data at a series of interim analyses. The aim is to stop recruitment to the study as soon as there is sufficient evidence to reach a firm conclusion. In this paper we present the advantages and disadvantages of conducting interim analyses in phase III clinical trials, together with the key steps to enable the successful implementation of sequential methods in this setting. Examples are given of completed trials, which have been carried out sequentially, and references to relevant literature and software are provided.

Modelling personal thermal sensations using C-Support Vector Classification (C-SVC) algorithm

The personalised conditioning system (PCS) is widely studied. Potentially, it is able to reduce energy consumption while securing occupants’ thermal comfort requirements. It has been suggested that automatic optimised operation schemes for PCS should be introduced to avoid energy wastage and discomfort caused by inappropriate operation. In certain automatic operation schemes, personalised thermal sensation models are applied as key components to help in setting targets for PCS operation. In this research, a novel personal thermal sensation modelling method based on the C-Support Vector Classification (C-SVC) algorithm has been developed for PCS control. The personal thermal sensation modelling has been regarded as a classification problem. During the modelling process, the method ‘learns’ an occupant’s thermal preferences from his/her feedback, environmental parameters and personal physiological and behavioural factors. The modelling method has been verified by comparing the actual thermal sensation vote (TSV) with the modelled one based on 20 individual cases. Furthermore, the accuracy of each individual thermal sensation model has been compared with the outcomes of the PMV model. The results indicate that the modelling method presented in this paper is an effective tool to model personal thermal sensations and could be integrated within the PCS for optimised system operation and control.

Evaluation of simulated sea-ice concentrations from sea-ice/ocean models using satellite data and polynya classification methods

Sea-ice concentrations in the Laptev Sea simulated by the coupled North Atlantic-Arctic Ocean-Sea-Ice Model and Finite Element Sea-Ice Ocean Model are evaluated using sea-ice concentrations from Advanced Microwave Scanning Radiometer-Earth Observing System satellite data and a polynya classification method for winter 2007/08. While developed to simulate largescale sea-ice conditions, both models are analysed here in terms of polynya simulation. The main modification of both models in this study is the implementation of a landfast-ice mask. Simulated sea-ice fields from different model runs are compared with emphasis placed on the impact of this prescribed landfast-ice mask. We demonstrate that sea-ice models are not able to simulate flaw polynyas realistically when used without fast-ice description. Our investigations indicate that without landfast ice and with coarse horizontal resolution the models overestimate the fraction of open water in the polynya. This is not because a realistic polynya appears but due to a larger-scale reduction of ice concentrations and smoothed ice-concentration fields. After implementation of a landfast-ice mask, the polynya location is realistically simulated but the total open-water area is still overestimated in most cases. The study shows that the fast-ice parameterization is essential for model improvements. However, further improvements are necessary in order to progress from the simulation of large-scale features in the Arctic towards a more detailed simulation of smaller-scaled features (here polynyas) in an Arctic shelf sea.

English compound and non-compound processing in bilingual and multilingual speakers: effects of dominance and sequential multilingualism

This article reports on a study investigating the relative influence of the first and dominant language on L2 and L3 morpho-lexical processing. A lexical decision task compared the responses to English NV-er compounds (e.g., taxi driver) and non-compounds provided by a group of native speakers and three groups of learners at various levels of English proficiency: L1 Spanish-L2 English sequential bilinguals and two groups of early Spanish-Basque bilinguals with English as their L3. Crucially, the two trilingual groups differed in their first and dominant language (i.e., L1 Spanish-L2 Basque vs. L1 Basque-L2 Spanish). Our materials exploit an (a)symmetry between these languages: while Basque and English pattern together in the basic structure of (productive) NV-er compounds, Spanish presents a construction that differs in directionality as well as inflection of the verbal element (V[3SG] + N). Results show between and within group differences in accuracy and response times that may be ascribable to two factors besides proficiency: the number of languages spoken by a given participant and their dominant language. An examination of response bias reveals an influence of the participants' first and dominant language on the processing of NV-er compounds. Our data suggest that morphological information in the nonnative lexicon may extend beyond morphemic structure and that, similarly to bilingualism, there are costs to sequential multilingualism in lexical retrieval.

Impact of lipoprotein lipase gene polymorphism, S447X, on postprandial triacylglycerol and glucose response to sequential meal ingestion

Lipoprotein lipase (LPL) is a key rate-limiting enzyme for the hydrolysis of triacylglycerol (TAG) in chylomicrons and very low-density lipoprotein. Given that postprandial assessment of lipoprotein metabolism may provide a more physiological perspective of disturbances in lipoprotein homeostasis compared to assessment in the fasting state, we have investigated the influence of two commonly studied LPL polymorphisms (rs320, HindIII; rs328, S447X) on postprandial lipaemia, in 261 participants using a standard sequential meal challenge. S447 homozygotes had lower fasting HDL-C (p = 0.015) and a trend for higher fasting TAG (p = 0.057) concentrations relative to the 447X allele carriers. In the postprandial state, there was an association of the S447X polymorphism with postprandial TAG and glucose, where S447 homozygotes had 12% higher TAG area under the curve (AUC) (p = 0.037), 8.4% higher glucose-AUC (p = 0.006) and 22% higher glucose-incremental area under the curve (IAUC) (p = 0.042). A significant gene–gender interaction was observed for fasting TAG (p = 0.004), TAG-AUC (Pinteraction = 0.004) and TAG-IAUC (Pinteraction = 0.016), where associations were only evident in men. In conclusion, our study provides novel findings of an effect of LPL S447X polymorphism on the postprandial glucose and gender-specific impact of the polymorphism on fasting and postprandial TAG concentrations in response to sequential meal challenge in healthy participants