11 resultados para multiple classification analysis
Resumo:
A compositional multivariate approach is used to analyse regional scale soil geochemical data obtained as part of the Tellus Project generated by the Geological Survey Northern Ireland (GSNI). The multi-element total concentration data presented comprise XRF analyses of 6862 rural soil samples collected at 20cm depths on a non-aligned grid at one site per 2 km2. Censored data were imputed using published detection limits. Using these imputed values for 46 elements (including LOI), each soil sample site was assigned to the regional geology map provided by GSNI initially using the dominant lithology for the map polygon. Northern Ireland includes a diversity of geology representing a stratigraphic record from the Mesoproterozoic, up to and including the Palaeogene. However, the advance of ice sheets and their meltwaters over the last 100,000 years has left at least 80% of the bedrock covered by superficial deposits, including glacial till and post-glacial alluvium and peat. The question is to what extent the soil geochemistry reflects the underlying geology or superficial deposits. To address this, the geochemical data were transformed using centered log ratios (clr) to observe the requirements of compositional data analysis and avoid closure issues. Following this, compositional multivariate techniques including compositional Principal Component Analysis (PCA) and minimum/maximum autocorrelation factor (MAF) analysis method were used to determine the influence of underlying geology on the soil geochemistry signature. PCA showed that 72% of the variation was determined by the first four principal components (PC’s) implying “significant” structure in the data. Analysis of variance showed that only 10 PC’s were necessary to classify the soil geochemical data. To consider an improvement over PCA that uses the spatial relationships of the data, a classification based on MAF analysis was undertaken using the first 6 dominant factors. Understanding the relationship between soil geochemistry and superficial deposits is important for environmental monitoring of fragile ecosystems such as peat. To explore whether peat cover could be predicted from the classification, the lithology designation was adapted to include the presence of peat, based on GSNI superficial deposit polygons and linear discriminant analysis (LDA) undertaken. Prediction accuracy for LDA classification improved from 60.98% based on PCA using 10 principal components to 64.73% using MAF based on the 6 most dominant factors. The misclassification of peat may reflect degradation of peat covered areas since the creation of superficial deposit classification. Further work will examine the influence of underlying lithologies on elemental concentrations in peat composition and the effect of this in classification analysis.
Resumo:
Poly(methylvinylether-co-maleic acid) (PMVE/MA) is commonly used as a component of pharmaceutical platforms, principally to enhance interactions with biological substrates (mucoadhesion). However, the limited knowledge on the rheological properties of this polymer and their relationships with mucoadhesion has negated the biomedical use of this polymer as a mono-component platform. This study presents a comprehensive study of the rheological properties of aqueous PMVE/MA platforms and defines their relationships with mucoadhesion using multiple regression analysis. Using dilute solution viscometry the intrinsic viscosities of un-neutralised PMVE/MA and PMVE/MA neutralised using NaOH or TEA were 22.32 ± 0.89 dL g-1, 274.80 ± 1.94 dL g-1 and 416.49 ± 2.21 dL g-1 illustrating greater polymer chain expansion following neutralisation using Triethylamine (TEA). PMVE/MA platforms exhibited shear-thinning properties. Increasing polymer concentration increased the consistencies, zero shear rate (ZSR) viscosities (determined from flow rheometry), storage and loss moduli, dynamic viscosities (defined using oscillatory analysis) and mucoadhesive properties, yet decreased the loss tangents of the neutralised polymer platforms. TEA neutralised systems possessed significantly and substantially greater consistencies, ZSR and dynamic viscosities, storage and loss moduli, mucoadhesion and lower loss tangents than their NaOH counterparts. Multiple regression analysis enabled identification of the dominant role of polymer viscoelasticity on mucoadhesion (r > 0.98). The mucoadhesive properties of PMVE/MA platforms were considerable and were greater than those of other platforms that have successfully been shown to enhance in vivo retention when applied to the oral cavity, indicating a positive role for PMVE/MA mono-component platforms for pharmaceutical and biomedical applications.
Resumo:
The paper addresses the development of non-governmental organisations (NGOs) in transition settings. Caught in the balance of knowledge exchange and translation of ideas from abroad, organisations in turbulent setting legitimise their existence by learning through professional networks. By association, organisational actors gain acknowledgement by their sector by traversing the corridors of influence provided by international partnerships. What they learn is how to conduct themselves as agents of change in society, and how to deliver on stated missions and goals, therefore, legitimising their presence in a budding civil society at home. The paper presents a knowledge production and learning practices framework which indicates a presence of dual identity of NGOs - their “embeddedness” locally and internationally. Selected framework dimensions and qualitative case study themes are discussed with respect to the level of independence of organisational actors in the East from their partners in the West in a post-socialist context. A professional global civil society as organisations are increasingly managed in similar, professional ways (Anheier & Themudo 2002). Here knowledge “handling” and knowledge “translation” take place through partnership exchanges fostering capable and/or competitive change-inducing institutions (Czarniawska & Sevon 2005; Hwang & Suarez 2005). How professional identity presents itself in the third sector, as well as the sector’s claim to expertise, need further attention, adding to ongoing discussions on professions in institutional theory (Hwang & Powell 2005; Scott 2008; Noordegraaf 2011). A conceptual framework on the dynamic involved for the construction professional fields follows: • Multiple case analysis provides a taxonomy for understanding what is happening in knowledge transition, adaptation, and organisational learning capacity for NGOs with respect to their role in a networked civil society. With the model we can observe the types of knowledge produced and learning employed by organisations. • There are elements of professionalisation in third sector work organisational activity with respect to its accreditation, sources and routines of learning, knowledge claims, interaction with the statutory sector, recognition in cross-sector partnerships etc. • It signals that there is a dual embeddedness in the development of the sector at the core to the shaping the sector’s professional status. This is instrumental in the NGOs’ goal to gain influence as institutions, as they are only one part of a cross-sector mission to address complex societal problems The case study material highlights nuances of knowledge production and learning practices in partnerships, with dual embeddedness a main feature of the findings. This provides some clues to how professionalisation as expert-making takes shape in organisations: • Depending on the type of organisations’ purpose, over its course of development there is an increase in participation in multiple networks, as opposed to reliance on a single strategic partner for knowledge artefacts and practices; • Some types of organisations are better connected within international and national networks than others and there seem to be preferences for each depending on the area of work; • The level of interpretation or adaptation of the knowledge artefacts is related to an organisation’s embeddedness locally, in turn giving it more influence within the network of key institutions; An overreaching theme across taxonomy categories (Table 1)is “professionalisation” or developing organisational “expertise”, embodied at the individual, organisational, and sector levels. Questions relevant to the exercise of power arise: Is competence in managing a dual embeddedness signals the development of a dual identity in professionalisation? Is professionalisation in this sense a sign of organisations maturing into more capable partners to the arguably more experienced (Western) institutions, shifting the power balance? Or is becoming more professional a sign of domestication to the agenda of certain powerful stakeholders, who define the boundaries of the profession? Which dominant dynamics can be observed in a broadly-defined transition country civil society, where individual participation in the form of activism may be overtaking the traditional forms of organised development work, especially with the spread of social media?
Resumo:
Hemizygous deletion of 17p (del(17p)) has been identified as a variable associated with poor prognosis in myeloma, although its impact in the context of thalidomide therapy is not well described. The clinical outcome of 85 myeloma patients with del(17p) treated in a clinical trial incorporating both conventional and thalidomide-based induction therapies was examined. The clinical impact of deletion, low expression, and mutation of TP53 was also determined. Patients with del(17p) did not have inferior response rates compared to patients without del(17p), but, despite this, del(17p) was associated with impaired overall survival (OS) (median OS 26.6 vs. 48.5 months, P <0.001). Within the del(17p) group, thalidomide induction therapy was associated with improved response rates compared to conventional therapy, but there was no impact on OS. Thalidomide maintenance was associated with impaired OS, although our analysis suggests that this effect may have been due to confounding variables. A minimally deleted region on 17p13.1 involving 17 genes was identified, of which only TP53 and SAT2 were underexpressed. TP53 was mutated in <1% in patients without del(17p) and in 27% of patients with del(17p). The higher TP53 mutation rate in samples with del(17p) suggests a role for TP53 in these clinical outcomes. In conclusion, del(17p) defined a patient group associated with short survival in myeloma, and although thalidomide induction therapy was associated with improved response rates, it did not impact OS, suggesting that alternative therapeutic strategies are required for this group. (C) 2011 Wiley-Liss, Inc.
Resumo:
We performed fluorescent in situ hybridization (FISH) for 16q23 abnormalities in 861 patients with newly diagnosed multiple myeloma and identified deletion of 16q [del(16q)] in 19.5%. In 467 cases in which demographic and survival data were available, del(16q) was associated with a worse overall survival (OS). It was an independent prognostic marker and conferred additional adverse survival impact in cases with the known poor-risk cytogenetic factors t(4;14) and del(17p). Gene expression profiling and gene mapping using 500K single-nucleotide polymorphism (SNP) mapping arrays revealed loss of heterozygosity (LOH) involving 3 regions: the whole of 16q, a region centered on 16q12 (the location of CYLD), and a region centered on 16q23 (the location of the WW domain-containing oxidoreductase gene WWOX). CYLD is a negative regulator of the NF-kappaB pathway, and cases with low expression of CYLD were used to define a "low-CYLD signature." Cases with 16q LOH or t(14;16) had significantly reduced WWOX expression. WWOX, the site of the translocation breakpoint in t(14;16) cases, is a known tumor suppressor gene involved in apoptosis, and we were able to generate a "low-WWOX signature" defined by WWOX expression. These 2 genes and their corresponding pathways provide an important insight into the potential mechanisms by which 16q LOH confers poor prognosis.
Resumo:
BACKGROUND AND OBJECTIVE: Molecular analysis by PCR of monoclonally rearranged immunoglobulin (Ig) genes can be used for diagnosis in B-cell lymphoproliferative disorders (LPD), as well as for monitoring minimal residual disease (MRD) after treatment. This technique has the risk of false-positive results due to the "background" amplification of similar rearrangements derived from polyclonal B-cells. This problem can be resolved in advance by additional analyses that discern between polyclonal and monoclonal PCR products, such as the heteroduplex analysis. A second problem is that PCR frequently fails to amplify the junction regions, mainly due to somatic mutations frequently present in mature (post-follicular) B-cell lymphoproliferations. The use of additional targets (e.g. Ig light chain genes) can avoid this problem. DESIGN AND METHODS: We studied the specificity of heteroduplex PCR analysis of several Ig junction regions to detect monoclonal products in samples from 84 MM patients and 24 patients with B cell polyclonal disorders. RESULTS: Using two distinct VH consensus primers (FR3 and FR2) in combination with one JH primer, 79% of the MM displayed monoclonal products. The percentage of positive cases was increased by amplification of the Vlamda-Jlamda junction regions or kappa(de) rearrangements, using two or five pairs of consensus primers, respectively. After including these targets in the heteroduplex PCR analysis, 93% of MM cases displayed monoclonal products. None of the polyclonal samples analyzed resulted in monoclonal products. Dilution experiments showed that monoclonal rearrangements could be detected with a sensitivity of at least 10(-2) in a background with >30% polyclonal B-cells, the sensitivity increasing up to 10(-3) when the polyclonal background was
Resumo:
Malware detection is a growing problem particularly on the Android mobile platform due to its increasing popularity and accessibility to numerous third party app markets. This has also been made worse by the increasingly sophisticated detection avoidance techniques employed by emerging malware families. This calls for more effective techniques for detection and classification of Android malware. Hence, in this paper we present an n-opcode analysis based approach that utilizes machine learning to classify and categorize Android malware. This approach enables automated feature discovery that eliminates the need for applying expert or domain knowledge to define the needed features. Our experiments on 2520 samples that were performed using up to 10-gram opcode features showed that an f-measure of 98% is achievable using this approach.
Resumo:
There has been an increasing interest in the development of new methods using Pareto optimality to deal with multi-objective criteria (for example, accuracy and time complexity). Once one has developed an approach to a problem of interest, the problem is then how to compare it with the state of art. In machine learning, algorithms are typically evaluated by comparing their performance on different data sets by means of statistical tests. Standard tests used for this purpose are able to consider jointly neither performance measures nor multiple competitors at once. The aim of this paper is to resolve these issues by developing statistical procedures that are able to account for multiple competing measures at the same time and to compare multiple algorithms altogether. In particular, we develop two tests: a frequentist procedure based on the generalized likelihood-ratio test and a Bayesian procedure based on a multinomial-Dirichlet conjugate model. We further extend them by discovering conditional independences among measures to reduce the number of parameters of such models, as usually the number of studied cases is very reduced in such comparisons. Data from a comparison among general purpose classifiers is used to show a practical application of our tests.
Resumo:
Safety on public transport is a major concern for the relevant authorities. We
address this issue by proposing an automated surveillance platform which combines data from video, infrared and pressure sensors. Data homogenisation and integration is achieved by a distributed architecture based on communication middleware that resolves interconnection issues, thereby enabling data modelling. A common-sense knowledge base models and encodes knowledge about public-transport platforms and the actions and activities of passengers. Trajectory data from passengers is modelled as a time-series of human activities. Common-sense knowledge and rules are then applied to detect inconsistencies or errors in the data interpretation. Lastly, the rationality that characterises human behaviour is also captured here through a bottom-up Hierarchical Task Network planner that, along with common-sense, corrects misinterpretations to explain passenger behaviour. The system is validated using a simulated bus saloon scenario as a case-study. Eighteen video sequences were recorded with up to six passengers. Four metrics were used to evaluate performance. The system, with an accuracy greater than 90% for each of the four metrics, was found to outperform a rule-base system and a system containing planning alone.