Pruning of Error Correcting Output Codes by optimization of accuracy–diversity trade off

Ensemble learning is a method of combining learners to obtain more reliable and accurate predictions in supervised and unsupervised learning. However, the ensemble sizes are sometimes unnecessarily large which leads to additional memory usage, computational overhead and decreased effectiveness. To overcome such side effects, pruning algorithms have been developed; since this is a combinatorial problem, finding the exact subset of ensembles is computationally infeasible. Different types of heuristic algorithms have developed to obtain an approximate solution but they lack a theoretical guarantee. Error Correcting Output Code (ECOC) is one of the well-known ensemble techniques for multiclass classification which combines the outputs of binary base learners to predict the classes for multiclass data. In this paper, we propose a novel approach for pruning the ECOC matrix by utilizing accuracy and diversity information simultaneously. All existing pruning methods need the size of the ensemble as a parameter, so the performance of the pruning methods depends on the size of the ensemble. Our unparametrized pruning method is novel as being independent of the size of ensemble. Experimental results show that our pruning method is mostly better than other existing approaches

Intracellular trafficking of prohormones and proneuropeptides: Cell type-specific sorting and targeting

Hormones and neuropeptides are usually synthesized as large precursor molecules which must undergo a series of post-translational modifications before they are released from secretory vesicles after stimulation by specific secretagogues. The classical vectorial transport of precursors and mature peptide products from the endoplasmic reticulum (ER) to their site of release has been the subject of intensive studies during the past 25 years, but there are a number of unresolved issues which still challenge cell biologists. The main issues are: (i) the molecular mechanisms underlying targeting and sorting of prohormones within the eukaryotic secretory pathway; (ii) further identification and intracellular site of action of post-translational processing enzymes; (iii) tissue-specific processing of hormone and neuropeptide precursors; and (iv) molecular mechanisms underlying intracellular transport ofl hormone and neuropeptide precursors and their cleavage products to alternative intracellular compartments besides the secretory pathway.Fil: Perone, Marcelo Javier. Universidad Austral. Facultad de Ciencias Biomédicas. Instituto de Investigaciones en Medicina Traslacional. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones en Medicina Traslacional; Argentina. University of Manchester; Reino UnidoFil: Windeatt, Simon. University of Manchester; Reino UnidoFil: Castro, Maria G.. University of Manchester; Reino Unid

Understanding the role of silence in conversations with people with aphasia.

This thesis demonstrates how silences are used and understood by people with aphasia (PWA) and their communication partners (CPs), highlighting the difference between silence as a reflex of communication difficulties resulting from aphasia, versus its use as a purposive communicative practice. Aphasia has a significant impact on the production and comprehension of speech, resulting in difficulties with relationships, careers, and mental health. Healthcare guidance encourages allowing extra silences in talk and giving PWA extra time to respond. This implies that silences have no communicative value and result only as an artefact of aphasia. However, prior research has shown that silences have many communicative functions within interaction. To investigate this, eleven hours of video-recorded conversations between nine dyads of PWA and their CPs were analysed using the methodology of Conversation Analysis. This research found that PWA use silence to convey communicative content in multiple ways: as part of a dispreferred response, signalling difficulty with their turn, as space to produce a display of affect, to invite their CP to talk, and as part of providing a legitimate display of understanding. When silences result from aphasia, PWA can account for silences using turn-holding devices, or mask silences through displays of embodied thinking. PWA’s silences are also part of claiming to undertake certain mental processes, such as doing thinking, word selection, and displaying understanding. CPs are receptive to these uses of silence and allow more time if the PWA signals it is required. These novel findings are positive for PWA, demonstrating that their communicative capabilities can overcome their impacted speech and that they possess more resources than previous research has indicated. The findings also demonstrate that the healthcare guidance requires further development so that it acknowledges the variable impact of aphasia on PWA’s use of silences, and the preserved communicative abilities of PWA

Assessing the potential of biochar from crop residues to sequester CO2: Scenarios to 2100

Amongst the suite of current or developing climate change mitigation tools, biochar is discussed within the literature as a method for long-term carbon sequestration (CS). The biochar field is rapidly developing, though there are uncertainties and limitations for which understanding could be improved. The aim of this thesis was to assess the potential of biochars from crop residues to sequester carbon, under the land-use pathways of the Representative Concentration Pathways, to 2100. Eight crop residue feedstocks and their biochars were fully characterised to examine the effects of feedstock and process conditions on biochar characteristics. Biochar yield, carbon content and recalcitrance values from this experimental work were utilized in the global modelling of scenarios exploring future carbon sequestration potential. Biochars produced were Class B or Class C, using the recalcitrance classification of Harvey et al. (2012), and classed as moderately or highly degradable. Recalcitrance increased with increasing pyrolysis temperature. The recalcitrance index of Harvey et al. (2012) may underestimate recalcitrance in high alkali metal content biochars. The carbon sequestration (CS) potential of the biochars was affected by the yield and content of stable carbon content of the biochar and predicted to be between 21.3 % and 32.5 %. The feedstock carbon remaining in the biochars decreased with increasing pyrolysis temperature although carbon stability increased with temperature. Biochar CS potential decreased with increasing pyrolysis temperature, despite increased stability and is due to the decreasing yields observed. A new equation was developed, using feedstock volatile content, as an alternative to the CS equation of Zhao et al. (2013). The Representative Concentration Pathways (RCPs) were used alongside the experimental results for biochar yield, carbon content and recalcitrance, and secondary data such as future crop yield and crop residue trends to project the CS potential of crop residues from 2005 to 2100. Scenarios of biochar production and carbon storage were developed, built around the RCPs, investigating biochar potential under changing crop land area and exploring parameters such as biochar characteristics and biochar systems. Scenario 1 used the mean or most likely values from experimental data and literature, Scenarios 2 to 7 explored parameter assumptions and Scenarios 8 and 9 explored the impact of climate change on crop yields and subsequent biochar CS potential. Global biochar production in Scenario 1 for the four RCPs over 95 years (2005 to 2100) was: RCP 2.6, 138.4 Gt biochar; RCP 4.5, 132.3 Gt biochar; RCP 6, 173.2 Gt biochar and RCP 8.5, 217.9 Gt biochar. Although the carbon mitigation potential of biochar in the scenarios generally increased from RCP 2.6 to RCP 8.5, the quantity of emissions requiring iv mitigation also increased. Scenario 1 saw 49.0, 45.8, 60.9 and 77.2 GtC sequestered over the 95 year period for the four RCPs respectively. These are reductions of 11 %, 5 %, 5 % and 4 % on the RCPs carbon emissions pathways. The maximum and minimum carbon emission mitigation potentials achievable under the assumptions of scenarios 1 to 7 were 22.5 %, 10.8 %, 10.0 %, 8.3 % and 4.7 %, 2.2 %, 1.9 %, 1.5 % for the four RCPs respectively. Climate change generally resulted in a decreasing carbon sequestration potential from RCP 2.6 up to RCP 8.5. This negative impact also increased over time. The maximum impact on mitigation potential in 2100 was - 0.14 GtC yr-1 for RCP 2.6, this increased to - 0.72 GtC yr-1 for RCP 8.5. Biochar has the potential to sequester carbon in all of the scenarios explored, however the magnitude of this sequestration potential is dependent on a number of factors of which many are currently subject to large amounts of uncertainty. Reduction in these areas of uncertainty would be a valuable area of further work following this study

Upper Facial Action Unit Recognition

This paper concentrates on the comparisons of systems that are used for the recognition of expressions generated by six upper face action units (AUs) by using Facial Action Coding System (FACS). Haar wavelet, Haar-Like and Gabor wavelet coe cients are compared, using Adaboost for feature selection. The binary classi cation results by using Support Vector Machines (SVM) for the upper face AUs have been observed to be better than the current results in the literature, for example 96.5% for AU2 and 97.6% for AU5. In multi-class classi cation case, the Error Correcting Output Coding (ECOC) has been applied. Although for a large number of classes, the results are not as accurate as the binary case, ECOC has the advantage of solving all problems simultaneously; and for large numbers of training samples and small number of classes, error rates are improved

Collaborative strategic reading on multi-touch and multi-user digital tabletop displays

This paper is part of a work-in-progress that reports on the design, development, and evaluation of a Digital Collaborative Strategic Reading (DCSR) application with regard to its effectiveness in improving English as a second language (ESL) reading comprehension. The DCSR application allows users to read collaboratively on multi-touch and multi-user digital tabletop displays that support both face-to-face and computer-based interaction. The application is designed to provide systematic instruction on tabletop computers using four main comprehension strategies that form the Collaborative Strategic Reading (CSR) instructional approach. The paper addresses one main research question: ‘How does the use of the tabletop-based reading application (DCSR) affect learners’ reading processes and outcomes?”, and the following sub-questions: (1) What is the impact of the tabletop-based reading system on learners’ reading scores with regard to the reading assessments? (2) How do learners collaboratively construct meaning on the tabletop? To answer these research questions, the subjects used the DCSR application on tabletop computers in groups of four, once a week for 5 weeks. Data were collected and analysed using both qualitative and quantitative methods. Each reading session was preceded by a cloze test and followed by two types of assessment: a written recall test and a cloze test; both tests were designed to reflect the students' comprehension of the reading passages. The paper will report on the design of the software and the administration of the study, but will focus on the analysis of the data from the different sources, and present insights into the nature of collaborative reading using the DCSR application on a tabletop computer

ECOC pruning using accuracy, diversity and Hamming distance information

Existing ensemble pruning algorithms in the literature have mainly been defined for unweighted or weighted voting ensembles, whose extensions to the Error Correcting Output Coding (ECOC) framework is not successful. This paper presents a novel pruning algorithm to be used in the pruning of ECOC, via using a new accuracy measure together with diversity and Hamming distance information. The results show that the novel method outperforms those existing in the state-of-the-art

Approximation of Ensemble Boundary Using Spectral Coefficients

IEEE A spectral analysis of a Boolean function is proposed for approximating the decision boundary of an ensemble of classifiers, and an intuitive explanation of computing Walsh coefficients for the functional approximation is provided. It is shown that the difference between the first- and third-order coefficient approximations is a good indicator of optimal base classifier complexity. When combining neural networks, the experimental results on a variety of artificial and real two-class problems demonstrate under what circumstances ensemble performance can be improved. For tuned base classifiers, the first-order coefficients provide performance similar to the majority vote. However, for weak/fast base classifiers, higher order coefficient approximation may give better performance. It is also shown that higher order coefficient approximation is superior to the Adaboost logarithmic weighting rule when boosting weak decision tree base classifiers