Learning from Data Streams with Randomized Forests

Non-stationary streaming data poses a familiar challenge in machine learning: the need to obtain fast and accurate predictions. A data stream is a continuously generated sequence of data, with data typically arriving rapidly. They are often characterised by a non-stationary generative process, with concept drift occurring as the process changes. Such processes are commonly seen in the real world, such as in advertising, shopping trends, environmental conditions, electricity monitoring and traffic monitoring. Typical stationary algorithms are ill-suited for use with concept drifting data, thus necessitating more targeted methods. Tree-based methods are a popular approach to this problem, traditionally focussing on the use of the Hoeffding bound in order to guarantee performance relative to a stationary scenario. However, there are limited single learners available for regression scenarios, and those that do exist often struggle to choose between similarly discriminative splits, leading to longer training times and worse performance. This limited pool of single learners in turn hampers the performance of ensemble approaches in which they act as base learners. In this thesis we seek to remedy this gap in the literature, developing methods which focus on increasing randomization to both improve predictive performance and reduce the training times of tree-based ensemble methods. In particular, we have chosen to investigate the use of randomization as it is known to be able to improve generalization error in ensembles, and is also expected to lead to fast training times, thus being a natural method of handling the problems typically experienced by single learners. We begin in a regression scenario, introducing the Adaptive Trees for Streaming with Extreme Randomization (ATSER) algorithm; a partially randomized approach based on the concept of Extremely Randomized (extra) trees. The ATSER algorithm incrementally trains trees, using the Hoeffding bound to select the best of a random selection of splits. Simultaneously, the trees also detect and adapt to changes in the data stream. Unlike many traditional streaming algorithms ATSER trees can easily be extended to include nominal features. We find that compared to other contemporary methods ensembles of ATSER trees lead to improved predictive performance whilst also reducing run times. We then demonstrate the Adaptive Categorisation Trees for Streaming with Extreme Randomization (ACTSER) algorithm, an adaption of the ATSER algorithm to the more traditional categorization scenario, again showing improved predictive performance and reduced runtimes. The inclusion of nominal features is particularly novel in this setting since typical categorization approaches struggle to handle them. Finally we examine a completely randomized scenario, where an ensemble of trees is generated prior to having access to the data stream, while also considering multivariate splits in addition to the traditional axis-aligned approach. We find that through the combination of a forgetting mechanism in linear models and dynamic weighting for ensemble members, we are able to avoid explicitly testing for concept drift. This leads to fast ensembles with strong predictive performance, whilst also requiring fewer parameters than other contemporary methods. For each of the proposed methods in this thesis, we demonstrate empirically that they are effective over a variety of different non-stationary data streams, including on multiple types of concept drift. Furthermore, in comparison to other contemporary data streaming algorithms, we find the biggest improvements in performance are on noisy data streams.Engineers Gat

Correction of non-linearity effects in detectors for electron spectroscopy

Using photoemission intensities and a detection system employed by many groups in the electron spectroscopy community as an example, we have quantitatively characterized and corrected detector non-linearity effects over the full dynamic range of the system. Non-linearity effects are found to be important whenever measuring relative peak intensities accurately is important, even in the low-countrate regime. This includes, for example, performing quantitative analyses for surface contaminants or sample bulk stoichiometries, where the peak intensities involved can differ by one or two orders of magnitude, and thus could occupy a significant portion of the detector dynamic range. Two successful procedures for correcting non-linearity effects are presented. The first one yields directly the detector efficiency by measuring a flat-background reference intensity as a function of incident x-ray flux, while the second one determines the detector response from a least-squares analysis of broad-scan survey spectra at different incident x-ray fluxes. Although we have used one spectrometer and detection system as an example, these methodologies should be useful for many other cases.Comment: 13 pages, 12 figure

Collisional quantum thermometry

We introduce a general framework for thermometry based on collisional models, where ancillas probe the temperature of the environment through an intermediary system. This allows for the generation of correlated ancillas even if they are initially independent. Using tools from parameter estimation theory, we show through a minimal qubit model that individual ancillas can already outperform the thermal Cramer-Rao bound. In addition, due to the steady-state nature of our model, when measured collectively the ancillas always exhibit superlinear scalings of the Fisher information. This means that even collective measurements on pairs of ancillas will already lead to an advantage. As we find in our qubit model, such a feature may be particularly valuable for weak system-ancilla interactions. Our approach sets forth the notion of metrology in a sequential interactions setting, and may inspire further advances in quantum thermometry

Differences in household income and other socioeconomic factors have been more important than subprime lending in explaining the growing gap in homeownership between blacks and whites

The consequences of the post 2006 housing bust disproportionately affected black households; rates of black homeownership are now 26 percentage points lower compared to whites. In new research, Kiat Ying Seah, Eric Fesselmeyer, and Kien T. Le examine some of the causes of this homeownership gap by focusing on socio-economic factors. They find that rather than being due to discrimination and subprime lending, the gap is mostly explained by changes in household income, whether the household earned dividend, interest, or rental income, and by marital status

Closing the gap: Pre-service teachers' perceptions of an ICT based, student centred learning curriculum

As technology continues to influence many aspects of our social and work lives, it is important that school experiences equip students the skills and knowledge that will enable them to develop into effective independent, creative, and lifelong learners to cope with the influx of changes. Given that teachers play a key role in the effective use of technology in education, there is a need to ensure that teacher education programs prepare teachers for the effective integration of ICT in the classrooms. We believe that there is a need to adopt a student-centered learning framework to design our ICT based Student-Centred Learning (SCL) curriculum for all pre-service teachers. In this paper, we presents parts of the findings from a curriculum review which evaluated 483 pre-service teachers' overall satisfaction level towards an ICT based SCL course. We also provide some recommendations to the ICT curriculum based on the results found. © 2007 Chwee Beng Lee, Timothy Teo, Ching Sing Chai, Doris Choy, Ashley Tan and Jimmy Seah

Virtual Simulation to Enhance Clinical Reasoning in Nursing: A Systematic Review and Meta-analysis.

Background: The COVID-19 pandemic has given rise to more virtual simulation training. This study aimed to review the effectiveness of virtual simulations and their design features in developing clinical reasoning skills among nurses and nursing students. Method: A systematic search in CINAHL, PubMed, Cochrane Library, Embase, ProQuest, PsycINFO, and Scopus was conducted. The PRISMA guidelines, Cochrane's risk of bias, and GRADE was used to assess the articles. Meta-analyses and random-effects meta-regression were performed. Results: The search retrieved 11,105 articles, and 12 randomized controlled trials (RCTs) were included. Meta-analysis demonstrated a significant improvement in clinical reasoning based on applied knowledge and clinical performance among learners in the virtual simulation group compared with the control group. Meta-regression did not identify any significant covariates. Subgroup analyses revealed that virtual simulations with patient management contents, using multiple scenarios with nonimmersive experiences, conducted more than 30-minutes and postscenario feedback were more effective. Conclusions: Virtual simulations can improve clinical reasoning skill. This study may inform nurse educators on how virtual simulation should be designed to optimize the development of clinical reasoning

Spin Motion in Electron Transmission through Ultrathin Ferromagnetic Films Accessed by Photoelectron Spectroscopy

Ab initio and model calculations demonstrate that the spin motion of electrons transmitted through ferromagnetic films can be analyzed in detail by means of angle- and spin-resolved core-level photoelectron spectroscopy. The spin motion appears as precession of the photoelectron spin polarization around and as relaxation towards the magnetization direction. In a systematic study for ultrathin Fe films on Pd(001) we elucidate its dependence on the Fe film thickness and on the Fe electronic structure. In addition to elastic and inelastic scattering, the effect of band gaps on the spin motion is addressed in particular.Comment: 4 pages, 5 figure

Sulfur-Oxidizing Symbionts without Canonical Genes for Autotrophic CO2 Fixation

Many animals and protists depend on symbiotic sulfur-oxidizing bacteria as their main food source. These bacteria use energy from oxidizing inorganic sulfur compounds to make biomass autotrophically from CO2, serving as primary producers for their hosts. Here we describe a clade of nonautotrophic sulfur-oxidizing symbionts, “Candidatus Kentron,” associated with marine ciliates. They lack genes for known autotrophic pathways and have a carbon stable isotope fingerprint heavier than other symbionts from similar habitats. Instead, they have the potential to oxidize sulfur to fuel the uptake of organic compounds for heterotrophic growth, a metabolic mode called chemolithoheterotrophy that is not found in other symbioses. Although several symbionts have heterotrophic features to supplement primary production, in Kentron they appear to supplant it entirely.Since the discovery of symbioses between sulfur-oxidizing (thiotrophic) bacteria and invertebrates at hydrothermal vents over 40 years ago, it has been assumed that autotrophic fixation of CO2 by the symbionts drives these nutritional associations. In this study, we investigated “Candidatus Kentron,” the clade of symbionts hosted by Kentrophoros, a diverse genus of ciliates which are found in marine coastal sediments around the world. Despite being the main food source for their hosts, Kentron bacteria lack the key canonical genes for any of the known pathways for autotrophic carbon fixation and have a carbon stable isotope fingerprint that is unlike other thiotrophic symbionts from similar habitats. Our genomic and transcriptomic analyses instead found metabolic features consistent with growth on organic carbon, especially organic and amino acids, for which they have abundant uptake transporters. All known thiotrophic symbionts have converged on using reduced sulfur to gain energy lithotrophically, but they are diverse in their carbon sources. Some clades are obligate autotrophs, while many are mixotrophs that can supplement autotrophic carbon fixation with heterotrophic capabilities similar to those in Kentron. Here we show that Kentron bacteria are the only thiotrophic symbionts that appear to be entirely heterotrophic, unlike all other thiotrophic symbionts studied to date, which possess either the Calvin-Benson-Bassham or the reverse tricarboxylic acid cycle for autotrophy

Visual field progression 8 years after trabeculectomy in Asian eyes: results from The Singapore 5-Fluorouracil Study

Background/Aims: This work aimed to study the effect of long-term intraocular pressure (IOP) fluctuation on visual field (VF) progression 8 years post-trabeculectomy in Asian eyes. / Methods: This was a retrospective analysis of 8-year post-trabeculectomy data from The Singapore 5-Fluorouracil (5-FU) Study. VFs were analysed using Progressor software (Medisoft, Leeds, UK). Outcome measures included mean slope for VF per year, number of progressing points and mean slope for progressing points per year. Multivariate regression analyses were performed adjusting for age, gender, ethnicity, glaucoma type, intraoperative 5-FU, diabetes mellitus, hypertension, best pre-trabeculectomy VF mean deviation, post-trabeculectomy mean IOP, IOP reduction and IOP fluctuation (SD of IOPs at 6-monthly timepoints). / Results: 127 (52.3%) subjects completed 8-year follow-up with ≥5 reliable VFs and ≥8 6-monthly IOP measurements. Mean age was 61.8±9.6 years. Post-operatively, mean IOP was 14.2±2.8 mm Hg and mean IOP fluctuation was 2.53±1.20 mm Hg. Higher IOP fluctuation was associated with greater mean slope for field (B=−0.071; p=0.013), number of progressing points (B=0.963; p=0.014) and VF progression as defined by ≥1 progressing point (OR=1.585; p=0.029). There was also a trend towards eyes with higher IOP fluctuation having ≥3 adjacent progressing points in the same hemifield (OR=1.489; p=0.055). Greater mean IOP reduction post-trabeculectomy was associated only with a lower mean slope for progressing points per year (B=−0.026; p=0.028). There was no significant effect of intra-operative 5-FU compared with placebo for all outcome measures. / Conclusion: In post-trabeculectomy Asian eyes with well-controlled IOP, higher long-term IOP fluctuation may be associated with greater VF progression