Short-term electricity price forecasting using wavelet and SVM techniques

In deregulated electricity market, modeling and forecasting the spot price present a number of challenges. By applying wavelet and support vector machine techniques, a new time series model for short term electricity price forecasting has been developed in this paper. The model employs both historical price and other important information, such as load capacity and weather (temperature), to forecast the price of one or more time steps ahead. The developed model has been evaluated with the actual data from Australian National Electricity Market. The simulation results demonstrated that the forecast model is capable of forecasting the electricity price with a reasonable forecasting accuracy.

Short-term electricity demand and gas price forecasts using wavelet transforms and adaptive models

This paper presents some forecasting techniques for energy demand and price prediction, one day ahead. These techniques combine wavelet transform (WT) with fixed and adaptive machine learning/time series models (multi-layer perceptron (MLP), radial basis functions, linear regression, or GARCH). To create an adaptive model, we use an extended Kalman filter or particle filter to update the parameters continuously on the test set. The adaptive GARCH model is a new contribution, broadening the applicability of GARCH methods. We empirically compared two approaches of combining the WT with prediction models: multicomponent forecasts and direct forecasts. These techniques are applied to large sets of real data (both stationary and non-stationary) from the UK energy markets, so as to provide comparative results that are statistically stronger than those previously reported. The results showed that the forecasting accuracy is significantly improved by using the WT and adaptive models. The best models on the electricity demand/gas price forecast are the adaptive MLP/GARCH with the multicomponent forecast; their MSEs are 0.02314 and 0.15384 respectively.

Creating innovation in small and medium-sized enterprises:evaluating the short-term effects of the creative credits pilot

This working paper looks at the short-term impact of the Creative Credits pilot scheme which operated in the Manchester City Region in the North West of England from September 2009 to September 2010, and was funded by NESTA, Manchester City Council, the North West Development Agency, the Economic and Social Research Council (ESRC) and the Arts and Humanities Research Council (AHRC). Creative Credits is a business-to-business (B2B) voucher mechanism designed to encourage small and medium-sized enterprises (SMEs) to work innovatively with creative companies. Businesses receive credits worth £4,000, which they must match with at least £1,000, to spend with creative firms on a variety of creative services.

Quantifying short-term dynamics of Parkinson's disease using self-reported symptom data from an internet social network

Background: Parkinson’s disease (PD) is an incurable neurological disease with approximately 0.3% prevalence. The hallmark symptom is gradual movement deterioration. Current scientific consensus about disease progression holds that symptoms will worsen smoothly over time unless treated. Accurate information about symptom dynamics is of critical importance to patients, caregivers, and the scientific community for the design of new treatments, clinical decision making, and individual disease management. Long-term studies characterize the typical time course of the disease as an early linear progression gradually reaching a plateau in later stages. However, symptom dynamics over durations of days to weeks remains unquantified. Currently, there is a scarcity of objective clinical information about symptom dynamics at intervals shorter than 3 months stretching over several years, but Internet-based patient self-report platforms may change this. Objective: To assess the clinical value of online self-reported PD symptom data recorded by users of the health-focused Internet social research platform PatientsLikeMe (PLM), in which patients quantify their symptoms on a regular basis on a subset of the Unified Parkinson’s Disease Ratings Scale (UPDRS). By analyzing this data, we aim for a scientific window on the nature of symptom dynamics for assessment intervals shorter than 3 months over durations of several years. Methods: Online self-reported data was validated against the gold standard Parkinson’s Disease Data and Organizing Center (PD-DOC) database, containing clinical symptom data at intervals greater than 3 months. The data were compared visually using quantile-quantile plots, and numerically using the Kolmogorov-Smirnov test. By using a simple piecewise linear trend estimation algorithm, the PLM data was smoothed to separate random fluctuations from continuous symptom dynamics. Subtracting the trends from the original data revealed random fluctuations in symptom severity. The average magnitude of fluctuations versus time since diagnosis was modeled by using a gamma generalized linear model. Results: Distributions of ages at diagnosis and UPDRS in the PLM and PD-DOC databases were broadly consistent. The PLM patients were systematically younger than the PD-DOC patients and showed increased symptom severity in the PD off state. The average fluctuation in symptoms (UPDRS Parts I and II) was 2.6 points at the time of diagnosis, rising to 5.9 points 16 years after diagnosis. This fluctuation exceeds the estimated minimal and moderate clinically important differences, respectively. Not all patients conformed to the current clinical picture of gradual, smooth changes: many patients had regimes where symptom severity varied in an unpredictable manner, or underwent large rapid changes in an otherwise more stable progression. Conclusions: This information about short-term PD symptom dynamics contributes new scientific understanding about the disease progression, currently very costly to obtain without self-administered Internet-based reporting. This understanding should have implications for the optimization of clinical trials into new treatments and for the choice of treatment decision timescales.

Selection & development of short-term project team members:developmental stability as an indicator of interpersonal skills

Short-term project teams do not have the advantage of prior performance or long-term membership to facilitate development of effective team performance. Research suggests interpersonal skills are crucial to success but this is under researched longitudinally. Evolutionary psychology can provide a lens to explain how people develop differing levels of interpersonal skills via the relationship between fluctuating asymmetry and pro-social behaviours. This research aims to investigate the relationship between fluctuating asymmetry and interpersonal skills, the impact of training and to further the evolutionary psychology field by embedding research in a real-world context as opposed to solely in laboratory or student settings.

Short-term changes in ocular biometry and refraction after discontinuation of long-term orthokeratology

OBJECTIVE: To assess refractive and biometric changes 1 week after discontinuation of lens wear in subjects who had been wearing orthokeratology (OK) contact lenses for 2 years. METHODS: Twenty-nine subjects aged 6 to 12 years and with myopia of -0.75 to -4.00 diopters (D) and astigmatism of ≤1.00 D participated in the study. Measurements of axial length and anterior chamber depth (Zeiss IOLMaster), corneal power and shape, and cycloplegic refraction were taken 1 week after discontinuation and compared with those at baseline and after 24 months of lens wear. RESULTS: A hyperopic shift was found at 24 months relative to baseline in spherical equivalent refractive error (+1.86±1.01 D), followed by a myopic shift at 1 week relative to 24 months (-1.93±0.92 D) (both P<0.001). Longer axial lengths were found at 24 months and 1 week in comparison to baseline (0.47±0.18 and 0.51±0.18 mm, respectively) (both P<0.001). The increase in axial length at 1 week relative to 24 months was statistically significant (0.04±0.06 mm; P=0.006). Anterior chamber depth did not change significantly over time (P=0.31). Significant differences were found between 24 months and 1 week relative to baseline and between 1-week and 24-month visits in mean corneal power (-1.68±0.80, -0.44±0.32, and 1.23±0.70 D, respectively) (all P≤0.001). Refractive change at 1 week in comparison to 24 months strongly correlated with changes in corneal power (r=-0.88; P<0.001) but not with axial length changes (r=-0.09; P=0.66). Corneal shape changed significantly between the baseline and 1-week visits (0.15±0.10 D; P<0.001). Corneal shape changed from a prolate to a more oblate corneal shape at the 24-month and 1-week visits in comparison to baseline (both P≤0.02) but did not change significantly between 24 months and 1 week (P=0.06). CONCLUSIONS: The effects of long-term OK on ocular biometry and refraction are still present after 1-week discontinuation of lens wear. Refractive change after discontinuation of long-term OK is primarily attributed to the recovery of corneal shape and not to an increase in the axial length.

Forecasting the term structure when short-term rates are near zero

This paper compares the experience of forecasting the UK government bond yield curve before and after the dramatic lowering of short-term interest rates from October 2008. Out-of-sample forecasts for 1, 6 and 12 months are generated from each of a dynamic Nelson-Siegel model, autoregressive models for both yields and the principal components extracted from those yields, a slope regression and a random walk model. At short forecasting horizons, there is little difference in the performance of the models both prior to and after 2008. However, for medium- to longer-term horizons, the slope regression provided the best forecasts prior to 2008, while the recent experience of near-zero short interest rates coincides with a period of forecasting superiority for the autoregressive and dynamic Nelson-Siegel models. © 2014 John Wiley & Sons, Ltd.

Effects of short-term detraining on postprandial metabolism, endothelial function, and inflammation in endurance-trained men:dissociation between changes in triglyceride metabolism and endothelial function

Endurance-trained athletes experience a low level of postprandial lipaemia, but this rapidly increases with detraining. We sought to determine whether detraining-induced changes to postprandial metabolism influenced endothelial function and inflammation. Eight endurance-trained men each undertook two oral fat tolerance tests [blood taken fasted and for 6 h following a high-fat test meal (80 g fat, 80 g carbohydrate)]: one during a period of their normal training (trained) and one after 1 wk of no exercise (detrained). Endothelial function in the cutaneous microcirculation was assessed using laser Doppler imaging with iontophoresis in the fasted state and 4 h postprandially during each test. Fasting plasma triglyceride (TG) concentrations increased by 35% with detraining (P = 0.002), as did postprandial plasma (by 53%, P = 0.002), chylomicron (by 68%, P = 0.02) and very low-density lipoprotein (by 51%, P = 0.005) TG concentrations. Endothelial function decreased postprandially in both the trained (by 17%, P = 0.03) and detrained (by 22%, P = 0.03) conditions but did not differ significantly between the trained and detrained conditions in either the fasted or the postprandial states. These results suggest that, although fat ingestion induces endothelial dysfunction, interventions that alter postprandial TG metabolism will not necessarily concomitantly influence endothelial function.

Exploration by Means of Computer Simulation of Nonlinear Hierarchical Structure of Neuronal Memory on the Model of Olfactory Bulb

Results of numerical experiments are introduced. Experiments were carried out by means of computer simulation on olfactory bulb for the purpose of checking of thinking mechanisms conceptual model, introduced in [2]. Key role of quasisymbol neurons in processes of pattern identification, existence of mental view, functions of cyclic connections between symbol and quasisymbol neurons as short-term memory, important role of synaptic plasticity in learning processes are confirmed numerically. Correctness of fundamental ideas put in base of conceptual model is confirmed on olfactory bulb at quantitative level.