The value of feedback in forecasting competitions

In this paper we challenge the traditional design used for forecasting competitions. We implement an online competition with a public leaderboard that provides instant feedback to competitors who are allowed to revise and resubmit forecasts. The results show that feedback significantly improves forecasting accuracy.Forecasting competition, feedback.

Modelling and forecasting Australian domestic tourism

In this paper, we model and forecast Australian domestic tourism demand. We use a regression framework to estimate important economic relationships for domestic tourism demand. We also identify the impact of world events such as the 2000 Sydney Olympics and the 2002 Bali bombings on Australian domestic tourism. To explore the time series nature of the data, we use innovation state space models to forecast the domestic tourism demand. Combining these two frameworks, we build innovation state space models with exogenous variables. These models are able to capture the time series dynamics in the data, as well as economic and other relationships. We show that these models outperform alternative approaches for short-term forecasting and also produce sensible long-term forecasts. The forecasts are compared with the official Australian government forecasts, which are found to be more optimistic than our forecasts.Australia, domestic tourism, exponential smoothing, forecasting, innovation state space models.

STME Hydrogen Mixer Study

The hydrogen mixer for the Space Transportation Main Engine is used to mix cold hydrogen bypass flow with warm hydrogen coolant chamber gas, which is then fed to the injectors. It is very important to have a uniform fuel temperature at the injectors in order to minimize mixture ratio problems due to the fuel density variations. In addition, the fuel at the injector has certain total pressure requirements. In order to achieve these objectives, the hydrogen mixer must provide a thoroughly mixed fluid with a minimum pressure loss. The AEROVISC computational fluid dynamics (CFD) code was used to analyze the STME hydrogen mixer, and proved to be an effective tool in optimizing the mixer design. AEROVISC, which solves the Reynolds Stress-Averaged Navier-Stokes equations in primitive variable form, was used to assess the effectiveness of different mixer designs. Through a parametric study of mixer design variables, an optimal design was selected which minimized mixed fuel temperature variation and fuel mixer pressure loss. The use of CFD in the design process of the STME hydrogen mixer was effective in achieving an optimal mixer design while reducing the amount of hardware testing

Hierarchical forecasts for Australian domestic tourism

In this paper we explore the hierarchical nature of tourism demand time series and produce short-term forecasts for Australian domestic tourism. The data and forecasts are organized in a hierarchy based on disaggregating the data for different geographical regions and for different purposes of travel. We consider five approaches to hierarchical forecasting: two variations of the top-down approach, the bottom-up method, a newly proposed top-down approach where top-level forecasts are disaggregated according to forecasted proportions of lower level series, and a recently proposed optimal combination approach. Our forecast performance evaluation shows that the top-down approach based on forecast proportions and the optimal combination method perform best for the tourism hierarchies we consider. By applying these methods, we produce detailed forecasts for the Australian domestic tourism market.Australia, exponential smoothing, hierarchical forecasting, innovations state space models, optimal combination forecasts, top-down method, tourism demand.

Optimal combination forecasts for hierarchical time series

In many applications, there are multiple time series that are hierarchically organized and can be aggregated at several different levels in groups based on products, geography or some other features. We call these "hierarchical time series". They are commonly forecast using either a "bottom-up" or a "top-down" method. In this paper we propose a new approach to hierarchical forecasting which provides optimal forecasts that are better than forecasts produced by either a top-down or a bottom-up approach. Our method is based on independently forecasting all series at all levels of the hierarchy and then using a regression model to optimally combine and reconcile these forecasts. The resulting revised forecasts add up appropriately across the hierarchy, are unbiased and have minimum variance amongst all combination forecasts under some simple assumptions. We show in a simulation study that our method performs well compared to the top-down approach and the bottom-up method. It also allows us to construct prediction intervals for the resultant forecasts. Finally, we apply the method to forecasting Australian tourism demand where the data are disaggregated by purpose of visit and geographical region.Bottom-up forecasting, combining forecasts, GLS regression, hierarchical forecasting, Moore-Penrose inverse, reconciling forecasts, top-down forecasting.

Effect of stimulation frequency on force, net power output, and fatigue in mouse soleus muscle in vitro

Abstract The effects of electrical stimulation frequency on force, work loop power output, and fatigue of mouse soleus muscle were investigated in vitro at 35 °C. Increasing stimulation frequency did not significantly affect maximal isometric tetanic stress (overall mean ± SD, 205 ± 16.6 kN·m–2 between 70 and 160 Hz) but did significantly increase the rate of force generation. The maximal net power output during work loops significantly increased with stimulation frequency: 18.2 ± 3.7, 22.5 ± 3.3, 26.8 ± 3.7, and 28.6 ± 3.4 W·kg–1 at 70, 100, 130, and 160 Hz, respectively. The stimulation frequency that was used affected the pattern of fatigue observed during work loop studies. At stimulation frequencies of 100 and 130 Hz, there were periods of mean net negative work during the fatigue tests due to a slowing of relaxation rate. In contrast, mean net work remained positive throughout the fatigue test when stimulation frequencies of 70 and 160 Hz were used. The highest cumulative work during the fatigue test was performed at 70 and 160 Hz, followed by 130 Hz, then 100 Hz. Therefore, stimulation frequency affects power output and the pattern of fatigue in mouse soleus muscle

An outburst of SS 433 observed on milliarcsecond scale

SS 433 is a high-mass X-ray binary system (XRB) and one of the most persistent sources of relativistic jets in the Milky Way. The object has been intensively studied in radio at arcsecond scales, however the high-resolution observations (i.e. VLBI) are relatively scarce. In 2008 November the system was in outburst. Using the e-VLBI capabilities of the European VLBI Network (EVN) we observed SS 433 for three epochs during the active phase. The data offered a detailed view of the system’s behaviour in outburst at milliarcsecond scales. We used the “kinematic model" (which predicts the position along the jet of any knot ejected at some particular time in the past) to investigate the dynamic parameters of SS 433 and we examined the polarization properties of the ejected material. We report here the preliminary results