Swinburne University of Technology

About: Swinburne University of Technology is a education organization based out in Melbourne, Victoria, Australia. It is known for research contribution in the topics: Galaxy & Population. The organization has 7223 authors who have published 25530 publications receiving 667955 citations. The organization is also known as: Swinburne Technical College & Swinburne College of Technology.

Forecasting of photovoltaic power generation and model optimization: A review

Abstract: To mitigate the impact of climate change and global warming, the use of renewable energies is increasing day by day significantly. A considerable amount of electricity is generated from renewable energy sources since the last decade. Among the potential renewable energies, photovoltaic (PV) has experienced enormous growth in electricity generation. A large number of PV systems have been installed in on-grid and off-grid systems in the last few years. The number of PV systems will increase rapidly in the future due to the policies of the government and international organizations, and the advantages of PV technology. However, the variability of PV power generation creates different negative impacts on the electric grid system, such as the stability, reliability, and planning of the operation, aside from the economic benefits. Therefore, accurate forecasting of PV power generation is significantly important to stabilize and secure grid operation and promote large-scale PV power integration. A good number of research has been conducted to forecast PV power generation in different perspectives. This paper made a comprehensive and systematic review of the direct forecasting of PV power generation. The importance of the correlation of the input-output data and the preprocessing of model input data are discussed. This review covers the performance analysis of several PV power forecasting models based on different classifications. The critical analysis of recent works, including statistical and machine-learning models based on historical data, is also presented. Moreover, the strengths and weaknesses of the different forecasting models, including hybrid models, and performance matrices in evaluating the forecasting model, are considered in this research. In addition, the potential benefits of model optimization are also discussed.

Nested incremental modeling in the development of computational theories: The CDP+ model of reading aloud.

Abstract: At least 3 different types of computational model have been shown to account for various facets of both normal and impaired single word reading: (a) the connectionist triangle model, (b) the dual-route cascaded model, and (c) the connectionist dual process model. Major strengths and weaknesses of these models are identified. In the spirit of nested incremental modeling, a new connectionist dual process model (the CDP model) is presented. This model builds on the strengths of 2 of the previous models while eliminating their weaknesses. Contrary to the dual-route cascaded model, CDP is able to learn and produce graded consistency effects. Contrary to the triangle and the connectionist dual process models, CDP accounts for serial effects and has more accurate nonword reading performance. CDP also beats all previous models by an order of magnitude when predicting individual item-level variance on large databases. Thus, the authors show that building on existing theories by combining the best features of previous models—a nested modeling strategy that is commonly used in other areas of science but often neglected in psychology—results in better and more powerful computational models.

Off-Grid Direction of Arrival Estimation Using Sparse Bayesian Inference

Abstract: Direction of arrival (DOA) estimation is a classical problem in signal processing with many practical applications. Its research has recently been advanced owing to the development of methods based on sparse signal reconstruction. While these methods have shown advantages over conventional ones, there are still difficulties in practical situations where true DOAs are not on the discretized sampling grid. To deal with such an off-grid DOA estimation problem, this paper studies an off-grid model that takes into account effects of the off-grid DOAs and has a smaller modeling error. An iterative algorithm is developed based on the off-grid model from a Bayesian perspective while joint sparsity among different snapshots is exploited by assuming a Laplace prior for signals at all snapshots. The new approach applies to both single snapshot and multi-snapshot cases. Numerical simulations show that the proposed algorithm has improved accuracy in terms of mean squared estimation error. The algorithm can maintain high estimation accuracy even under a very coarse sampling grid.

The ATLAS3D project – XX. Mass–size and mass–σ distributions of early-type galaxies: bulge fraction drives kinematics, mass-to-light ratio, molecular gas fraction and stellar initial mass function

Abstract: In the companion Paper XV of this series, we derive accurate total mass-to-light ratios (M/L)(JAM) approximate to (M/L)(r = R-e) within a sphere of radius r = R-e centred on the galaxy, as well as stellar (M/L)(stars) (with the dark matter removed) for the volume-limited and nearly mass-selected (stellar mass M-star greater than or similar to 6 x 10(9) M-circle dot) ATLAS(3D) sample of 260 early-type galaxies (ETGs, ellipticals Es and lenticulars S0s). Here, we use those parameters to study the two orthogonal projections (M-JAM, sigma(e)) and (M-JAM, R-e(maj)) of the thin Mass Plane (MP) (M-JAM, sigma(e), R-e(maj)) which describes the distribution of the galaxy population, where M-JAM = L x (M/L)(JAM) approximate to M-star. The distribution of galaxy properties on both projections of the MP is characterized by: (i) the same zone of exclusion (ZOE), which can be transformed from one projection to the other using the scalar virial equation. The ZOE is roughly described by two power laws, joined by a break at a characteristic mass M-JAM approximate to 3 x 10(10) M-circle dot, which corresponds to the minimum R-e and maximum stellar density. This results in a break in the mean M-JAM-sigma(e) relation with trends M-JAM proportional to sigma(2.3)(e) and M-JAM proportional to sigma(4.7)(e) at small and large sigma(e), respectively; (ii) a characteristic mass M-JAM approximate to 2 x 10(11) M-circle dot which separates a population dominated by flat fast rotator with discs and spiral galaxies at lower masses, from one dominated by quite round slow rotators at larger masses; (iii) below that mass the distribution of ETGs' properties on the two projections of the MP tends to be constant along lines of roughly constant sigma(e), or equivalently along lines with R-e(maj) proportional to M-JAM, respectively (or even better parallel to the ZOE: R-maj(e) proportional to M-JAM(0.75)); (iv) it forms a continuous and parallel sequence with the distribution of spiral galaxies; (v) at even lower masses, the distribution of fast-rotator ETGs and late spirals naturally extends to that of dwarf ETGs (Sph) and dwarf irregulars (Im), respectively. We use dynamical models to analyse our kinematic maps. We show that Sigma(e) traces the bulge fraction, which appears to be the main driver for the observed trends in the dynamical (M/L)(JAM) and in indicators of the (M/L)(pop) of the stellar population like H beta and colour, as well as in the molecular gas fraction. A similar variation along contours of Sigma(e) is also observed for the mass normalization of the stellar initial mass function (IMF), which was recently shown to vary systematically within the ETGs' population. Our preferred relation has the form log(10)[(M/L)(stars)/(M/L)(Salp)] = a + b x log(10)(sigma(e)/130 km s(-1)) with a = -0.12 +/- 0.01 and b = 0.35 +/- 0.06. Unless there are major flaws in all stellar population models, this trend implies a transition of the mean IMF from Kroupa to Salpeter in the interval log(10)(sigma(e)/km s(-1)) approximate to 1.9-2.5 (or sigma e approximate to 90-290 km s-1), with a smooth variation in between, consistently with what was shown in Cappellari et al. The observed d205 (or sigma e istribution of galaxy properties on the MP provides a clean and novel view for a number of previously reported trends, which constitute special two-dimensional projections of the more general four-dimensional parameters trends on the MP. We interpret it as due to a combination of two main effects: (i) an increase of the bulge fraction, which increases Sigma(e), decreases R-e, and greatly enhance the likelihood for a galaxy to have its star formation quenched, and (ii) dry merging, increasing galaxy mass and R-e by moving galaxies along lines of roughly constant Sigma(e) (or steeper), while leaving the population nearly unchanged.