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.

The SAGES Legacy Unifying Globulars and GalaxieS Survey (SLUGGS): Sample definition, methods, and initial results

Abstract: We introduce and provide the scientific motivation for a wide-field photometric and spectroscopic chemodynamical survey of nearby early-type galaxies (ETGs) and their globular cluster (GC) systems The SAGES Legacy Unifying Globulars and GalaxieS (SLUGGS) survey is being carried out primarily with Subaru/Suprime-Cam and Keck/DEIMOS The former provides deep gri imaging over a 900 arcmin2 field-of-view to characterize GC and host galaxy colors and spatial distributions, and to identify spectroscopic targets The NIR Ca II triplet provides GC line-of-sight velocities and metallicities out to typically ~8 R e, and to ~15 R e in some cases New techniques to extract integrated stellar kinematics and metallicities to large radii (~2-3 R e) are used in concert with GC data to create two-dimensional (2D) velocity and metallicity maps for comparison with simulations of galaxy formation The advantages of SLUGGS compared with other, complementary, 2D-chemodynamical surveys are its superior velocity resolution, radial extent, and multiple halo tracers We describe the sample of 25 nearby ETGs, the selection criteria for galaxies and GCs, the observing strategies, the data reduction techniques, and modeling methods The survey observations are nearly complete and more than 30 papers have so far been published using SLUGGS data Here we summarize some initial results, including signatures of two-phase galaxy assembly, evidence for GC metallicity bimodality, and a novel framework for the formation of extended star clusters and ultracompact dwarfs An integrated overview of current chemodynamical constraints on GC systems points to separate, in situ formation modes at high redshifts for metal-poor and metal-rich GCs

The 1000 brightest hipass galaxies: The HI mass function and Omega(HI)

Abstract: We present a new, accurate measurement of the H I mass function of galaxies from the HIPASS Bright Galaxy Catalog, a sample of 1000 galaxies with the highest H I peak flux densities in the southern (delta<0D) hemisphere. This sample spans nearly 4 orders of magnitude in H I mass [ log (M-H I/M-O) + 2 log h(75)=6.8-10.6] and is the largest sample of H I-selected galaxies to date. We develop a bivariate maximum likelihood technique to measure the space density of galaxies and show that this is a robust method, insensitive to the effects of large-scale structure. The resulting H I mass function can be fitted satisfactorily with a Schechter function with faint-end slope α=-1.30. This slope is found to be dependent on morphological type, with late-type galaxies giving steeper slopes. We extensively test various effects that potentially bias the determination of the H I mass function, including peculiar motions of galaxies, large-scale structure, selection bias, and inclination effects, and we quantify these biases. The large sample of galaxies enables an accurate measurement of the cosmological mass density of neutral gas: U(H) I=(3.8P0.6)x10(-4) h(75)(-1). Low surface brightness galaxies contribute only similar to15% to this value, consistent with previous findings.

An under‐sampled software defect prediction method based on hybrid multi‐objective cuckoo search

Abstract: Both the problem of class imbalance in datasets and parameter selection of Support Vector Machine (SVM) are crucial to predict software defects. However, there is no one working to solve these problems synchronously at present. To tackle this problem, a hybrid multi‐objective cuckoo search under‐sampled software defect prediction model based on SVM (HMOCS‐US‐SVM) is proposed to solve synchronously above two problems. Firstly, a hybrid multi‐objective cuckoo search with dynamical local search (HMOCS) is utilized to select synchronously the non‐defective sampling and optimize the parameters of SVM. Then, three under‐sampled methods for decision region range are proposed to select the non‐defective modules. In the simulation, the three indicators, including the false positive rate (pf), the probability of detection (pd), and G‐mean, are employed to measure the performance of the proposed algorithm. In addition, eight datasets from Promise database are selected to verify the proposed software defect predication model. Comparing with the result of eight prediction models, the proposed method comes into effect on solving software defect prediction problem.

ArcheOpterix: An extendable tool for architecture optimization of AADL models

Abstract: For embedded systems quality requirements are equally if not even more important than functional requirements. The foundation for the fulfillment of these quality requirements has to be set in the architecture design phase. However, finding a suitable architecture design is a difficult task for software and system architects. Some of the reasons for this are an ever-increasing complexity of today's systems, strict design constraints and conflicting quality requirements. To simplify the task, this paper presents an extendable Eclipse-based tool, called ArcheOpterix, which provides a framework to implement evaluation techniques and optimization heuristics for AADL specifications. Currently, evolutionary strategies have been implemented to identify optimized deployment architectures with respect to multiple quality objectives and design constraints. Experiments with a set of initial deployment architectures provide evidence that the tool can successfully find architecture specifications with better quality.