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.

Adaptive Random Testing

Abstract: Summary form only given. Random testing is a basic testing technique. Motivated by the observation that neighboring inputs normally exhibit similar failure behavior, the approach of adaptive random testing has recently been proposed to enhance the fault detection capability of random testing. The intuition of adaptive random testing is to evenly spread the randomly generated test cases. Experimental results have shown that adaptive random testing can use as fewer as 50% of test cases required by random testing with replacement to detect the first failure. These results have very significant impact in software testing, because random testing is a basic and popular technique in software testing. In view of such a significant improvement of adaptive random testing over random testing, it is very natural to consider to replace random testing by adaptive random testing. Hence, many works involving random testing may be worthwhile to be reinvestigated using adaptive random testing instead. Obviously, there are different approaches of evenly spreading random test cases. In this tutorial, we are going to present several approaches, and discuss their advantages and disadvantages. Furthermore, the favorable and unfavorable conditions for adaptive random testing would also be discussed. Most existing research on adaptive random testing involves only numeric programs. The recent success of applying adaptive random testing for non-numeric programs would be discussed.

Thermally enhanced machining of hard-to-machine materials: a review

Abstract: Thermally enhanced machining uses external heat sources to heat and soften the workpiece locally in front of the cutting tool. The temperature rise at the shear zone reduces the yield strength and work hardening of the workpiece, which make the plastic deformation of hard-to-machine materials easier during machining. This review summarizes the up-to-date progress and benefits of thermally enhanced machining (with a focus on laser and plasma assistance) of ceramics, metals and metal matrix composites. It covers the integration of the external heat source with cutting tools, analysis of temperature distribution around the cutting region, material removal mechanisms, tool wear mechanisms and the improvement in machinability of various engineering materials by the assistance of external heat source.

Virial Scaling of Massive Dark Matter Halos: Why Clusters Prefer a High Normalization Cosmology

Abstract: We present a precise estimate of the bulk virial scaling relation of halos formed via hierarchical clustering in an ensemble of simulated cold dark matter cosmologies. The result is insensitive to cosmological parameters, the presence of a trace, dissipationless gas component, and numerical resolution down to a limit of ~1000 particles. The dark matter velocity dispersion scales with total mass as log(sigma_{DM}(M,z)) = log(1082.9 +- 4.0 \kms) + (0.3361 +- 0.0026) log(h(z)M_{200}/10^{15} Msun), with h(z) the dimensionless Hubble parameter. At fixed mass, the velocity dispersion likelihood is nearly log-normal, with scatter sigma_{ln sigma} = 0.0426 +- 0.015, except for a tail to higher dispersions containing 10% of the population that are merger transients. We combine this relation with the halo mass function in LCDM models, and show that a low normalization condition, S_8 = sigma_8(Omega_m/0.3)^{0.35} \= 0.69, favored by recent WMAP and SDSS analysis requires that galaxy and gas specific energies in rich clusters be 50% larger than that of the underlying dark matter. Such large energetic biases are in conflict with the current generation of direct simulations of cluster formation. A higher normalization, S_8 = 0.80, alleviates this tension and implies that the hot gas fraction within r_{500} is (0.71 +- 0.09) h_{70}^{-3/2} Omega_b/\Omega_m, a value consistent with recent Sunyaev-Zel'dovich observations.