A Cost-sensitive Intelligent Prediction Model for Outsourced Software Project Risk

Outsourced software project is one of the main ways of software development, which is of high failure rate. Intelligent risk prediction model can help identify high risk project in time. However, the existing models are mostly based on such a hypothesis that all the cost of misclassification is equal, which is not consistent with the reality that in the domain of software project risk prediction, the cost of predicting a fail-prone project as a success-prone project is different from predicting a success-prone project as a fail-prone project. To the best of our knowledge, the cost-sensitive learning method has not yet been applied in the domain of outsourced software project risk management though it has been widely used in a variety of fields. Based on this situation, we selected five classifiers, and introduced cost-sensitive learning method to build intelligent prediction models respectively. This paper totally collected 292 real data of outsourced software project for modeling. Experiment results showed that, under cost-sensitive scenario, the polynomial kernel support vector machine is the best classifier for outsourced software project risk prediction among the five classifiers due to its high prediction accuracy, stability and low cost

The Effect of Superparamagnetic Iron Oxide Nanoparticle Surface Charge on Antigen Cross-Presentation.

Magnetic nanoparticles (NPs) of superparamagnetic iron oxide (SPIO) have been explored for different kinds of applications in biomedicine, mechanics, and information. Here, we explored the synthetic SPIO NPs as an adjuvant on antigen cross-presentation ability by enhancing the intracellular delivery of antigens into antigen presenting cells (APCs). Particles with different chemical modifications and surface charges were used to study the mechanism of action of antigen delivery. Specifically, two types of magnetic NPs, γF

Where to find lossless metals?

Hypothetical metals having optical absorption losses as low as those of the transparent insulators, if found, could revolutionize optoelectronics. We perform the first high-throughput search for lossless metals among all known inorganic materials in the databases of over 100,000 entries. The 381 candidates are identified -- having well-isolated partially-filled bands -- and are analyzed by defining the figures of merit and classifying their real-space conductive connectivity. The existing experimental evidence of most candidates being insulating, instead of conducting, is due to the limitation of current density functional theory in predicting narrow-band metals that are unstable against magnetism, structural distortion, or electron-electron interactions. We propose future research directions including conductive oxides, intercalating layered materials, and compressing these false-metal candidates under high pressures into eventual lossless metals.Comment: 36 pages, 86 figures, 3 tabl

Effect of TiF₃ catalyst on the tribological properties of carbon black-contaminated engine oils

AbstractThe effects of a TiF3 catalyst on the tribological behaviour of carbon black-contaminated liquid paraffin and a fully formulated engine lubricating oil (CD SAE15W-40) were investigated using a four-ball tribological test. Scanning electronic microscopy with energy-dispersive spectroscopy, X-ray photoelectron spectroscopy, surface roughness, and thermogravimetric analyses were used to investigate the surface element content, chemical valence state, surface roughness, and initial decomposition temperature of the oil samples, respectively. Results showed that the average wear scar diameter (AWSD) and friction coefficient of the two kinds of carbon black-contaminated lubricants decreased in the presence of 0.5wt% TiF3. The variation rates of the carbon black-contaminated liquid paraffin and fully formulated engine lubricating oil were 29.45% and 11.54%, respectively, and their initial decomposition temperatures decreased. These phenomena were ascribed to the decomposition of TiF3 catalyst into TiO2 and fluoride that resulted in the formation of improved boundary lubrication films. Moreover, for the fully formulated engine oil, the lubrication additive zinc dialkyldithiophosphate was catalyzed by TiF3, decomposing into polyphosphate, which aided the formation of mixture boundary lubrication films