Toward Intelligent Software Defect Detection

Source code level software defect detection has gone from state of the art to a software engineering best practice. Automated code analysis tools streamline many of the aspects of formal code inspections but have the drawback of being difficult to construct and either prone to false positives or severely limited in the set of defects that can be detected. Machine learning technology provides the promise of learning software defects by example, easing construction of detectors and broadening the range of defects that can be found. Pinpointing software defects with the same level of granularity as prominent source code analysis tools distinguishes this research from past efforts, which focused on analyzing software engineering metrics data with granularity limited to that of a particular function rather than a line of code

Surrounding neighborhood-based SMOTE for learning from imbalanced data sets

Many traditional approaches to pattern classifi- cation assume that the problem classes share similar prior probabilities. However, in many real-life applications, this assumption is grossly violated. Often, the ratios of prior probabilities between classes are extremely skewed. This situation is known as the class imbalance problem. One of the strategies to tackle this problem consists of balancing the classes by resampling the original data set. The SMOTE algorithm is probably the most popular technique to increase the size of the minority class by generating synthetic instances. From the idea of the original SMOTE, we here propose the use of three approaches to surrounding neighborhood with the aim of generating artificial minority instances, but taking into account both the proximity and the spatial distribution of the examples. Experiments over a large collection of databases and using three different classifiers demonstrate that the new surrounding neighborhood-based SMOTE procedures significantly outperform other existing over-sampling algorithms

Biomedical Perspectives II

Abstract book of International Scientific Conference of Students, Postgraduates and Young Scientist

DAFI: a single mode optical fibre interferometer for astronomy

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Collagen-phosphate glass fibres for biomedical and tissue engineering applications.

The aim of this project was to develop three-dimensional (3-D) constructs of phosphate-based glass fibres (PGF) incorporated dense collagen matrices for biomedical and tissue engineering applications. For this, a novel method of "plastic compression" (PC) was used which rapidly removes fluid from hyper-hydrated collagen gels through the application of unconfined compressive load. The project objectives were: the understanding of structure-property relationship of PGF the understanding of the mechanisms of PC to produce dense collagenous matrices, and the application of PC to produce cellular 3-D constructs of PGF reinforced collagen matrices. PGF are unique glasses as they are degradable and biocompatible, and their degradation can be controlled through their chemistry. Two different quaternary glass systems incorporating CuO and Fe2O3 into the ternary glass system (in molar percentage) 50 P2O5- 30 CaO-20 Na2O were developed for either antibacterial or tissue engineering applications. These additional oxides were incorporated into the glass structure by partially substituting Na20. The rate of degradation was significantly decreased by the incorporation of both oxides possibly due to increased cross-link density, which correlated with an increase in the density and glass transition temperature. There was a further decrease in degradation with increasing fibre diameter. The amount of Cu2+ release increased with increasing CuO content, and 10 mol % was the most effective in killing Staphylococcus epidermidis. YqjOt, had a much more significant effect on rate of degradation, and the rate of Fe3+ release decreased with increasing Fe203 content. From the compositions and fibre diameters investigated, fibres containing 3-5 mol % Fe203 with a diameter of 30 urn were more durable, and therefore suitable for use as scaffolds. Furthermore, upon long term degradation, the iron containing glass systems showed the potential for tube formation. PC depends mainly on the ability of collagen to undergo creep deformation and no recovery upon load removal. Using this principle, a dense collagen matrix with improved mechanical properties was produced. PC was also successful in producing PGF-PC collagen constructs with different compositions. It was anticipated that PGF would initially further enhance the mechanical properties of the constructs. Moreover, PGF also provided the intriguing possibility of capillary-like channels within the collagen for cell and nutrient transportations. The effect of PGF incorporation was assessed morphologically, mechanically, and biologically using live/dead staining. Increasing the proportion of PGF yielded significantly stiffer, stronger constructs while compromising their compliance. At greatest, only 20 % cell death due to either PC or PGF incorporation occurred, however, a significant increase in cell viability after 24 hours was observed. The findings suggested that PC is effective for engineering composite, biomimetic collagen matrices with controllable properties