Heartbeat Anomaly Detection using Adversarial Oversampling

Cardiovascular diseases are one of the most common causes of death in the world. Prevention, knowledge of previous cases in the family, and early detection is the best strategy to reduce this fact. Different machine learning approaches to automatic diagnostic are being proposed to this task. As in most health problems, the imbalance between examples and classes is predominant in this problem and affects the performance of the automated solution. In this paper, we address the classification of heartbeats images in different cardiovascular diseases. We propose a two-dimensional Convolutional Neural Network for classification after using a InfoGAN architecture for generating synthetic images to unbalanced classes. We call this proposal Adversarial Oversampling and compare it with the classical oversampling methods as SMOTE, ADASYN, and RandomOversampling. The results show that the proposed approach improves the classifier performance for the minority classes without harming the performance in the balanced classes

Protective wrapping of off-the-shelf components

System designers using off-the-shelf components (OTSCs), whose internals they cannot change, often use add-on “wrappers” to adapt the OTSCs’ behaviour as required. In most cases, wrappers are used to change “functional” properties of the components they wrap. In this paper we discuss instead protective wrapping, the use of wrappers to improve the dependability – i.e., “non-functional” properties like availability, reliability, security, and/or safety – of a component and thus of a system. Wrappers can improve dependability by adding fault tolerance, e.g. graceful degradation, or error recovery mechanisms. We discuss the rational specification of such protective wrappers in view of system dependability requirements, and highlight some of the design trade-offs and uncertainties that affect system design with OTSCs and wrappers, and that differentiate it from other forms of fault-tolerant design

Development of improved plastic foam generating agents and techniques for Saturn applications Final report, Jul. 1964 - Jun. 1965

Foam system compressive strength analysis, solid urethane castings to screen polymer systems, and prepolymer methods of foam preparation in plastic foam development for Saturn projec

Phase Variation of Poly-N-Acetylglucosamine Expression in Staphylococcus aureus

Polysaccharide intercellular adhesin (PIA), also known as poly-N-acetyl-β-(1–6)-glucosamine (PIA/PNAG) is an important component of Staphylococcus aureus biofilms and also contributes to resistance to phagocytosis. The proteins IcaA, IcaD, IcaB, and IcaC are encoded within the intercellular adhesin (ica) operon and synthesize PIA/PNAG. We discovered a mechanism of phase variation in PIA/PNAG expression that appears to involve slipped-strand mispairing. The process is reversible and RecA-independent, and involves the expansion and contraction of a simple tetranucleotide tandem repeat within icaC. Inactivation of IcaC results in a PIA/PNAG-negative phenotype. A PIA/PNAG-hyperproducing strain gained a fitness advantage in vitro following the icaC mutation and loss of PIA/PNAG production. The mutation was also detected in two clinical isolates, suggesting that under certain conditions, loss of PIA/PNAG production may be advantageous during infection. There was also a survival advantage for an icaC-negative strain harboring intact icaADB genes relative to an isogenicicaADBC deletion mutant. Together, these results suggest that inactivation of icaC is a mode of phase variation for PIA/PNAG expression, that high-level production of PIA/PNAG carries a fitness cost, and that icaADB may contribute to bacterial fitness, by an unknown mechanism, in the absence of an intact icaC gene and PIA/PNAG production