Inferring extended finite state machine models from software executions

The ability to reverse-engineer models of software behaviour is valuable for a wide range of software maintenance, validation and verification tasks. Current reverse-engineering techniques focus either on control-specific behaviour (e.g., in the form of Finite State Machines), or data-specific behaviour (e.g., as pre / post-conditions or invariants). However, typical software behaviour is usually a product of the two; models must combine both aspects to fully represent the software’s operation. Extended Finite State Machines (EFSMs) provide such a model. Although attempts have been made to infer EFSMs, these have been problematic. The models inferred by these techniques can be non-deterministic, the inference algorithms can be inflexible, and only applicable to traces with specific characteristics. This paper presents a novel EFSM inference technique that addresses the problems of inflexibility and non-determinism. It also adapts an experimental technique from the field of Machine Learning to evaluate EFSM inference techniques, and applies it to three diverse software systems.     

Thread-Locking Adhesive Failure and a Unique Corrective Action

Thread-locking adhesives are commonly added to impart extra torque strength as well preventing screws from backing out during use. Many of these adhesives rely on anaerobic (oxygen free) conditions for curing. Often, if not properly cured, the locking compounds which are usually oily liquids, actually behave in a manner completely opposite of design and screws intended to be strengthened are in fact compromised beyond if no locking compound were present at all. Discussed herein is such an example in which, if a solution were not found to allow for curing of the locking compounds on assembled systems, over 2,000 costly sensor assemblies would have been scrapped. Fortunately, an unconventional solution was found.     

Starch–methylcellulose–whey protein film properties

Four % (wt/wt) aqueous solutions were prepared at corn starch:methylcellulose:whey protein isolate (CS:MC:WPI) ratios of 2:2:2, 1:2:3, 2:1:3, 2:2:0, 1:2:0 and 2:1:0. Glycerol (gly) was used as a plasticiser at CS–MC–WPI:gly ratios of 2:1, 2.5:1 and 3:1. CS–MC–WPI blend films were stronger than CS–WPI films and had lower oxygen permeability (OP) than MC–WPI films. The highest tensile strength (TS) of blend films was 8.01 ± 3.41 MPa, at CS:MC:WPI ratio of 2:2:0 and CS–MC–WPI:gly ratio of 3:1. Lowest OP value was 45.05 ± 7.24 cm³ μm m^?2 per day kPa^?1, at CS:MC:WPI ratio of 2:2:2 and CS–MC–WPI:gly ratio of 3:1. OP values were predictable based on relative amounts of components. However, TS and elastic modulus properties of the CS–MC–WPI blend films did not reflect the relative amounts of the components. All of CS–MC–WPI films were translucent indicating some degree of immiscibility among the CS, MC and WPI. These results indicate the influence of complex molecular interactions among the components.     

An NMR-based metabolomic assessment of cultured cobia health in response to dietary manipulation

Commercial aquaculture feeds rely heavily on fishmeal and fish oil, which can be expensive and ecologically unsustainable. To evaluate the efficacy of reduced fishmeal diets for outgrowth, a dietary study was conducted on the finfish cobia, Rachycentron canadum. NMR-based metabolomic techniques were used to assess the effect of decreasing dietary fishmeal on the health of the cobia. Filtered serum ¹H NMR spectra analysed by principal components analysis (PCA) showed cobia fed reduced fishmeal diets were metabolically different than cobia on control diets. In particular, tyrosine and betaine increased in cobia fed reduced fishmeal diets while glucose decreased, suggesting that these cobia were not receiving the necessary nutritional components required for energy and growth. The formulated control diet contributed to enriched growth and significantly elevated lactate levels suggesting enhanced gut microflora metabolism in response to dietary components. The results show that NMR-based metabolomic analysis is a useful tool in aquaculture studies.     

Drink-driving in community sports clubs: Adopting the Good Sports alcohol management program

Throughout the developed world, community sports clubs are a high-risk setting for alcohol-impaired driving. The Good Sports program accredits community sports clubs to encourage implementation of alcohol-focussed harm-reduction and safe-transport strategies. This study tested for associations between participation in the Good Sports program and reduced rates of drink-driving amongst club members. Multilevel modelling indicated that for each season a club was in the program there was an 8% reduction in the odds of drink-driving. These findings may arise due to clubs with lower rates of alcohol use maintaining longer involvement in the program. However, the findings are also compatible with the intention of the Good Sports program to reduce the risk that club members will drive whilst alcohol impaired.     

Extraction of Siphonochilus aethiopicus Essential Oil by Steam Distillation

Siphonochilus aethiopicus is an indigenous South African plant also known as African ginger. It has often been used for its medicinal properties to treat various ailments such as flu, colds, and so forth. The research aim of this study was to optimize the process parameters of steam distillation for the extraction of oil from African ginger rhizomes. This technology is the oldest and well known for extracting essential oils due to its economic viability and the higher final oil purity. The effects of operating parameters such as extraction duration, moisture content, particle size, and temperatures between 80°C and 100°C were studied for maximum oil recovery. The oil recovery of 0.61% (w/w) was achieved after 270?min of extraction time, using 6.37% (dry) moisture content of particle size 2.4?mm–4?mm at a maximum temperature of 100°C. Fick’s first law was used to mathematically model the experimental data of this study.     

Experimental validation of a type-2 fuzzy logic controller for energy management in hybrid electrical vehicles

The aim of this paper is to present experimental validation results of an energy management system for hybrid electrical vehicles based on type-2 fuzzy logic. The energy management system (EMS) is designed by extracting knowledge from several experts using surveys. The consideration of interval type-2 fuzzy sets enables modeling the uncertainty in the answers of the experts. The validation of the EMS is performed on a real-scale heavy duty vehicle equipped with different energy sources such as batteries, fuel cell system and ultracapacitors. Experimental results are strong evidence that type-2 fuzzy logic is wide adapted for performing the energy management in hybrid electrical vehicles.