Handling causality and schedulability when designing and prototyping cyber-physical systems

Software and Systems Modeling - Cyber physical systems are built upon digital and analog circuits, making it necessary to handle different models of computation during their design and verification...     

Fractal dimension applied to plant identification

This article discusses methods to identify plants by analysing leaf complexity based on estimating their fractal dimension. Leaves were analyzed according to the complexity of their internal and external shapes. A computational program was developed to process, analyze and extract the features of leaf images, thereby allowing for automatic plant identification. Results are presented from two experiments, the first to identify plant species from the Brazilian Atlantic forest and Brazilian Cerrado scrublands, using fifty leaf samples from ten different species, and the second to identify four different species from genus Passiflora, using twenty leaf samples for each class. A comparison is made of two methods to estimate fractal dimension (box-counting and multiscale Minkowski). The results are discussed to determine the best approach to analyze shape complexity based on the performance of the technique, when estimating fractal dimension and identifying plants.     

A general topology-based framework for adaptive insertion of cohesive elements in finite element meshes

Large-scale simulation of separation phenomena in solids such as fracture, branching, and fragmentation requires a scalable data structure representation of the evolving model. Modeling of such phenomena can be successfully accomplished by means of cohesive models of fracture, which are versatile and effective tools for computational analysis. A common approach to insert cohesive elements in finite element meshes consists of adding discrete special interfaces (cohesive elements) between bulk elements. The insertion of cohesive elements along bulk element interfaces for fragmentation simulation imposes changes in the topology of the mesh. This paper presents a unified topology-based framework for supporting adaptive fragmentation simulations, being able to handle two- and three-dimensional models, with finite elements of any order. We represent the finite element model using a compact and “complete” topological data structure, which is capable of retrieving all adjacency relationships needed for the simulation. Moreover, we introduce a new topology-based algorithm that systematically classifies fractured facets (i.e., facets along which fracture has occurred). The algorithm follows a set of procedures that consistently perform all the topological changes needed to update the model. The proposed topology-based framework is general and ensures that the model representation remains always valid during fragmentation, even when very complex crack patterns are involved. The framework correctness and efficiency are illustrated by arbitrary insertion of cohesive elements in various finite element meshes of self-similar geometries, including both two- and three-dimensional models. These computational tests clearly show linear scaling in time, which is a key feature of the present data-structure representation. The effectiveness of the proposed approach is also demonstrated by dynamic fracture analysis through finite element simulations of actual engineering problems.

Advanced product planning: a comprehensive process for systemic definition of new product requirements

This paper reports results of research into the definition of requirements for new consumer products––specifically, electro-mechanical products. The research dealt with the derivation of design requirements that are demonstrably aligned with stakeholder needs. The paper describes a comprehensive process that can enable product development teams to deal with statements of product requirements, as originally collected through market research activities, in a systematic and traceable manner from the early, fuzzy front end, stages of the design process. The process described has been based on principles of systems engineering. A case study from its application and evaluation drawn from the power sector is described in this paper. The case study demonstrates how the process can significantly improve product quality planning practices through revision of captured product requirements, analysis of stakeholder requirements and derivation of design requirements. The paper discusses benefits and issues from the use of the process by product development teams, and identifies areas for further research. Finally, the conclusions drawn from the reported research are presented.

Microbiological survey of a South African poultry processing plant

Bacterial populations associated with poultry processing were determined on neck skin samples, equipment surfaces and environmental samples by replicate surveys. Aerobic plate counts, Enterobacteriaceae counts, Enterobacteriaceae counts and Pseudomonas counts were performed by standard procedures and the prevalence of Listeria, presumptive Salmonella and Staphylococcus aureus determined. Statistically significant (P < 0.05) increases in counts of all types of bacteria were obtained on product samples as a result of processing. Although bacterial counts on neck skin samples decreased by 0.3 to 0.4 log CFU g-1 after spray washing of carcasses, subsequent spinchilling and packaging of whole carcasses resulted in 0.7 to 1.2 log CFU g-1 increases. Bacterial numbers on equipment surfaces, however, decreased significantly from the "dirty" to the "clean" areas of the abattoir. Transport cages, "rubber fingers", defeathering curtains, shackles and conveyor belts repeatedly showed aerobic plate counts in excess of 5.0 log CFU 25 cm-2. Aerobic plate counts of scald tank and spinchiller water were 2 log CFU ml-1 higher than those of potable water samples. Bacterial numbers of the air in the "dirty" area were higher than those of the "clean" area. Listeria, presumptive Salmonella and Staphylococcus aureus were isolated from 27.6, 51.7 and 24.1% of all product samples, respectively, and Listeria and Staphylococcus aureus were also isolated from selected equipment surfaces.