Criteria for ERP selection using an AHP approach

Information systems are a foundation key element of modern organizations. Quite often, chief executive officers and managers have to decide about the acquisition of new software solution based in an appropriated set of criteria. Analytic Hierarchy Process (AHP) is one technique used to support that kind of decisions. This paper proposes the application of AHP method to the selection of ERP (Enterprise Resource Planning) systems, identifying the set of criteria to be used. A set of criteria was retrieved from the scientific literature and validated through a survey-based approach.

Effect of fiber alignment in gelled electrospun membranes based on poly(vinylidene fluoride) for battery applications

Battery separators based on electrospun membranes of poly(vinylidene fluoride) (PVDF) have been prepared in order to study the effect of fiber alignment on the performance and characteristics of the membrane. The prepared membranes show an average fiber diameter of 272 nm and a degree of porosity of 87 %. The gel polymer electrolytes are prepared by soaking the membranes in the electrolyte solution. The alignment of the fibers improves the mechanical properties for the electrospun membranes. Further, the microstructure of the membrane also plays an important role in the ionic conductivity, being higher for the random electrospun membrane due to the lower tortuosity value. Independently of the microstructure, both membranes show good electrochemical stability up to 5.0 V versus Li/Li+. These results show that electrospun membranes based on PVDF are appropriate for battery separators in lithium-ion battery applications, the random membranes showing a better overall performance.

A mobile health care rule-based system

The relation between patient and physician in most modern Health Care Sys- tems is sparse, limited in time and very in exible. On the other hand, and in contradiction with several recent studies, most physicians do not rely their patient diagnostics evaluations on intertwined psychological and social nature factors. Facing these problems and trying to improve the patient/physician relation we present a mobile health care solution to im- prove the interaction between the physician and his patients. The solution serves not only as a privileged mean of communication between physicians and patients but also as an evolutionary intelligent platform delivering a mobile rule based system.

Automatic segmentation and 3D feature extraction of protein aggregates in Caenorhabditis Elegans

In the last years, it has become increasingly clear that neurodegenerative diseases involve protein aggregation, a process often used as disease progression readout and to develop therapeutic strategies. This work presents an image processing tool to automatic segment, classify and quantify these aggregates and the whole 3D body of the nematode Caenorhabditis Elegans. A total of 150 data set images, containing different slices, were captured with a confocal microscope from animals of distinct genetic conditions. Because of the animals’ transparency, most of the slices pixels appeared dark, hampering their body volume direct reconstruction. Therefore, for each data set, all slices were stacked in one single 2D image in order to determine a volume approximation. The gradient of this image was input to an anisotropic diffusion algorithm that uses the Tukey’s biweight as edge-stopping function. The image histogram median of this outcome was used to dynamically determine a thresholding level, which allows the determination of a smoothed exterior contour of the worm and the medial axis of the worm body from thinning its skeleton. Based on this exterior contour diameter and the medial animal axis, random 3D points were then calculated to produce a volume mesh approximation. The protein aggregations were subsequently segmented based on an iso-value and blended with the resulting volume mesh. The results obtained were consistent with qualitative observations in literature, allowing non-biased, reliable and high throughput protein aggregates quantification. This may lead to a significant improvement on neurodegenerative diseases treatment planning and interventions prevention