ChangeLedge: Change design and planning in networked systems based on reuse of knowledge and automation

Proper management of Information Technology (IT) resources and services has become imperative for the success of modern organizations. The IT Infrastructure Library (ITIL) represents, in this context, the most widely accepted framework to help achieve this end. Among the processes that compose ITIL, change management has an important role in defining best practices and processes for the efficient and prompt handling of IT changes. In practice, however, such changes are usually described and documented in an ad hoc fashion, due to the lack of proper support to assist the design process. This hampers knowledge acquired when specifying, planning, and carrying out previous changes to be reused in subsequent requests, even though such reuse may result in fewer incidents and faster specification of change plans. To address this problem, in this paper we present a conceptual solution to support the design and planning of IT changes and explore the concept of change templates as a mechanism to formalize, preserve, and (re)use knowledge in the specification of (recurrent and similar) IT changes. To prove concept and technical feasibility of the proposed solution, we have developed a prototypical implementation of a change management system called ChangeLedge and used it to carry out a set of experiments, considering typical IT changes. The results obtained indicate the effectiveness and efficiency of the system, which is able to generate accurate and actionable change plans in substantially less time than would be spent by a skilled human operator.     

Implementation of Industry 4.0 and lean production in Brazilian manufacturing companies

The adoption of Industry 4.0 technologies has been deemed as a strategy to increase product quality and make manufacturing processes more efficient. However, the way that these technologies are integrated into existing production systems and which processes they can support is still under investigation. Thus, this paper aims to examine the relationship between lean production (LP) practices and the implementation of Industry 4.0 in Brazilian manufacturing companies. To achieve that we use data from a survey carried out with 110 companies of different sizes and sectors, at different stages of LP implementation. Data collected were analysed by means of multivariate analysis. Our findings indicate that LP practices are positively associated with Industry 4.0 technologies and their concurrent implementation leads to larger performance improvements. Further, the contextual variables investigated do matter to this association, although not all aspects matter to the same extent and effect.     

Neural network ensembles: immune-inspired approaches to the diversity of components

This work applies two immune-inspired algorithms, namely opt-aiNet and omni-aiNet, to train multi-layer perceptrons (MLPs) to be used in the construction of ensembles of classifiers. The main goal is to investigate the influence of the diversity of the set of solutions generated by each of these algorithms, and if these solutions lead to improvements in performance when combined in ensembles. omni-aiNet is a multi-objective optimization algorithm and, thus, explicitly maximizes the components’ diversity at the same time it minimizes their output errors. The opt-aiNet algorithm, by contrast, was originally designed to solve single-objective optimization problems, focusing on the minimization of the output error of the classifiers. However, an implicit diversity maintenance mechanism stimulates the generation of MLPs with different weights, which may result in diverse classifiers. The performances of opt-aiNet and omni-aiNet are compared with each other and with that of a second-order gradient-based algorithm, named MSCG. The results obtained show how the different diversity maintenance mechanisms presented by each algorithm influence the gain in performance obtained with the use of ensembles.     

Improved similarity trees and their application to visual data classification

An alternative form to multidimensional projections for the visual analysis of data represented in multidimensional spaces is the deployment of similarity trees, such as Neighbor Joining trees. They organize data objects on the visual plane emphasizing their levels of similarity with high capability of detecting and separating groups and subgroups of objects. Besides this similarity-based hierarchical data organization, some of their advantages include the ability to decrease point clutter; high precision; and a consistent view of the data set during focusing, offering a very intuitive way to view the general structure of the data set as well as to drill down to groups and subgroups of interest. Disadvantages of similarity trees based on neighbor joining strategies include their computational cost and the presence of virtual nodes that utilize too much of the visual space. This paper presents a highly improved version of the similarity tree technique. The improvements in the technique are given by two procedures. The first is a strategy that replaces virtual nodes by promoting real leaf nodes to their place, saving large portions of space in the display and maintaining the expressiveness and precision of the technique. The second improvement is an implementation that significantly accelerates the algorithm, impacting its use for larger data sets. We also illustrate the applicability of the technique in visual data mining, showing its advantages to support visual classification of data sets, with special attention to the case of image classification. We demonstrate the capabilities of the tree for analysis and iterative manipulation and employ those capabilities to support evolving to a satisfactory data organization and classification.     

UPLC-PDA–MS evaluation of bioactive compounds from leaves of Ilex paraguariensis with different growth conditions,treatments and ageing

Teas from Maté have been widely consumed for centuries in Brazil, Argentina, Paraguay, and Uruguay. We now determine how age, growth conditions and post-harvesting processes of leaves from Ilex paraguariensis affect the concentration of bioactive compounds and their antioxidant capacity. Phenolics, xanthines, and carbohydrates were identified and quantified by electrospray ionisation mass spectrometry (ESI-MS) and ultra performance liquid chromatography (UPLC), which dramatically reduces the time for each analysis (<3 min). On average, sun-exposed (monoculture) leaf extracts exhibited higher levels of bioactive compounds as compared to shaded (forest grown) ones. PCA (principal component analysis) analysis of all the samples indicated that those obtained after blanching and drying contained more phenolics and a smaller concentration of xanthine than those in natura. The oxidised leaves had lower concentrations of phenolics, and consequently a decline in antioxidant activity. No differences were found based on the leaf age.     

Cacao quality: Highlighting selected attributes

World demand for cacao and the requirements for quality beans have increased every year. Research studies have developed standards for aspects of cacao quality that meet industrial criteria as well as international import and export legislation that is aimed at food security. This review focused on selected attributes of cacao bean quality. These attributes include the amount of acids, simple carbohydrates, proteins, amino acids, lipids, phenolic substances, and methylxanthines. Other attributes are bean moisture content, quantity of mineral nutrients, and presence of potentially toxic elements. Microbiological and organoleptic attributes are also of interest. Future research on cacao quality should focus on bean sampling, geographical location of plantations, genetic diversity of the cacao material, and standardized analytical methods for determination of organic and mineral substances.     

Application of <Emphasis Type="Italic">L</Emphasis><Subscript>cr</Subscript> Waves to Evaluate Residual Stresses in the RIM of Railroad Forged Wheels

The process of manufacturing wrought railroad wheels consists of forging heated blocks of steel, which are machined, heated, and quenched to reach the correct level of the mechanical properties to be used in railroads. The process generates compressive hoop stresses in the wheel rim. In field conditions, the original stress pattern can be changed mainly by overheating, which is caused by severe braking. The change from compressive stresses in the rim to traction can facilitate crack propagation. Indeed, even a small crack can propagate suddenly, causing a derailment. This work presents a new approach to evaluate the stresses generated by braking heating. It is based on the acoustoelastic effect, which relates the wave speed of ultrasonic waves to the strain state of the part. The method uses longitudinal critically refracted waves and a simplified system based on ultrasonic commercial products. The results show that the method is a stress sensitive and high resolution way to improve the safety of railroad wheels, making it a suitable alternative to be used at maintenance shops.