Autonomic computing for scheduling in manufacturing systems

We describe a novel approach to scheduling resolution by combining Autonomic Computing (AC), Multi-Agent Systems (MAS) and Nature Inspired Optimization Techniques (NIT). Autonomic Computing has emerged as paradigm aiming at embedding applications with a management structure similar to a central nervous system. A natural Autonomic Computing evolution in relation to Current Computing is to provide systems with Self-Managing ability with a minimum human interference. In this paper we envisage the use of Multi-Agent Systems paradigm for supporting dynamic and distributed scheduling in Manufacturing Systems with Autonomic properties, in order to reduce the complexity of managing systems and human interference. Additionally, we consider the resolution of realistic problems. The scheduling of a Cutting and Treatment Stainless Steel Sheet Line will be evaluated. Results show that proposed approach has advantages when compared with other scheduling systems.

PCMAT Metadata Authoring Tool

This paper introduces the PCMAT platform project and, in particular, one of its components, the PCMAT Metadata Authoring Tool. This is an educational web application that allows the project metadata creators to write the metadata associated to each learning object without any concern for the metadata schema semantics. Furthermore it permits the project managers to add or delete elements to the schema, without having to rewrite or compile any code.

SmartClean: an incremental data cleaning tool

This paper presents the SmartClean tool. The purpose of this tool is to detect and correct the data quality problems (DQPs). Compared with existing tools, SmartClean has the following main advantage: the user does not need to specify the execution sequence of the data cleaning operations. For that, an execution sequence was developed. The problems are manipulated (i.e., detected and corrected) following that sequence. The sequence also supports the incremental execution of the operations. In this paper, the underlying architecture of the tool is presented and its components are described in detail. The tool's validity and, consequently, of the architecture is demonstrated through the presentation of a case study. Although SmartClean has cleaning capabilities in all other levels, in this paper are only described those related with the attribute value level.

IGTAI - an Idea Generation Tool for Ambient Inteligence

Today, business group decision making is an extremely important activity. A considerable number of applications and research have been made in the past years in order to increase the effectiveness of decision making process. In order to support the idea generation process, IGTAI (Idea Generation Tool for Ambient Intelligence) prototype was created. IGTAI is a Group Decision Support System designed to support any kind of meetings namely distributed, asynchronous or face to face. It aims at helping geographically distributed (or not) people and organizations in the idea generation task, by making use of pervasive hardware in a meeting room, expanding the meeting beyond the room walls by allowing a ubiquitous access through different kinds of equipment. This paper focus on the research made to build IGTAI prototype, its architecture and its main functionalities, namely the support given in the different phases of the idea generation meeting.

Arrow Plot: a new graphical tool for selecting up and down regulated genes and genes differentially expressed on samples subgroups

Background: A common task in analyzing microarray data is to determine which genes are differentially expressed across two (or more) kind of tissue samples or samples submitted under experimental conditions. Several statistical methods have been proposed to accomplish this goal, generally based on measures of distance between classes. It is well known that biological samples are heterogeneous because of factors such as molecular subtypes or genetic background that are often unknown to the experimenter. For instance, in experiments which involve molecular classification of tumors it is important to identify significant subtypes of cancer. Bimodal or multimodal distributions often reflect the presence of subsamples mixtures. Consequently, there can be genes differentially expressed on sample subgroups which are missed if usual statistical approaches are used. In this paper we propose a new graphical tool which not only identifies genes with up and down regulations, but also genes with differential expression in different subclasses, that are usually missed if current statistical methods are used. This tool is based on two measures of distance between samples, namely the overlapping coefficient (OVL) between two densities and the area under the receiver operating characteristic (ROC) curve. The methodology proposed here was implemented in the open-source R software. Results: This method was applied to a publicly available dataset, as well as to a simulated dataset. We compared our results with the ones obtained using some of the standard methods for detecting differentially expressed genes, namely Welch t-statistic, fold change (FC), rank products (RP), average difference (AD), weighted average difference (WAD), moderated t-statistic (modT), intensity-based moderated t-statistic (ibmT), significance analysis of microarrays (samT) and area under the ROC curve (AUC). On both datasets all differentially expressed genes with bimodal or multimodal distributions were not selected by all standard selection procedures. We also compared our results with (i) area between ROC curve and rising area (ABCR) and (ii) the test for not proper ROC curves (TNRC). We found our methodology more comprehensive, because it detects both bimodal and multimodal distributions and different variances can be considered on both samples. Another advantage of our method is that we can analyze graphically the behavior of different kinds of differentially expressed genes. Conclusion: Our results indicate that the arrow plot represents a new flexible and useful tool for the analysis of gene expression profiles from microarrays.

Commercial agents portfolio optimization in electricity markets

As it is well known, competitive electricity markets require new computing tools for power companies that operate in retail markets in order to enhance the management of its energy resources. During the last years there has been an increase of the renewable penetration into the micro-generation which begins to co-exist with the other existing power generation, giving rise to a new type of consumers. This paper develops a methodology to be applied to the management of the all the aggregators. The aggregator establishes bilateral contracts with its clients where the energy purchased and selling conditions are negotiated not only in terms of prices but also for other conditions that allow more flexibility in the way generation and consumption is addressed. The aggregator agent needs a tool to support the decision making in order to compose and select its customers' portfolio in an optimal way, for a given level of profitability and risk.

Azorean Agriculture Efficiency by PAR

Copyright © 2013 Springer Netherlands.

Computing the phase diagram of binary mixtures: A patchy particle case study

We investigate the phase behaviour of 2D mixtures of bi-functional and three-functional patchy particles and 3D mixtures of bi-functional and tetra-functional patchy particles by means of Monte Carlo simulations and Wertheim theory. We start by computing the critical points of the pure systems and then we investigate how the critical parameters change upon lowering the temperature. We extend the successive umbrella sampling method to mixtures to make it possible to extract information about the phase behaviour of the system at a fixed temperature for the whole range of densities and compositions of interest. (C) 2013 AIP Publishing LLC.

Demand response in future power systems management – a conceptual framework and simulation tool

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Deep ocean species. The little that is known mostly comes from collected specimens. Comment on L.A. Rocha et al. Letter "Specimen collection: An essential tool" (23 May, 344: 814).

Deep Ocean Species. The little that is known mostly comes from collected specimens. L.A. Rocha et al. Letter "Specimen collection: An essential tool" (23 May, 344: 814) brilliantly discuss the importance of specimen collection and present the evolution of collecting since the mid-19th century until our present strict codes and conducts. However, it is also important to emphasize the fact that the vast majority of deep ocean macro-organisms are only known to us because of collection and this is a strong argument that should be present in our actions as scientists. If the deep is considered the least known of Earth’s habitats (1% or so according to recent estimates) then what awesome collection of yet to discover species are still there to be properly described? As the authors point citing (1), something around 86% of species remain unknown. Voucher specimens are fundamental for the reasons pointed out and perhaps the vast depths of the World’s oceans are the best example of that importance. The resumed report of 2010 Census of Marine Life (2) showed that among the millions of specimens collected in both familiar and seldom-explored waters, the Census found more than 6,000 potentially new species and completed formal descriptions of more than 1,200 of them. It also found that a number of rare species are in fact common. Voucher specimens are essential and, again agreeing with L.A. Rocha et al. Letter (see above), the modern approach for collecting will not be a cause for extinctions but instead a valuable tool for knowledge, description and even, as seen above, a way to find out that supposed rare species may not be that rare and even prove to reach abundant populations.

An ultrasound based computer-aided diagnosis tool for steatosis detection

Liver steatosis is a common disease usually associated with social and genetic factors. Early detection and quantification is important since it can evolve to cirrhosis. In this paper, a new computer-aided diagnosis (CAD) system for steatosis classification, in a local and global basis, is presented. Bayes factor is computed from objective ultrasound textural features extracted from the liver parenchyma. The goal is to develop a CAD screening tool, to help in the steatosis detection. Results showed an accuracy of 93.33%, with a sensitivity of 94.59% and specificity of 92.11%, using the Bayes classifier. The proposed CAD system is a suitable graphical display for steatosis classification.

Evaluation of 99mTc-Sestamibi as a potential tool to investigate PgP activity in inflammation

Introduction: In the XXI Century ’s Society the scientific investigation process has been growing steadily , and the field of the pharmaceutical research is one of the most enthusiastic and relevant . Here, it is very important to correlate observed functional alterations with possibly modified drug bio distribution patterns . Cancer, inflammation and inf ection are processes that induce many molecular intermediates like cytokines, chemokines and other chemical complexes that can alter the pharmacokinetics of many drugs. One cause of such changes is thought to be the modulator action of these complexes in t he P - Glyco p rotein activity, because they can act like inducers/inhibitors of MDR - 1 expression. This protein results from the expression of MDR - 1 gene, and acts as an ATP energy - dependent efflux pump, with their substrates including many drugs , like antiretrovirals, anticancers, anti - infectives, immunosuppressants, steroids or opioids . Objectives: Because of the lack of methods to provide helpful information in the investigation of in vivo molecular changes in Pgp activity during infection/infl ammation processes, and its value in the explanation of the altered drug pharmacokinetic, this paper want to evaluate the potential utility of 99m Tc - Sestamibi scintigraphy during this kind of health sciences investigation. Although the a im is indeed to create a technique to the in vivo study of Pgp activity, this preliminary Project only reaches the in vitro study phase, assumed as the first step in a n evaluation period for a new tool development. Materials and Methods: For that reason , we are performing in vitro studies of influx and efflux of 99m Tc - Sestamibi ( that is a substrate of Pgp) in hepatocytes cell line (HepG2). We are interested in clarify the cellular behavior of this radiopharmaceutical in Lipopolysaccharide(LPS) stimulated cells ( well known in vitro model of inflammation) to possibly approve this methodology. To validate the results, the Pgp expression will be finally evaluated using Western Blot technique. Results: Up to this moment , we still don’t have the final results, but we have already enough data to let us believe that LPS stimulation induce a downregulation of MDR - 1, and consequently Pgp, which could conduce to a prolonged retention of 99m Tc - Sestamibi in the inflamed cells . Conclusions: If and when this methodology demonstrate the promising results we expect, one will be able to con clude that Nuclear Medicine is an important tool to help evidence based research also on this specific field .

Previsão de vento baseado em técnicas de Data Mining

Mestrado em Engenharia Electrotécnica – Sistemas Eléctricos de Energia

Projetos de empreendedorismo nas escolas : impactos nos alunos e na organização escolar

Dissertação de Mestrado em Educação, especialidade em Administração e Organização Escolar.