Organization knowledge management change from a complex adaptive systems perpective with ability for ambidexeterity

We are working on the confluence of knowledge management, organizational memory and emergent knowledge with the lens of complex adaptive systems. In order to be fundamentally sustainable organizations search for an adaptive need for managing ambidexterity of day-to-day work and innovation. An organization is an entity of a systemic nature, composed of groups of people who interact to achieve common objectives, making it necessary to capture, store and share interactions knowledge with the organization, this knowledge can be generated in intra-organizational or inter-organizational level. The organizations have organizational memory of knowledge of supported on the Information technology and systems. Each organization, especially in times of uncertainty and radical changes, to meet the demands of the environment, needs timely and sized knowledge on the basis of tacit and explicit. This sizing is a learning process resulting from the interaction that emerges from the relationship between the tacit and explicit knowledge and which we are framing within an approach of Complex Adaptive Systems. The use of complex adaptive systems for building the emerging interdependent relationship, will produce emergent knowledge that will improve the organization unique developing.

Análise do investimento direto estrangeiro em Portugal utilizando a metodologia de box-jenkins

Dissertação para obtenção do Grau de Mestre em Contabilidade e Finanças Orientadora: Professora Doutora Patrícia Ramos

Matrix Converter-Based Unified Power-Flow Controllers: Advanced Direct Power Control Method

This paper presents a direct power control (DPC) for three-phase matrix converters operating as unified power flow controllers (UPFCs). Matrix converters (MCs) allow the direct ac/ac power conversion without dc energy storage links; therefore, the MC-based UPFC (MC-UPFC) has reduced volume and cost, reduced capacitor power losses, together with higher reliability. Theoretical principles of direct power control (DPC) based on sliding mode control techniques are established for an MC-UPFC dynamic model including the input filter. As a result, line active and reactive power, together with ac supply reactive power, can be directly controlled by selecting an appropriate matrix converter switching state guaranteeing good steady-state and dynamic responses. Experimental results of DPC controllers for MC-UPFC show decoupled active and reactive power control, zero steady-state tracking error, and fast response times. Compared to an MC-UPFC using active and reactive power linear controllers based on a modified Venturini high-frequency PWM modulator, the experimental results of the advanced DPC-MC guarantee faster responses without overshoot and no steady-state error, presenting no cross-coupling in dynamic and steady-state responses.

Solubility of red 153 and blue 1 in supercritical carbon dioxide

Solubilities of red 153, (3-[[4-[[5,6(or 6,7)-dichloro-2-benzothiazolyl]azo]phenyl]ethylamino]propanenitrile), an azo compound, and disperse blue1 (1,4,5,8-tetraaminoantraquinone) in supercritical carbon dioxide (SC CO(2)) were measured at T = (333.2 to 393.2) K over the pressure range (12.0 to 40.0) MPa by a flow type apparatus. The solubility of red 153 (0.985. 10(-6) to 37.2. 10(-6)) in the overall region of measurements is found to be significantly higher than that of disperse blue 1 (1.12.10(-7) to 4.89.10(-7)). The solubility behavior of disperse red 153 follows the general solubility trend displayed by disperse dyes with a crossover pressure at about 20 MPa. On the other hand, blue 1, which is a disperse anthraquinone dye, exhibits unexpected behavior not recorded previously there is no crossover pressure at the temperature and pressure ranges studied, and the dye's solubility at T = 333.2 K practically does not increase with pressure. To the best of our knowledge, there are no previous measurements of blue 1 solubility in SC CO(2) reported in the literature. The experimental data were correlated by using the Soave Redlich Kwong equation of state (EoS) with the one-fluid van der Waals mixing rule, and an acceptable correlation of the solubility data for both dyes was obtained.

Knowledge extraction from medium voltage load diagrams to support the definition of electrical tariffs

With the electricity market liberalization, distribution and retail companies are looking for better market strategies based on adequate information upon the consumption patterns of its electricity customers. In this environment all consumers are free to choose their electricity supplier. A fair insight on the customer´s behaviour will permit the definition of specific contract aspects based on the different consumption patterns. In this paper Data Mining (DM) techniques are applied to electricity consumption data from a utility client’s database. To form the different customer´s classes, and find a set of representative consumption patterns, we have used the Two-Step algorithm which is a hierarchical clustering algorithm. Each consumer class will be represented by its load profile resulting from the clustering operation. Next, to characterize each consumer class a classification model will be constructed with the C5.0 classification algorithm.

Symbolic Knowledge Extraction from Trained Neural Networks Governed by Lukasiewicz Logics

This work describes a methodology to extract symbolic rules from trained neural networks. In our approach, patterns on the network are codified using formulas on a Lukasiewicz logic. For this we take advantage of the fact that every connective in this multi-valued logic can be evaluated by a neuron in an artificial network having, by activation function the identity truncated to zero and one. This fact simplifies symbolic rule extraction and allows the easy injection of formulas into a network architecture. We trained this type of neural network using a back-propagation algorithm based on Levenderg-Marquardt algorithm, where in each learning iteration, we restricted the knowledge dissemination in the network structure. This makes the descriptive power of produced neural networks similar to the descriptive power of Lukasiewicz logic language, minimizing the information loss on the translation between connectionist and symbolic structures. To avoid redundance on the generated network, the method simplifies them in a pruning phase, using the "Optimal Brain Surgeon" algorithm. We tested this method on the task of finding the formula used on the generation of a given truth table. For real data tests, we selected the Mushrooms data set, available on the UCI Machine Learning Repository.

Simulated annealing metaheuristic to solve the optimal power flow

The optimal power flow problem has been widely studied in order to improve power systems operation and planning. For real power systems, the problem is formulated as a non-linear and as a large combinatorial problem. The first approaches used to solve this problem were based on mathematical methods which required huge computational efforts. Lately, artificial intelligence techniques, such as metaheuristics based on biological processes, were adopted. Metaheuristics require lower computational resources, which is a clear advantage for addressing the problem in large power systems. This paper proposes a methodology to solve optimal power flow on economic dispatch context using a Simulated Annealing algorithm inspired on the cooling temperature process seen in metallurgy. The main contribution of the proposed method is the specific neighborhood generation according to the optimal power flow problem characteristics. The proposed methodology has been tested with IEEE 6 bus and 30 bus networks. The obtained results are compared with other wellknown methodologies presented in the literature, showing the effectiveness of the proposed method.

Ant colony search algorithm for the optimal power flow problem

To maintain a power system within operation limits, a level ahead planning it is necessary to apply competitive techniques to solve the optimal power flow (OPF). OPF is a non-linear and a large combinatorial problem. The Ant Colony Search (ACS) optimization algorithm is inspired by the organized natural movement of real ants and has been successfully applied to different large combinatorial optimization problems. This paper presents an implementation of Ant Colony optimization to solve the OPF in an economic dispatch context. The proposed methodology has been developed to be used for maintenance and repairing planning with 48 to 24 hours antecipation. The main advantage of this method is its low execution time that allows the use of OPF when a large set of scenarios has to be analyzed. The paper includes a case study using the IEEE 30 bus network. The results are compared with other well-known methodologies presented in the literature.

Determination of chitin content in fungal cell wall: an alternative flow cytometric method

The conventional methods used to evaluate chitin content in fungi, such as biochemical assessment of glucosamine release after acid hydrolysis or epifluorescence microscopy, are low throughput, laborious, time-consuming, and cannot evaluate a large number of cells. We developed a flow cytometric assay, efficient, and fast, based on Calcofluor White staining to measure chitin content in yeast cells. A staining index was defined, its value was directly related to chitin amount and taking into consideration the different levels of autofluorecence. Twenty-two Candida spp. and four Cryptococcus neoformans clinical isolates with distinct susceptibility profiles to caspofungin were evaluated. Candida albicans clinical isolate SC5314, and isogenic strains with deletions in chitin synthase 3 (chs3Δ/chs3Δ) and genes encoding predicted Glycosyl Phosphatidyl Inositol (GPI)-anchored proteins (pga31Δ/Δ and pga62Δ/Δ), were used as controls. As expected, the wild-type strain displayed a significant higher chitin content (P < 0.001) than chs3Δ/chs3Δ and pga31Δ/Δ especially in the presence of caspofungin. Ca. parapsilosis, Ca. tropicalis, and Ca. albicans showed higher cell wall chitin content. Although no relationship between chitin content and antifungal drug susceptibility phenotype was found, an association was established between the paradoxical growth effect in the presence of high caspofungin concentrations and the chitin content. This novel flow cytometry protocol revealed to be a simple and reliable assay to estimate cell wall chitin content of fungi.

A novel flow cytometric protocol for assessment of yeast cell adhesion

Microbial adhesion is a field of recognized relevance and, as such, an impressive array of tools has been developed to understand its molecular mechanisms and ultimately for its quantification. Some of the major limitations found within these methodologies concern the incubation time, the small number of cells analyzed, and the operator's subjectivity. To overcome these aspects, we have developed a quantitative method to measure yeast cells' adhesion through flow cytometry. In this methodology, a suspension of yeast cells is mixed with green fluorescent polystyrene microspheres (uncoated or coated with host proteins). Within 2 h, an adhesion profile is obtained based on two parameters: percentage and cells-microsphere population's distribution pattern. This flow cytometry protocol represents a useful tool to quantify yeast adhesion to different substrata in a large scale, providing manifold data in a speedy and informative manner.

Ontologies for reusing data cleaning knowledge

The emergence of new business models, namely, the establishment of partnerships between organizations, the chance that companies have of adding existing data on the web, especially in the semantic web, to their information, led to the emphasis on some problems existing in databases, particularly related to data quality. Poor data can result in loss of competitiveness of the organizations holding these data, and may even lead to their disappearance, since many of their decision-making processes are based on these data. For this reason, data cleaning is essential. Current approaches to solve these problems are closely linked to database schemas and specific domains. In order that data cleaning can be used in different repositories, it is necessary for computer systems to understand these data, i.e., an associated semantic is needed. The solution presented in this paper includes the use of ontologies: (i) for the specification of data cleaning operations and, (ii) as a way of solving the semantic heterogeneity problems of data stored in different sources. With data cleaning operations defined at a conceptual level and existing mappings between domain ontologies and an ontology that results from a database, they may be instantiated and proposed to the expert/specialist to be executed over that database, thus enabling their interoperability.

Sistema multi-agente para gestão de tráfego em centros urbanos

Mestrado em Engenharia Informática

Conservation of limpet populations: a heavily exploited resource in Azores, NE-Atlantic

10th International Temperate Reefs Symposium, The University of Western Australia, 12-17 de janeiro.

Avaliação da infecção de megacariócitos e plaquetas pelo VHC e sua influência na fisiopatologia da hepatite C

Pós-graduação em Pesquisa e Desenvolvimento (Biotecnologia Médica) - FMB

Knowledge, attitude and practice of mammography among women users of public health services

OBJECTIVE: To evaluate knowledge, attitude and practice related to mammography among women users of local health services, identifying barriers to its performance. METHODS: A total of 663 women were interviewed at 13 local health centers in a city of Southeastern Brazil, in 2001. Interviewees were randomly selected at each center and they were representative from different socioeconomic conditions. The number of interviewees at each center was proportional to monthly mean appointments. For data analysis, answers were described as knowledge, attitude, practice and their respective adequacies and then they were correlated with control variables through the chi-square test. RESULTS: Only 7.4% of the interviewees had adequate knowledge on mammography, while 97.1% of women had an adequate attitude. The same was seen for the practice of mammography that was adequate in 35.7% of the cases. The main barrier to mammography was lack of referral by physicians working at the health center (81.8%). There was an association between adequacy of attitude and five years or more of education and being married. There was also an association between adequacy of mammography practice and being employed and family income up to four minimum wages. CONCLUSIONS: Women users of local health services had no adequate knowledge and practice related to mammography despite having an adequate attitude about this exam.