An approach to implement data fusion techniques in wireless sensor networks using genetic machine learning algorithms

Wireless Sensor Networks (WSNs) can be used to monitor hazardous and inaccessible areas. In these situations, the power supply (e.g. battery) of each node cannot be easily replaced. One solution to deal with the limited capacity of current power supplies is to deploy a large number of sensor nodes, since the lifetime and dependability of the network will increase through cooperation among nodes. Applications on WSN may also have other concerns, such as meeting temporal deadlines on message transmissions and maximizing the quality of information. Data fusion is a well-known technique that can be useful for the enhancement of data quality and for the maximization of WSN lifetime. In this paper, we propose an approach that allows the implementation of parallel data fusion techniques in IEEE 802.15.4 networks. One of the main advantages of the proposed approach is that it enables a trade-off between different user-defined metrics through the use of a genetic machine learning algorithm. Simulations and field experiments performed in different communication scenarios highlight significant improvements when compared with, for instance, the Gur Game approach or the implementation of conventional periodic communication techniques over IEEE 802.15.4 networks. © 2013 Elsevier B.V. All rights reserved.

A model for analysing data portal performance: The biodiversity case

Currently, many museums, botanic gardens and herbariums keep data of biological collections and using computational tools researchers digitalize and provide access to their data using data portals. The replication of databases in portals can be accomplished through the use of protocols and data schema. However, the implementation of this solution demands a large amount of time, concerning both the transfer of fragments of data and processing data within the portal. With the growth of data digitalization in institutions, this scenario tends to be increasingly exacerbated, making it hard to maintain the records updated on the portals. As an original contribution, this research proposes analysing the data replication process to evaluate the performance of portals. The Inter-American Biodiversity Information Network (IABIN) biodiversity data portal of pollinators was used as a study case, which supports both situations: conventional data replication of records of specimen occurrences and interactions between them. With the results of this research, it is possible to simulate a situation before its implementation, thus predicting the performance of replication operations. Additionally, these results may contribute to future improvements to this process, in order to decrease the time required to make the data available in portals. © Rinton Press.

Ambiente data cleaning: suporte extensível, semântico e automático para análise e transformação de dados

Pós-graduação em Ciência da Computação - IBILCE

OntoSDM: an approach to improve quality on spatial data mining algorithms

The increase in new electronic devices had generated a considerable increase in obtaining spatial data information; hence these data are becoming more and more widely used. As well as for conventional data, spatial data need to be analyzed so interesting information can be retrieved from them. Therefore, data clustering techniques can be used to extract clusters of a set of spatial data. However, current approaches do not consider the implicit semantics that exist between a region and an object’s attributes. This paper presents an approach that enhances spatial data mining process, so they can use the semantic that exists within a region. A framework was developed, OntoSDM, which enables spatial data mining algorithms to communicate with ontologies in order to enhance the algorithm’s result. The experiments demonstrated a semantically improved result, generating more interesting clusters, therefore reducing manual analysis work of an expert.

Growth and survival of pacu Piaractus mesopotamicus (Holmberg, 1887) juveniles reared in ponds or at different initial larviculture periods indoors

Five-day-old pacu larvae (Piaractus mesopotamicus) with average length and weight of 5.96 mm and 0.42 mg, respectively, were reared as follows: in a semi-intensive system with larvae stocked directly into fertilized ponds (IL0)-and an initial intensive larviculture system with larvae maintained in a laboratory for 3 (IL3), 6 (IL6) and 9 (IL9) days, before being transferred to fertilized ponds. During the indoor phase, larvae were fed Artemia nauplii. Intensive-culture survivals were high (95.6%, 86.4% and 83.8% for IL3, IL6 and IL9, respectively) and at the end of the 45-day period, the longer the larvae were kept in the intensive system, the better the juvenile survival in the ponds. IL9 and IL6 survival rates were 54.0% and 45.4%, respectively, significantly higher (P < 0.05) than IL0 (11%) and IL3 presented an intermediate rate (25.3%). Due to the low survival rate of IL0, length and weight were higher (P < 0.05) when compared to IL6 and IL9; and the differences between their survival rates affected size distribution of juveniles among treatments. Treatments, which resulted in high survival (IL6 and IL9), presented a great number of small fish. In contrast, IL0 and IL3 produced many large and extra large individuals. In general, the results indicate that pacu juvenile production by initial intensive larviculture (IL6 and IL9) was the most efficient method. Therefore, further studies should be conducted in order to improve larval growth in the laboratory and handling techniques in both the laboratory and ponds. (C) 2003 Elsevier B.V. B.V. All rights reserved.

First record of L-quebrachitol in Allophylus edulis (Sapindaceae)

Allophylus edulis, commonly called 'Chal chal', is a member of the Sapindaceae occurring in the Uruguayan and Brazilian native flora. During the phytochemical analysis of two Chal chal specimens from two welldifferentiated geographical zones (Assis, São Paulo, Brazil, and Santa Lucia, Canelones, Uruguay), considerable amounts of L-quebrachitol were isolated from both samples. The isolation was carried out from the ethanolic twig extracts obtained by maceration of both vegetal samples. White easily distinguishable crystals were mechanically separated, washed, and characterized by 1D and 2D NMR experiments and by MS data. Such techniques confirmed that the crystals isolated from sources collected in both countries resulted in the same compound, L-quebrachitol, a natural product not previously reported for this species and one that has been investigated as a sugar substitute for diabetics. Worthy of note, the content of L-quebrachitol in A. edulis may be the chemical basis to explain its ethnobotanical uses, since infusions of this plant are used to treat diabetes in the practice of local traditional medicine. (c) 2008 Elsevier Ltd. All rights reserved.

Experimental damage detection using system norms

Nowadays there is great interest in structural damage detection in systems using nondestructive tests. Once the failure is detected, as for instance a crack, it is possible to take providences. There are several different approaches that can be used to obtain information about the existence, location and extension of the fault in the system by non-destructive tests. Among these methodologies, one can mention different optimization techniques, as for instance classical methods, genetic algorithms, neural networks, etc. Most of these techniques, which are based on element-byelement adjustments of a finite element (FE) model, take advantage of the dynamic behavior of the model. However, in practical situations, usually, is almost impossible to obtain an accuracy model. In this paper, it is proposed an experimental technique for damage location. This technique is based on H: norm to obtain the damage location. The dynamic properties of the structure were identified using experimental data by eigensystem realization algorithm (ERA). The experimental test was carried out in a beam structure through varying the mass of an element. For the output signal was used a piezoelectric sensor. The signal of input of sine form was generated through SignalCalc® software.

An intelligent system to detect drilling problems through drilled cuttings return analysis

Cuttings return analysis is an important tool to detect and prevent problems during the petroleum well drilling process. Several measurements and tools have been developed for drilling problems detection, including mud logging, PWD and downhole torque information. Cuttings flow meters were developed in the past to provide information regarding cuttings return at the shale shakers. Their use, however, significantly impact the operation including rig space issues, interferences in geological analysis besides, additional personel required. This article proposes a non intrusive system to analyze the cuttings concentration at the shale shakers, which can indicate problems during drilling process, such as landslide, the collapse of the well borehole walls. Cuttings images are acquired by a high definition camera installed above the shakers and sent to a computer coupled with a data analysis system which aims the quantification and closure of a cuttings material balance in the well surface system domain. No additional people at the rigsite are required to operate the system. Modern Artificial intelligence techniques are used for pattern recognition and data analysis. Techniques include the Optimum-Path Forest (OPF), Artificial Neural Network using Multilayer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC). Field test results conducted on offshore floating vessels are presented. Results show the robustness of the proposed system, which can be also integrated with other data to improve the efficiency of drilling problems detection. Copyright 2010, IADC/SPE Drilling Conference and Exhibition.

Engaging environments: Tacit knowledge sharing on the shop floor

Purpose: The purpose of this paper is to identify factors that facilitate tacit knowledge sharing in unstructured work environments, such as those found in automated production lines. Design/methodology/approach: The study is based on a qualitative approach, and it draws data from a four-month field study at a blown-molded glass factory. Data collection techniques included interviews, informal conversations and on-site observations, and data were interpreted using content analysis. Findings: The results indicated that sharing of tacit knowledge is facilitated by an engaging environment. An engaging environment is supported by shared language and knowledge, which are developed through intense communication and a strong sense of collegiality and a social climate that is dominated by openness and trust. Other factors that contribute to the creation of an engaging environment include managerial efforts to provide appropriate work conditions and to communicate company goals, and HRM practices such as the provision of formal training, on-the-job training and incentives. Practical implications: This paper clarifies the scope of managerial actions that impact knowledge creation and sharing among blue-collar workers. Originality/value: Despite the acknowledgement of the importance of blue-collar workers' knowledge, both the knowledge management and operations management literatures have devoted limited attention to it. Studies related to knowledge management in unstructured working environments are also not abundant. © Emerald Group Publishing Limited.

Molecularly designed layer-by-layer (LbL) films to detect catechol using information visualization methods

The control of molecular architectures has been exploited in layer-by-layer (LbL) films deposited on Au interdigitated electrodes, thus forming an electronic tongue (e-tongue) system that reached an unprecedented high sensitivity (down to 10-12 M) in detecting catechol. Such high sensitivity was made possible upon using units containing the enzyme tyrosinase, which interacted specifically with catechol, and by processing impedance spectroscopy data with information visualization methods. These latter methods, including the parallel coordinates technique, were also useful for identifying the major contributors to the high distinguishing ability toward catechol. Among several film architectures tested, the most efficient had a tyrosinase layer deposited atop LbL films of alternating layers of dioctadecyldimethylammonium bromide (DODAB) and 1,2-dipalmitoyl-sn-3-glycero-fosfo-rac-(1-glycerol) (DPPG), viz., (DODAB/DPPG)5/DODAB/Tyr. The latter represents a more suitable medium for immobilizing tyrosinase when compared to conventional polyelectrolytes. Furthermore, the distinction was more effective at low frequencies where double-layer effects on the film/liquid sample dominate the electrical response. Because the optimization of film architectures based on information visualization is completely generic, the approach presented here may be extended to designing architectures for other types of applications in addition to sensing and biosensing. © 2013 American Chemical Society.

Mapeamento de fragmentos de mata no município de Maringá, PR: uma abordagem da ecologia da paisagem

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Os saberes docentes na história de vida do professor de educação física

Pós-graduação em Educação - IBRC

A disciplina de ginástica artística na formação do licenciado em educação física sob a perspectiva de docentes universitários

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Os saberes da experiência discente: um estudo de caso na educação física

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Concepções e experiências de estudantes e profissionais da educação e da saúde sobre o projeto saúde e prevenção nas escolas

Pós-graduação em Enfermagem (mestrado profissional) - FMB