Evolving Takagi–Sugeno fuzzy model based on switching to neighboring models

In this paper, we propose a new online identification approach for evolving Takagi–Sugeno (TS) fuzzy models. Here, for a TS model, a certain number of models as neighboring models are defined and then the TS model switches to one of them at each stage of evolving. We define neighboring models for an in-progress (current) TS model as its fairly evolved versions, which are different with it just in two fuzzy rules. To generate neighboring models for the current model, we apply specially designed split and merge operations. By each split operation, a fuzzy rule is replaced with two rules; while by each merge operation, two fuzzy rules combine to one rule. Among neighboring models, the one with the minimum sum of squared errors – on certain time intervals – replaces the current model.To reduce the computational load of the proposed evolving TS model, straightforward relations between outputs of neighboring models and that of current model are established. Also, to reduce the number of rules, we define and use first-order TS fuzzy models whose generated local linear models can be localized in flexible fuzzy subspaces. To demonstrate the improved performance of the proposed identification approach, the efficiency of the evolving TS model is studied in prediction of monthly sunspot number and forecast of daily electrical power consumption. The prediction and modeling results are compared with that of some important existing evolving fuzzy systems.     

Fractal dimension applied to plant identification

This article discusses methods to identify plants by analysing leaf complexity based on estimating their fractal dimension. Leaves were analyzed according to the complexity of their internal and external shapes. A computational program was developed to process, analyze and extract the features of leaf images, thereby allowing for automatic plant identification. Results are presented from two experiments, the first to identify plant species from the Brazilian Atlantic forest and Brazilian Cerrado scrublands, using fifty leaf samples from ten different species, and the second to identify four different species from genus Passiflora, using twenty leaf samples for each class. A comparison is made of two methods to estimate fractal dimension (box-counting and multiscale Minkowski). The results are discussed to determine the best approach to analyze shape complexity based on the performance of the technique, when estimating fractal dimension and identifying plants.     

A multiscale directional operator and morphological tools for reconnecting broken ridges in fingerprint images

In this paper, we introduce a multiscale operator which, together with some morphological tools, can be used to reconnect broken components of fingerprint images. This operator, which can be applied to both binary and gray-scale pictures, extracts the orientation field of an image by taking into account information parameters of sets of pixels in a given neighborhood and located in different directions. It has proved to be very robust to noise and outperforms the gradient- and directional mask-based methods, generally used for orientation field definition. Although we illustrate its application in the fingerprint domain, the approach described here can be easily extended to images whose components exhibit well-defined directional information.     

A multi-agent legal recommender system

Infonorma is a multi-agent system that provides its users with recommendations of legal normative instruments they might be interested in. The Filter agent of Infonorma classifies normative instruments represented as Semantic Web documents into legal branches and performs content-based similarity analysis. This agent, as well as the entire Infonorma system, was modeled under the guidelines of MAAEM, a software development methodology for multi-agent application engineering. This article describes the Infonorma requirements specification, the architectural design solution for those requirements, the detailed design of the Filter agent and the implementation model of Infonorma, according to the guidelines of the MAAEM methodology.     

The Green language type system

A programming language that considers basic values and classes as objects brings more opportunities of code reuse and it is easier to use than a language that does not support this feature. However, popular statically typed object-oriented languages do not consider classes as first-class objects because this concept is difficult to integrate with static type checking. They also do not consider basic values as objects for sake of efficiency. This article presents the Green language type system which supports classes as classless objects and offers a mechanism to treat basic values as objects. The result is a reasonably simple type system which is statically typed and easy to implement. It simplifies several other language mechanisms and prevents any infinite regression of metaclasses.     

Post-embryonic development of the antennal sensilla in Melipona quadrifasciata anthidioides (Hymenoptera: Meliponini)

The sensilla are sensory organs formed by cuticular and cellular structures specialized in reception of chemical and physical stimuli from the environment and transmission to the insect's central nervous system. In function of the great concentration of sensilla, the antennae are the main organs for interaction between bees and with the environment. This work studied the presence of antennal sensilla in the different phases of pupal development of the stingless bee Melipona quadrifasciata anthidioides by means of scanning electron microscopy and light microscopy. The results showed that antennal sensilla begin their development in the transition of the prepupae to the white-eyed pupae and finish it in the pigmented-body pupae phase. The antennal sensilla were exposed to the environment in the black-eyed pupae when the old cuticle is completely digested, suggesting that only in the final pupal phases can these bees perceive the environmental stimuli.     

Clinical and epidemiological findings during a measles outbreak occurring in a population with a high vaccination coverage

Malignant mesothelioma is caused almost exclusively by occupational exposure to asbestos. During the past few years, however, increasing evidence has mounted that background exposure to asbestos could be sufficient to cause mesothelioma. Treatment of malignant mesothelioma remains a big problem. Some new approaches are on their way, and the most exciting ones are local immunotherapy in very early cases. Some success has been reported with local interferon treatment. As for treatment of metastatic pleural disease, the main purpose is symptomatic relief of dyspnea caused by fluid accumulation. The best way to achieve a lasting palliation is pleurodesis, and the most common way to do this, is by chemical means. The drug of choice in the United States has for many years been tetracycline, but since injectable tetracycline is no longer available, some substitute must be found. The substance that will "win" is not yet clear, but the two leading contestants are talc and doxycycline. Bleomycin also has its supporters, and a dark horse is quinacrine, which although not easily available in the United States, has been used in many European centers for decades.     

Ocular recognition databases and competitions: a survey

The use of the iris and periocular region as biometric traits has been extensively investigated, mainly due to the singularity of the iris features and the use of the periocular region when the image resolution is not sufficient to extract iris information. In addition to providing information about an individual’s identity, features extracted from these traits can also be explored to obtain other information such as the individual’s gender, the influence of drug use, the use of contact lenses, spoofing, among others. This work presents a survey of the databases created for ocular recognition, detailing their protocols and how their images were acquired. We also describe and discuss the most popular ocular recognition competitions (contests), highlighting the submitted algorithms that achieved the best results using only iris trait and also fusing iris and periocular region information. Finally, we describe some relevant works applying deep learning techniques to ocular recognition and point out new challenges and future directions. Considering that there are a large number of ocular databases, and each one is usually designed for a specific problem, we believe this survey can provide a broad overview of the challenges in ocular biometrics.