Estimating outcomes in newborn infants using fuzzy logic

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Fuzzy logic to evaluate vitality of Catasetum fimbiratum species (Orchidacea)

The fuzzy logic accepts infinite intermediate logical values between false and true. In view of this principle, a system based on fuzzy rules was established to provide the best management of Catasetum fimbriatum. For the input of the developed fuzzy system, temperature and shade variables were used, and for the output, the orchid vitality. The system may help orchid experts and amateurs to manage this species. ?Low? (L), ?Medium? (M) and ?High? (H) were used as linguistic variables. The objective of the study was to develop a system based on fuzzy rules to improve management of the Catasetum fimbriatum species, as its production presents some difficulties, and it offers high added value

An extension of the invariance principle for dwell-time switched nonlinear systems

In this paper, we propose an extension of the invariance principle for nonlinear switched systems under dwell-time switched solutions. This extension allows the derivative of an auxiliary function V, also called a Lyapunov-like function, along the solutions of the switched system to be positive on some sets. The results of this paper are useful to estimate attractors of nonlinear switched systems and corresponding basins of attraction. Uniform estimates of attractors and basin of attractions with respect to time-invariant uncertain parameters are also obtained. Results for a common Lyapunov-like function and multiple Lyapunov-like functions are given. Illustrative examples show the potential of the theoretical results in providing information on the asymptotic behavior of nonlinear dynamical switched systems. (C) 2012 Elsevier B.V. All rights reserved.

A Stress-Detection System Based on Physiological Signals and Fuzzy Logic

A stress-detection system is proposed based on physiological signals. Concretely, galvanic skin response (GSR) and heart rate (HR) are proposed to provide information on the state of mind of an individual, due to their nonintrusiveness and noninvasiveness. Furthermore, specific psychological experiments were designed to induce properly stress on individuals in order to acquire a database for training, validating, and testing the proposed system. Such system is based on fuzzy logic, and it described the behavior of an individual under stressing stimuli in terms of HR and GSR. The stress-detection accuracy obtained is 99.5% by acquiring HR and GSR during a period of 10 s, and what is more, rates over 90% of success are achieved by decreasing that acquisition period to 3-5 s. Finally, this paper comes up with a proposal that an accurate stress detection only requires two physiological signals, namely, HR and GSR, and the fact that the proposed stress-detection system is suitable for real-time applications.

Sustainable development using fuzzy logic

Se utiliza la lógica borrosa para elaborar un modelo útil para analizar el desarrollo sostenible de proyectos. The sustainable development is defined as “the development that satisfies needs of the present time without endangering the capacity of future generations to satisfy theirs”. The term “sustainable development” represents that balance between the satisfaction of present needs and the future ones, offering options of technological and social growth for reducing the risks meaning trends of topical increase. The idea of sustainability can be analysed from three perspectives: environmental, social and economic

Control of a solar dryer through using a fuzzy logic and low-cost model-based sensor

Solar drying is one of the important processes used for extending the shelf life of agricultural products. Regarding consumer requirements, solar drying should be more suitable in terms of curtailing total drying time and preserving product quality. Therefore, the objective of this study was to develop a fuzzy logic-based control system, which performs a ?human-operator-like? control approach through using the previously developed low-cost model-based sensors. Fuzzy logic toolbox of MatLab and Borland C++ Builder tool were utilized to develop a required control system. An experimental solar dryer, constructed by CONA SOLAR (Austria) was used during the development of the control system. Sensirion sensors were used to characterize the drying air at different positions in the dryer, and also the smart sensor SMART-1 was applied to be able to include the rate of wood water extraction into the control system (the difference of absolute humidity of the air between the outlet and the inlet of solar dryer is considered by SMART-1 to be the extracted water). A comprehensive test over a 3 week period for different fuzzy control models has been performed, and data, obtained from these experiments, were analyzed. Findings from this study would suggest that the developed fuzzy logic-based control system is able to tackle difficulties, related to the control of solar dryer process.

The Balanced Cross-Layer Design Routing Algorithm in Wireless Sensor Networks Using Fuzzy Logic

Recently, the cross-layer design for the wireless sensor network communication protocol has become more and more important and popular. Considering the disadvantages of the traditional cross-layer routing algorithms, in this paper we propose a new fuzzy logic-based routing algorithm, named the Balanced Cross-layer Fuzzy Logic (BCFL) routing algorithm. In BCFL, we use the cross-layer parameters’ dispersion as the fuzzy logic inference system inputs. Moreover, we give each cross-layer parameter a dynamic weight according the value of the dispersion. For getting a balanced solution, the parameter whose dispersion is large will have small weight, and vice versa. In order to compare it with the traditional cross-layer routing algorithms, BCFL is evaluated through extensive simulations. The simulation results show that the new routing algorithm can handle the multiple constraints without increasing the complexity of the algorithm and can achieve the most balanced performance on selecting the next hop relay node. Moreover, the Balanced Cross-layer Fuzzy Logic routing algorithm can adapt to the dynamic changing of the network conditions and topology effectively.

An application of fuzzy logic for hardware/software partitioning in embedded systems

Hardware/Software partitioning (HSP) is a key task for embedded system co-design. The main goal of this task is to decide which components of an application are to be executed in a general purpose processor (software) and which ones, on a specific hardware, taking into account a set of restrictions expressed by metrics. In last years, several approaches have been proposed for solving the HSP problem, directed by metaheuristic algorithms. However, due to diversity of models and metrics used, the choice of the best suited algorithm is an open problem yet. This article presents the results of applying a fuzzy approach to the HSP problem. This approach is more flexible than many others due to the fact that it is possible to accept quite good solutions or to reject other ones which do not seem good. In this work we compare six metaheuristic algorithms: Random Search, Tabu Search, Simulated Annealing, Hill Climbing, Genetic Algorithm and Evolutionary Strategy. The presented model is aimed to simultaneously minimize the hardware area and the execution time. The obtained results show that Restart Hill Climbing is the best performing algorithm in most cases.