Fuzzy rule-based system for evaluation of uncertainty transaction in cassava chain

A fuzzy ruled-based system was developed in this study and resulted in an index indicating the level of uncertainty related to commercial transactions between cassava growers and their dealers. The fuzzy system was developed based on Transaction Cost Economics approach. The fuzzy system was developed from input variables regarding information sharing between grower and dealer on “Demand/purchase Forecasting”, “Production Forecasting” and “Production Innovation”. The output variable is the level of uncertainty regarding the transaction between seller and buyer agent, which may serve as a system for detecting inefficiencies. Evidences from 27 cassava growers registered in the Regional Development Offices of Tupa and Assis, São Paulo, Brazil, and 48 of their dealers supported the development of the system. The mathematical model indicated that 55% of the growers present a Very High level of uncertainty, 33% present Medium or High. The others present Low or Very Low level of uncertainty. From the model, simulations of external interferences can be implemented in order to improve the degree of uncertainty and, thus, lower transaction costs.

Fuzzy logic applied to the modeling of water dynamics in an Oxisol in northeastern Brazil

Modeling of water movement in non-saturated soil usually requires a large number of parameters and variables, such as initial soil water content, saturated water content and saturated hydraulic conductivity, which can be assessed relatively easily. Dimensional flow of water in the soil is usually modeled by a nonlinear partial differential equation, known as the Richards equation. Since this equation cannot be solved analytically in certain cases, one way to approach its solution is by numerical algorithms. The success of numerical models in describing the dynamics of water in the soil is closely related to the accuracy with which the water-physical parameters are determined. That has been a big challenge in the use of numerical models because these parameters are generally difficult to determine since they present great spatial variability in the soil. Therefore, it is necessary to develop and use methods that properly incorporate the uncertainties inherent to water displacement in soils. In this paper, a model based on fuzzy logic is used as an alternative to describe water flow in the vadose zone. This fuzzy model was developed to simulate the displacement of water in a non-vegetated crop soil during the period called the emergency phase. The principle of this model consists of a Mamdani fuzzy rule-based system in which the rules are based on the moisture content of adjacent soil layers. The performances of the results modeled by the fuzzy system were evaluated by the evolution of moisture profiles over time as compared to those obtained in the field. The results obtained through use of the fuzzy model provided satisfactory reproduction of soil moisture profiles.

Morphological Features of Trypanosomes from Squirrel Monkeys from the Brazilian Amazon

A morphometric analysis of blood trypomastigotes identified as Trypanosoma minasense, T. saimirii, and T. rangeli harbored by squirrel monkeys from the Brazilian Amazon was performed. Additionally, morphological and biological comparative analyses were conducted of T. saimirii-like and T. rangeli development forms from haemoculture and xenodiagnosis. Illustrations are given of blood trypomastigotes as well as of developing flagellates in triatomine and axenic culture. Mean values of blood trypomastigotes of T. saimirii differ statistically from those of T. rangeli in only two out of ten morphological characters measured, and ranges overlapped. The developing forms of T. saimrii-like parasites were essentially identical in both xenodiagnosis and haemoculture to those of T. rangeli. Trypanosomes confirmed as T. rangeli were transmitted to mice by the bites of the great majority of triatomines that fed on T. saimirii-like infected monkeys. We conclude that, based on morphology and on the development in triatomine bugs and haemoculture, T. saimirii should not be considered a distinct species. We therefore propose T. saimirii to be a junior synonym of T. rangeli

Antimalarial Drug Resistance: Surveillance and Molecular Methods for National Malaria Control Programmes

National malaria control programmes have the responsibility to develop a policy for malaria disease management based on a set of defined criteria as efficacy, side effects, costs and compliance. These will fluctuate over time and national guidelines will require periodic re-assessment and revision. Changing a drug policy is a major undertaking that can take several years before being fully operational. The standard methods on which a decision can be taken are the in vivo and the in vitro tests. The latter allow a quantitative measurement of the drug response and the assessment of several drugs at once. However, in terms of drug policy change its results might be difficult to interpret although they may be used as an early warning system for 2nd or 3rd line drugs. The new WHO 14-days in vivo test addresses mainly the problem of treatment failure and of haematological parameters changes in sick children. It gives valuable information on whether a drug still `works'. None of these methods are well suited for large-scale studies. Molecular methods based on detection of mutations in parasite molecules targeted by antimalarial drugs could be attractive tools for surveillance. However, their relationship with in vivo test results needs to be established

Transferência de calibração em métodos multivariados

Calibration transfer has received considerable attention in the recent literature. Several standardization methods have been proposed for transferring calibration models between equipments. The goal of this paper is to present a general revision of calibration transfer techniques. Basic concepts will be reviewed, as well as the main advantages and drawbacks of each technique. A case study based on a set of 80 NIR spectra of maize samples recorded on two different instruments is used to illustrate the main calibration transfer techniques (direct standardization, piecewise direct standardization, orthogonal signal correction and robust variable selection).

Utilization of microsatellites for the analysis of genomic alterations in colorectal cancers in Brazil

Two different pathogenetic mechanisms are proposed for colorectal cancers. One, the so-called "classic pathway", is the most common and depends on multiple additive mutational events (germline and/or somatic) in tumor suppressor genes and oncogenes, frequently involving chromosomal deletions in key genomic regions. Methodologically this pathway is recognizable by the phenomenon of loss of heterozygosity. On the other hand, the "mutator pathway" depends on early mutational loss of the mismatch repair system (germline and/or somatic) leading to accelerated accumulation of gene mutations in critical target genes and progression to malignancy. Methodologically this second pathway is recognizable by the phenomenon of microsatellite instability. The distinction between these pathways seems to be more than academic since there is evidence that the tumors emerging from the mutator pathway have a better prognosis. We report here a very simple methodology based on a set of tri-, tetra- and pentanucleotide repeat microsatellites allowing the simultaneous study of microsatellite instability and loss of heterozygosity which could allocate 70% of the colorectal tumors to the classic or the mutator pathway. The ease of execution of the methodology makes it suitable for routine clinical typing

Management zones using fuzzy clustering based on spatial-temporal variability of soil and corn yield

Clustering soil and crop data can be used as a basis for the definition of management zones because the data are grouped into clusters based on the similar interaction of these variables. Therefore, the objective of this study was to identify management zones using fuzzy c-means clustering analysis based on the spatial and temporal variability of soil attributes and corn yield. The study site (18 by 250-m in size) was located in Jaboticabal, São Paulo/Brazil. Corn yield was measured in one hundred 4.5 by 10-m cells along four parallel transects (25 observations per transect) over five growing seasons between 2001 and 2010. Soil chemical and physical attributes were measured. SAS procedure MIXED was used to identify which variable(s) most influenced the spatial variability of corn yield over the five study years. Basis saturation (BS) was the variable that better related to corn yield, thus, semivariograms models were fitted for BS and corn yield and then, data values were krigged. Management Zone Analyst software was used to carry out the fuzzy c-means clustering algorithm. The optimum number of management zones can change over time, as well as the degree of agreement between the BS and corn yield management zone maps. Thus, it is very important take into account the temporal variability of crop yield and soil attributes to delineate management zones accurately.

Selection of patients for myocardial perfusion scintigraphy based on fuzzy sets theory applied to clinical-epidemiological data and treadmill test results

Coronary artery disease (CAD) is a worldwide leading cause of death. The standard method for evaluating critical partial occlusions is coronary arteriography, a catheterization technique which is invasive, time consuming, and costly. There are noninvasive approaches for the early detection of CAD. The basis for the noninvasive diagnosis of CAD has been laid in a sequential analysis of the risk factors, and the results of the treadmill test and myocardial perfusion scintigraphy (MPS). Many investigators have demonstrated that the diagnostic applications of MPS are appropriate for patients who have an intermediate likelihood of disease. Although this information is useful, it is only partially utilized in clinical practice due to the difficulty to properly classify the patients. Since the seminal work of Lotfi Zadeh, fuzzy logic has been applied in numerous areas. In the present study, we proposed and tested a model to select patients for MPS based on fuzzy sets theory. A group of 1053 patients was used to develop the model and another group of 1045 patients was used to test it. Receiver operating characteristic curves were used to compare the performance of the fuzzy model against expert physician opinions, and showed that the performance of the fuzzy model was equal or superior to that of the physicians. Therefore, we conclude that the fuzzy model could be a useful tool to assist the general practitioner in the selection of patients for MPS.

Fuzzy linguistic model for evaluating the risk of neonatal death

OBJECTIVE: To introduce a fuzzy linguistic model for evaluating the risk of neonatal death. METHODS: The study is based on the fuzziness of the variables newborn birth weight and gestational age at delivery. The inference used was Mamdani's method. Neonatologists were interviewed to estimate the risk of neonatal death under certain conditions and to allow comparing their opinions and the model values. RESULTS: The results were compared with experts' opinions and the Fuzzy model was able to capture the expert knowledge with a strong correlation (r=0.96). CONCLUSIONS: The linguistic model was able to estimate the risk of neonatal death when compared to experts' performance.

Application of fuzzy logic for the evaluation of livestock slaughtering

The fuzzy logic admits infinite intermediate logical values between false and true. With this principle, it developed in this study a system based on fuzzy rules, which indicates the body mass index of ruminant animals in order to obtain the best time to slaughter. The controller developed has as input the variables weight and height, and as output a new body mass index, called Fuzzy Body Mass Index (Fuzzy BMI), which may serve as a detection system at the time of livestock slaughtering, comparing one another by the linguistic variables "Very Low", "Low", "Average ", "High" and "Very High". For demonstrating the use application of this fuzzy system, an analysis was made with 147 Nellore beeves to determine Fuzzy BMI values for each animal and indicate the location of body mass of any herd. The performance validation of the system was based on a statistical analysis using the Pearson correlation coefficient of 0.923, representing a high positive correlation, indicating that the proposed method is appropriate. Thus, this method allows the evaluation of the herd comparing each animal within the group, thus providing a quantitative method of farmer decision. It was concluded that this study established a computational method based on fuzzy logic that mimics part of human reasoning and interprets the body mass index of any bovine species and in any region of the country.

Prediction of free-stall occupancy rate in dairycattle barns through fuzzy sets

The goal of this study was to develop a fuzzy model to predict the occupancy rate of free-stalls facilities of dairy cattle, aiding to optimize the design of projects. The following input variables were defined for the development of the fuzzy system: dry bulb temperature (Tdb, °C), wet bulb temperature (Twb, °C) and black globe temperature (Tbg, °C). Based on the input variables, the fuzzy system predicts the occupancy rate (OR, %) of dairy cattle in free-stall barns. For the model validation, data collecting were conducted on the facilities of the Intensive System of Milk Production (SIPL), in the Dairy Cattle National Research Center (CNPGL) of Embrapa. The OR values, estimated by the fuzzy system, presented values of average standard deviation of 3.93%, indicating low rate of errors in the simulation. Simulated and measured results were statistically equal (P>0.05, t Test). After validating the proposed model, the average percentage of correct answers for the simulated data was 89.7%. Therefore, the fuzzy system developed for the occupancy rate prediction of free-stalls facilities for dairy cattle allowed a realistic prediction of stalls occupancy rate, allowing the planning and design of free-stall barns.

Electrically driven fertilizer applicator controlled by fuzzy logic

The present study shows the development, simulation and actual implementation of a closed-loop controller based on fuzzy logic that is able to regulate and standardize the mass flow of a helical fertilizer applicator. The control algorithm was developed using MATLAB's Fuzzy Logic Toolbox. Both open and closed-loop simulations of the controller were performed in MATLAB's Simulink environment. The instantaneous deviation of the mass flow from the set point (SP), its derivative, the equipment´s translation velocity and acceleration were all used as input signals for the controller, whereas the voltage of the applicator's DC electric motor (DCEM) was driven by the controller as output signal. Calibration and validation of the rules and membership functions of the fuzzy logic were accomplished in the computer simulation phase, taking into account the system's response to SP changes. The mass flow variation coefficient, measured in experimental tests, ranged from 6.32 to 13.18%. The steady state error fell between -0.72 and 0.13g s-1 and the recorded average rise time of the system was 0.38 s. The implemented controller was able to both damp the oscillations in mass flow that are characteristic of helical fertilizer applicators, and to effectively respond to SP variations.