Mathematical modelling of the alcoholic fermentation of glucose by Zymomonas mobilis mobilis

The kinetics of alcoholic fermentation of a strain of Zymomonas mobilis, isolated from sugarcane juice, has been studied with the objective of determining the constansts of a non-structured mathematical model that represents the fermentation process. Assays in batch and in continuous culture have been carried out with different initial concentrations of glucose. The final concentrations of glucose, ethanol and biomass were determined. The following kinetic parameters were obtained: μ_max, 0·5 h^?1; K_s, 4·64 g dm^?3; P_max, 106 g dm^?3; Y_x/s, 0·0265 g g^?1; m, 1·4 g g^?1 h^?1; α, 17·38 g g^?1; β, 0·69 g g^?1 h^?1.     

Mining fuzzy association rules from low-quality data

Data mining is most commonly used in attempts to induce association rules from databases which can help decision-makers easily analyze the data and make good decisions regarding the domains concerned. Different studies have proposed methods for mining association rules from databases with crisp values. However, the data in many real-world applications have a certain degree of imprecision. In this paper we address this problem, and propose a new data-mining algorithm for extracting interesting knowledge from databases with imprecise data. The proposed algorithm integrates imprecise data concepts and the fuzzy apriori mining algorithm to find interesting fuzzy association rules in given databases. Experiments for diagnosing dyslexia in early childhood were made to verify the performance of the proposed algorithm.     

Neural Network and Classification Approach in Identifying Customer Behavior in the Banking Sector: A Case Study of an International Bank

The customer relationship focus for banks is in development of main competencies and strategies of building strong profitable customer relationships through considering and managing the customer impression, influence on the culture of the bank, satisfactory treatment, and assessment of valued relationship building. Artificial neural networks (ANNs) are used after data segmentation and classification, where the designed model register records into two class sets, that is, the training and testing sets. ANN predicts new customer behavior from previously observed customer behavior after executing the process of learning from existing data. This article proposes an ANN model, which is developed using a six‐step procedure. The back‐propagation algorithm is used to train the ANN by adjusting its weights to minimize the difference between the current ANN output and the desired output. An evaluation process is conducted to determine whether the ANN has learned how to perform. The training process is halted periodically, and its performance is tested until an acceptable result is obtained. The principles underlying detection software are grounded in classical statistical decision theory.     

Equivalent-optical-waveguide model for the analysis of optical waveguides by means of an asymptotic effective-index method

We present a theoretical method that makes it possible to analyze three-dimensional (3-D) integrated optical waveguides with arbitrary refractive-index profiles. With this method it is easy to obtain effective indexes, propagation constants, and coupling-switching properties of planar and channel optical waveguides. This theoretical approach involves one's modeling the original optical waveguide by means of an equivalent optical waveguide whose effective index is evaluated by the application of a technique that we call the asymptotic effective-index method. The numerical values show good convergence and accuracy for effective indexes, propagation constants, and coupling-switching characteristics. Theoretical and experimental results are given.     

MOE prediction in Abies pinsapo Boiss. timber: Application of an artificial neural network using non-destructive testing

Determining the modulus of elasticity of wood by applying an artificial neural network using the physical properties and non-destructive testing can be a useful method in assessments of the timber structure in old constructions. The modulus of elasticity of Abies pinsapo Boiss. timber was predicted in this study through the parameters of density, width, thickness, moisture content, ultrasonic wave propagation velocity and visual grading of the test pieces. A feedforward multilayer perceptron network was designed for this purpose, achieving 75.0% success in the testing or unknown group.     

The solubility of copper in lime-saturated and calcium ferrite-saturated liquid iron oxide

The solubility of copper in lime-saturated and calcium ferrite-saturated liquid iron oxide has been measured at 1300 °C by equilibrating copper-gold alloys with the melts in CO-CO₂ atmospheres of oxygen potentials 10^?7, 10^?8, 10^?9, and 10^?10 atm. It was found that copper exhibits Henrian behavior in the oxide melts and that the solubility is given by $$wt pct Cu = 17.6a_{CuO_{0.5} } $$ The copper capacity of the melts, 17.6, is approximately one-half of that of silica-saturated iron silicate melts at the same temperature. The results are compared with those of previous studies, and the difference between the solubilities of copper in silica-saturated and lime-saturated melts are discussed in terms of ionic interactions in the melts.     

Cloud detection in the Tropics--a suitable tool for climate-ecological studies in the high mountains of Ecuador

The detection of clouds and the analysis of cloud frequency play an important role for operational weather prediction as well as for climate-ecological studies. A threshold technique for cloud detection in the tropical mountainous area of Ecuador is presented which is based on National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) data. Cloud classification is performed for both day and night overpasses by applying several threshold tests which also include ancillary terrain information. From a set of 155 images, maps of relative cloud frequency are calculated for Ecuador and adjacent areas as well as the central study area of an ecological project in southern Ecuador (Loja). Results show a clear relation between topography, main airflow and cloudiness due to barrage and lee-effects. The spatial extension of high mountain ecosystems such as the Ecuadorian Páramo has been proven to be significantly influenced by the spatial pattern of cloud frequency.