An elitist non-dominated sorting genetic algorithm enhanced with a neural network applied to the multi-objective optimization of a polysiloxane synthesis process

This paper presents an original software implementation of the elitist non-dominated sorting genetic algorithm (NSGA-II) applied and adapted to the multi-objective optimization of a polysiloxane synthesis process. An optimized feed-forward neural network, modeling the variation in time of the main parameters of the process, was used to calculate the vectorial objective function of NSGA-II, as an enhancement to the multi-objective optimization procedure. An original technique was utilized in order to find the most appropriate parameters for maximizing the performance of NSGA-II. The algorithm provided the optimum reaction conditions (reaction temperature, reaction time, amount of catalyst, and amount of co-catalyst), which maximize the reaction conversion and minimize the difference between the obtained viscometric molecular weight and the desired molecular weight. The algorithm has proven to be able to find the entire non-dominated Pareto front and to quickly evolve optimal solutions as an acceptable compromise between objectives competing with each other. The use of the neural network makes it also suitable to the multi-objective optimization of processes for which the amount of knowledge is limited.     

Models and Simulations for Portfolio Rebalancing

In 1950 Markowitz first formalized the portfolio optimization problem in terms of mean return and variance. Since then, the mean-variance model has played a crucial role in single-period portfolio optimization theory and practice. In this paper we study the optimal portfolio selection problem in a multi-period framework, by considering fixed and proportional transaction costs and evaluating how much they affect a re-investment strategy. Specifically, we modify the single-period portfolio optimization model, based on the Conditional Value at Risk (CVaR) as measure of risk, to introduce portfolio rebalancing. The aim is to provide investors and financial institutions with an effective tool to better exploit new information made available by the market. We then suggest a procedure to use the proposed optimization model in a multi-period framework. Extensive computational results based on different historical data sets from German Stock Exchange Market (XETRA) are presented.     

Software reuse: The Brazilian industry scenario

This paper aims at identifying some of the key factors in adopting an organization-wide software reuse program. The factors are derived from practical experience reported by industry professionals, through a survey involving 57 Brazilian small, medium and large software organizations. Some of them produce software with commonality between applications, and have mature processes, while others successfully achieved reuse through isolated, ad hoc efforts. The paper compiles the answers from the survey participants, showing which factors were more associated with reuse success. Based on this relationship, a guide is presented, pointing out which factors should be more strongly considered by small, medium and large organizations attempting to establish a reuse program.     

Unified methodology of neural analysis in decision support systems built for pharmaceutical technology

The objective of this study was to create universal methodology of artificial neural networks (ANNs) application in construction of decision support systems designed for various dosage forms. Two different dosage forms (solid dispersions and microemulsions) were modeled with use of the same methodology, software and hardware environments. Completely different models prepared confirmed their generalization ability both for solid dosage forms (solid dispersions) and liquid dosage forms (microemulsions). ME_expert and SD_expert systems basing on the neural expert committees were created. In the pilot study their application allowed for appropriate choice of qualitative and quantitative composition of particular pharmaceutical formulation. It was also proposed that ME_expert and SD_expert might provide in silico formulation procedures. Unified methodology of neural modeling in pharmaceutical technology was confirmed to be effective in providing valuable tools for pharmaceutical product development.     

A multivariate fuzzy c-means method

Fuzzy c-means (FCMs) is an important and popular unsupervised partitioning algorithm used in several application domains such as pattern recognition, machine learning and data mining. Although the FCM has shown good performance in detecting clusters, the membership values for each individual computed to each of the clusters cannot indicate how well the individuals are classified. In this paper, a new approach to handle the memberships based on the inherent information in each feature is presented. The algorithm produces a membership matrix for each individual, the membership values are between zero and one and measure the similarity of this individual to the center of each cluster according to each feature. These values can change at each iteration of the algorithm and they are different from one feature to another and from one cluster to another in order to increase the performance of the fuzzy c-means clustering algorithm. To obtain a fuzzy partition by class of the input data set, a way to compute the class membership values is also proposed in this work. Experiments with synthetic and real data sets show that the proposed approach produces good quality of clustering.     

On graph reasoning

In this paper, we study the (positive) graph relational calculus. The basis for this calculus was introduced by Curtis and Lowe in 1996 and some variants, motivated by their applications to semantics of programs and foundations of mathematics, appear scattered in the literature. No proper treatment of these ideas as a logical system seems to have been presented. Here, we give a formal presentation of the system, with precise formulation of syntax, semantics, and derivation rules. We show that the set of rules is sound and complete for the valid inclusions, and prove a finite model result as well as decidability. We also prove that the graph relational language has the same expressive power as a first-order positive fragment (both languages define the same binary relations), so our calculus may be regarded as a notational variant of the positive existential first-order logic of binary relations. The graph calculus, however, has a playful aspect, with rules easy to grasp and use. This opens a wide range of applications which we illustrate by applying our calculus to the positive relational calculus (whose set of valid inclusions is not finitely axiomatizable), obtaining an algorithm for deciding the valid inclusions and equalities of the latter.     

Dietary assessment of pre-school children from Federal District Brazil

The objective was to assess food consumption among children attending non-profit nurseries in the Federal District, Brazil.A representative sample was obtained and stratified by income. Food intake among 678 children, between 4 and 82 months old, was analyzed in nine nurseries using the 24-h dietary recall and direct food weighing methods. In children under 13 months old mean intake was above AI between 93.6 to 100% for carbohydrates, proteins, vitamins B1, B2, B12, B6, and zinc. In children from 7-12 months 56.5% presented iron consumption below EAR. Calcium intake was above AI for 35.4% of children over 1 year old. For vitamins with EAR values, the prevalence of inadequate consumption was 53.2% for vitamin E, and 90% for folate for children over 12 months old. Iron and zinc intake was above UL for 6.4% and 32.5% of children under 1 year old, and 1.5% and 5.3% for the remaining children, respectively. Lipid percentage distribution range among children between 13 and 47 months old was within the acceptable range for only 16.2%. Nonetheless, children between 36 and 82 months of both genders presented mean intake below energy requirements. Inadequate consumption observed for some nutrients points to the need for improvements in the standard of meals and nutritional assistance offered to children enrolled in charitably run nurseries in the Federal District.     

A collaborative study of a method for the enumeration of probiotic bifidobacteria in animal feed

An enumeration method to be used as an official control method in the framework of Council Directive 70/524/EEC for probiotic bifidobacteria used as feed additives was validated. Seventeen laboratories in 11 European Countries carried out a collaborative study. A spread plate method following BS ISO 15214:1998 using four different agars, Man Rogosa Sharpe (MRS), acidified MRS, MRS with triphenyl tetrazolium chloride (TTC) and a selective bifidobacteria medium, was validated. Precision data in terms of repeatability (r) and reproducibility (R) of the method for each medium using different feeding stuffs with a high and a low inoculation level were determined. Bifidobacteria were present in the samples as a single component or in mixtures with other probiotics. The enumeration of bifidobacteria on all agars showed a relative standard deviation of repeatability (RSD(r)) between 1.2% and 6.3% and a relative standard deviation of reproducibility (RSD(R)) between 2.6% and 8.7%. MRS agar was preferred, followed by acidified MRS and MRS+TTC agar. The selective bifidobacteria medium gave similar counts as the MRS media. For routine analysis, the use of MRS agar with supplementation of cysteine hydrochloride (the selective bifidobacteria medium without antibiotics) is recommended. Depending on the presence and concentration of other probiotics such as enterococci, lactobacilli and pediococci, acidified MRS or MRS+TTC agar is recommended. The selective bifidobacteria medium was selective for bifidobacteria.An official control method for enumeration of probiotic bifidobacteria as a single component and in mixtures with other probiotic microorganisms in feeding stuffs was validated. The methodology is not applicable to mineral feed. The results are intended for consideration for adaptation as CEN and ISO standards.