Estudo de adulteração em méis brasileiros através de razão isotópica do carbono

Neste trabalho, objetivou-se analisar isotopicamente méis comercializados nas regiões Sul e Sudeste do Brasil, para a detecção de fraude. Foram colhidas amostras comerciais com registro no Serviço de Inspeção Federal, Estadual ou Municipal. As amostras foram submetidas à combustão no Analisador Elementar EA 1108 CHN e analisadas no espectrômetro de massas de razão isotópica DELTA-S (Finningan Mat). Os valores isotópicos (δ13C) dos méis in natura foram comparados aos de suas respectivas proteínas (padrão interno). Foram consideradas adulteradas as amostras cuja diferença entre o valor isotópico da proteína e do mel foi igual ou inferior a -1 . As amostras consideradas adulteradas pela análise isotópica foram submetidas a testes químicos qualitativos que não foram capazes de indicar adulteração para algumas delas. Das 61 amostras analisadas, 18,0% encontram-se adulteradas, sendo 11,5% na Região Sudeste e 6,5% na Região Sul. Ao contrário dos testes químicos, a análise isotópica mostrou-se eficaz em identificar e quantificar a adulteração de méis comerciais.

A New Approach for Nontechnical Losses Detection Based on Optimum-Path Forest

Nowadays, fraud detection is important to avoid nontechnical energy losses. Various electric companies around the world have been faced with such losses, mainly from industrial and commercial consumers. This problem has traditionally been dealt with using artificial intelligence techniques, although their use can result in difficulties such as a high computational burden in the training phase and problems with parameter optimization. A recently-developed pattern recognition technique called optimum-path forest (OPF), however, has been shown to be superior to state-of-the-art artificial intelligence techniques. In this paper, we proposed to use OPF for nontechnical losses detection, as well as to apply its learning and pruning algorithms to this purpose. Comparisons against neural networks and other techniques demonstrated the robustness of the OPF with respect to commercial losses automatic identification.

Detection and Identification of Abnormalities in Customer Consumptions in Power Distribution Systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Feature selection through gravitational search algorithm

In this paper we deal with the problem of feature selection by introducing a new approach based on Gravitational Search Algorithm (GSA). The proposed algorithm combines the optimization behavior of GSA together with the speed of Optimum-Path Forest (OPF) classifier in order to provide a fast and accurate framework for feature selection. Experiments on datasets obtained from a wide range of applications, such as vowel recognition, image classification and fraud detection in power distribution systems are conducted in order to asses the robustness of the proposed technique against Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and a Particle Swarm Optimization (PSO)-based algorithm for feature selection.

Determinação da razão isotópica delta13C em bebidas comerciais a base de laranja

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

Bovine carcass sexing by PCR method

Objetivou-se, nesta pesquisa, o desenvolvimento de uma metodologia que permitisse a sexagem de carne bovina pronta para comercialização. Para tanto, utilizou-se primers seqüência macho-específica e posterior análise do produto amplificado. O método proposto mostrou-se eficiente para verificar o sexo, bem como sua utilização prática, a fim de evitar fraudes na comercialização de carne bovina.

Using the Euclidean Distance as a Mechanism Distance between Signatures to the Detect Spam and Phishing Scams

Spams and Phishing Scams are some of the abuse forms on the Internet that have grown up now. These abuses influence in user's routine of electronic mail and in the infrastructure of Internet communication. So, this paper proposes a new model messages filter based in Euclidian distance, beyond show the containment's methodologies currently more used. A new model messages filter, based in frequency's distribution of character present in your content and in signature generation is described. An architecture to combat Phishing Scam and spam is proposed in order to contribute to the containment of attempted fraud by mail.

Fast non-technical losses identification through Optimum-Path Forest

Fraud detection in energy systems by illegal consumers is the most actively pursued study in non-technical losses by electric power companies. Commonly used supervised pattern recognition techniques, such as Artificial Neural Networks and Support Vector Machines have been applied for automatic commercial frauds identification, however they suffer from slow convergence and high computational burden. We introduced here the Optimum-Path Forest classifier for a fast non-technical losses recognition, which has been demonstrated to be superior than neural networks and similar to Support Vector Machines, but much faster. Comparisons among these classifiers are also presented. © 2009 IEEE.

Determinação de GMP e CMP* no leite por métodos espectrofotométrico (ANSM) e cromatográfico (HPLC) - parâmetros metodológicos (*glicomacropeptídeo e caseinomacropeptídeo)

Glycomacropeptide is a glycosilated fraction of bovine kappa-casein that remains soluble when milk is clotted by rennin. Determinations of milk sialic acid content are useful because its concentration reflects the amount of free GMP of milk. In normal milk these amounts are very low, 12 to 16 times lower than in sweet whey. Therefore, its determination may be applied to verify possible frauds with whey addictions, since it works as a fingerprint. With the description of a new spectrophotometric method for determination of free GMP (ANSM) occurred a simplification of procedures, being faster than others (HPLC method), without loss of accuracy. However, due to variations of glycosilation in kappa-casein between animals, during the lactation period, due to mastitis and yet due to proteolysis on milk, it was necessary to know these variations to interpret correctly the analytical results. It was analyzed 1,703 samples of producer's raw milk and 1,189 samples of processed milk (HTST and UHT). The results showed that normal milk from herd (producer's milk) have only small amounts of free GMP, with A470nm = 0.232±0.088 or 3.89±1.25 mg of sialic acid/L. The upper limit of this distribution was A = 0.496; thus every bigger value may represent a problem, being outside of normal distribution.

Rastreabilidade de camarão amazônico proveniente de cultivo e ambiente natural utilizando a técnica de isótopos estáveis

Pós-graduação em Aquicultura - FCAV

Sistema inteligente híbrido intercomunicativo para detecção de perdas comerciais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Desenvolvimento de ferramentas computacionais inteligentes para identificação de perdas comerciais em sistemas de energia

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Os direitos e obrigações da terceirização na administração pública

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Aplicação da razão isotópica do carbono (13C/12C) para detecção de adulteração em bebidas a base de maracujá – Passiflora edulis Sims. f. flavicarpa Deg

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Impacto do FUNDEF na estruturação da rede municipal de ensino do município de Pirapozinho-SP

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)