Identification and phylogenetic inferences on stocks of sharks affected by the fishing industry off the Northern coast of Brazil

The ongoing decline in abundance and diversity of shark stocks, primarily due to uncontrolled fishery exploitation, is a worldwide problem. An additional problem for the development of conservation and management programmes is the identification of species diversity within a given area, given the morphological similarities among shark species, and the typical disembarkation of processed carcasses which are almost impossible to differentiate. The main aim of the present study was to identify those shark species being exploited off northern Brazil, by using the 12S-16S molecular marker. For this, DNA sequences were obtained from 122 specimens collected on the docks and the fish market in Bragança, in the Brazilian state of Pará. We identified at least 11 species. Three-quarters of the specimens collected were either Carcharhinus porosus or Rhizoprionodon sp, while a notable absence was the daggernose shark, Isogomphodon oxyrhyncus, previously one of the most common species in local catches. The study emphasises the value of molecular techniques for the identification of cryptic shark species, and the potential of the 12S-16S marker as a tool for phylogenetic inferences in a study of elasmobranchs.

Machine vision to identify broiler breeder behavior

Animal behavioral parameters can be used to assess welfare status in commercial broiler breeders. Behavioral parameters can be monitored with a variety of sensing devices, for instance, the use of video cameras allows comprehensive assessment of animal behavioral expressions. Nevertheless, the development of efficient methods and algorithms to continuously identify and differentiate animal behavior patterns is needed. The objective this study was to provide a methodology to identify hen white broiler breeder behavior using combined techniques of image processing and computer vision. These techniques were applied to differentiate body shapes from a sequence of frames as the birds expressed their behaviors. The method was comprised of four stages: (1) identification of body positions and their relationship with typical behaviors. For this stage, the number of frames required to identify each behavior was determined; (2) collection of image samples, with the isolation of the birds that expressed a behavior of interest; (3) image processing and analysis using a filter developed to separate white birds from the dark background; and finally (4) construction and validation of a behavioral classification tree, using the software tool Weka (model 148). The constructed tree was structured in 8 levels and 27 leaves, and it was validated using two modes: the set training mode with an overall rate of success of 96.7%, and the cross validation mode with an overall rate of success of 70.3%. The results presented here confirmed the feasibility of the method developed to identify white broiler breeder behavior for a particular group of study. Nevertheless, more improvements in the method can be made in order to increase the validation overall rate of success. (C) 2013 Elsevier B.V. All rights reserved.

Thermodynamic and economic analysis of hydrogen production integration in the Brazilian sugar and alcohol industry

One of the biggest challenges today is to develop clean fuels, which do not emit pollutant and with viable implementation. One of the options currently under study is the hydrogen production process. In this context, this work aims to study the technical and economical aspects of the incorporation process of hydrogen producing by ethanol steam reforming in the sugar cane industry and MCFC (molten carbonate fuel cell) application on it to generate electric power. Therefore, it has been proposed a modification in the traditional process of sugar cane industry, in order to incorporate hydrogen production, besides the traditional products (sugar, ethylic, hydrated and anhydric alcohol). For this purpose, a detailed theoretical study of the ethanol production process, describing the considerations to incorporate the hydrogen production will be performed. After that, there will be a thermodynamic study for analysing the innovation of this production chain, as well as a study of economic engineering to allocate the costs of products of the new process, optimising it and considering the thermoeconomics as being as an analysis tool. This proposal aims to improve Brazil's position in the ranking of international biofuels, corroborating the nation to be a power in the hydrogen era. (C) 2013 Elsevier Ltd. All rights reserved.

Avaliação da usinagem do INCONEL 718

The nickel superalloys are known as being a material with poor machinability, they have some properties like high hardness, good resistance at high temperature, tendency to weld with the tool material at high temperature, etc. In the aerospace, biomedical and petrochemical industry, are increasing the need to use materials that resist to aggressive process and environment. In these uses, it has increased the use of nickel-based superalloys like Inconel 718 and consequently the need to research new techniques and tools to improve the machinability of this material. For the superalloys and resistant alloys at high temperatures is considered that the difficulty in the machining regards to the combination of the relatively high cutting forces and high temperatures that grow during the machine process, causing deformation or breakage of the cutting tool. This work purpose is to develop the study of the machining of external cylindrical turning of the nickel based alloy Inconel 718, using ceramic tools, seeking the optimization of machining this alloy, looking to provide real productive increases without the need of investments in new production means. The machining test were accomplished using commercials hard metal tools and the results were compared each other to find the best tool and the best parameter. The conclusion is that the tool TNMG160408-23 -class 1005- was the better one, when used with the parameter 60_15_08

Monitoramento da condição da ferramenta de dressagem usando sinais de vibração e modelos neurais

Pós-graduação em Engenharia Elétrica - FEB

Introducing the Discriminative Paraconsistent Machine (DPM)

This paper introduces a new tool for pattern recognition. Called the Discriminative Paraconsistent Machine (DPM), it is based on a supervised discriminative model training that incorporates paraconsistency criteria and allows an intelligent treatment of contradictions and uncertainties. DPMs can be applied to solve problems in many fields of science, using the tests and discussions presented here, which demonstrate their efficacy and usefulness. Major difficulties and challenges that were overcome consisted basically in establishing the proper model with which to represent the concept of paraconsistency.

Neural tool condition estimation in the grinding of advanced ceramics

Ceramic parts are increasingly replacing metal parts due to their excellent physical, chemical and mechanical properties, however they also make them difficult to manufacture by traditional machining methods. The developments carried out in this work are used to estimate tool wear during the grinding of advanced ceramics. The learning process was fed with data collected from a surface grinding machine with tangential diamond wheel and alumina ceramic test specimens, in three cutting configurations: with depths of cut of 120 mu m, 70 mu m and 20 mu m. The grinding wheel speed was 35m/s and the table speed 2.3m/s. Four neural models were evaluated, namely: Multilayer Perceptron, Radial Basis Function, Generalized Regression Neural Networks and the Adaptive Neuro-Fuzzy Inference System. The models'performance evaluation routines were executed automatically, testing all the possible combinations of inputs, number of neurons, number of layers, and spreading. The computational results reveal that the neural models were highly successful in estimating tool wear, since the errors were lower than 4%.

Tool condition monitoring of aluminum oxide grinding wheel in dressing operation using acoustic emission and neural networks

The grinding operation gives workpieces their final finish, minimizing surface roughness through the interaction between the abrasive grains of a tool (grinding wheel) and the workpiece. However, excessive grinding wheel wear due to friction renders the tool unsuitable for further use, thus requiring the dressing operation to remove and/or sharpen the cutting edges of the worn grains to render them reusable. The purpose of this study was to monitor the dressing operation using the acoustic emission (AE) signal and statistics derived from this signal, classifying the grinding wheel as sharp or dull by means of artificial neural networks. An aluminum oxide wheel installed on a surface grinding machine, a signal acquisition system, and a single-point dresser were used in the experiments. Tests were performed varying overlap ratios and dressing depths. The root mean square values and two additional statistics were calculated based on the raw AE data. A multilayer perceptron neural network was used with the Levenberg-Marquardt learning algorithm, whose inputs were the aforementioned statistics. The results indicate that this method was successful in classifying the conditions of the grinding wheel in the dressing process, identifying the tool as "sharp''(with cutting capacity) or "dull''(with loss of cutting capacity), thus reducing the time and cost of the operation and minimizing excessive removal of abrasive material from the grinding wheel.

Evaluation of neural models applied to the estimation of tool wear in the grinding of advanced ceramics

Conselho Nacional de Desenvolvimento Cientifico e Tecnológico (CNPq)

THE ROLE OF INDUSTRY IN DEVELOPING NEW MATERIALS FOR VERTEBRATE PEST CONTROL

In the first paper presented to you today by Dr. Spencer, an expert in the Animal Biology field and an official authority at the same time, you heard about the requirements imposed on a chemical in order to pass the different official hurdles before it ever will be accepted as a proven tool in wildlife management. Many characteristics have to be known and highly sophisticated tests have to be run. In many instances the governmental agency maintains its own screening, testing or analytical programs according to standard procedures. It would be impossible, however, for economic and time reasons to work out all the data necessary for themselves. They, therefore, depend largely on the information furnished by the individual industry which naturally has to be established as conscientiously as possible. This, among other things, Dr. Spencer has made very clear; and this is also what makes quite a few headaches for the individual industry, but I am certainly not speaking only for myself in saying that Industry fully realizes this important role in developing materials for vertebrate control and the responsibilities lying in this. This type of work - better to say cooperative work with the official institutions - is, however, only one part and for the most of it, the smallest part of work which Industry pays to the development of compounds for pest control. It actually refers only to those very few compounds which are known to be effective. But how to get to know about their properties in the first place? How does Industry make the selection from the many thousands of compounds synthesized each year? This, by far, creates the biggest problems, at least from the scientific and technical standpoint. Let us rest here for a short while and think about the possible ways of screening and selecting effective compounds. Basically there are two different ways. One is the empirical way of screening as big a number of compounds as possible under the supposition that with the number of incidences the chances for a "hit" increase, too. You can also call this type of approach the statistical or the analytical one, the mass screening of new, mostly unknown candidate materials. This type of testing can only be performed by a producer of many new materials,that means by big industries. It requires a tremendous investment in personnel, time and equipment and is based on highly simplified but indicative test methods, the results of which would have to be reliable and representative for practical purposes. The other extreme is the intellectual way of theorizing effective chemical configurations. Defenders of this method claim to now or later be able to predict biological effectiveness on the basis of the chemical structure or certain groups in it. Certain pre-experience should be necessary, that means knowledge of the importance of certain molecular requirements, then the detection of new and effective complete molecules is a matter of coordination to be performed by smart people or computers. You can also call this method the synthetical or coordinative method.

Delivery Levels of Support Competencies to Organizational Eco-efficiency: a case study in an electro-electronics sector industry

This article aims to develop and implement a search tool which, through the perception of its respondents, allows assessing how eco-efficient an organization is based on the identification of delivery levels of support competencies to organizational eco-efficiency. A mixed (qualitative and quantitative) exploratory-descriptive research was conducted, from a case study in an 'ISE Company'. A semi-structured interview and pictures of verification were used as data collection instruments. The data were analyzed via documentary analysis and triangulation of information collected. It was inferred that at the 'ISE Company' professionals at the high-level of the organizational hierarchy recognize, in part, the growth of organizational actions that contribute to sustainability, which is not fully consistent with national publications on the subject. The result of the research showed that organizational strategies addressing eco-efficiency are partially aligned with the professional performance of the organization.

Safety illusion and error trap in a collectively-operated machine accident

Workplace accidents involving machines are relevant for their magnitude and their impacts on worker health. Despite consolidated critical statements, explanation centered on errors of operators remains predominant with industry professionals, hampering preventive measures and the improvement of production-system reliability. Several initiatives were adopted by enforcement agencies in partnership with universities to stimulate production and diffusion of analysis methodologies with a systemic approach. Starting from one accident case that occurred with a worker who operated a brake-clutch type mechanical press, the article explores cognitive aspects and the existence of traps in the operation of this machine. It deals with a large-sized press that, despite being endowed with a light curtain in areas of access to the pressing zone, did not meet legal requirements. The safety devices gave rise to an illusion of safety, permitting activation of the machine when a worker was still found within the operational zone. Preventive interventions must stimulate the tailoring of systems to the characteristics of workers, minimizing the creation of traps and encouraging safety policies and practices that replace judgments of behaviors that participate in accidents by analyses of reasons that lead workers to act in that manner.

EXAM-S: an Analysis tool for Multi-Domain Policy Sets

As distributed collaborative applications and architectures are adopting policy based management for tasks such as access control, network security and data privacy, the management and consolidation of a large number of policies is becoming a crucial component of such policy based systems. In large-scale distributed collaborative applications like web services, there is the need of analyzing policy interactions and integrating policies. In this thesis, we propose and implement EXAM-S, a comprehensive environment for policy analysis and management, which can be used to perform a variety of functions such as policy property analyses, policy similarity analysis, policy integration etc. As part of this environment, we have proposed and implemented new techniques for the analysis of policies that rely on a deep study of state of the art techniques. Moreover, we propose an approach for solving heterogeneity problems that usually arise when considering the analysis of policies belonging to different domains. Our work focuses on analysis of access control policies written in the dialect of XACML (Extensible Access Control Markup Language). We consider XACML policies because XACML is a rich language which can represent many policies of interest to real world applications and is gaining widespread adoption in the industry.

The cutting stock problem in the wood industry

This thesis proposes a solution for board cutting in the wood industry with the aim of usage minimization and machine productivity. The problem is dealt with as a Two-Dimensional Cutting Stock Problem and specific Combinatorial Optimization methods are used to solve it considering the features of the real problem.

Applications of infrared thermography in the food industry

In the last 20-30 years, the implementation of new technologies from the research centres to the food industry process was very fast. The infrared thermography is a tool used in many fields, including agriculture and food science technology, because of it's important qualities like non-destructive method, it is fast, it is accurate, it is repeatable and economical. Almost all the industrial food processors have to use the thermal process to obtain an optimal product respecting the quality and safety standards. The control of temperature of food products during the production, transportation, storage and sales is an essential process in the food industry network. This tool can minimize the human error during the control of heat operation, and reduce the costs with personal. In this thesis the application of infrared thermography (IRT) was studies for different products that need a thermal process during the food processing. The background of thermography was presented, and also some of its applications in food industry, with the benefits and limits of applicability. The measurement of the temperature of the egg shell during the heat treatment in natural convection and with hot-air treatment was compared with the calculated temperatures obtained by a simplified finite element model made in the past. The complete process shown a good results between calculated and observed temperatures and we can say that this technique can be useful to control the heat treatments for decontamination of egg using the infrared thermography. Other important application of IRT was to determine the evolution of emissivity of potato raw during the freezing process and the control non-destructive control of this process. We can conclude that the IRT can represent a real option for the control of thermal process from the food industry, but more researches on various products are necessary.