A ictiofauna no monitoramento da qualidade ambiental em um distrito industrial do estuário amazônico

Vila do Conde está localizada no município de Barcarena, Pará, Brasil. Nesta região está concentrado um importante pólo industrial de mineração, constituindo um fator de risco para a qualidade da água. Diante do exposto, este trabalho teve o objetivo de avaliar a qualidade da água no ambiente estuarino localizado no entorno de Vila do Conde utilizando a ictiofauna como bioindicador e o fígado de duas espécies de peixes como biomarcador histopatológico. As coletas do material abiótico (água) e da ictiofauna ocorreram em três áreas considerando os diferentes níveis de impacto: Zona 1, localizado no entorno do terminal portuário e industrial de Vila do Conde, considerada como alto risco de contaminação; Zona 2, localizada na ilha do Capim, na divisa dos municípios de Barcarena e Abaetetuba, classificada com risco médio de impacto; Zona 3, localizada na ilha das Onças, município de Barcarena, classificada com risco minímo por está distante das fontes de contaminação. Para todas as áreas de estudo foram feitas amostragens tanto no ambiente de canal quanto no canal de maré ao longo de quatro coletas bimestrais -, transição chuvoso para o seco (Junho 2009), seco (Setembro 2009), transição seco para chuvoso (Janeiro 2010) e período chuvoso (Abril 2010), no período de um ano de coleta. Para a obtenção dos dados foram utilizados rede de emalhar e rede de tapagem. Como forma de abordar diferentes vertentes sobre a qualidade da água em Vila do Conde, este trabalho foi dividido em etapas. A primeira etapa consistiu do uso da ictiofauna como bioindicadora (capítulo 1). Na segunda etapa foram selecionadas duas espécies abundantes com hábitos alimentares distintos, Plagioscion squamosissimus e Lithodoras dorsalis, para avaliar a saúde do ambiente através da utilização do fígado como iomarcador histopatológico (capítulo 2). Por fim todas as famílias de descritores da comunidade estudadas nos capítulos 1 e 2 foram integralizadas através do uso de índices de integridade biológica (capítulo 3). A análise da ictiofauna como bioindicadora mostrou que, para os dois ambientes (canal e igarapé), considerando as várias famílias de descritores, foi evidente a composição diferenciada entre os locais. Das 77 espécies capturadas, apenas 23 foram encontradas na zona 1. Adicionalmente, também foi observada a diminuição de organismos de grande porte. Este decréscimo foi considerado como uma resposta ecológica inicial as alterações antrópicas. A análise dos biomarcadores, feito através do estudo histopatológico do fígado se mostrou eficiente e demonstrou que presença antrópica naquela região está afetando a saúde da P. squamosissimus e L. dorsalis. O MAV (Mean Assessment Values), HAI (Histological Alteration Index) e o MDS (multidimensional scaling) mostraram claramente as diferenças entre as áreas estudadas. Nas áreas em que existe o contato mais próximo com o porto e as indústrias, as alterações foram mais severas e algumas consideradas irreversíveis para as duas espécies. As principais lesões encontradas nas duas espécies foram: o aumento do centro melanomacrófagos, degeneração gordurosa, inflamação nos hepatócitos, hepatite, congestão nos vasos e necrose focal. As alterações hepáticas observadas neste estudo foram mais intensas em P. squamosissimus que é carnívora e se alimenta na área de estudo predominantemente de camarão. Através dos índices de integridade todas as informações sobre a comunidade descritas anteriormente foram agregadas e denominadas de métricas. Para os dois ambientes (canal e igarapé), a curva de biomassa/dominância ABC mostrou que as zonas 1 e 2 apresentaram alterações, sendo estas áreas classificadas como moderadamente impactadas. Os índices BHI (Estuarine biological health index), EFCI (Estuarine fish community índex), TFCI (Transitional fish classification índex) e EBI (Estuarine biotic integrity index) foram considerados excelentes indicadores de integridade nas áreas de estudos e foram eficientes em mostrar alterações graves da comunidade de peixes na zona 1. Quanto à zona 2, já foi possível observar algum tipo de alteração no ambiente, mostrando que a contaminação não está se restringindo apenas ao entorno de Vila do Conde. As metodologias aplicadas foram capazes de detectar as interferências antrópicas na área de estudo e podem para ser replicadas em outros ambientes estuarinos. Entretanto, estudos mais detalhados e por um maior período de tempo ainda são necessários em Vila do Conde, principalmente relacionadas à bioacumulação de metais pesados nas principais espécies consumidas.

Analyzing training dependencies and posterior fusion in discriminant classification of apnoea patients based on sustained and connected speech

We present a novel approach using both sustained vowels and connected speech, to detect obstructive sleep apnea (OSA) cases within a homogeneous group of speakers. The proposed scheme is based on state-of-the-art GMM-based classifiers, and acknowledges specifically the way in which acoustic models are trained on standard databases, as well as the complexity of the resulting models and their adaptation to specific data. Our experimental database contains a suitable number of utterances and sustained speech from healthy (i.e control) and OSA Spanish speakers. Finally, a 25.1% relative reduction in classification error is achieved when fusing continuous and sustained speech classifiers. Index Terms: obstructive sleep apnea (OSA), gaussian mixture models (GMMs), background model (BM), classifier fusion.

Independent component analysis for the identification of sources of variation on an industrial nirs application

A Near Infrared Spectroscopy (NIRS) industrial application was developed by the LPF-Tagralia team, and transferred to a Spanish dehydrator company (Agrotécnica Extremeña S.L.) for the classification of dehydrator onion bulbs for breeding purposes. The automated operation of the system has allowed the classification of more than one million onion bulbs during seasons 2004 to 2008 (Table 1). The performance achieved by the original model (R2=0,65; SEC=2,28ºBrix) was enough for qualitative classification thanks to the broad range of variation of the initial population (18ºBrix). Nevertheless, a reduction of the classification performance of the model has been observed with the passing of seasons. One of the reasons put forward is the reduction of the range of variation that naturally occurs during a breeding process, the other is the variations in other parameters than the variable of interest but whose effects would probably be affecting the measurements [1]. This study points to the application of Independent Component Analysis (ICA) on this highly variable dataset coming from a NIRS industrial application for the identification of the different sources of variation present through seasons.

Grapevine Yield and Leaf Area Estimation Using Supervised Classification Methodology on RGB Images Taken under Field Conditions

The aim of this research was to implement a methodology through the generation of a supervised classifier based on the Mahalanobis distance to characterize the grapevine canopy and assess leaf area and yield using RGB images. The method automatically processes sets of images, and calculates the areas (number of pixels) corresponding to seven different classes (Grapes, Wood, Background, and four classes of Leaf, of increasing leaf age). Each one is initialized by the user, who selects a set of representative pixels for every class in order to induce the clustering around them. The proposed methodology was evaluated with 70 grapevine (V. vinifera L. cv. Tempranillo) images, acquired in a commercial vineyard located in La Rioja (Spain), after several defoliation and de-fruiting events on 10 vines, with a conventional RGB camera and no artificial illumination. The segmentation results showed a performance of 92% for leaves and 98% for clusters, and allowed to assess the grapevine’s leaf area and yield with R2 values of 0.81 (p < 0.001) and 0.73 (p = 0.002), respectively. This methodology, which operates with a simple image acquisition setup and guarantees the right number and kind of pixel classes, has shown to be suitable and robust enough to provide valuable information for vineyard management.

Discernment of bee pollen loads using computer vision and one-class classification techniques

In this paper, we propose a system for authenticating local bee pollen against fraudulent samples using image processing and classification techniques. Our system is based on the colour properties of bee pollen loads and the use of one-class classifiers to reject unknown pollen samples. The latter classification techniques allow us to tackle the major difficulty of the problem, the existence of many possible fraudulent pollen types. Also presented is a multi-classifier model with an ambiguity discovery process to fuse the output of the one-class classifiers. The method is validated by authenticating Spanish bee pollen types, the overall accuracy of the final system of being 94%. Therefore, the system is able to rapidly reject the non-local pollen samples with inexpensive hardware and without the need to send the product to the laboratory.

Fusion of probabilistic knowledge-based classification rules and learning automata for automatic recognition of digital images

In this paper, the fusion of probabilistic knowledge-based classification rules and learning automata theory is proposed and as a result we present a set of probabilistic classification rules with self-learning capability. The probabilities of the classification rules change dynamically guided by a supervised reinforcement process aimed at obtaining an optimum classification accuracy. This novel classifier is applied to the automatic recognition of digital images corresponding to visual landmarks for the autonomous navigation of an unmanned aerial vehicle (UAV) developed by the authors. The classification accuracy of the proposed classifier and its comparison with well-established pattern recognition methods is finally reported.

Active Optical Sensors for Tree Stem Detection and Classification in Nurseries.

Active optical sensing (LIDAR and light curtain transmission) devices mounted on a mobile platform can correctly detect, localize, and classify trees. To conduct an evaluation and comparison of the different sensors, an optical encoder wheel was used for vehicle odometry and provided a measurement of the linear displacement of the prototype vehicle along a row of tree seedlings as a reference for each recorded sensor measurement. The field trials were conducted in a juvenile tree nursery with one-year-old grafted almond trees at Sierra Gold Nurseries, Yuba City, CA, United States. Through these tests and subsequent data processing, each sensor was individually evaluated to characterize their reliability, as well as their advantages and disadvantages for the proposed task. Test results indicated that 95.7% and 99.48% of the trees were successfully detected with the LIDAR and light curtain sensors, respectively. LIDAR correctly classified, between alive or dead tree states at a 93.75% success rate compared to 94.16% for the light curtain sensor. These results can help system designers select the most reliable sensor for the accurate detection and localization of each tree in a nursery, which might allow labor-intensive tasks, such as weeding, to be automated without damaging crops.

Region-dependent vehicle classification using PCA features

Video-based vehicle detection is the focus of increasing interest due to its potential towards collision avoidance. In particular, vehicle verification is especially challenging due to the enormous variability of vehicles in size, color, pose, etc. In this paper, a new approach based on supervised learning using Principal Component Analysis (PCA) is proposed that addresses the main limitations of existing methods. Namely, in contrast to classical approaches which train a single classifier regardless of the relative position of the candidate (thus ignoring valuable pose information), a region-dependent analysis is performed by considering four different areas. In addition, a study on the evolution of the classification performance according to the dimensionality of the principal subspace is carried out using PCA features within a SVM-based classification scheme. Indeed, the experiments performed on a publicly available database prove that PCA dimensionality requirements are region-dependent. Hence, in this work, the optimal configuration is adapted to each of them, rendering very good vehicle verification results.

Sea Bottom Classification by Means of Bathymetric LIDAR Data

Light Detection and Ranging (LIDAR) provides high horizontal and vertical resolution of spatial data located in point cloud images, and is increasingly being used in a number of applications and disciplines, which have concentrated on the exploit and manipulation of the data using mainly its three dimensional nature. Bathymetric LIDAR systems and data are mainly focused to map depths in shallow and clear waters with a high degree of accuracy. Additionally, the backscattering produced by the different materials distributed over the bottom surface causes that the returned intensity signal contains important information about the reflection properties of these materials. Processing conveniently these values using a Simplified Radiative Transfer Model, allows the identification of different sea bottom types. This paper presents an original method for the classification of sea bottom by means of information processing extracted from the images generated through LIDAR data. The results are validated using a vector database containing benthic information derived by marine surveys.

Coordination mechanisms and software in industrial networks - a literature review

This paper groups recent supply chain management research focused on organizational design and its software support. The classification encompasses criteria related to research methodology and content. Empirical studies from management science focus on network types and organizational fit. Novel planning algorithms and innovative coordination schemes are developed mostly in the field of operations research in order to propose new software features. Operations and production management realize cost-benefit analysis of IT software implementations. The success of software solutions for network coordination depends strongly on the fit of three dimensions: network configuration, coordination scheme and software functionality. This paper concludes with proposals for future research on unaddressed issues within and among the identified research streams.

Morphological classification of microtidal sand and gravel beaches

A new classification of microtidal sand and gravel beaches with very different morphologies is presented below. In 557 studied transects, 14 variables were used. Among the variables to be emphasized is the depth of the Posidonia oceanica. The classification was performed for 9 types of beaches: Type 1: Sand and gravel beaches, Type 2: Sand and gravel separated beaches, Type 3: Gravel and sand beaches, Type 4: Gravel and sand separated beaches, Type 5: Pure gravel beaches, Type 6: Open sand beaches, Type 7: Supported sand beaches, Type 8: Bisupported sand beaches and Type 9: Enclosed beaches. For the classification, several tools were used: discriminant analysis, neural networks and Support Vector Machines (SVM), the results were then compared. As there is no theory for deciding which is the most convenient neural network architecture to deal with a particular data set, an experimental study was performed with different numbers of neuron in the hidden layer. Finally, an architecture with 30 neurons was chosen. Different kernels were employed for SVM (Linear, Polynomial, Radial basis function and Sigmoid). The results obtained for the discriminant analysis were not as good as those obtained for the other two methods (ANN and SVM) which showed similar success.

European Industrial Policy. Bruges European Economic Policy (BEEP) Briefing 15/2006

This survey of European industrial policy aims to set out and explain the great significance of European integration in determining (changes in) structure and performance of industry in the EU. This influence is explored from the policy side by analysing the transformation of the framework within which both EU and Member States' industrial policy can be pursued. Empirical economic analysis is not included because this BEEP Briefing was originally written for a handbook3 in which other authors were assigned a range of industrial economics subjects. In the last 25 years or so, the transformation is such that the nature and scope of industrial policy at both levels of government has profoundly changed as well. Indeed, the toolkit of measures has shrunk considerably, disciplines have been tightened and the economic policy views behind industrial policy have altered everywhere. The pro-competitive logic of deeper market integration itself is rarely questioned nowadays and industrial policy at the two levels takes on different forms. The survey discusses at some length the division of powers between, and the complementarity of, the Member States' and EU levels of government when it comes to industrial policy, based on a fairly detailed classification of industrial policy instruments. The three building blocks of the wide concept of industrial policy as defined in this BEEP Briefing consist of the EU framework of market integration, EU horizontal industrial policy and its EU sectoral or specific counterpart. Each one is surveyed at the EU level. Preceding these three sections is a discussion of three cross-cutting issues, namely, the indiscriminate use of the 'competitiveness' label in the EU circuit of business and policy makers, the relation between services and EU industrial policy and, finally, that of European infrastructure. One major conclusion is that, today, the incentive structure for industry and industrial markets is dominated by the stringency of the overall EU framework and to some moderate degree by the horizontal approach.

The development of a classification scheme for brake linings. Volume I. Summary report.

National Highway Traffic Safety Administration, Washington, D.C.

The development of a classification scheme for brake linings. Volume II. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Classification of safety appliance defects to be reported by federal inspectors : July 1, 1911 /

At head of title: Interstate Commerce Commission.