1,354,400 research outputs found
Lateral resolution of electrostatic force microscopy for mapping of dielectric interfaces in ambient conditions
No full textThe attainable lateral resolution of electrostatic force microscopy (EFM) in an ambient air environment on dielectric materials was characterized on a reference sample comprised of two distinct, immiscible glassy polymers cut in a cross-section by ultramicrotomy. Such a sample can be modeled as two semi-infinite dielectrics with a sharp interface, presenting a quasi-ideal, sharp dielectric contrast. Electric polarizability line profiles across the interface were obtained, in both lift-mode and feedback-regulated dynamic mode EFM, as a function of probe/surface separation, for different cases of oscillation amplitudes. We find that the results do not match predictions for dielectric samples, but comply well or are even better than predicted for conductive interfaces. A resolution down to 3 nm can be obtained by operating in feedback-regulated EFM realized by adopting constant-excitation frequency-modulation mode. This suggests resolution is ruled by the closest approach distance rather than by average separation, even with probe oscillation amplitudes as high as 10 nm. For better comparison with theoretical predictions, effective probe radii and cone aperture angles were derived from approach curves, by also taking into account the finite oscillation amplitude of the probe, by exploiting a data reduction procedure previously devised for the derivation of interatomic potentials
Dimensionality Reduction for CCD Sensor-Based Image to Control Fall Armyworm in Agriculture.
No full textReconhecimento de padrões da Spodoptera frugiperda na cultura do milho baseado em processamento avançado de imagens e aprendizado de máquina.
No full textAtualmente, a identificação da Lagarta do cartucho (Spodoptera frugperda) na cultura do milho (Zea mays) depende muito do fator humano, assim como seu controle ocorre principalmente por meio de armadilhas de captura. Isso faz com que o diagnóstico de infestações dessa praga seja pouco eficiente, ocasionando significativos prejuízos à produção agrícola, assim como pode levar ao uso excessivo de agrotóxicos. Este trabalho apresenta um método para o controle da referida praga com base no uso de técnicas do processamento de imagens e inteligência computacional. Desta forma, é realizado outro reconhecimento de padrões da Lagarta do Cartucho em seus diferentes estágios de desenvolvimento, permitindo assim, seu reconhecimento precoce, confiável e monitorado. Seu emprego melhora o estado da arte dos procedimentos de controle para se chegar à possibilidade de automatização. Para o desenvolvimento do método foram consideradas técnicas de obtenção de imagens, pré-processamento, segmentação, extração de características, estatística multivariada e classificação supervisionada. Para a etapa de aquisição de imagens, foi utilizado banco de imagens online. Na etapa de pré-processamento, foram avaliados filtros Gaussiano e Non-local Means para a suavização de ruídos. As métricas de Erro Quadrado Médio (Mean Square Error - MSE) e Pico da Razão Sinal-Ruído (Peak Sigtal-to-Noise Ratio - PSNR) foram utilizadas para a validação do processo de filtragem das imagens. Para a etapa de segmentação de imagens, foram avaliadas técnicas de limiarização e pixels sementes por meio do padrão de cores HSV (Hue, Saturation e Value) e CIE L*a*b*. Foi também estabelecido a automatização do processo de segmentação das imagens a partir da técnica de Otsu. Para a etapa de extração de características, foram aplicados e considerados os descritores de textura (Histogram of Orientation Gradient - HOG), de momentos invariantes de Hu, para a obtenção de descrição de formas e tamanhos, assim como a redução de dimensionalidade dos vetores de características por meio da Análise de Componentes Principais (Principal Component Analysis - PCA). Por fim, para a classificação dos padrões da Lagarta do Cartucho foi estabelecido um conjunto de classificadores baseados em Máquinas de Vetores de Suporte (Support Vector Machine – SVM). Os resultados mostram a eficácia do método para o reconhecimento e classificação da Lagarta do cartucho na cultua do milho com acurácia e precisão superiores a 70% e 80% respectivamente.Assim, sua utilização possibilita automatizar mecanismos de controle de populações dessa praga, sendo de interesse dos agricultores, que pretendem promover ganhos de produtividade, robustez no controle da praga e segurança alimentar
Computational Intelligence Approach for Fall Armyworm Control in Maize Crop.
No full textAbstract: This paper presents a method for dynamic pattern recognition and classification of one dangerous caterpillar species to allow for its control in maize crops. The use of dynamic pattern recognition supports the identification of patterns in digital image data that change over time. In fact, identifying fall armyworms (Spodoptera frugiperda) is critical in maize production, i.e., in all of its growth stages. For such pest control, traditional agricultural practices are still dependent on human visual effort, resulting in significant losses and negative impacts on maize production, food security, and the economy. Such a developed method is based on the integration of digital image processing, multivariate statistics, and machine learning techniques. We used a supervised machine learning algorithm that classifies data by finding an optimal hyperplane that maximizes the distance between each class of caterpillar with different lengths in N-dimensional spaces. Results show the method’s efficiency, effectiveness, and suitability to support decision making for this customized control context
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
No full text“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Seasonal changes in soil respiration rates in olive orchards
No full textA field study was conducted on olive trees growing at two locations in Tuscany, Italy, to determine seasonal changes in soil respiration rates (Rs) under different conditions of soil moisture. The two orchards differed in cultivar, age, soil texture and soil management. The soil was managed by either periodic disking or permanent grass cover. Soil water availability was modified using drip irrigation. Soil respiration rates were measured using a closed-chamber system connected to an infrared gas analyzer at different positions around six trees in one orchard (three irrigated and three non-irrigated) and three trees in the other orchard. Seasonal courses of Rs were similar in both orchards, with maximum values reached either in mid-spring or autumn over the two years of study. Low Rs occurred in the summer under rain-fed conditions. In both orchards irrigation resulted in dramatic increases of Rs. Soil respiration rates of the orchard with a grass cover were higher than those of the periodically disked soil and, on an annual basis, we estimated 11.79 and 7.84 t ha-1 of carbon emissions out of the soil in the two orchards, respectively. Carbon emissions due to soil respiration of irrigated trees were 7% higher than those of rain-fed ones
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