198 research outputs found
A Multicultivar Approach for Grape Bunch Weight Estimation Using Image Analysis
The determination of bunch features that are relevant for bunch weight estimation is an
important step in automatic vineyard yield estimation using image analysis. The conversion of 2D
image features into mass can be highly dependent on grapevine cultivar, as the bunch morphology
varies greatly. This paper aims to explore the relationships between bunch weight and bunch features
obtained from image analysis considering a multicultivar approach. A set of 192 bunches from four
cultivars, collected at sites located in Portugal and South Africa, were imaged using a conventional
digital RGB camera, followed by image analysis, where several bunch features were extracted, along
with physical measurements performed in laboratory conditions. Image data features were explored
as predictors of bunch weight, individually and in a multiple stepwise regression analysis, which
were then tested on 37% of the data. The results show that the variables bunch area and visible
berries are good predictors of bunch weight (R2 ranging from 0.72 to 0.90); however, the simple
regression lines fitted between these predictors and the response variable presented significantly
different slopes among cultivars, indicating cultivar dependency. The elected multiple regression
model used a combination of four variables: bunch area, bunch perimeter, visible berry number, and
average berry area. The regression analysis between the actual and estimated bunch weight yielded a
R2 = 0.91 on the test set. Our results are an important step towards automatic yield estimation in the
vineyard, as they increase the possibility of applying image-based approaches using a generalized
model, independent of the cultivarinfo:eu-repo/semantics/publishedVersio
Can Customers Detect Script Usage in Service Encounters? An Experimental Video Analysis
Service scripts are predetermined guides for employees to follow when delivering service to customers. Some services require employees to strictly follow a script, whereas others use scripts more flexibly, if at all. Extant research regarding service scripts in the domain of service operations has mainly addressed the topic from more of a process view as a control mechanism for the encounter but minimal research has examined customer perceptions of scripted service. The authors examine a pivotal first question, which is if customers can detect different approaches to script use. To answer the question, the authors conducted a video experiment of face‐to‐face service encounters in the hospitality industry. The results indicate that customers can detect degrees of script use across both standardized and customized encounter types. This work serves as initial empirical evidence that customers are indeed capable of detecting subtleties in scripting approaches in different service situations and supports that script level is an important service design construct for research. Furthermore, the authors highlight the use of a video experiment as an innovative methodology for assessing customer perceptions of intangible aspects to services in a realistic setting. One implication of this study is that managers need to assess the impact that different script levels have on customer perceptions of various service performance measures. Managers should also consider the effect script detection has on customer perceptions of the service experience and service brand to assure their script approach aligns with the organization’s service strategy
Grapevine yield prediction using image analysis - improving the estimation of non-visible bunches
Yield forecast is an issue of utmost importance for the entire grape and wine sectors. There are several methods for vineyard yield estimation. The ones based on estimating yield components are the most commonly used in commercial vineyards. Those methods are generally destructive and very labor intensive and can provide inaccurate results as they are based on the assessment of a small sample of bunches. Recently, several attempts have been made to apply image analysis technologies for bunch and/or berries recognition in digital images. Nonetheless, the effectiveness of image analysis in predicting yield is strongly dependent of grape bunch visibility, which is dependent on canopy density at fruiting zone and on bunch number, density and dimensions. In this work data on bunch occlusion obtained in a field experiment is presented. This work is set-up in the frame of a research project aimed at the development of an unmanned ground vehicle to scout vineyards for non-intrusive estimation of canopy features and grape yield. The objective is to evaluate the use of explanatory variables to estimate the fraction of non-visible bunches (bunches occluded by leaves). In the future, this estimation can potentially improve the accuracy of a computer vision algorithm used by the robot to estimate total yield.
In two vineyard plots with Encruzado (white) and Syrah (red) varieties, several canopy segments of 1 meter length were photographed with a RGB camera and a blue background, close to harvest date. Out of these images, canopy gaps (porosity) and bunches’ region of interest (ROI) files were computed in order to estimate the corresponding projected area. Vines were then defoliated at fruiting zone, in two steps and new images were obtained before each step.
Overall the area of bunches occluded by leaves achieved mean values between 67% and 73%, with Syrah presenting the larger variation. A polynomial regression was fitted between canopy porosity (independent variable) and percentage of bunches not occluded by leaves which showed significant R2 values of 0.83 and 0.82 for the Encruzado and Syrah varieties, respectively.
Our results show that the fraction of non-visible bunches can be estimated indirectly using canopy porosity as explanatory variable, a trait that can be automatically obtained in the future using a laser range finder deployed on the mobile platforminfo:eu-repo/semantics/publishedVersio
A phenomenological fitting curve for the magnetocaloric effect of materials with a second-order phase transition
The magnetic entropy change of polycrystalline samples Gd, La(Fe0.92Co0.08)11.83Al1.17, LaFe10.8Si2.2, Mn5Ge2.7Ga0.3, Nd2AlFe13Mn3, and TbCo2 with a second-order phase transition has been investigated. A uniform phenomenological function that describes the magnetic entropy change is found for these materials. This could be of great benefit for the design of magnetic refrigerators. The field dependence of the critical exponent for the variation in the maximum entropy change with field is studied. The critical exponent value of 2/3, which is predicted by the mean field theory, is only satisfied for moderate field values. The refrigerant capacity is analyzed and compared to the predictions of the fitting function
Rice Straw Geotextile As Ground Cover ForSoil Erosion Mitigation
Generally, the study aimed to mitigate soil erosion using rice straw geotextile as ground cover. Specifically, it attempted to: evaluate the effect of RSM and RSN as ground cover in mitigating soil erosion at varying slope gradients and different rainfall intensities, and; determine the relationship of slope gradient versus sediment concentration, sediment yield and quantity of soil loss at different levels of rainfall intensity. Results revealed that RSGT as ground cover greatly affected soil erosion. Under rainfall intensities of 75, 100 and 125 mm/hr, RSM had significantly lower soil loss as compared to RSN, CCN And NGC. However, RSN and CCN were comparable with each other but differ significantly with NGC. Sediment concentration, sediment yield and soil erosion exhibited a nonlinear relationship with slope gradient. At any given level of rainfall intensity, the three indicators increased correspondingly as the slope was increased from 10 to 35o and then declined when the slope was further increased from 35 to 60o. Sediment concentration best fitted (R2 = 0.977) in a quadratic model in the form of a second-degree polynomial equation: SC = 0.551 + 0.626S - 0.008S2 Likewise, observed sediment yield best fitted (R2 = 0.954) a second degree polynomial equation as expressed by a quadratic model: SY = 356.0 + 61.70S – 0.972S2 Moreover, the observed soil erosion was best modeled with R2 = 97.1% confidence by a second degree polynomial equation. The regression model is quadratic in form and is given by the equation: SE = 68.92 + 11.11S - 0.174S2. Keywords: rice straw, geotextile, ground cover, soil erosion, mitigation, rainfall simulatio
Respuesta de gramas nativas a la fertilización de nitrógeno, fósforo y potasio en el trópico húmedo
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Proposal of a Brazilian database government open linked data - DBgoldbr invited paper
© 2017 Copyright is held by the owner/author(s). The Brazilian Government has made available on the Web a massive volume of public data. This data may be structured, semistructured or non-structured in order to turn the administration as transparent as possible. Thus, we notice the great challenge in providing applications capable enough to handle this Big Data environment, and to make information available for decision making. In this environment, data processing is done via new approaches from Information Science and Computer Science areas, by involving Technologies and processes for collecting, representing, storing and disseminating information. This paper presents a conceptual model, the technical architecture and the prototype implementation of a tool DBgoldbr, designed to classify government public information with the help of ontologies, by transforming open data into open linked data. To fulfill the purpose of the solution, we used Soft System Methodology to identify problems, to collect users needs and to design solutions that fit the purpose of specific groups. The DBgoldbr tool was designed to ease up the search for open data made available by many Brazilian Government institutions, so that this data can be reused to support the evaluation and monitoring of social programs, in order to support the design and management of public policies
Human FOXN1-Deficiency Is Associated with αβ Double-Negative and FoxP3+ T-Cell Expansions That Are Distinctly Modulated upon Thymic Transplantation
Forkhead box N1 (FOXN1) is a transcription factor crucial for thymic epithelium development and prevention of its involution. Investigation of a patient with a rare homozygous FOXN1 mutation (R255X), leading to alopecia universalis and thymus aplasia, unexpectedly revealed non-maternal circulating T-cells, and, strikingly, large numbers of aberrant double-negative αβ T-cells (CD4negCD8neg, DN) and regulatory-like T-cells. These data raise the possibility that a thymic rudiment persisted, allowing T-cell development, albeit with disturbances in positive/negative selection, as suggested by DN and FoxP3+ cell expansions. Although regulatory-like T-cell numbers normalized following HLA-mismatched thymic transplantation, the αβDN subset persisted 5 years post-transplantation. Involution of thymus allograft likely occurred 3 years post-transplantation based on sj/βTREC ratio, which estimates intrathymic precursor T-cell divisions and, consequently, thymic explant output. Nevertheless, functional immune-competence was sustained, providing new insights for the design of immunological reconstitution strategies based on thymic transplantation, with potential applications in other clinical settings
VINBOT - um robô terrestre para viticultura de precisão
I Congresso Luso-Brasileiro de Horticultura. Sessão ViticulturaNos últimos anos tem-se verificado um aumento exponencial da utilização de
robôs na agricultura, estando a União Europeia a fomentar fortemente a investigação
nesta área através da Agenda de Investigação Estratégica para a Robótica na Europa. A
grande importância do conhecimento da variabilidade espacial do vigor e produção em
Viticultura, tem levado ao desenvolvimento de ferramentas de Viticultura de Precisão
baseadas em sensores diversos montados em veículos autónomos. Neste trabalho
apresentam-se alguns resultados de validação de campo obtidos no âmbito do projeto
europeu VINBOT (“Autonomous cloud-computing vineyard robot to optimise yield
management and wine quality”) que teve por objectivo o desenvolvimento de um robô
terrestre, equipado com diversas câmaras e sensores, para obtenção de mapas de
variabilidade espacial quer de características da sebe quer da produção de uma parcela
de vinha. O ensaio de validação decorreu numa vinha experimental do Instituto Superior
de Agronomia, onde vários segmentos de várias linhas da casta Alvarinho foram
rotuladas, submetidas ao registo manual das características da sebe e da produção e,
simultaneamente, monitorizados pela plataforma de sensores do robô. Os dados obtidos
manualmente foram comparados com os valores estimados pelos algoritmos de análise
de imagem do robô. Relativamente às dimensões da sebe os resultados de validação
mostram um bom ajustamento entre dados observados e as estimativas proporcionadas
pela reconstrução 3D da sebe através do sensor laser “Range Finder”. No que se refere à
produção, verificou-se uma ligeira subestimativa resultante da oclusão de alguns cachos
quer por outros cachos quer pela vegetação da videira. Estão em curso novos ensaios
com vista a testar o robô noutras castas e sistemas de condução e a melhorar os
algoritmos de análise de imageminfo:eu-repo/semantics/publishedVersio
Lung volume calculated from electrical impedance tomography in ICU patients at different PEEP levels
Purpose: To study and compare the relationship between end-expiratory lung volume (EELV) and changes in end-expiratory lung impedance (EELI) measured with electrical impedance tomography (EIT) at the basal part of the lung at different PEEP levels in a mixed ICU population. Methods: End-expiratory lung volume, EELI and tidal impedance variation were determined at four PEEP levels (15-10-5-0 cm H2O) in 25 ventilated ICU patients. The tidal impedance variation and tidal volume at 5 cm H2O PEEP were used to calculate change in impedance per ml; this ratio was then used to calculate change in lung volume from change in EELI. To evaluate repeatability, EELV was measured in quadruplicate in five additional patients. Results: There was a significant but relatively low correlation (r = 0.79; R2= 0.62) and moderate agreement (bias 194 ml, SD 323 ml) between ΔEELV and change in lung volume calculated from the ΔEELI. The ratio of tidal impedance variation and tidal volume differed between patients and also varied at different PEEP levels. Good agreement was found between repeated EELV measurements and washin/washout of a simulated nitrogen washout technique. Conclusion: During a PEEP trial, the assumption of a linear relationship between change in global tidal impedance and tidal volume cannot be used to calculate EELV when impedance is measured at only one thoracic level just above the diaphragm
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