Evaluation of a computer model to simulate water table response to subirrigation

The objective of this work was to evaluate the water flow computer model, WATABLE, using experimental field observations on water table management plots from a site located near Hastings, FL, USA. The experimental field had scale drainage systems with provisions for subirrigation with buried microirrigation and conventional seepage irrigation systems. Potato (Solanum tuberosum L.) growing seasons from years 1996 and 1997 were used to simulate the hydrology of the area. Water table levels, precipitation, irrigation and runoff volumes were continuously monitored. The model simulated the water movement from a buried microirrigation line source and the response of the water table to irrigation, precipitation, evapotranspiration, and deep percolation. The model was calibrated and verified by comparing simulated results with experimental field observations. The model performed very well in simulating seasonal runoff, irrigation volumes, and water table levels during crop growth. The two-dimensional model can be used to investigate different irrigation strategies involving water table management control. Applications of the model include optimization of the water table depth for each growth stage, and duration, frequency, and rate of irrigation.

Models and applications for risk assessment and prediction of Asian soybean rust epidemics

Asian rust of soybean [Glycine max (L.) Merril] is one of the most important fungal diseases of this crop worldwide. The recent introduction of Phakopsora pachyrhizi Syd. & P. Syd in the Americas represents a major threat to soybean production in the main growing regions, and significant losses have already been reported. P. pachyrhizi is extremely aggressive under favorable weather conditions, causing rapid plant defoliation. Epidemiological studies, under both controlled and natural environmental conditions, have been done for several decades with the aim of elucidating factors that affect the disease cycle as a basis for disease modeling. The recent spread of Asian soybean rust to major production regions in the world has promoted new development, testing and application of mathematical models to assess the risk and predict the disease. These efforts have included the integration of new data, epidemiological knowledge, statistical methods, and advances in computer simulation to develop models and systems with different spatial and temporal scales, objectives and audience. In this review, we present a comprehensive discussion on the models and systems that have been tested to predict and assess the risk of Asian soybean rust. Limitations, uncertainties and challenges for modelers are also discussed.

MODELING A COMPUTER APPLICATION FOR MANAGEMENT OF MAINTENANCE ACTIVITIES OF UNPAVED ROADS

ABSTRACTThis study presents a contribution to the modeling of a computer application employing a method of serviceability performance for unpaved roads, aiming the management of maintenance/restoration activities of the primary surface layer. The proposed methodology consisted of field inspections during dry (April to September) and rainy (October to March) periods, during which objective evaluations were performed to survey of defects and their densities and degrees of severity. To aid the functional classification of analyzed road sections and the determination of the defect with major influence on the serviceability of these roads, the method of serviceability performance proposed by Silva (2009)was implemented in the Visual Basic for Applications (VBA) language in Microsoft Excel software. With the use of the computer application proposed it was possible to identify among the defects analyzed in field, through the index of serviceability of the sampling unit per defect type (ISUdef), which one had the greatest influence on determining the relative serviceability index per road section (IST). The results allow us to conclude that the computer application Road achieved satisfactory results, since the objective evaluation criteria applied to road sections denotes consistency regarding their serviceability.

Augmented reality systems for weed economic thresholds applications

The augmented reality (AR) technology has applications in many fields as diverse as aeronautics, tourism, medicine, and education. In this review are summarized the current status of AR and it is proposed a new application of it in weed science. The basic algorithmic elements for AR implementation are already available to develop applications in the area of weed economic thresholds. These include algorithms for image recognition to identify and quantify weeds by species and software for herbicide selection based on weed density. Likewise, all hardware necessary for AR implementation in weed science are available at an affordable price for the user. Thus, the authors propose weed science can take a leading role integrating AR systems into weed economic thresholds software, thus, providing better opportunities for science and computer-based weed control decisions.

Measuring higher order optical aberrations of the human eye: techniques and applications

In the present paper we discuss the development of "wave-front", an instrument for determining the lower and higher optical aberrations of the human eye. We also discuss the advantages that such instrumentation and techniques might bring to the ophthalmology professional of the 21st century. By shining a small light spot on the retina of subjects and observing the light that is reflected back from within the eye, we are able to quantitatively determine the amount of lower order aberrations (astigmatism, myopia, hyperopia) and higher order aberrations (coma, spherical aberration, etc.). We have measured artificial eyes with calibrated ametropia ranging from +5 to -5 D, with and without 2 D astigmatism with axis at 45º and 90º. We used a device known as the Hartmann-Shack (HS) sensor, originally developed for measuring the optical aberrations of optical instruments and general refracting surfaces in astronomical telescopes. The HS sensor sends information to a computer software for decomposition of wave-front aberrations into a set of Zernike polynomials. These polynomials have special mathematical properties and are more suitable in this case than the traditional Seidel polynomials. We have demonstrated that this technique is more precise than conventional autorefraction, with a root mean square error (RMSE) of less than 0.1 µm for a 4-mm diameter pupil. In terms of dioptric power this represents an RMSE error of less than 0.04 D and 5º for the axis. This precision is sufficient for customized corneal ablations, among other applications.

Applications of artificial intelligence to condition-based maintenance

In this paper we discuss interesting developments of expert systems for machine diagnosis and condition-based maintenance. We review some elements of condition-based maintenance and its applications, expert systems for machine diagnosis, and an example of machine diagnosis. In the last section we note some problems to be resolved so that expert systems for machine diagnosis may gain wider acceptance in the future.