A linear model to predict with a multi‐spectral radiometer the amount of nitrogen in winter wheat

The objective was to develop an optimal vegetation index (VI_opt) to predict with a multi‐spectral radiometer nitrogen in wheat crop (kg[N] ha^?1). Optimality means that nitrogen in the crop can be measured accurately in the field during the growing season. It also means that the measurements are stable under changing light conditions and vibrations of the measurement platform. Different fields, on which various nitrogen application rates and seeding densities were applied in experimental plots, were measured optically during the growing season. These measurements were performed over three years. Optical measurements on eight dates were related to calibration measurements of nitrogen in the crop (kg[N] ha^?1) as measured in the laboratory. By making combinations of the wavelength bands, and whether or not the soil factor was taken into account, numerous vegetation indices (VIs) were examined for their accuracy in predicting nitrogen in wheat. The effect of changing light conditions in the field and vibrations of the measurement platform on the VIs were determined based on tests in the field. VI_opt ((1+L)?(R ² _NIR+1)/(R _red+L) with L = 0.45), the optimal vegetation index found, was best in predicting nitrogen in grain crop. The root mean squared error (RMSE), determined by means of cross‐validation, was 16.7 kg[N] ha^?1. The RMSE was significantly lower compared to other frequently used VIs such as NDVI, RVI, DVI, and SAVI. The L‐value can change between 0.16 and 1.6 without deteriorating the RMSE of prediction. Besides being the best predictor for nitrogen, VI_opt had the advantage of being a stable vegetation index under circumstances of changing light conditions and platform vibrations. In addition, VI_opt also had a simple structure of physically meaningful bands.     

CR1Dinv: A Matlab program to invert 1D spectral induced polarization data for the Cole–Cole model including electromagnetic effects

An inversion code has been constructed using Matlab, to recover 1D parameters of the Cole–Cole model from spectral induced polarization data. In a spectral induced polarization survey, impedances are recorded at various frequencies. Both induced polarization and electromagnetic coupling effects occur simultaneously over the experimental frequency bandwidth, and these become progressively more dominant when the frequency increases. We used the CR1Dmod code published by Ingeman-Nielsen and Baumgartner [2006]. This code solves for electromagnetic responses, in the presence of complex resistivity effects in a 1D Earth. In this paper, a homotopy method has been designed by the authors to overcome the local convergence problem of normal iterative methods. In addition, in order to further condition the inverse problem, we incorporated standard Gauss–Newton (or quasi-Newton) methods. Graphical user interfaces enable straightforward entering of the data and the a priori model, as well as the cable configuration. Two synthetic examples are presented, showing that the spectral parameters can be recovered from multifrequency, complex resistivity data.     

Egocentric interaction as a tool for designing ambient ecologies—The case of the easy ADL ecology

The visions of ambient intelligence demand novel interaction paradigms that enable designers and system developers to frame and manage the dynamic and complex interaction between humans and environments populated with physical (real) and virtual (digital) objects of interest. So far, many proposed approaches have adhered to a device-centric stance when including virtual objects into the ambient ecology; a stance inherited from existing interaction paradigms for mobile and stationary interactive devices. In this article, we introduce egocentric interaction as an alternative approach, taking the human agent’s body and mind as the center of reference. We show how this interaction paradigm has influenced both the conception and implementation of the easy ADL ecology, comprising of smart objects, a personal activity-centric middleware attempting to simplify interaction given available resources, ambient intelligence applications aimed at everyday activity support, and a human agent literally in the middle of it all.     

An agrometeorological–spectral model to estimate soybean yield,applied to southern Brazil

Soybean yield is modelled from data gathered from crops in Rio Grande do Sul State, Brazil. The model comprises an agrometeorological term, obtained by adjusting the multiplicative model of Jensen, modified by Berlato, and a spectral term, obtained from National Oceanic and Atmospheric Administration (NOAA) satellite images of the maximum Normalized Difference Vegetation Index (NDVI). The weather data used to calculate the relative evapotranspiration (ET _r /ET ₀) cover the period from 1975 to 2000, and the NDVI/NOAA images were obtained from 1982 to 2000. Application of the agrometeorological–spectral model produced better yield estimates (of about 5%) than Jensen's model, allowing the further generation of yield maps for the most significant soybean production regions within the Rio Grande do Sul State.     

A Scheil–Gulliver model dedicated to the solidification of steel

Modelling of solidification is of industrial and theoretical relevance. An accurate estimation of the actual liquidus and solidus temperatures leads to significant improvements in quality and efficiency of steel production as well as substantially reduces the energy consumption and the ecological footprint.An optimisation of the Scheil–Gulliver model for solidification with the aim to predict the solidus temperature of steels (Scheil–Gulliver for Steel, SGS) is presented. The SGS model allows an easy and accurate simulation of the solidification interval using software based on the CALPHAD approach. Based only on the steel composition, the model consistently choses between full equilibrium for ferrite and partial redistribution of alloying elements (Scheil–Gulliver approach) for austenite. The predictions of the model were compared to differential thermal analysis (DTA) measurements of industrial heats, which represent a wide range of compositions. The agreement of the data calculated with the SGS model with the values measured by DTA represents an improvement compared to existing models.     

Visual perception of noise in a simulated holographic display—A user study

This work explores ways to bypass the fundamental image quality limitations of displays using Computer Generated Holograms (CGHs) and, specifically, the high-frequency noise associated with phase-only holograms. Although there is a wealth of literature on building experimental holographic systems, there are no user studies to assess the performance of a holographic system projecting a dynamic two-dimensional image. In this study, 18 participants blindly compared three groups of images displayed on a conventional monitor. The first group contained the original image, the second the simulated holographic reconstruction of the original image, and the third group had the foveated reconstruction of the original image, based on the pupil position. Holograms in the second group were computed using the Fienup algorithm and the third group using the Fienup with Perceptual Don’t Care Areas (FiPDoC) algorithm, a novel algorithm that uses eye tracking to optimize image quality in CGHs. The aim of the study was to find out if the holographic display, assuming an ideal hardware, can be as good as a conventional display and whether eye tracking can help this goal. Most participants distinguished between the original image and the un-foveated simulated reconstruction. However, the participants could not differentiate between the original image and the foveated reconstruction. Thus, foveation may be essential in designing and building the first commercial holographic displays.     

Grenade Explosion Method—A novel tool for optimization of multimodal functions

This work presents a new optimization technique called Grenade Explosion Method (GEM). The fundamental concepts and ideas which underlie the method are fully explained. It is seen that this simple and robust algorithm is quite powerful in finding all global and some local optima of multimodal functions. The method is tested with several multimodal benchmark functions and the results show it usually converges to the global minima faster than other evolutionary methods such as Genetic Algorithm (GA) and Artificial Bee Colony (ABC). Based on the performance on classical benchmark functions, the efficiency of the method in solving engineering applications can be highly appreciated.     

Machine learning: A tool to support usability?

One problem facing designers of interactive systems is catering to the wide range of users who will use a particular application. Understanding the user is critical to designing a usable interface. There are a number of ways of addressing this problem, including improved design methodologies using ''intuitive'' interface styles, adaptive interfaces, and better training and user support materials. In this article, we argue that each of these solutions involves pattern recognition in one form or another and that machine learning can therefore aid designers of interactive systems in these areas. We report on experiments that demonstrate the potential of machine learning to user modeling that has application to two of these areas in particular: adaptive systems and design methodologies.     

A simple geometrical model for analysing the spectral response of a citrus canopy using satellite images †

Abstract

A simple geometrical model has been proposed for a citrus canopy. We assume the citrus orchard to be a lattice structure, with the trees positioned at its points and where the composite-scene reflectance is the sum of the reflectance of its individual components as weighted by their respective surfaces within a unit area. The model has been used to analyse the citrus spectral response obtained from Landsat-5 TM images for winter and summer, where the status of the orchard is different. The correlations between spectral and geometrical data show the influence of per cent crop cover, shadows and background in the composite scene reflectance. We conclude that the summer images could be more useful than the winter ones for parcel classification according to per cent crop cover.     

Further applications of the non-stationary operational calculus to the synthesis of closed-loop distributed systems A new approach to distributed white noise†

By using a differential polynomial algebra one can obtain a new definition for the distributed transfer functions of distributed systems which apply even when these latter are governed by partial differential equations with space-varying coefficients. We so have a new ‘ system approach ’ to distributed systems, which provides synthesis methods similar to that of Guillemin and Truxal's.

Further extensions of this approach are considered here. After a brief background on previous results by the author, and the statement of new theoretical complements, time sampled-data distributed systems are examined and their digital compensation is solved. Then it is shown that the approach holds also for space sampled-data systems by using the algebra of finite-difference polynomials. A new model is proposed for ditributed noises; it is a compromise between the models of the engineering literature and those of mathematicians, and by using the distributed transfer function above it provides an extension of some results of Wiener's theory. Illustrative examples are given.     

Summary SQL — A fuzzy tool for data mining

The increasing use of computers for transactions and communication have created mountains of data that contain potentially valuable knowledge. To search for this knowledge we have to develop a new generation of tools, which have the ability of flexible querying and intelligent searching. In this paper we will introduce an extension of a fuzzy query language called Summary SQL which can be used for knowledge discovery and data mining. We show how it can be used to search for fuzzy rules.     

GRDM—A digital field-mapping tool for management and analysis of field geological data

Field geological observations have both spatial and non-spatial aspects and recording them directly on a personal computer using a digital mapping tool has become a practical and effective alternative to traditional methods of field data collection and mapping. This paper presents the design of a cost-effective, stand-alone digital field-mapping tool named GRDM that caters to special requirements of field-based studies concerned with spatial disposition of the statistics of field measurements. Such studies require recording multiple observations for individual attributes at each field location to capture the inter-site variability and automatic computation of their statistics. Field observations include directional data that are circular in nature. Therefore, computation of their exclusive statistics within the field system is also necessary. To meet these requirements, GRDM was designed for field personnel lacking expertise in customizing a GIS. Its design automatically accommodates a list of values for each non-spatial attribute attached to individual location points and generates statistics from the lists. The system treats the orientation values as a distinct numeric data type and computes circular statistics for them. It makes both the original data as well as their statistics simultaneously available for extraction of thematic information.     

Active spline model: A shape based model—interactive segmentation

We propose to formulate point distribution model in terms of centripetal-parameterized Catmull–Rom spline, so that the model-based segmentation is augmented to permit quick edit, and the consequent shape is independent of scale. We train the model in a fashion similar to active shape model, but with fewer salient/landmark points. We use gradient vector flow field as the external force field to drive the segmentation, but we did not adopt the procedures panned out by Cootes et al. to update a shape. Instead, we transform the shape back and forth between model scale and image scale to get the shape converged to the object of interest. To test the method, we turned the solution into an automated algorithm to segment lung on chest radiographs, and achieved an average overlap of 0.879. With edit, the average overlap increased to 0.945, with a minimum of 0.925. The method can be applied on a variety of images, as illustrated in Appendix C. The source code of the algorithm and the demo video can be located at http://jenh.co/2014/01/09/active-spline-models/.     

A non-parametric visual-sense model of images—extending the cluster hypothesis beyond text

The main challenge of a search engine is to find information that are relevant and appropriate. However, this can become difficult when queries are issued using ambiguous words. Rijsbergen first hypothesized a clustering approach for web pages wherein closely associated pages are treated as a semantic group with the same relevance to the query (Rijsbergen 1979). In this paper, we extend Rijsbergen’s cluster hypothesis to multimedia content such as images. Given a user query, the polysemy in the return image set is related to the many possible meanings of the query. We develop a method to cluster the polysemous images into their semantic categories. The resulting clusters can be seen as the visual senses of the query, which collectively embody the visual interpretations of the query. At the heart of our method is a non-parametric Bayesian approach that exploits the complementary text and visual information of images for semantic clustering. Latent structures of polysemous images are mined using the Hierarchical Dirichlet Process (HDP). HDP is a non-parametric Bayesian model that represents images using a mixture of components. The main advantage of our model is that the number of mixture components is not fixed a priori, but is determined during the posterior inference process. This allows our model to grow with the level of polysemy (and visual diversity) of images. The same set of components is used to model all images, with only the mixture weights varying amongst images. Evaluation results on a large collection of web images show the efficacy of our approach.     

MASAS—A user-friendly simulation tool for modeling the fate of anthropogenic substances in lakes

MASAS is a computer simulation tool to investigate anthropogenic organic compounds in lakes. Models included are based on a dynamic one-dimensional vertical lake model describing the time-dependent concentration of a compound in the water column and in the sediment. Provision of data is ensured by library files. Interactive specification of transport and transformation processes yields models of different complexity, suitable for the initial assessment of chemicals and for chemodynamic studies. A hypothetical spill of an insecticide (disulfoton) serves as an illustration. Aspects relevant to the development of user-friendly software in the environmental sciences are discussed. User-friendliness is found to depend more on program concepts than on a particular user interface. The management of data sets on lakes and compounds, and the implementation of transport and transformation processes in MASAS exemplify the significance of modularization, program data structures, the use of metaphors, and the distinction between automatic and user-controlled program functions.