Real-time image processing for crop/weed discrimination in maize fields

This paper presents a computer vision system that successfully discriminates between weed patches and crop rows under uncontrolled lighting in real-time. The system consists of two independent subsystems, a fast image processing delivering results in real-time (Fast Image Processing, FIP), and a slower and more accurate processing (Robust Crop Row Detection, RCRD) that is used to correct the first subsystem's mistakes. This combination produces a system that achieves very good results under a wide variety of conditions. Tested on several maize videos taken of different fields and during different years, the system successfully detects an average of 95% of weeds and 80% of crops under different illumination, soil humidity and weed/crop growth conditions. Moreover, the system has been shown to produce acceptable results even under very difficult conditions, such as in the presence of dramatic sowing errors or abrupt camera movements. The computer vision system has been developed for integration into a treatment system because the ideal setup for any weed sprayer system would include a tool that could provide information on the weeds and crops present at each point in real-time, while the tractor mounting the spraying bar is moving

Validation of microsatellite markers for cytotype discrimination in the model grass Brachypodium distachyon

Brachypodium distachyon (2n = 2x = 10) is a small annual grass species where the existence of three different cytotypes (10, 20 and 30 chromosomes) has long been regarded as a case of autopolyploid series, with x = 5. However, it has been demonstrated that the cytotypes assumed to be polyploids represent two separate Brachypodium species recently named as B. stacei (2n = 2x = 20) and B. hybridum (2n = 4x = 30). The aim of this study was to find a PCR-based alternative approach that could replace standard cytotyping methods (i. e., chromosome counting and flow cytometry) to characterize each of the three Brachypodium species. We have analyzed with four microsatellite (SSR) markers eighty-three Brachypodium distachyon-type lines from varied locations in Spain, including the Balearic and Canary Islands. Within this set of lines, 64, 4 and 15 had 10, 20 and 30 chromosomes, respectively. The surveyed markers produced cytotype-specific SSR profiles. So, a single amplification product was generated in the diploid samples, with non-overlapping allelic ranges between the 2n = 10 and 2n = 20 cytotypes, whereas two bands, one in the size range of each of the diploid cytotypes, were amplified in the 2n = 30 lines. Furthermore, the remarkable size difference obtained with the SSR ALB165 allowed the identification of the Brachypodium species by simple agarose gel electrophoresis.

Time-Frequency based Feature Selection for Discrimination of non stationary Biosignals.

This research proposes a generic methodology for dimensionality reduction upon time-frequency representations applied to the classification of different types of biosignals. The methodology directly deals with the highly redundant and irrelevant data contained in these representations, combining a first stage of irrelevant data removal by variable selection, with a second stage of redundancy reduction using methods based on linear transformations. The study addresses two techniques that provided a similar performance: the first one is based on the selection of a set of the most relevant time?frequency points, whereas the second one selects the most relevant frequency bands. The first methodology needs a lower quantity of components, leading to a lower feature space; but the second improves the capture of the time-varying dynamics of the signal, and therefore provides a more stable performance. In order to evaluate the generalization capabilities of the methodology proposed it has been applied to two types of biosignals with different kinds of non-stationary behaviors: electroencephalographic and phonocardiographic biosignals. Even when these two databases contain samples with different degrees of complexity and a wide variety of characterizing patterns, the results demonstrate a good accuracy for the detection of pathologies, over 98%.The results open the possibility to extrapolate the methodology to the study of other biosignals.

Codificador de voz MIDI

El presente proyecto tiene el objetivo de facilitar la composición de canciones mediante la creación de las distintas pistas MIDI que la forman. Se implementan dos controladores. El primero, con objeto de transcribir la parte melódica, convierte la voz cantada o tarareada a eventos MIDI. Para ello, y tras el estudio de las distintas técnicas del cálculo del tono (pitch), se implementará una técnica con ciertas variaciones basada en la autocorrelación. También se profundiza en el segmentado de eventos, en particular, una técnica basada en el análisis de la derivada de la envolvente. El segundo, dedicado a la base rítmica de la canción, permite la creación de la percusión mediante el golpe rítmico de objetos que disponga el usuario, que serán asignados a los distintos elementos de percusión elegidos. Los resultados de la grabación de estos impactos serán señales de corta duración, no lineales y no armónicas, dificultando su discriminación. La herramienta elegida para la clasificación de los distintos patrones serán las redes neuronales artificiales (RNA). Se realizara un estudio de la metodología de diseño de redes neuronales especifico para este tipo de señales, evaluando la importancia de las variables de diseño como son el número de capas ocultas y neuronas en cada una de ellas, algoritmo de entrenamiento y funciones de activación. El estudio concluirá con la implementación de dos redes de diferente naturaleza. Una red de Elman, cuyas propiedades de memoria permiten la clasificación de patrones temporales, procesará las cualidades temporales analizando el ataque de su forma de onda. Una red de propagación hacia adelante feed-forward, que necesitará de robustas características espectrales y temporales para su clasificación. Se proponen 26 descriptores como los derivados de los momentos del espectro: centroide, curtosis y simetría, los coeficientes cepstrales de la escala de Mel (MFCCs), y algunos temporales como son la tasa de cruces por cero y el centroide de la envolvente temporal. Las capacidades de discriminación inter e intra clase de estas características serán evaluadas mediante un algoritmo de selección, habiéndose elegido RELIEF, un método basado en el algoritmo de los k vecinos mas próximos (KNN). Ambos controladores tendrán función de trabajar en tiempo real y offline, permitiendo tanto la composición de canciones, como su utilización como un instrumento más junto con mas músicos. ABSTRACT. The aim of this project is to make song composition easier by creating each MIDI track that builds it. Two controllers are implemented. In order to transcribe the melody, the first controler converts singing voice or humming into MIDI files. To do this a technique based on autocorrelation is implemented after having studied different pitch detection methods. Event segmentation has also been dealt with, to be more precise a technique based on the analysis of the signal's envelope and it's derivative have been used. The second one, can be used to make the song's rhythm . It allows the user, to create percussive patterns by hitting different objects of his environment. These recordings results in short duration, non-linear and non-harmonic signals. Which makes the classification process more complicated in the traditional way. The tools to used are the artificial neural networks (ANN). We will study the neural network design to deal with this kind of signals. The goal is to get a design methodology, paying attention to the variables involved, as the number of hidden layers and neurons in each, transfer functions and training algorithm. The study will end implementing two neural networks with different nature. Elman network, which has memory properties, is capable to recognize sequences of data and analyse the impact's waveform, precisely, the attack portion. A feed-forward network, needs strong spectral and temporal features extracted from the hit. Some descriptors are proposed as the derivates from the spectrum moment as centroid, kurtosis and skewness, the Mel-frequency cepstral coefficients, and some temporal features as the zero crossing rate (zcr) and the temporal envelope's centroid. Intra and inter class discrimination abilities of those descriptors will be weighted using the selection algorithm RELIEF, a Knn (K-nearest neighbor) based algorithm. Both MIDI controllers can be used to compose, or play with other musicians as it works on real-time and offline.

Discrimination of AE Signals From Friction and Concrete Cracking in a Reinforced Concrete Frame Subjected to Seismic Trainings

This paper shows the preliminary results of the development and application of a procedure to filter the Acoustic Emission (AE) signals to distinguish between AE signals coming from friction and AE signals coming from concrete cracking. These signals were recorded during the trainings of an experiment carried out on a reinforced concrete frame subjected to dynamic loadings with the shaking table of the University of Granada (Spain). Discrimination between friction and cracking AE signals is the base to develop a successful procedure and damage index based on AE testing for health monitoring of RC structures subjected to earthquakes.

Diseño de sistema de pitch pasivo para aerogeneradores en entornos urbanos

El presente proyecto desarrolla el diseño de un sistema de pitch pasivo para aerogeneradores en entornos urbanos en el marco del proyecto SWIP (Soluciones, componentes y herramientas novedosos e innovadores para la integración de la energía eólica en áreas urbanas y suburbanas) En primer lugar se describe el marco de trabajo así como una introducción teórica de energía eólica y de sistemas de pitch o de control de paso de pala. Aquí son presentados los fundamentos del accionamiento del pitch pasivo diseñado. A continuación se presenta el mecanismo diseñado y los cálculos sobre él efectuados para el ajuste de sus parámetros de funcionamiento. Posteriormente se plantea el análisis estructural de los distintos casos de carga a los que estará sometido y el estudio de su respuesta dinámica a perturbaciones reales con las que trabajará durante su funcionamiento normal. Por último, se aclaran otra serie de factores como la seguridad y el sobredimensionamiento del generador y se hace un análisis económico del diseño junto con una comparativa con las tecnologías alternativas existentes. ABSTRACT The present project develops the design of a passive pitch system for wind turbines for urban and sub-urban areas for the SWIP European Project (New innovative solutions, components and tools for the integration of wind energy in urban and peri-urban áreas) Firstly, the framework is described, as well as a theoretical introduction to wind energy and pitch systems. Here, the principles of the designed passive pitch mechanism are presented. Subsequently, the designed mechanism is presented together with the calculations on it for the adjustment of its working parameters. After that, the structural analyses for the different load cases that will affect the design are studied. Afterwards, the dynamic response of the system to real perturbations during its operation is studied. Finally, some concepts concerning security issues or oversizing of the electric generator are considered and an economic analysis is performed for the design and also to compare it with the alternative existing technologies.

Guiding functional connectivity estimation by structural connectivity in MEG: an application to discrimination of mild cognitive impaired conditions

Whole brain resting state connectivity is a promising biomarker that might help to obtain an early diagnosis in many neurological diseases, such as dementia. Inferring resting-state connectivity is often based on correlations, which are sensitive to indirect connections, leading to an inaccurate representation of the real backbone of the network. The precision matrix is a better representation for whole brain connectivity, as it considers only direct connections. The network structure can be estimated using the graphical lasso (GL), which achieves sparsity through l1-regularization on the precision matrix. In this paper, we propose a structural connectivity adaptive version of the GL, where weaker anatomical connections are represented as stronger penalties on the corre- sponding functional connections. We applied beamformer source reconstruction to the resting state MEG record- ings of 81 subjects, where 29 were healthy controls, 22 were single-domain amnestic Mild Cognitive Impaired (MCI), and 30 were multiple-domain amnestic MCI. An atlas-based anatomical parcellation of 66 regions was ob- tained for each subject, and time series were assigned to each of the regions. The fiber densities between the re- gions, obtained with deterministic tractography from diffusion-weighted MRI, were used to define the anatomical connectivity. Precision matrices were obtained with the region specific time series in five different frequency bands. We compared our method with the traditional GL and a functional adaptive version of the GL, in terms of log-likelihood and classification accuracies between the three groups. We conclude that introduc- ing an anatomical prior improves the expressivity of the model and, in most cases, leads to a better classification between groups.

The influence of antiferroelectric compounds on helical pitch of orthoconic W-1000 mixture

The influence of six antiferroelectric compounds on the helical pitch of mixture W-1000, which was reported as long pitch orthoconic antiferroelectric liquid crystalline mixture, was checked by spectrophotometry and polarimetry methods. The electro-optical properties for the mixture with the longest pitch were measured. An improvement in electro-optical response due to the long pitch is reported. The novelty in electro-optical properties is the good symmetry response.