Collaborative Geographic Information Systems for Business Intelligence

This paper shows a number of sceneries where information (specifically, geographical-related information) is lost because there is no method for storing or sharing it. This research has been done with the aim to solve those scenery problems in a general way, by means of a geographical information system that can store geographical-related information and publish it in order to avoid loss of information and enabling geographical information sharin

Acquiring plant features with optical sensing devices in an organic strip-cropping system

There is an increasing market for organic agriculture (Golijan & Popovi\vs, 2016). However, the lack of attention for biodiversity and soil fertility of current practices is a pressing issue. The SUREVEG project (CORE Organic Cofund, 2018) therefore looks at strip-cropping in organic production and its implementation in intensive farming to improve soil fertility and biodiversity throughout Europe. The aim is to enhance resilience (Wojtkowski, 2008), system sustainability, local nutrient recycling, and soil carbon storage (Wang, Li & Alva, 2010) among others. To counteract the additional labour of a multi-crop system, a robotic tool is proposed, which will operate upside down suspended from a wide-span mobile carriage. Within the project framework, a modular proof-of-concept (POC) version will be produced, combining sensing technologies with actuation in the form of a robotic arm. This POC will focus on fertilization needs, which are to be identified in real-time at the single-plant scale

La reforma a la acción de tutela contra providencias judiciales

En el primer semestre de 2006, en el marco del segundo período de la legislatura 2005-2006, la Honorable Representante Gina María Parody organizó en las instalaciones del Congreso de la República un debate sobre la noción y el alcance de la Acción de Tutela respecto a providencias judiciales, tema de gran discusión por parte de diferentes sectores del Gobierno Nacional así como de las Altas Cortes, la Academia y la Doctrina en general. En ese orden de ideas, la Facultad de Jurisprudencia y la Decanatura del Medio Universitario de la Universidad del Rosario, a través de su Observatorio Legislativo y de Opinión, solicitaron a algunos docentes su opinión sobre el referido tema de amplia polémica, con el fin de presentar al público en general argumentos que sustenten las múltiples posturas que al respecto existen. Así las cosas, en el presente documento encontrarán recogidos los comentarios preliminares y generales de la posición sobre el tema en debate emitida por los doctores José Roberto Herrera, Manuel Fernando Quinche y Juan Enrique Medina, docentes de la Facultad de Jurisprudencia. El objetivo de esta publicación no es otro que el de brindar herramientas para adelantar este debate que cotidianamente se surte sobre este tema en diferentes escenarios de la vida nacional, y servir de sustento para el trabajo de aquellos que en adelante le den vida a éste tema al interior del Congreso, quizá de manera concreta en la realización de una iniciativa legislativa, como recientemente se ha anunciado

Detección de características de cultivo a través de sensores ópticos en un sistema orgánico de tipo strip-cropping

Hay un mercado creciente para la agricultura orgánica. Sin embargo, la falta de atención a la biodiversidad y la fertilidad del suelo de las prácticas actuales es un tema urgente. En este contexto, el proyecto SUREVEG analiza el cultivo en franjas en la producción orgánica y su implementación en cultivos intensivos para mejorar la fertilidad del suelo y la biodiversidad en toda Europa. Para contrarrestar la mano de obra adicional de un sistema de cultivos múltiples, se propone una herramienta robótica. Dentro del marco del proyecto, se producirá una versión modular de prueba de concepto (POC) que combinará tecnologías de detección con la actuación en forma de un brazo robótico. Este sistema POC se centrará en las necesidades de fertilización, que se identificarán en tiempo real y se aplicarán en una sola planta. Este artículo se centra en la captación de las características del cultivo mediante nubes de puntos obtenidas con dos lidares y en su procesamiento

Acquiring plant features with optical sensing devices in an organic strip-cropping system

The SUREVEG project focuses on improvement of biodiversity and soil fertility in organic agriculture through strip-cropping systems. To counter the additional workforce a robotic tool is proposed. Within the project, a modular proof of concept (POC) version will be produced that will combine detection technologies with actuation on a single-plant level in the form of a robotic arm. This article focuses on the detection of crop characteristics through point clouds obtained with two lidars. Segregation in soil and plants was successfully achieved without the use of additional data from other sensor types, by calculating weighted sums, resulting in a dynamically obtained threshold criterion. This method was able to extract the vegetation from the point cloud in strips with varying vegetation coverage and sizes. The resulting vegetation clouds were compared to drone imagery, to prove they perfectly matched all green areas in said image. By dividing the remaining clouds of overlapping plants by means of the nominal planting distance, the number of plants, their volumes, and thereby the expected yields per row could be determined.</p

Automobile indexation from 3D point clouds of urban scenarios

In this paper, we introduce a methodology for the detection and segmentation of automobiles in urban scenarios. We use the LiDAR Velodyne HDL-64E to scan the surroundings. The method is comprised of three steps: (1) remove facades, ground plan, and unstructured objects, (2) smoothing data using robust principal component analysis (RPCA), and finally, (3) unstructured objects model and indexing. The dataset is partitioned into training with 4500 objects and test with 3000 objects. Mean Shift thresholds, the filter, the Delaunay parameters, and the histogram modelling are optimized via ROC analysis. It is observed that the car scan quality affects our method to a lesser degree when compared with state-of-the-art methods

Design of haptic vibrational feedback control in upper extremity myoelectric prostheses

Current prosthesis systems use haptic technology, have a brain-machine interaction that is dependent on visual feedback from the user, also have limitations by the details of the sense of touch both textures, roughness, weights, and contact forces applied. This research shows the development and implementation of haptic technology in a myoelectric prosthesis of the upper extremity, to simulate the sense of touch in the claw of the prosthesis to obtain a better control in the grip force taking as parameter the reaction and efficiency that the device has in different conditions for the patient to have an improvement in the feedback and the grip force of the prosthesis. For the development of the investigation, the VDI2206 methodology was used, simulating each part of the myoelectric prosthesis in different software for an improvement in the process of signal interpretation. Also by diagramming the motor execution process it facilitates the interpretation of the design. The results of the investigation show an alternative model of the conventional ones contributing with improvements in the signals received by the haptic prosthesis and better ergonomics, in addition, the perceived signals showed a better subjection and sensitivity. From the presented design it is desired to replicate to future research since the presented model can be taken as research material

Gaussianization of LA-ICP-MS features to improve calibration in forensic glass comparison

The forensic comparison of glass aims to compare a glass sample of an unknown source with a control glass sample of a known source. In this work, we use multi-elemental features from Laser Ablation Inductively Coupled Plasma with Mass Spectrometry (LA-ICP-MS) to compute a likelihood ratio. This calculation is a complex procedure that generally requires a probabilistic model including the within-source and betweensource variabilities of the features. Assuming the within-source variability to be normally distributed is a practical premise with the available data. However, the between-source variability is generally assumed to follow a much more complex distribution, typically described with a kernel density function. In this work, instead of modeling distributions with complex densities, we propose the use of simpler models and the introduction of a data pre-processing step consisting on the Gaussianization of the glass features. In this context, to obtain a better fit of the features with the Gaussian model assumptions, we explore the use of different normalization techniques of the LA-ICP-MS glass features, namely marginal Gaussianization based on histogram matching, marginal Gaussianization based on Yeo-Johnson transformation and a more complex joint Gaussianization using normalizing flows. We report an improvement in the performance of the Likelihood Ratios computed with the previously Gaussianized feature vectors, particularly relevant in their calibration, which implies a more reliable forensic glass comparisonThis work has been supported by the Spanish Ministerio de Ciencia e Innovación through grant PID2021-125943OB-I0