Bosques urbanos de guadua en Pereira. Potencial para la conformación de Núcleos Forestales Productivos

A causa de la constante expansión urbana y la escasa planificación en el crecimiento de la ciudad, los Bosques urbanos de Guadua Angustifolia Kunth (Guadua) han ido desapareciendo poco a poco del paisaje de Pereira, viéndose relegados a zonas de difícil acceso no aptas para construir, a pesar de este hecho es evidente la presión a la que son sometidos constantemente sin existir herramientas administrativas que permitan su adecuado manejo y gestión para garantizar su conservación. Hasta hoy se puede evidenciar una dinámica urbana expansiva donde se heredan los procesos del pasado que no han sido planificados. (Salazar M. 2017). La especie de bambú Guadua es un elemento fundamental en el paisaje de la zona urbana del municipio de Pereira; la mayoría de estos bosques urbanos de Guadua de acuerdo al POT (Alcaldía de Pereira, 2016) se encuentran localizadas en las zonas forestales protectoras de caños, quebradas y ríos; estos bosques urbanos de Guadua, prestan servicios ecosistémicos que son fundamentales en la conservación y protección de cuencas hidrográficas, realizando la regulación de caudales. Los bosques de Guadua localizados en la región del Eje Cafetero de Colombia, entre los 900 y los 2000 msnm (metros sobre el nivel del mar), cumplen funciones ecológicas importantes como la protección del suelo, refugio para la biodiversidad y secuestro de carbono (Arango A et al, 2010)

Spectrum Sensing Framework based on Blind Source Separation for Cognitive Radio Environments

El uso eficiente del espectro se ha convertido en un área de investigación activa, debido a la escasez de este recurso y a su subutilización. En un escenario en el que el espectro es un recurso compartido como en la radio cognitiva (CR), los espacios sin uso dentro de las bandas de frecuencias con licencia podrían ser detectados y posteriormente utilizados por un usuario secundario a través de técnicas de detección y sensado del espectro. Generalmente, estas técnicas de detección se utilizan a partir de un conocimiento previo de las características de canal. En el presente trabajo se propone un enfoque de detección ciega del espectro basado en análisis de componentes independientes (ICA) y análisis de espectro singular (SSA). La técnica de detección se valida a través de simulación, y su desempeño se compara con metodologías propuestas por otros autores en la literatura. Los resultados muestran que el sistema propuesto es capaz de detectar la mayoría de las fuentes con bajo consumo de tiempo, un aspecto que cabe resaltar para aplicaciones en línea con exigencias de tiempo.The efficient use of spectrum has become an active research area, due to its scarcity and underutilization. In a spectrum sharing scenario as Cognitive Radio (CR), the vacancy of licensed frequency bands could be detected by a secondary user through spectrum sensing techniques. Usually, this sensing approaches are performed with a priori knowledge of the channel features. In the present work, a blind spectrum sensing approach based on Independent Component Analysis and Singular Spectrum Analysis is proposed. The approach is tested and compared with other outcomes. Results show that the proposed scheme is capable of detect most of the sources with low time consumption, which is a remarkable aspect for online applications with demanding time issues

Analysis of complexity and modulation spectra parameterizations to characterize voice roughness

Disordered voices are frequently assessed by speech pathologists using acoustic perceptual evaluations. This might lead to problems due to the subjective nature of the process and due to the in uence of external factors which compromise the quality of the assessment. In order to increase the reliability of the evaluations the design of new indicator parameters obtained from voice signal processing is desirable. With that in mind, this paper presents an automatic evaluation system which emulates perceptual assessments of the roughness level in human voice. Two parameterization methods are used: complexity, which has already been used successfully in previous works, and modulation spectra. For the latter, a new group of parameters has been proposed as Low Modulation Ratio (LMR), Contrast (MSW) and Homogeneity (MSH). The tested methodology also employs PCA and LDA to reduce the dimensionality of the feature space, and GMM classiffers for evaluating the ability of the proposed features on distinguishing the different roughness levels. An effciency of 82% and a Cohen's Kappa Index of 0:73 is obtained using the modulation spectra parameters, while the complexity parameters performed 73% and 0:58 respectively. The obtained results indicate the usefulness of the proposed modulation spectra features for the automatic evaluation of voice roughness which can derive in new parameters to be useful for clinicians

GPU Acceleration and Game Engines for Wireless Channel Estimation in Millimeter Waves

In this article, the intended purpose is to show an innovative technique for estimating the MIMO channel at millimeter wave bands, candidates for mobile 5G technology, by using hardware acceleration, game engines and heuristic algorithms applied to optical ray launching techniques. To verify the performance of the ray launching tool, the normalized Power Delay Profile (PDP) was simulated. The channel was analyzed using the mean square delay error (RMS), the average value of the delay (MD) and the basic propagation loss (PL). The results obtained in computational precision and time were compared with those of a traditional ray tracing tool simulation programmed in MATLAB and with the measurements made in the 57 to 66 GHz range in a specialized laboratory. The results show that the presented technique becomes efficiently profitable from a small number of simulated events (reflections, diffractions).This work was supported by the Vicerrectoría de Investigación of the Universidad del Magdalena by FONCIENCIAS 2018 announcement. This research was funded by COLCIENCIAS GRANT, grant number 528/2012

Non uniform embedding based on relevance analysis with reduced computational complexity: application to the detection of pathologies from biosignal recordings

Nonlinear analysis tools for studying and characterizing the dynamics of physiological signals have gained popularity, mainly because tracking sudden alterations of the inherent complexity of biological processes might be an indicator of altered physiological states. Typically, in order to perform an analysis with such tools, the physiological variables that describe the biological process under study are used to reconstruct the underlying dynamics of the biological processes. For that goal, a procedure called time-delay or uniform embedding is usually employed. Nonetheless, there is evidence of its inability for dealing with non-stationary signals, as those recorded from many physiological processes. To handle with such a drawback, this paper evaluates the utility of non-conventional time series reconstruction procedures based on non uniform embedding, applying them to automatic pattern recognition tasks. The paper compares a state of the art non uniform approach with a novel scheme which fuses embedding and feature selection at once, searching for better reconstructions of the dynamics of the system. Moreover, results are also compared with two classic uniform embedding techniques. Thus, the goal is comparing uniform and non uniform reconstruction techniques, including the one proposed in this work, for pattern recognition in biomedical signal processing tasks. Once the state space is reconstructed, the scheme followed characterizes with three classic nonlinear dynamic features (Largest Lyapunov Exponent, Correlation Dimension and Recurrence Period Density Entropy), while classification is carried out by means of a simple k-nn classifier. In order to test its generalization capabilities, the approach was tested with three different physiological databases (Speech Pathologies, Epilepsy and Heart Murmurs). In terms of the accuracy obtained to automatically detect the presence of pathologies, and for the three types of biosignals analyzed, the non uniform techniques used in this work lightly outperformed the results obtained using the uniform methods, suggesting their usefulness to characterize non-stationary biomedical signals in pattern recognition applications. On the other hand, in view of the results obtained and its low computational load, the proposed technique suggests its applicability for the applications under study

Analysis of the influence of signal compression techniques for voice disorder detection through filter-banked based features

En este artículo se comparan los resultados de utilizar señales de voz comprimidas frente a señales de voz sin comprimir para detectar de forma automática anomalías vocales. Las técnicas de codificación y compresión de voz usadas en este estudio son las mismas que se utilizan de forma estándar en los sistemas de telefonía fija, móvil e IP, y las técnicas de caracterización y clasificación usadas también están dentro de las más utilizadas para la detección automática de anomalías de voz. Los resultados obtenidos permiten concluir que es posible utilizar señales de voz comprimidas para detección automática de patologías vocales sin detrimento en el porcentaje de acierto en el diagnóstico, lo que haría posible la implementación de sistemas de telediagnóstico automático de patologías vocales.This paper compares the results of using compressed voice signals versus uncompressed speech signals to automatically detect voice abnormalities. Coding techniques and voice compression used in this study are the same as those used by default in the fixed, mobile and ip telephony systems, and techniques of characterization and classification used are also among the most used for detecting automatic speech abnormalities. The results obtained indicate that it is possible to use compressed voice signals for automatic detection of vocal pathologies without compromising the success rate in the diagnosis, which would make the implementation of automatic remote diagnosis of vocal pathologies possible

The Use of Hydrodynamic Models in the Determination of the Chart Datum Shape in a Tropical Estuary

Estuaries are transitional environments with ideal conditions for port construction and navigation. They represent a challenge to hydrographic services due to the dynamics of the seabed and the tidal wave deformation. The bottom slope, the convergence of the channels, and the nonlinear efects produced by the bottom friction produce variation in both the tidal range and the location of the chart datum (CD). In this study, sea level data series obtained from the nodes of the mesh of a hydrodynamic model (virtual tide gauges) were used to calculate the harmonic constituents, form factor, asymmetry, and estuary type. The final chart datum surface, obtained from the hydrodynamic model, was used to determine the separation values between zones and also the number of tidal zones in an estuarine system. It was found that in a complex hydrodynamics scenario, the use of the ellipsoidal referenced surveying (ERS) method is more convenient than traditional tidal zoning survey. In the ERS method, once the CD model is complete, it must be attached to the ellipsoid directly. Finally, the variation of the CD in di erent scenarios (due to anthropogenic action) was assessed

Automatic age detection in normal and pathological voice

Systems that automatically detect voice pathologies are usually trained with recordings belonging to population of all ages. However such an approach might be inadequate because of the acoustic variations in the voice caused by the natural aging process. In top of that, elder voices present some perturbations in quality similar to those related to voice disorders, which make the detection of pathologies more troublesome. With this in mind, the study of methodologies which automatically incorporate information about speakers’ age, aiming at a simplification in the detection of voice disorders is of interest. In this respect, the present paper introduces an age detector trained with normal and pathological voice, constituting a first step towards the study of age-dependent pathology detectors. The proposed system employs sustained vowels of the Saarbrucken database from which two age groups are examinated: adults and elders. Mel frequency cepstral coefficients for characterization, and Gaussian mixture models for classification are utilized. In addition, fusion of vowels at score level is considered to improve detection performance. Results suggest that age might be effectively recognized using normal and pathological voices when using sustained vowels as acoustical material, opening up possibilities for the design of automatic age-dependent voice pathology detection systems

A Novel Tool to Assess Basic Activities of Daily Living in Spanish Preschoolers

Background: Basic activities of daily living (BADLs) are those related to self-care. Their performance depends on the development of sensorimotor and cognitive skills, as well as social and environmental aspects. A good performance in BADLs is required for independence and social participation, so they play an important role in early education and early care. We aim to create a tool for BADLs assessment for Spanish preschoolers. Methods: The tool was administered to 303 participants (48.5% boys and 51.5% girls) between three and six years of age. Analyses to find out the factorial structure and internal consistency was carried out. Results: The instrument was composed of 84 items in four scales (eating, personal hygiene, dressing, and daily functioning) with nine factors (oral sensitivity, good manners, manual dexterity, brushing teeth, toilet management, hygiene and grooming, dressing, higher-order and core executive function). Reliability values were from acceptable to preferred (0.74–0.94). Conclusions: The instrument could be useful and shows preliminary good indicators in construct validity and reliability.Occupational Therapy Association of Extremadura (Colegio Profesional de Terapeutas Ocupacionales de Extremadura

Análisis de la influencia de las técnicas de compresión de voz en la detección de anomalías vocales

This paper compares the results of using compressed voice signals versus uncompressed speech signals to automatically detect voice abnormalities. Coding techniques and voice compression used in this study are the same as those used by default in the fixed, mobile and ip telephony systems, and techniques of characterization and classification used are also among the most used for detecting automatic speech abnormalities. The results obtained indicate that it is possible to use compressed voice signals for automatic detection of vocal pathologies without compromising the success rate in the diagnosis, which would make the implementation of automatic remote diagnosis of vocal pathologies possible.En este artículo se comparan los resultados de utilizar señales de voz comprimidas frente a señales de voz sin comprimir para detectar de forma automática anomalías vocales. Las técnicas de codificación y compresión de voz usadas en este estudio son las mismas que se utilizan de forma estándar en los sistemas de telefonía fija, móvil e IP, y las técnicas de caracterización y clasificación usadas también están dentro de las más utilizadas para la detección automática de anomalías de voz. Los resultados obtenidos permiten concluir que es posible utilizar señales de voz comprimidas para detección automática de patologías vocales sin detrimento en el porcentaje de acierto en el diagnóstico, lo que haría posible la implementación de sistemas de telediagnóstico automático de patologías vocales