ASHuR: Evaluation of the Relation Summary-Content Without Human Reference Using ROUGE

In written documents, the summary is a brief description of important aspects of a text. The degree of similarity between the summary and the content of a document provides reliability about the summary. Some efforts have been done in order to automate the evaluation of a summary. ROUGE metrics can automatically evaluate a summary, but it needs a model summary built by humans. The goal of this study is to find a quantitative relation between an article content and its summary using ROUGE tests without a model summary built by humans. This work proposes a method for automatic text summarization to evaluate a summary (ASHuR) based on extraction of sentences. ASHuR extracts the best sentences of an article based on the frequency of concepts, cue-words, title words, and sentence length. Extracted sentences constitute the essence of the article; these sentences construct the model summary. We performed two experiments to assess the reliability of ASHuR. The first experiment compared ASHuR against similar approaches based on sentences extraction; the experiment placed ASHuR in the first place in each applied test. The second experiment compared ASHuR against human-made summaries, which yielded a Pearson correlation value of 0.86. Assessments made to ASHuR show reliability to evaluate summaries written by users in collaborative sites (e.g. Wikipedia) or to review texts generated by students in online learning systems (e.g. Moodle)

GUMCARS: General User Model for Context-Aware Recommender Systems

Context-Aware Recommender Systems (CARS) are extensions of traditional recommender systems that use information about the context of the user to improve the recommendation accuracy. Whatever the specific algorithm exploited by the CARS, it can provide high-quality recommendations only after having modeled the user and context aspects. Despite the importance of the data models in CARS, nowadays there is a lack of models and tools to support the modeling and management of the data when developing a new CARS, leaving designers, developers and researchers the work of creating their own models, which can be a hard and time-consuming labor, and often resulting in overspecialized or incomplete models. In this paper, we describe GUMCARS - a General User Model for Context-Aware Recommender Systems, where the main goal is to help designers and researchers when creating a CARS by providing an extensive set of User, Context and Item aspects that covers the information needed by different recommendation domains. To validate GUMCARS, two experiments are performed; first, the completeness and generality of the model are evaluated showing encouraging results as the proposal was able to support most of the information loaded from real-world datasets. Then the structural correctness of the model is assessed, the obtained results strongly suggest that the model is correctly constructed according to Object-Oriented design paradigm

Heat Map based Feature Ranker: In Depth Comparison with Popular Methods

International audienceThe new era of technology allows us to gather more data than ever before, complex data emerge and a lot of noise can be found among high dimensional datasets. In order to discard useless features and help build more generalized models, feature selection seeks a reduced subset of features that improve the performance of the learning algorithm. The evaluation of features and their interactions are an expensive process, hence the need for heuristics. In this work, we present HeatMap Based Feature Ranker, an algorithm to estimate feature importance purely based on its interaction with other variables. A compression mechanism reduces evaluation space up to 66% without compromising efficacy. Our experiments show that our proposal is very competitive against popular algorithms, producing stable results across different types of data. We also show how noise reduction through feature selection aids data visualization using emergent self-organizing maps

Pedagogical models in higher education: action and experience in comprehensive training

En este artículo se relata la experiencia de la investigación doctoral titulada “Modelos pedagógicos comprensivos: la construcción de ciudadanía a través de la formación integral” enfatizando su papel como red anidada de acciones y experiencias que son capaces de configurar significados trasladados a la vida cotidiana y en los perfiles de egreso en la formación de estudiantes de nivel licenciatura. El objetivo de la investigación fue caracterizar los modelos pedagógicos en la Universidad Veracruzana para conocer las formas en que se despliegan y constituyen tanto acciones como experiencias de vida. Se trató de una investigación cualitativa con enfoque antropológico cuya metodología utilizada fue la etnografía; en cuanto a las técnicas e instrumentos utilizados, los grupos focales y entrevistas semiestructuradas dieron cuenta de las primeras mientras que cartas asociativas, árboles de soluciones y problemas así como guiones de entrevista, de los segundos. En lo relativo al análisis de la información y la obtención de los resultados, se echó mano del método contrastivo, lo que permitió generar recurrencias e interpretaciones que aquí se sintetizan y que buscan ofrecer elementos para la reflexión sobre la riqueza contenida en la experiencia vital de los docentes, útil para el diseño de proyectos e innovaciones institucionales.This article reports the experience of the doctoral research entitled "Comprehensive pedagogical models: the construction of citizenship through comprehensive education" emphasizing its role as a nested network of actions and experiences that are capable of configuring meanings transferred to everyday life and in the graduate profiles in the training of undergraduate students. The objective of the research was to characterize the pedagogical models at the Universidad Veracruzana to know the ways in which they are deployed and constitute both actions and life experiences. It was a qualitative research with an anthropological approach whose methodology was ethnography; Regarding the techniques and instruments used, the focus groups and semi-structured interviews accounted for the former, while associative letters, solution and problem trees, as well as interview scripts, for the latter. Regarding the analysis of the information and the obtaining of the results, the contrastive method was used, which allowed generating recurrences and interpretations that are synthesized here and that seek to offer elements for reflection on the richness contained in the vital experience of teachers, useful for the design of projects and institutional innovations

Pot-Pollen and Pot-Honey from Stingless Bees of the Alto Balsas, Michoacán, Mexico: Botanical and Physicochemical Characteristics

The demand for stingless bees’ products (pot-honey and pot-pollen) has increased. No formal quality standards have been defined, which is very complex, because of the variety of species and types of honey specific to each region. For this reason, it is important to deepen the understanding of stingless bees’ honey characteristics. From the above, the aim of this chapter is to present the advances in the characterization of botanical origin of stingless bees’ honey, and the analysis of their physicochemical properties in the Alto Balsas, Michoacán, Mexico, as a way to contribute to the strengthening of new local economic strategies, generating information on the quality of the honey produced in the region

MODELO DE PROCESAMIENTO BASADO EN TRANSFORMADA WAVELET COMO OPCIÓN COMPETENTE PARA APLICACIONES MÉDICAS

ResumenActualmente, en el área del procesamiento y reconocimiento de patrones con aplicaciones médicas es un área del conocimiento ampliamente investigada, en la cual hay una diversidad de técnicas de procesamiento que utilizan algoritmos matemáticos que buscan resaltar o mejorar zonas específicas de especial interés en las imágenes médicas. También existen propuestas comerciales de equipos médicos que integran el análisis de imágenes, sin embargo, son equipos de importación y en su mayoría de tecnología extranjera, lo que los puede hacer costosos e inaccesibles para la población. Pero sin lugar a dudas, el apoyo mediante el análisis de una cantidad exhaustiva de estudios de un paciente, posibilita un acertado diagnóstico médico por parte de un especialista, sin que cambie su postura analítica que depende de factores propios del tipo de imagen, de su estado de ánimo y de su experiencia. Por lo tanto, en este trabajo se propone un modelo para procesar imágenes médicas que utiliza transformada Wavelet, que al basarse en la descomposición de imágenes, permite mejorar la identificación de zonas sospechosas y de interés para analizar por el médico especialista. Cabe mencionar que dicha propuesta es competitiva en el ámbito tecnológico ya que provee una herramienta de apoyo al médico especialista para emitir un diagnóstico adecuado. Así también es competitiva en el ámbito económico y aunado a lo anterior, este tipo de estudios por análisis de imágenes médicas son un método totalmente indoloro y no invasivo para el paciente, por lo que se observa como una importante opción para mejorar los diagnósticos.Palabras Clave: Compresión, imágenes médicas, reconocimiento, RNA, transformada Wavelet. AbstractCurrently, in the area of processing and pattern recognition with medical applications is an area of knowledge widely investigated, in which there is a variety of processing techniques that use mathematical algorithms that seek to highlight or improve specific areas of special interest in medical imaging. There are also medical equipment business proposals that integrate image analysis, however, are equipment import and mostly foreign technology, which can make them expensive and inaccessible to the population. But without doubt, the support by analyzing an exhaustive amount of studies of a patient enables a successful medical diagnosis by a specialist, without changing its analytical approach that depends on factors specific to the type of image, its mood and experience. Therefore, this paper proposes a model to process medical images using wavelet transform, which based on the decomposition of images, enables improved identification of suspicious areas of interest to be analyzed by the specialist. It is worth mentioning that the proposal is competitive in technology because it provides a support tool specialist doctor to issue a proper diagnosis. This is also competitive in the economic sphere and coupled with the above, this type of study for medical image analysis are completely painless and noninvasive method for the patient, so it is seen as an important option to improve diagnostics.Keywords: Compression, medical imaging, recognition, RNA, Wavelet transform

ROBOTS BIOLOID Y NAO COMO ESTRATEGIA PEDAGÓGICA PARA FORMAR COMPETENCIAS EN LOS ESTUDIANTES DE LICENCIATURA

ResumenCon base al análisis de experiencias docentes que tienen como finalidad la enseñanza-aprendizaje en áreas específicas como la robótica, en el nivel superior de la licenciatura de Ingeniería en Computación, se presenta un procedimiento que integra las estrategias para fomentar la interacción, participación y aprendizaje de los estudiantes. Estas experiencias se plasman en las unidades de aprendizaje de Fundamentos de Robótica, Robótica Avanzada, Interacción Hombre-Máquina, Sistemas Expertos y Visión Artificial que se imparten dentro del programa de Ingeniería en Computación del Centro Universitario UAEM Valle de Chalco. El proceso de enseñanza-aprendizaje en robótica implica tres aspectos básicos: interdisciplinariedad, constructivismo y colaboración, mismas que se presentan como fases modulares y que cada docente, según las características y alcances de sus cursos puede decidir en integrar total o parcialmente para fomentar el desarrollo de competencias. Para el caso de la programación de robots se requieren de plataformas robóticas que se caractericen por varios aspectos: montaje sencillo e intuitivo, programación sencilla, bajo costo, capacidad de movimiento del robot de manera autónoma, software instalable en diferentes sistemas operativos, flexible y escalable. Dentro de este grupo de plataformas, se encuentran los robots humanoides, los cuales han sido utilizados para este caso de estudio; donde se analizaron diversas estrategias docentes implementadas mediante los robots Bioloid Premium y NAO H25.Palabras clave: Bioloid, competencias, enseñanza-aprendizaje, NAO, robot. AbstractBased on the analysis of learning experiences that aim to teaching and learning in specific areas such as robotics, at the top level of the degree in Computer Engineering, a procedure that integrates strategies to promote interaction, participation and learning occurs of the students. These experiences are reflected in the learning units Fundamentals of Robotics, Advanced Robotics, Human-Computer Interaction, Expert Systems and Artificial Vision taught within the program of Computer Engineering University Center UAEM Valley of Chalco. The process of teaching and learning in robotics involves three basic aspects: interdisciplinarity, constructivism and collaboration, which are being presented as modular phases and each teacher, depending on the characteristics and scope of their courses may decide to integrate whole or in part to foster development skills. In the case of programming robots require robotic platforms that are characterized by several aspects: simple and intuitive installation, simple programming, low cost, ability to move the robot autonomously, installable software on different operating, flexible and scalable systems. Within this group of platforms are humanoid robots, which have been used for this case study; where various teaching strategies implemented by the NAO H25 Premium Bioloid robots were analyzed.   Keywords: Bioloid, competencies, NAO, robot, teaching-learning

Nutritional value of Acacia amentacea and parkinsonia texana grown in semiarid conditions

In order to evaluate the nutritional value of Parkinsonia texana and Acacia amentacea, two leguminosae species of the Tamaulipan scrubland, Northeastern Mexico, two experiments were carried out: the first tested the effects of season and browse species on chemical composition as nutritional variable to small ruminants; the second tested the effect of the addition of polyethylene glycol (PEG) on fermentation parameters. Foliage samples were collected from three sites. Data of chemical composition were analysed using analysis of variance for a bi-factorial arrangement, whereas the effect of PEG was analysed by a strip plot design. Results of chemical composition were affected by interacting factors season*species as individually they were significantly different (P<0.001). Addition of PEG affected (P<0.001) fermentation parameters. Significantly higher values of neutral detergent fibre (42%), condensed tannins (19%), purines (9 μmol), partitioning factor (PF) (6.1) and gross energy losses (GEL=6.7%) were found in A. amentacea, while P. texana gave higher crude protein (18%), in vitro true organic matter digestibility (82%), metabolisable energy (ME) [2.1 Mcal/kg dry matter (DM)], A (183 mL), c (0.07/h) and L (0.86 h). Addition of PEG increased ME, and affected (P<0.001) fermentation parameters A and c, while purines and PF decreased. Results indicate that chemical composition and fermentation parameters vary according to seasons and species. PEG addition increases the fermentation parameters, which indicates that PEG counteracts the detrimental effects of secondary components of samples. Data suggest that using both species combined could supply necessary nutritional requirements to small ruminants in the Tamaulipan scrubland