Advances in Hyperspectral Image Classification: Earth monitoring with statistical learning methods

Hyperspectral images show similar statistical properties to natural grayscale or color photographic images. However, the classification of hyperspectral images is more challenging because of the very high dimensionality of the pixels and the small number of labeled examples typically available for learning. These peculiarities lead to particular signal processing problems, mainly characterized by indetermination and complex manifolds. The framework of statistical learning has gained popularity in the last decade. New methods have been presented to account for the spatial homogeneity of images, to include user's interaction via active learning, to take advantage of the manifold structure with semisupervised learning, to extract and encode invariances, or to adapt classifiers and image representations to unseen yet similar scenes. This tutuorial reviews the main advances for hyperspectral remote sensing image classification through illustrative examples.Comment: IEEE Signal Processing Magazine, 201

Current Challenges and Visions in Music Recommender Systems Research

Music recommender systems (MRS) have experienced a boom in recent years, thanks to the emergence and success of online streaming services, which nowadays make available almost all music in the world at the user's fingertip. While today's MRS considerably help users to find interesting music in these huge catalogs, MRS research is still facing substantial challenges. In particular when it comes to build, incorporate, and evaluate recommendation strategies that integrate information beyond simple user--item interactions or content-based descriptors, but dig deep into the very essence of listener needs, preferences, and intentions, MRS research becomes a big endeavor and related publications quite sparse. The purpose of this trends and survey article is twofold. We first identify and shed light on what we believe are the most pressing challenges MRS research is facing, from both academic and industry perspectives. We review the state of the art towards solving these challenges and discuss its limitations. Second, we detail possible future directions and visions we contemplate for the further evolution of the field. The article should therefore serve two purposes: giving the interested reader an overview of current challenges in MRS research and providing guidance for young researchers by identifying interesting, yet under-researched, directions in the field

Knowledge building as a mediator of conflict in conceptual change

This study examined how individuals and peers process scientific information that contradicts what they believe and assessed the contribution of this activity to conceptual change. Participants included 54 students in Grade 9 and 54 students in Grade 12, who were randomly assigned to four conditions: (a) individual conflict, (b) peer conflict, (c) individual assimilation, and (d) peer assimilation. Depending on the condition, students were asked to think aloud or discuss with their peers eight scientifically valid statements, which were presented in an order that either maximized or minimized the conflict between new information and existing beliefs. Pretest and posttest measures of prior knowledge and conceptual change were obtained, and student verbalizations were tape-recorded and coded for five levels of knowledge-processing activity. Two major approaches were identified from this analysis: direct assimilation, which involved fitting new information with what was already known, and knowledge building, which involved treating new information as something problematic that needed to be explained. A path analysis indicated that the level of knowledge-processing activity exerted a direct effect on conceptual change and that this activity mediated the effect of conflict. Knowledge building as a mediator of conflict in conceptual change helps to explicate previous equivocal research findings and highlights the importance of students' constructive activity in learning.published_or_final_versio

Evaluación basada en rúbricas digitales de la competencia de presentación oral con recursos tecnológicos para profesorado en formación

Este estudio está dirigido a la e-evaluación de la competencia de presentación oral utilizando recursos tecnológicos en un modelo activo que combina aprendizaje basado en proyectos y aula invertida. Este estudio aplica el uso de una rúbrica digital para la evaluación de la competencia en presentación oral en diferentes situaciones de evaluación activa y progresiva de 99 futuros docentes en las que la participación es opcional u obligatoria. Los resultados muestran que la rúbrica digital empleada en varios momentos es una metodología y una tecnología que facilita el proceso de retroalimentación y diálogo entre docentes y estudiantes sobre los criterios de evaluación. Los resultados apoyan futuras decisiones de diseño metodológico de evaluación formativa apropiadas en entornos de aprendizaje online.This study focuses on e-assessment of oral presentation competence using technology resources in a model that combines project-based learning and fl ipped learning. This study uses a digital rubric to assess oral presentation competence in different situations of progressive assessment for 99 preservice teachers, situations in which participation was either optional or compulsory. Findings show that the digital rubric used at various times is a methodology and a technology that facilitates the feedback process and dialogue between teachers and students about the assessment criteria. The results support future decisions for methodological design of formative assessment appropriate to online learning environments

Digital rubric-based assessment of oral presentation competence with technological resources for preservice teachers

This study focuses on e-assessment of oral presentation competence using technology resources in a model that combines project-based learning and flipped learning. This study uses a digital rubric to assess oral presentation competence in different situations of progressive assessment for 99 preservice teachers, situations in which participation was either optional or compulsory. Findings show that the digital rubric used at various times is a methodology and a technology that facilitates the feedback process and dialogue between teachers and students about the assessment criteria. The results support future decisions for methodological design of formative assessment appropriate to online learning environments.   Evaluación basada en rúbricas digitales de la competencia de presentación oral con recursos tecnológicos para profesorado en formación Este estudio está dirigido a la e-evaluación de la competencia de presentación oral utilizando recursos tecnológicos en un modelo activo que combina aprendizaje basado en proyectos y aula invertida. Este estudio aplica el uso de una rúbrica digital para la evaluación de la competencia en presentación oral en diferentes situaciones de evaluación activa y progresiva de 99 futuros docentes en las que la participación es opcional u obligatoria. Los resultados muestran que la rúbrica digital empleada en varios momentos es una metodología y una tecnología que facilita el proceso de retroalimentación y diálogo entre docentes y estudiantes sobre los criterios de evaluación. Los resultados apoyan futuras decisiones de diseño metodológico de evaluación formativa apropiadas en entornos de aprendizaje online

Environmental scanning strategy of manufacturing companies in Southwestern Nigeria

In this paper, we examine the environmental scanning strategy of manufacturing companies in Southwestern Nigeria against the background that manufacturing companies in Nigeria exist in a challenging environment characterised by high import dependency, inappropriate policies, lack of transparent governance and weak industrial capabilities. Empirical data was collected with a questionnaire from a sample of 84 manufacturing firms in Southwestern Nigeria. We found that generally, companies in the industry actively engage in systematic gathering, analyses and assimilation of information about the business environment as strategic input into planning. The main objective of search was to obtain information required to initiate or support strategies for competing in the domestic market. Central among the factors determining the companies' level of intrusiveness into the environment are companies' capacity to interpret changes in the environment, available channels of information and quality of information.business environment; environmental scanning; environmental analysability; environmental uncertainty; manufacturing, strategy; technology; capabilities

Active Learning to Reduce Cold Start in Recommender Systems

Every time a recommender system has a new user, it does not have enough information to generate recommendations with high precision, this is known as cold start. Adapting this problem to a classification problem allow us to apply Active Learning techniques that, as we well see, offer some methods to, given the less possible information about a new user, make right predictions with higher precision than the standard solutions applied in this situation.Eje: XVIII Workshop de Agentes y Sistemas Inteligentes (WASI).Red de Universidades con Carreras en Informática (RedUNCI

In pursuit of satisfaction and the prevention of embarrassment : affective state in group recommender systems

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