Homenaje a Hohannes Vincke.

Es fotocopi

Bullying: Cruel innocence

El acoso escolar es el principal problema a erradicar dentro de nuestro sistema educativo. Alumnado, profesorado y familias buscan soluciones a una situación normalizada en las aulas. 1 de cada 4 jóvenes sufre bullying en España, una intimidación basada en la discriminación, homofobia, racismo y xenofobia. En este escenario, la educación juega un papel fundamental. El profesorado, las instituciones y la justicia siguen con el objetivo de conseguir un control exhaustivo y eficaz de las vejaciones y maltratos que pueden sufrir las víctimas. El maltrato mental, físico, psicológico e, incluso, cibernético, suelen ser las principales formas en las que se realiza el bullying. Durante la pandemia, los casos de ciberbullying han aumentado gracias a la digitalización y la alta actividad de los jóvenes en redes sociales como Whatsapp, TikTok e Instagram. Las consecuencias del bullying en los acosados van desde la depresión a, en casos extremos, el suicidio. El acoso sólo se puede parar con empatía y educación.Bullying is the main problem to eradicate within our education system. Students, teachers and families are looking for solutions to a normalized situation in the classroom. 1 in 4 young people suffer bullying in Spain, an intimidation based on discrimination, homophobia, racism and xenophobia. In this scenario, education plays a fundamental role. Teachers, institutions and justice continue with the aim of achieving an exhaustive and effective control of the harassment and mistreatment that victims may suffer. Mental, physical, psychological and even cyber abuses are usually the main ways in which bullying is carried out. During the pandemic, cases of ciberbullying have increased thanks to digitalization and the high activity of young people in social networks such as Whatsapp, Tik Tok and Instagram. The consequences of bullying on the bullied range from depression to, in extreme cases, suicide. Bullying can only be stopped with empathy and education

Deconstructing AMO framework: A systematic review

Purpose: The AMO framework has been widely accepted in HRM literature for explaining the linkage between human resources practices and performance. However, it remains unclear whether this model has been fully demonstrated or not. Hence, we propose a systematic review that aims at identifying those investigations that have thoroughly tested the model, as well as the approaches used by them. Design/methodology: Systematic literature review, filtering scientific papers published in journals indexed in Scopus, Web of Science or Google Scholar, from the year 1993 to 2016, in the field of Social Sciences and Humanities with research that indirectly apply the AMO model in their analysis. Findings: AMO model is an excellent and structured framework that provides a better understanding of the relationship between HRM and performance. Moreover, the effectiveness of the model's proposal appears to be beyond doubt. In fact, a well trained and skilled employee will perform better, and a motivated worker will be ready to "go the extra mile". Likewise, if the work environment does not provide adequate opportunities, both abilities and motivation might become meaningless. However, we consider that many other factors could influence the positive effects of HPWS. As a matter of fact, not only contextual factors, but also individual beliefs, personal affinities, or personal circumstances (among others) might affect the implementation of these practices and the subsequent outcomes. For this reason, we consider that developing an HRM model that perfectly fit any situation is a very complicated, if not impossible, task. Research limitations/implications: The results show a significant variability in both research approaches and variables taken into consideration. In addition, it seems that little research has been conducted to verify the AMO model directly. Therefore, we consider that there is a great need to study the model from a more systematic perspective. A thorough understanding of the model could lead to a better understanding of the problems that organizations face when implementing human resource practices. Originality/value: Our study shed light on some aspects of the AMO framework within the HRM context. Specifically, we aimed to identify whether or not it is possible to confirm the model as it was originally proposed. We also find out which HR practices and measures of performance were considered across investigations, to define a standard approach.Marín García, JA.; Martínez Tomás, J. (2016). Deconstructing AMO framework: A systematic review. Intangible Capital. 12(4):1040-1087. doi:10.3926/ic.838S1040108712

Optimal Grid-Based Filtering for Crop Phenology Estimation with Sentinel-1 SAR Data

In the last decade, suboptimal Bayesian filtering (BF) techniques, such as Extended Kalman Filtering (EKF) and Particle Filtering (PF), have led to great interest for crop phenology monitoring with Synthetic Aperture Radar (SAR) data. In this study, a novel approach, based on the Grid-Based Filter (GBF), is proposed to estimate crop phenology. Here, phenological scales, which consist of a finite number of discrete stages, represent the one-dimensional state space, and hence GBF provides the optimal phenology estimates. Accordingly, contrarily to literature studies based on EKF and PF, no constraints are imposed on the models and the statistical distributions involved. The prediction model is defined by the transition matrix, while Kernel Density Estimation (KDE) is employed to define the observation model. The approach is applied on dense time series of dual-polarization Sentinel-1 (S1) SAR images, collected in four different years, to estimate the BBCH stages of rice crops. Results show that 0.94 ≤ R2 ≤ 0.98, 5.37 ≤ RMSE ≤ 7.9 and 20 ≤ MAE ≤ 33.This research was funded in part by the Spanish Ministry of Science and Innovation (State Agency of Research, AEI) and the European Funds for Regional Development (EFRD) under Projects TEC2017-85244-C2-1-P and PID2020-117303GB-C22, and in part by the University of Alicante (ref. VIGROB-114)

Self-Efficacy of Teachers in Initial Training: A Comparison between the Populations of Two Universities

This article carries out a comparison of the self-efficacy of teachers in initial training, between the populations of two universities. A questionnaire with two Likert scales is applied in two samples, 836 subjects from the Universidad Nacional (Costa Rica) and 588 from the Universidad de Granada (Spain). The data is reviewed by means of descriptive and inferential statistics (95% confidence interval), correlation tests (Kendall τ correlation coefficient) and variance analysis (Mann–Whitney U test and Kruskal–Wallis H test). The results indicate that both populations show high levels of self-efficiency during their initial training, where the self-perceived capacity to pay attention to the explanations and instructions of the teachers excels. Meaningful differences are observed with getting ahead with difficult situations, doing the extra-class tasks and having motivation in the less interesting classes

Crop Phenology Estimation Using a Multitemporal Model and a Kalman Filtering Strategy

In this letter, a new approach for crop phenology estimation with remote sensing is presented. The proposed methodology is aimed to exploit tools from a dynamical system context. From a temporal sequence of images, a geometrical model is derived, which allows us to translate this temporal domain into the estimation problem. The evolution model in state space is obtained through dimensional reduction by a principal component analysis, defining the state variables, of the observations. Then, estimation is achieved by combining the generated model with actual samples in an optimal way using a Kalman filter. As a proof of concept, an example with results obtained with this approach over rice fields by exploiting stacks of TerraSAR-X dual polarization images is shown.This project was supported in part by the Spanish Ministry of Economy and Competitiveness (MINECO) and in part by EU FEDER under Project TEC2011-28201-C02-02

Dynamical Approach for Real-Time Monitoring of Agricultural Crops

In this paper, a novel approach for exploiting multitemporal remote sensing data focused on real-time monitoring of agricultural crops is presented. The methodology is defined in a dynamical system context using state-space techniques, which enables the possibility of merging past temporal information with an update for each new acquisition. The dynamic system context allows us to exploit classical tools in this domain to perform the estimation of relevant variables. A general methodology is proposed, and a particular instance is defined in this study based on polarimetric radar data to track the phenological stages of a set of crops. A model generation from empirical data through principal component analysis is presented, and an extended Kalman filter is adapted to perform phenological stage estimation. Results employing quad-pol Radarsat-2 data over three different cereals are analyzed. The potential of this methodology to retrieve vegetation variables in real time is shown.This work was supported in part by the Spanish Ministry of Economy and Competitiveness (MINECO) and EU FEDER under Project TEC2011-28201-C02-02 and in part by the Generalitat Valenciana under Project ACOMP/2014/136

Estimation of Key Dates and Stages in Rice Crops Using Dual-Polarization SAR Time Series and a Particle Filtering Approach

Information of crop phenology is essential for evaluating crop productivity. In a previous work, we determined phenological stages with remote sensing data using a dynamic system framework and an extended Kalman filter (EKF) approach. In this paper, we demonstrate that the particle filter is a more reliable method to infer any phenological stage compared to the EKF. The improvements achieved with this approach are discussed. In addition, this methodology enables the estimation of key cultivation dates, thus providing a practical product for many applications. The dates of some important stages, as the sowing date and the day when the crop reaches the panicle initiation stage, have been chosen to show the potential of this technique.This work was supported in part by the Spanish Ministry of Economy and Competitiveness (MINECO) and EU FEDER under Project TEC2011-28201-C02-02, and in part by the Generalitat Valenciana under Project ACOMP/2014/136. All SAR images have been provided by DLR in the framework of projects LAN0021 and LAN0234 of the prelaunch AO of TerraSAR-X

Particle Filter Approach for Real-Time Estimation of Crop Phenological States Using Time Series of NDVI Images

Knowing the current phenological state of an agricultural crop is a powerful tool for precision farming applications. In the past, it has been estimated with remote sensing data by exploiting time series of Normalised Difference Vegetation Index (NDVI), but always at the end of the campaign and only providing results for some key states. In this work, a new dynamical framework is proposed to provide real-time estimates in a continuous range of states, for which NDVI images are combined with a prediction model in an optimal way using a particle filter. The methodology is tested over a set of 8 to 13 rice parcels during 2008–2013, achieving a high determination factor R2=0.93 ( n=379 ) for the complete phenological range. This method is also used to predict the end of season date, obtaining a high accuracy with an anticipation of around 40–60 days. Among the key advantages of this approach, phenology is estimated each time a new observation is available, hence enabling the potential detection of anomalies in real-time during the cultivation. In addition, the estimation procedure is robust in the case of noisy observations, and it is not limited to a few phenological stages.This work is supported by the Spanish Ministry of Economy and Competitiveness (MINECO) and EU FEDER under Projects TEC2011-28201-C02-02 and TIN2014-55413-C2-2-P

Protocol: How to measure teamwork and networking competencies

[EN] Our aim is present a protocol to develop a measurement questionnaire that allows a valid and reliable self-evaluation of the transversal competencies related to team work (TW) and networking (NW). It will be design to evaluate these competences among professionals from different organizations or job applicants. In this paper, we will focus on how to filter a bank of behavioral items, verifying that the items finally analysed: a) Represent one or several conceptual dimensions within TW or NW. b) Ensure the inter-agreement between independent evaluators to analyze the overlap between items and dimensions, and be able to classify the items in the correct dimension.c) Check that the set of items retained by agreement between evaluators represent all the subdimensions of team work and networking.Marín García, JA.; Martínez Villaescusa, M.; Bonavía, T. (2019). Protocolo: Cómo medir las competencias transversales de trabajo en equipo y red de trabajo. WPOM-Working Papers on Operations Management. 10(2):55-68. https://doi.org/10.4995/wpom.v10i2.12369OJS556810