Omni-channel retailing:Some reflections

In this paper, I discuss some reflections on the emerging literature on multi- and omni-channel retailing. I discuss four important area’s of prior research and briefly describe some general findings. Next, I consider three important emerging trends: 1) digital only, 2) Covid-19 effects and 3) New Technologies. I discuss the implications of these trend for omni-channel retailing and provide some ideas for future research on these trends

Vakdidactiek wiskunde in een Community of Learners (CoL)

Vakdidactiek op de lerarenopleiding in een Community of Learners (CoL) was stimulerend voor docenten in opleiding (DIO’s). Zij leerden door wetenschappelijke artikelen over de didactiek van de wiskunde aan el-kaar te presenteren en samen problemen op te lossen. De vertaling van de opleidingssituatie naar de schoolsituatie stond voortdurend centraal. In de voorbereiding was er in alle gevallen sprake van integratie van de aangereikte theorie. In de uitvoering bracht de schoolpraktijk echter zo’n schokeffect teweeg dat DIO’s niet in staat waren de geplande onderwijsleergesprekken met het oog op de ontwikkeling van wis-kundige begrippen daadwerkelijk te houden. In de evaluatie lag het accent op het keurslijf van het boek, de sommencultuur, de studiewijzer en de cultuur van zelfstandig werken, en niet op de inbedding van de theorie. De aanbeveling is om inrichting van een CoL te verrijken met de concrete deelname van docenten die lesgeven op school

Retrieval of canopy component temperatures through Bayesian inversion of directional thermal measurements

Evapotranspiration is usually estimated in remote sensing from single temperature value representing both soil and vegetation. This surface temperature is an aggregate over multiple canopy components. The temperature of the individual components can differ significantly, introducing errors in the evapotranspiration estimations. The temperature aggregate has a high level of directionality. An inversion method is presented in this paper to retrieve four canopy component temperatures from directional brightness temperatures. The Bayesian method uses both a priori information and sensor characteristics to solve the ill-posed inversion problem. The method is tested using two case studies: 1) a sensitivity analysis, using a large forward simulated dataset, and 2) in a reality study, using two datasets of two field campaigns. The results of the sensitivity analysis show that the Bayesian approach is able to retrieve the four component temperatures from directional brightness temperatures with good success rates using multi-directional sensors (Srspectra˜0.3, Srgonio˜0.3, and SrAATSR˜0.5), and no improvement using mono-angular sensors (Sr˜1). The results of the experimental study show that the approach gives good results for high LAI values (RMSEgrass=0.50 K, RMSEwheat=0.29 K, RMSEsugar beet=0.75 K, RMSEbarley=0.67 K); but for low LAI values the results were unsatisfactory (RMSEyoung maize=2.85 K). This discrepancy was found to originate from the presence of the metallic construction of the setup. As these disturbances, were only present for two crops and were not present in the sensitivity analysis, which had a low LAI, it is concluded that using masked thermal images will eliminate this discrepanc

Technique for validating remote sensing products of water quality

Remote sensing of water quality is initiated as an additional part of the on going activities of the EAGLE2006 project. Within this context intensive in-situ and airborne measurements campaigns were carried out over the Wolderwijd and Veluwemeer natural waters. However, in-situ measurements and image acquisitions were not simultaneous. This poses some constraints on validating air/space-borne remote sensing products of water quality. Nevertheless, the detailed insitu measurements and hydro-optical model simulations provide a bench mark for validating remote sensing products. That is realized through developing a stochastic technique to quantify the uncertainties on the retrieved aquatic inherent optical properties (IOP). The output of the proposed technique is applied to validate remote sensing products of water quality. In this processing phase, simulations of the radiative transfer in the coupled atmosphere-water system are performed to generate spectra at-sensor-level. The upper and the lower boundaries of perturbations, around each recorded spectrum, are then modelled as function of residuals between simulated and measured spectra. The perturbations are parameterized as a function of model approximations/inversion, sensor-noise and atmospheric residual signal. All error sources are treated as being of stochastic nature. Three scenarios are considered: spectrally correlated (i.e. wavelength dependent) perturbations, spectrally uncorrelated perturbations and a mixed scenario of the previous two with equal probability of occurrence. Uncertainties on the retrieved IOP are quantified with the relative contribution of each perturbation component to the total error budget of the IOP. This technique can be used to validate earth observation products of water quality in remote areas where few or no in– situ measurements are available

Lesson study: the effect on teachers' professional development

This study combines elements of the Japanese Lesson Study approach and teachers’ professional development. An explorative research design is conducted with three upper level high school teachers in the light of educational design research, whereby design activities will be cyclically evaluated. The Lesson Study team observed and evaluated two different research lesson cycles. The first one focused on the concept of the derivative. The second one deepened teachers’ pilot experiences with regard to another mathematical concept. The Lesson Study revealed students’ misconceptions with regard to the tangent line. Results of teachers’ professional development are used to refine the Lesson Study observation instrument