A Roadmap to Gamify Programming Education

Learning programming relies on practicing it which is often hampered by the barrier of difficulty. The combined use of automated assessment, which provides fast feedback to the students experimenting with their code, and gamification, which provides additional motivation for the students to intensify their learning effort, can help pass the barrier of difficulty in learning programming. In such environment, students keep receiving the relevant feedback no matter how many times they try (thanks to automated assessment), and their engagement is retained (thanks to gamification). While there is a number of open software and programming exercise collections supporting automated assessment, up to this date, there are no available open collections of gamified programming exercises, no open interactive programming learning environment that would support such exercises, and even no open standard for the representation of such exercises so that they could be developed in different educational institutions and shared among them. This gap is addressed by Framework for Gamified Programming Education (FGPE), an international project whose primary objective is to provide necessary prerequisites for the application of gamification to programming education, including a dedicated gamification scheme, a gamified exercise format and exercises conforming to it, software for editing the exercises and an interactive learning environment capable of presenting them to students. This paper presents the FGPE project, its architecture and main components, as well as the results achieved so far

<i>KISS1</i> and KISS1R expression in the human and rat carotid body and superior cervical ganglion

KISS1 and its receptor, KISS1R, have both been found to be expressed in central nervous system, but few data are present in the literature about their distribution in peripheral nervous structures. Thus, the aim of the present study was to investigate, through immunohistochemistry, the expression and distribution of KISS1 and KISS1R in the rat and human carotid bodies and superior cervical ganglia, also with particular reference to the different cellular populations. Materials consisted of carotid bodies and superior cervical ganglia were obtained at autopsy from 10 adult subjects and sampled from 10 adult Sprague-Dawley rats. Immunohistochemistry revealed diffuse expression of KISS1 and KISS1R in type I cells of both human and rat carotid bodies, whereas type II cells were negative. In both human and rat superior cervical ganglia positive anti-KISS1 and -KISS1R immunostainings were also selectively found in ganglion cells, satellite cells being negative. Endothelial cells also showed moderate immunostaining for both KISS1 and KISS1R. The expression of both kisspeptins and kisspeptin receptors in glomic type I cells and sympathetic ganglion cells supports a modulatory role of KISS1 on peripheral chemoreception and sympathetic function. Moreover, local changes in blood flow have been considered to be involved in carotid body chemoreceptor discharge and kisspeptins and kisspeptin receptors have also been found in the endothelial cells. As a consequence, a possible role of kisspeptins in the regulation of carotid body blood flow and, indirectly, in chemoreceptor discharge may also be hypothesized

A virtualized software based on the NVIDIA cuFFT library for image denoising:performance analysis

Generic Virtualization Service (GVirtuS) is a new solution for enabling GPGPU on Virtual Machines or low powered devices. This paper focuses on the performance analysis that can be obtained using a GPGPU virtualized software. Recently, GVirtuS has been extended in order to support CUDA ancillary libraries with good results. Here, our aim is to analyze the applicability of this powerful tool to a real problem, which uses the NVIDIA cuFFT library. As case study we consider a simple denoising algorithm, implementing a virtualized GPU-parallel software based on the convolution theorem in order to perform the noise removal procedure in the frequency domain. We report some preliminary tests in both physical and virtualized environments to study and analyze the potential scalability of such an algorithm. Peer-review under responsibility of the Conference Program Chairs

some remarks about a community open source lagrangian pollutant transport and dispersion model

Nowadays fishes and mussels farming is very important, from an economical point of view, for the local social background of the Bay of Naples. Hence, the accurate forecast of marine pollution becomes crucial to have reliable evaluation of its adverse effects on coastal inhabitants' health. The use of connected smart devices for monitoring the sea water pollution is getting harder because of the saline environment, the network availability and the maintain and calibration costs2. To this purpose, we designed and implemented WaComM (Water Community Model), a community open source model for sea pollutants transport and dispersion. WaComM is a model component of a scientific workflow which allows to perform, on a dedicated computational infrastructure, numerical simulations providing spatial and temporal high-resolution predictions of weather and marine conditions of the Bay of Naples leveraging on the cloud based31FACE-IT workflow engine27. In this paper we present some remarks about the development of WaComM, using hierarchical parallelism which implies distributed memory, shared memory and GPGPUs. Some numerical details are also discussed. Peer-review under responsibility of the Conference Program Chairs

Wave run-up prediction and observation in a micro-tidal beach

Abstract. Extreme weather events bear a significant impact on coastal human activities and on the related economy. Forecasting and hindcasting the action of sea storms on piers, coastal structures and beaches is an important tool to mitigate their effects. To this end, with particular regard to low coasts and beaches, we have developed a computational model chain based partly on open-access models and partly on an ad-hoc-developed numerical calculator to evaluate beach wave run-up levels and flooding. The offshore wave simulations are carried out with a version of the WaveWatch III model, implemented by CCMMMA (Campania Centre for Marine and Atmospheric Monitoring and Modelling – University of Naples Parthenope), validated with remote-sensing data. The waves thus computed are in turn used as initial conditions for the run-up calculations, carried out with various empirical formulations; the results were finally validated by a set of specially conceived video-camera-based experiments on a micro-tidal beach located on the Ligurian Sea. Statistical parameters are provided on the agreement between the computed and observed values. It appears that, while the system is a useful tool to properly simulate beach flooding during a storm, empirical run-up formulas, when used in a coastal vulnerability context, have to be carefully chosen, applied and managed, particularly on gravel beaches

Heterogeneous Secure Multi-level Remote Acceleration Service for Low-Power Integrated Systems and Devices

AbstractThis position paper presents a novel heterogeneous CPU-GPU multi-level cloud acceleration focusing on applications running on embedded systems found on low-power devices. A runtime system performs energy and performance estimations in order to automatically select local CPU-based and GPU-based tasks that should be seamlessly executed on more powerful remote devices or cloud infrastructures. Moreover, it proposes, for the first time, a secure unified model where almost any device or infrastructure can operate as an accelerated entity and/or as an accelerator serving other less powerful devices in a secure way

A wot-based method for creating digital sentinel twins of iot devices

The data produced by sensors of IoT devices are becoming keystones for organizations to conduct critical decision-making processes. However, delivering information to these processes in real-time represents two challenges for the organizations: the first one is achieving a constant dataflow from IoT to the cloud and the second one is enabling decision-making processes to retrieve data from dataflows in real-time. This paper presents a cloud-based Web of Things method for creating digital twins of IoT devices (named sentinels).The novelty of the proposed approach is that sentinels create an abstract window for decision-making processes to: (a) find data (e.g., properties, events, and data from sensors of IoT devices) or (b) invoke functions (e.g., actions and tasks) from physical devices (PD), as well as from virtual devices (VD). In this approach, the applications and services of decision-making processes deal with sentinels instead of managing complex details associated with the PDs, VDs, and cloud computing infrastructures. A prototype based on the proposed method was implemented to conduct a case study based on a blockchain system for verifying contract violation in sensors used in product transportation logistics. The evaluation showed the effectiveness of sentinels enabling organizations to attain data from IoT sensors and the dataflows used by decision-making processes to convert these data into useful information.This research was partially funded by the project Num.41756 “Plataforma tecnológica para la gestión, aseguramiento, intercambio y preservación de grandes volúmenes de datos en salud y construcción de un repositorio nacional de servicios de análisis de datos de salud” by FORDECYT-PRONACES, Conacyt (México