Lately, gamification (i.e., employing game-design elements and game principles in nongame contexts) has gained massive popularity and widespread usage in various areas, including education. However, gamification deployment in education in general and remote education in particular still faces many challenges that mainly influence user quality of experience. These challenges include lack of dedicated communication-based systems, potential additional load on teachers, absence of customization and personalization for users, and no support for advanced technology-enhanced learning (TEL). This paper investigates the use of gamification for networked delivery of science, technology, engineering and mathematics (STEM) subjects. It proposes an innovative gamification framework, the NEWTONenhanced gamification model (N-EGM), which was designed as part of the European Horizon 2020 project NEWTON. The paper also describes the proposed N-EGM model deployment in the gamification engine of a real learning management system and its associated communication and networking solution. The communication support provides easy-to-use gamification configuration functionality and efficient data collection and processing in a heterogeneous technology context. Finally, the paper evaluates the proposed N-EGM model as part of a NEWTON project pilot deployed in a Romanian school. The results demonstrate the effectiveness of the proposed gamification solution in improving both students' learning experience and their engagement, while also increasing student knowledge gain.

In this work we introduce a mathematical model to improve the aircraft\ud departures planning system. The objective is to maximize the airport\ud performances, minimize delays in the runway operations and to support the\ud air controller work. The followed approach is based on the combination of a\ud single runway two stages algorithm with a multi-runway procedure to find the\ud better departures scheduling. By means of the two stages algorithm, a\ud complex problem dealing with multi-objective functions is split into two\ud inter-connected one dimensional problems. In the first stage the aim is to\ud minimize the throughput, defined as the number of aircraft in the time unit,\ud subject to Wake Vortex Separations constraint. An "ad\ud hoc" control heuristic method is used to mix the pre-fixed\ud landing arrivals slots with the departure ones outgoing from the first\ud stage. In the second stage the class sequence, generated by the first stage,\ud is computed in order to minimize the delays between the actual and estimated\ud take-off time of each departing aircraft, subject to fixed CTOTs (Calculated Take Off Time) and ETOTs (Estimated Take Off Times),\ud and considering some possible departing priority. Then a\ud multi-runway procedure is introduced, consisting of an heuristic\ud methodology, which uses the two stage algorithm, to locate as better as\ud possible the aircraft on each available runway. The result is the better\ud feasible take-off sequence in a referred time window. Some simulations on\ud typical flight strips from Milano Malpensa airport in Italy, having two\ud runways, are shown

We deal with an algorithm that, once origin and destination are fixed, individuates the route that permits to reach the destination in the shortest time, respecting an assigned maximal travel time, and with risks measure below a given threshold. A fluid dynamic model for road networks, according to initial car densities on roads and traffic coefficients at junctions, forecasts the future traffic evolution, giving dynamical weights to a constrained K shortest path algorithm. Simulations are performed on a case study to test the efficiency of the proposed procedure.

It is recognised that many European countries are currently facing a crisis amongst their younger generations in respect of scientific learning vocations. The number of students specialising in science, technology, engineering and maths (STEM) disciplines has been in steady decline in recent years and Europe faces nowadays the concrete risk of an acute shortage of suitably qualified scientists, technicians and engineers. There is strong evidence that for many young people their disengagement from STEM subjects starts during secondary education. The drivers of this disengagement are various but research indicates that there are primarily two factors at play: first, there is a commonly held perception that amongst young people that scientific subjects are difficult to learn and master; second, there are misapprehensions regarding the employment pathways available to STEM students with many young people believing that studying these subjects will lead to poorer pay and a less attractive working life.Evidence suggests that the teaching of STEM subjects requires radical reform. Immersive, experiential learning and the deployment of self-directed learning approaches can be the catalyst for deepening student engagement and improving learning outcomes. However, too much STEM teaching remains teacher-led, didactic and one-dimensional. At best, this makes the learning experience more challenging in relation to student performance; at worst, potential STEM students are put off these subjects for life due to an inability to fully engage in the content of lessons. For those students who do stick with STEM subjects, their ability to develop the skills and competencies they need to operate effectively within highly technical employment environments can be diminished meaning that employers are required to undertake considerable retraining in order to bring graduates up to speed.These dual problemsof the attractiveness of STEM subjects to learners and the effectiveness of STEM teaching in relation to learning outcomesrequire novel solutions. The NEWTON projectfunded under the Horizon2020 E.U. programme -is a large scale initiative to develop and integrate innovative technology-enhanced tools for teaching and learning and to create a pan-European learning network platform that supports fast dissemination of learning content to a wide audience in a ubiquitous manner. NEWTON is seeking to deploy a range of novel techniques and methodologies, such as AR/VR, Fab-Lab, Virtual Labs, user profiling, self-directed learning and gamificationthat is the use of game mechanicsand game-based learning (the use of so-called 'serious games') for the engagement of the student and for the enhancement of the learning experience, in general. Within the context of a project of this scaleand one that utilises the many and various elements of a modern learning management systemthe authors of this paper have developed a specific model, the Newton Enhanced Gamification Model (N-EGM), which provides a coherent approach to the implementation and use of gamif...

Resequencing problem is a crucial issue in communication systems, databases, production and information networks because correct processing of information by them may often be performed only if original order of packets, queries, jobs is preserved. In this paper consideration is given to one of the queueing systems that may model processes of discrete nature where resequencing phenomenon may arise. Specifically Geo/Geo/2/∞ queueing system with reordering buffer of infinite capacity is being analyzed. Expressions for stationary sojourn time distribution and joint stationary distribution of the number of customers in system and reordering buffer are given in explicit form and in terms of generating functions. Illustrative numerical example is presented.