No abstract

Cyber-Physical-Human Systems (CPHS) combine sensing, communication and control to obtain desirable outcomes in physical environments for human beings, such as buildings or vehicles. A particularly important application area is emergency management. While recent work on the design and optimisation of emergency management schemes has relied essentially on discrete event simulation, which is challenged by the substantial amount of programming or reprogramming of the simulation tools and by the scalability and the computing time needed to obtain useful performance estimates, this paper proposes an approach that offers fast estimates based on graph models and probability models. We show that graph models can offer insight into the critical areas in an emergency evacuation and that they can suggest locations where sensor systems are particularly important and may require hardening. On the other hand, we also show that analytical models based on queueing theory can provide useful estimates of evacuation times and for routing optimisation. The results are illustrated with regard to the evacuation of a real-life building.

Cyber-Physical-Human Systems (CPHS) combine sensing, communication and control to obtain desirable outcomes in physical environments for human beings, such as buildings or vehicles. A particularly important application area is emergency management. While recent work on the design and optimisation of emergency management schemes has relied essentially on discrete event simulation, which is challenged by the substantial amount of programming or reprogramming of the simulation tools and by the scalability and the computing time needed to obtain useful performance estimates, this paper proposes an approach that offers fast estimates based on graph models and probability models. We show that graph models can offer insight into the critical areas in an emergency evacuation and that they can suggest locations where sensor systems are particularly important and may require hardening. On the other hand, we also show that analytical models based on queueing theory can provide useful estimates of evacuation times and for routing optimisation. The results are illustrated with regard to the evacuation of a real-life building.

We introduce two congestion metrics to guide emergency evacuations using sensing and local area networks, that use current congestion and congestion forecasts, together with the Cognitive Packet Network (CPN), a routing algorithm which intelligently discovers paths. Using simulations we find that CPN performs well for emergency evacuation with such metrics, and also reveal the dynamics that these schemes can create.

Due to the general aging population and the fashion trend of sun exposure, non-melanoma skin cancer (NMSC) is rising. The management of NMSC is difficult and necessitates a multidisciplinary team (i.e., pathologists, dermatologists, medical oncologists, surgeons, and radiation oncologists). When surgery is not an option or will cause unacceptably functional morbidity, radiation therapy (RT) may be a preferable tissue-preserving option. Whether used alone or in conjunction with other treatments, RT has been shown to be quite effective in terms of cosmetic results and local control. Contact hypofractionated RT, brachytherapy, and electronic brachytherapy are all promising new treatments. However, rigorous, randomized trials are missing, explaining the disparity in dose, fractionation, and technique recommendations. Therefore, it is essential that interdisciplinary teams better understand RT modalities, benefits, and drawbacks. Our review will provide the role and indications for RT in patients with NMSC.