Abstract

Abstract
With the continuous growth and complexity of public transport systems, it is essential that the users have access to transport maps that help them easily understand the underlying network, thus facilitating the user experience and public transports ridership. Spider Maps combine elements from geographical and schematic maps, to allow answering questions like "From where I am, where can I go?". Although these maps could be very useful for travellers, they still are mostly manually generated and not widely used. Moreover, these maps have several design constraints, which turns the automation of the generation process into a complex problem. Although optimisation techniques can be applied to support the generation process, current solutions are time expensive and require heavy computational power. This paper presents a solution to automatically generate spider maps. It proposes an algorithm that adapts current methods and generates viable spider map solutions in a short execution time. Results show successful spider maps solutions for areas in Porto city.

Abstract
Photosynthesis is an important and complex physical process in nature, whose comprehensive understanding would have many relevant industrial applications, for instance, in the field of energy production. In this paper, we propose a quantum algorithm for the simulation of the excitonic transport of energy, occurring in the first stage of the process of photosynthesis. The algorithm takes in account the quantum and environmental effects (pure dephasing), influencing the quantum transport. We performed quantum simulations of such phenomena, for a proof of concept scenario, in an actual quantum computer, IBMQ, of 5 qubits. We validate the results with the Haken-Strobl model and discuss the influence of environmental parameters on the efficiency of the energy transport.

Abstract
With the ever-increasing occurrence of skin cancer, timely and accurate skin cancer detection has become clinically more imperative. A clinical mobile-based deep learning approach is a possible solution for this challenge. Nevertheless, there is a major impediment in the development of such a model: the scarce availability of labelled data acquired with mobile devices, namely macroscopic images. In this work, we present two experiments to assemble a robust deep learning model for macroscopic skin lesion segmentation and to capitalize on the sizable dermoscopic databases. In the first experiment two groups of deep learning models, U-Net based and DeepLab based, were created and tested exclusively in the available macroscopic images. In the second experiment, the possibility of transferring knowledge between the domains was tested. To accomplish this, the selected model was retrained in the dermoscopic images and, subsequently, fine-tuned with the macroscopic images. The best model implemented in the first experiment was a DeepLab based model with a MobileNetV2 as feature extractor with a width multiplier of 0.35 and optimized with the soft Dice loss. This model comprehended 0.4 million parameters and obtained a thresholded Jaccard coefficient of 72.97% and 78.51% in the Dermofit and SMARTSKINS databases, respectively. In the second experiment, with the usage of transfer learning, the performance of this model was significantly improved in the first database to 75.46% and slightly decreased to 78.04% in the second. © 2020, The Author(s).

Abstract
This paper presents a new intermediate bus converter topology based on a zero voltage switching switched capacitor circuit including a novel non-isolated gate driver ICs enabling high power density in 48-V data center applications. The proposed topology inherently ensure zero voltage switching operation enabling high switching frequency keeping high efficiency. The novel non-isolated driver IC, with truly differential input, works also as floating high side driver, which lead to a driver circuit footprint reduction by 75% compared to an equivalent dual isolated driver IC. Experimental results show the effectiveness of the proposed approach, the prototype achieves 3060 W=in3 power density and a peak efficiency of 97.13% at 48-V input voltage including auxiliary losses. © VDE VERLAG GMBH · Berlin · Offenbach.

Abstract