Due to modifications of the definition of the bbob-largescale testbed of COCO [2] and of the corresponding source code, a second, updated version of the article [1] is presented here, with corrections/additions indicated by the colored text. Additionally to this, the following corrections/modifications have been done:• All figures have been updated: they present post processed results after benchmarking the solvers on the updated suite.• The links to plots of specific testbed functions within the text redirect to an updated repository, containing the whole new dataset of post processed results.

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Telemedicine has been developed to allow practitioners to remotely connect with patients and with other medical staff. We propose a new system (hardware and software), named DICODERM (COllaborative DIagnosis of DERMatosis), which makes it possible to monitor the evolution of scars after the excision of a tumorous dermatosis (like melanoma). The hardware part of this system is composed of a new optical innovative probe with which two types of images can be acquired simultaneously: anatomic with a white light image and functional with a fluorescence image (using autofluorescence from the protoporphyrin within the cancer cell). The software part is composed of two components: the image stitching component, and the collaborative/adaptive layer component. Our system creates a panoramic view of these scars obtained by stitching a sequence of small images. We conducted experiments for different image stitching algorithms to define the best solution. We also deployed a second component: a collaborative system layer which allows to remotely share images of scars and to adapt these images. We also made the system adaptive to communicate across different client platforms. We conducted experiments to compare the exchange of images with or without adaptation: these tests showed the efficiency of our layer.

Thales new generation digital multi-missions radars, fully-digital and software-defined, like the Sea Fire and Ground Fire radars, benefit from a considerable increase of accessible degrees of freedoms to optimally design their operational modes. To effectively leverage these design choices and turn them into operational capabilities, it is necessary to develop new engineering tools, using artificial intelligence. Innovative optimization algorithms in the discrete and continuous domains, coupled with a radar Digital Twins, allowed construction of a generic tool for "search" mode design (beam synthesis, waveform and volume grid) compliant with the available radar time budget. The high computation speeds of these algorithms suggest tool application in a "Proactive Radar" configuration, which would dynamically propose to the operator, operational modes better adapted to environment, threats and the equipment failure conditions.