Abstract: A process for preparing a catalyst material, includes: (a) providing a support material having surface hydroxyl (OH) groups, the support material is ceria (CeO2), zirconia (ZrO2) or a combination, and the support material contains between 0.3 and 2.0 mmol OH groups/g of the support material; (b) reacting the support material with at least one of: (b1) a compound containing at least one alkoxy or phenoxy group bound though its oxygen atom to a metal element from Group 5 (V, Nb, Ta) or Group 6 (Cr, Mo, W); (b2) a compound containing at least one hydrocarbon group bound though a carbon atom to a metal element from Group 5 or 6; (b3) a compound containing at least one hydrocarbon group bound though a carbon atom to a metal element which is copper (Cu); and (c) calcining the product obtained in step (b).

Abstract: A system and a method for training a model to be used for semantic segmentation of images, comprising: a—obtaining (S01) a first plurality of foggy images (101), b—training (S02) a classification model for estimating fog density, c—classifying (S03) a second plurality of images (101) having light fog, d—obtaining (S04) a third plurality of foggy images (103) having light fog, e—training (S05) a semantic segmentation model using the third plurality of foggy images, f—applying (S06) the semantic segmentation model to the second plurality of foggy (102) images to obtain semantic segmentations (102?), g—obtaining (S07) a fourth plurality of foggy images (104) having dense fog, h—training (S08) using the previously obtained foggy images.

Abstract: A conveying system including a conveying channel, a reinforcement feed duct connected to the conveying channel at a reinforcement feed opening and configured to feed a reinforcement material to the conveying channel, and a blower configured to provide a blow in the reinforcement feed duct to push the reinforcement material towards the conveying channel. A compounding system including the same.

Abstract: A system for brain-based digital menu selection includes an acquisition device to obtain one or more electrical signals corresponding to an operator's brain response, a stimulation generation device to generate a first stimulus with one or more target options based on the operator triggering the system, a first database including a first classification model, and processor. The processor receives a first response from the acquisition device corresponding to an operator's brain response to the first stimulus with the one or more target options, determines a probability of intended target, when the probability of intended target option is higher than a predefined confidence threshold value, selecting the intended target option and presenting a second stimulus, or executing a final action, according to the selected target option, and storing the first response and the selected target option in the first database with a classification identifier identifying the operator.

Abstract: A method for producing a solid electrolyte for an all-solid state battery, the solid electrolyte having the following chemical formula XM2(PS4)3, where X is lithium (Li), sodium (Na), silver (Ag) or magnesium (Mg0,5) and M is titanium (Ti), zirconium (Zr), germanium (Ge), silicon (Si), tin (Sn) or a mixture of X and aluminium (X+Al) and the method including: mixing powders so as to obtain a powder mixture; pressing a component with powder mixture; and sintering component for a period of time equal to or greater than 100 hours so as to obtain the solid electrolyte. The solid electrolyte exhibits the peaks in positions of 2?=13.64° (±1°), 13.76° (±1°), 14.72° (±1°), 15.36° (±1°), 15.90° (±1°), 16.48° (±1°), 17.42° (±1°), 17.56° (±1°), 18.58° (±1°), and 22.18° (±1°) in a X-ray diffraction measurement using CuK? line. The disclosure is also related to a method of producing a solid electrolyte.

Abstract: A system and a method for processing a plurality of images, each image of the plurality of images being acquired by a respective image acquisition module of a vehicle and each image acquisition module being oriented outwardly with respect to the vehicle, the method comprising: elaborating a bird's eye view image of surroundings of the vehicle using pixel values of pixels of at least one portion of each image of the plurality of images as pixel values of the bird's eye view image, and performing, on the bird's eye view image, a detection of at least one lane marked on a surface on which the vehicle is and visible on the bird's eye view image.

Abstract: A control method for a host vehicle (100), comprising a) acquiring a speed (Vx) of the host vehicle, a relative speed (Vr) and distance (Dr) between a preceding vehicle (200) and the host vehicle (100); b) calculating a perceived risk level (PRL) as a function of said speed Vx of the host vehicle, said relative speed Vr, said relative distance Dr, and at least one of variables Vx*Vr and Vx2; and c) controlling at least one vehicle device (32, 34, 36, 38) of the host vehicle as a function of the perceived risk level (PRL). A computer program, a non-transitory computer-readable medium, and an automated driving system for implementing the above method.

Abstract: A traffic signal fixture verification system including an optical recognition means configured to obtain one or more images of two or more traffic signal fixtures in proximity to an ego vehicle, and to detect a motion status of one or more vehicles in proximity to the ego vehicle, a processing means configured to determine a relevance value for two or more traffic signal fixtures identified in the one or more images, monitor a status of each of two or more relevant traffic signal fixtures having a relevance value greater than a threshold value, and based on the relevance values of the two or more relevant traffic signal fixtures, the respective status of each of the two or more relevant traffic signal fixtures, and optionally, and/or the motion status of the one or more vehicles surrounding the vehicle, actuate an accelerator function or a braking function of the ego vehicle.

Abstract: A system and a method for processing an image so as to perform instance segmentation. The system/method includes: a—inputting (S1) the image (IMG) to a first neural network configured to output an affinity graph (AF), and b—inputting (S2), to a second neural network, the affinity graph and a predefined seed-map (SM), so as to determine whether other pixels belong to a same instance, and set at a first value the value of the other pixels determined as belonging to the same instance.

Abstract: A device and a method for representing the yaw orientation of a vehicle visible on an image, including: obtaining the position in the image of a rectangular bounding box surrounding the vehicle, obtaining the position of a vertical split line of the bounding box configured to be placed at a corner of the vehicle separating a first portion of the vehicle from a second portion of the vehicle, the first and second portion being either the front, the back, or a side of the vehicle, determining a signed horizontal shift of a horizontal position, associated with the vertical split line, with respect to a horizontal reference position, associated to the bounding box, normalizing the signed horizontal shift to obtain a value ? to be used in the representation of the pose of the vehicle.

Abstract: A method includes calculating a stereo-disparity map between the initial image and the final image, for each column of the stereo-disparity map, calculating an average value of the stereo-disparities of the pixels of the column, calculating the slope and/or constant factor of a linear function approximating variations of said average values; and calculating said information relative to the relative speed between the object and the camera, based on the slope and/or the constant factor.

Abstract: The disclosure relates to system for uploading data from a main vehicle to a cloud server, comprising: a first sensor configured to obtain geo localization information of the main vehicle; a second sensor configured to monitor at least one predetermined characteristic of the main vehicle and/or of the environment of the man vehicle; a communication unit configured to transmit a report to an external cloud server and configured to receive network information from the external cloud server via a wireless communications network, said network information comprising at least one locally varying characteristic of the wireless communications network across a geographic region, and an electronic control unit configured to: repeatedly generate reports by collecting the at least one monitored characteristic and transmit them in predetermined time intervals via the communication unit, modify the predetermined time intervals as a function of the received network information and the obtained geo localization information.

Abstract: The invention relates to a control device (1) for a vehicle for determining the perceptual load of a visual and dynamic driving scene. The control device is configured to: ?receive a sensor output (101) of a sensor (3), the sensor (3) sensing the visual driving scene, ?extract a set of scene features (102) from the sensor output (101), the set of scene features (102) representing static and/or dynamic information of the visual driving scene, ?determine the perceptual load (104) of the set of extracted scene features (102) based on a predetermined load model (103), the load model (103) being predetermined based on reference video scenes each being labelled with a load value, ?map the perceptual load to the sensed driving and ?determine a spatial and temporal intensity distribution of the perceptual load across the sensed driving scene. The invention further relates to a vehicle, a system and a method.

Abstract: The disclosed subject matter relates to a method for determining a type and a state of an object of interest, comprising: generating a depth map of a scene by means of a depth sensor, the scene containing the object of interest and an occlusion object lying between the depth sensor and the object of interest; computing three 2D occupancy views, each in a different viewing direction, and three 2D occlusion views; feeding each of said occupancy and occlusion views into a different input of a trained convolutional neural network; receiving both a class and a bounding box of the object of interest from the convolutional neural network; and determining the type of the object of interest and the state of the object of interest. The disclosed subject matter further relates to a system for carrying out said method.

Abstract: A method (100) for making a non-aqueous rechargeable metal-air battery is provided. The method includes before and/or after inserting (108) a cathode in the battery, a pre-conditioning step (104, 106, 110) of a 3D nanomesh structure, so as to obtain a pre-conditioned 3D nanomesh structure, the pre-conditioned 3D nanomesh structure being free of cathode active material. A cathode to be inserted into a non-aqueous rechargeable metal-air battery is also provided. The cathode includes a pre-conditioned 3D nanomesh structure made of nanowires made of electronic conductive metal material, the pre-conditioned 3D nanomesh structure being free of cathode active material. A non-aqueous rechargeable metal-air battery including such a cathode is also provided.

Abstract: An electronic device for a vehicle for augmenting image data of a passive optical sensor. The electronic device is configured to: receive first image data of a passive optical sensor, the first image data comprising a plurality of pixels in an image plane, receive second data of an active sensor, the passive optical sensor and the active sensor sensing the same scene outside the vehicle, the active sensor including a plurality of scan areas distributed over the scene, the second data including measurement values at returned scan areas, identify at least one cluster based on the distribution of returned scan areas, project the cluster onto the image plane, identify pixels which match with the projected cluster in the image plane, and associate the identified pixels with second data of the matching cluster. Further relates to a system and a method.

Abstract: The invention relates to a system for detecting objects in a digital image. The system comprises a neural network which is configured to generate candidate windows indicating object locations, and to generate for each candidate window a score representing the confidence of detection. Generating the scores comprises: generating a latent representation for each candidate window, updating the latent representation of each candidate window based on the latent representation of neighboring candidate windows, and generating the score for each candidate window based on its updated latent representation The invention further relates to a system for rescoring object detections in a digital image and to methods of detecting objects and rescoring objects.

Abstract: A method for identifying a cause of blockage in a sequence of images provided by a camera of a vehicle, the method comprising iteratively: S10) acquiring an image of the camera; successively acquired images forming a sequence of images; S20) detecting a blockage in last images of the sequence of images; S60) determining whether it is day-time or night-time based on time information; if it is determined that it is night-time: S82) determining whether toggling front light(s) of the vehicle on/off causes a change in images acquired by the camera; and S84) in this case, determining that for the current iteration, the cause of the blockage is presumably the road being dark. A computer program for performing said method, a computer-readable recording medium containing such computer program, a driving assistance system capable of executing said method.

Abstract: An electronic device for determining a semantic grid of an environment of a vehicle is provided. The electronic device is configured to: receive first image data of an optical sensor, the first image data comprising a 2D image of the environment, perform a semantic segmentation of the 2D image and project the resulting semantic image into at least one predetermined semantic plane, receive an occupancy grid representing an allocentric bird eye's view of the environment. The control device further includes a neural network configured to determine a semantic grid by fusing the occupancy grid with the at least one predetermined semantic plane.

Abstract: A composite material made of an amorphous (bi)metal sulfide nanoparticles directly linked, through coordinate covalent bonds, to a sulfur-containing polymer and a method of preparation of the composite material. The composite material can also be used as a catalyst for hydrogen production. Finally, a proton-exchange membrane (PEM) electrolyser and a photoelectrochemical cell, can both including the composite material.