Abstract: A system for generating a mask for object instances in an image is provided. The system includes a first module comprising a trained neural network and configured to input the image to the neural network, wherein the neural network is configured to generate: pixel offset vectors for the pixels of the object instance configured to point towards a unique center of an object instance, the pixel offset vectors thereby forming a cluster with a cluster distribution, and for each object instance an estimate of said cluster distribution defining a margin for determining which pixels belong to the object instance. A method for training a neural network map to be used for generating a mask for object instances in an image is also provided.

Abstract: A control device for a vehicle for determining perceptual load of a visual and dynamic driving scene, the control device being configured to: receive an image sequence representing the driving scene, extract a set of scene features from the image sequence, the set of scene features representing static and/or dynamic information of the driving scene, calculate a time-aggregated representation of the image sequence based on the extracted set of scene features, calculate an attention map of the driving scene by attentional pooling of the time-aggregated representation of the image sequence, and determine the perceptual load of the driving scene based on the attention map. The invention further relates to a corresponding method.

Abstract: A lithium-air battery cell wherein the positive electrode includes a solid p-type electroactive organic catalyst lithium salt and a battery pack including several lithium-air battery cells. The use of a battery pack as a rechargeable battery for vehicles, such as electric vehicles and hybrid vehicles, electronic devices, and stationary power generating devices. Finally, a vehicle, an electronic device, and a stationary power generating device, including a battery pack.

Abstract: A process for preparing a catalyst material, includes the steps of: (a) providing a support material having surface hydroxyl (OH) groups, wherein the support material is ceria (CeO2), zirconia (ZrO2) or a combination of thereof; (b) reacting the support material having surface hydroxyl (OH) groups of step (a) with a precursor containing two transition metal atoms, each chosen independently from the group consisting of: W, Mo, Cr, Ta, Nb, V, Mn; (c) calcining the product obtained in step (b) in order to provide a catalyst material showing dual site surface species containing pairs of transition metal atoms derived from the precursor that are present in oxide form on the support material. Additionally, a catalyst material is obtained by the process set out above, and the catalyst material is used as an ammonia selective catalytic reduction (NH3-SCR) catalyst for nitrogen oxides (NOx) reduction.

Abstract: A method for determining a driving intention of a user in a vehicle using electroencephalography (EEG) signals, comprising: acquiring (100) a plurality of EEG signals on a user in the vehicle, determining (101, . . . , 104) a plurality of features of the EEG signals, for each feature of the EEG signals, performing (111, . . . , 114?) a respective preliminary soft classification process, so as to obtain a plurality of preliminary soft predictions of driving intention each based on a feature of the EEG signals, performing (120) a soft classification process based on the plurality of preliminary soft predictions so as to obtain the driving intention of the user.

Abstract: A system for adjusting external position information of a vehicle driving on a road, including a sensor configured to sense a predetermined static lane object of the road, the vehicle driving on the road, and an electronic control device configured to: receive external position information indicating the vehicle position, detect the static lane object based on a sensor output received from the sensor, determine the position of the static lane object with regard to the vehicle position based on the received sensor output, and adjust the external vehicle position information by calibrating the vehicle position with regard to the determined position of the static lane object.

Abstract: A system and a method for processing an image include inputting the image to a neural network configured to: obtain a plurality of feature maps, each feature map having a respective resolution and a respective depth, perform a classification on each feature map to deliver, for each feature map: the type of at least one object visible on the image, the position and shape in the image of at least one two-dimensional bounding box surrounding the at least one object, a plurality of rotation hypotheses for the at least one object.

Abstract: An image obtaining means including: a processor; a memory module communicatively coupled to the processor; a camera communicatively coupled to the processor; and the processor being configured to: receive, from the camera, image data; determine whether a predetermined object is present based on the image data; if a predetermined object is detected as present, determine if the predetermined object is moving or stationary; and if the predetermined object is stationary for at least a predetermined time period, record the duration that the predetermined object is stationary in the memory module.

Abstract: A solid electrolyte material for a solid state battery (10) having the following chemical formula XM2(PS4)3, where P is phosphorus, S is sulfur and 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 exhibiting peaks in positions of 2?=13,64° (±1°), 16,48° (±1°) and 22,18° (±1°) in a X-ray diffraction measurement using CuK? line, where IA is the intensity in arbitrary units of the peak at 13,64° (±1°) and IB is the intensity in arbitrary units of a peak at 23,34° (±1°), (IA?IB)/(IA+IB)>0. The disclosure is also related to a solid electrolyte comprising the solid electrolyte material and a solid state battery comprising the solid electrolyte.

Abstract: A device for coating semiconductor/semiconductor precursor particles on a flexible substrate and a preparation method of a semiconducting thin film, wherein the device includes: a container for a first and second solvent substantially immiscible; injection means for injecting a predetermined dispersion volume of at least one layered semiconductor particle material or its precursor(s), occurring at a liquid-liquid interface formed within the container and between the first and second solvent, and creating a particle film at the liquid-liquid interface; a first support means; substrate extracting means; substrate supply means; compression means, reducing a distance between particles and push the film onto the substrate, wherein the compression means includes several pushing means mounted on a drive device, wherein at least two of the several pushing means are at least partially submerged in the second solvent during drive device rotation, and moved through the second solvent toward the first support means.

Abstract: A composition of general formula (1): Nax[MnaNibCrc]O2+y (1), wherein: 0.6?x?0.8; ?0.1?y?0.1; 0.55?a?0.7; 0.25?b?0.3; c?0.05; and a+b+c?1.0, an intermediate product for preparing a composition of general formula (1) and a process of synthesis, wherein the mixed sodium-transition metal oxide of general formula (1) may generally show an essentially or solely P2 structure, and may be used as a positive electrode material for a sodium ion secondary battery.

Abstract: A depth maps prediction system comprising a neural network (1000) configured to receive images (I) of a scene at successive time steps (t?1, t, t+1, . . . ) and comprising three sub-networks: an encoder (100), a ConvLSTM (200) and a decoder (300). The neural network (1000) is configured so that at each time step: a) the encoder sub-network (100) processes an image (I) and outputs a low resolution initial image representation (X); b) the CONVLSTM sub-network (200) processes the initial image representation (X), values for a previous time step (t?1) of an internal state (C(t?1)) and of an LSTM hidden variable data (H(t?1)) of the ConvLSTM sub-network, and outputs updated values of the internal state (C(t)) and of the LSTM hidden variable data (H(t)); and c) the decoder sub-network (300) inputs the LSTM output data (LOD) and generates a predicted dense depth map (D?) for the inputted image (I).

Abstract: A tracking system and an image obtaining means include: a processor; a memory module communicatively coupled to the processor; a pan-tilt camera including angle sensors communicatively coupled to the processor for tracking a predetermined object and sensing the coordinates of the pan-tilt camera; and machine readable instructions stored in the memory module that cause the image obtaining means to determine whether the predetermined object becomes lost within the image periphery of the image data; and if the predetermined object becomes lost, record the coordinates of the camera in the memory module where the predetermined has been tracked for the last time.

Abstract: A high strength cold rolled steel sheet has a composition consisting of the following elements (in wt. %):C 0.08-0.14, Mn 2.5-3.0, Si 0.7-1.1, Cr 0.05-0.4, optionally Al?0.2, Nb?0.1, Mo?0.1, V?0.1, Ti?0.1, Ca?0.05, Cu?0.1, Ni?0.2, B?0.005, balance Fe apart from impurities. The steel has a yield ratio ?0.72 and a bendability (Ri/t) is ?2.0. A method of manufacturing the steel sheet and an automotive structural part comprising the steel sheet also is provided.

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 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.