Bringer IP

A proton hop supported gas adsorption/desorption of carbon dioxide (CO₂) gas molecules in a sorbent powder is provided. The proton hop supported gas adsorption/desorption includes a configuration of liquid wetting amine particulate grains which is sufficient to suppress carbamic acid production from present CO₂ gas molecules in favor of carbonate production. Thereafter, CO₂ gas molecules interact with the liquid in proximity to an ingress surface of respective ones of the grains. Protons of the liquid proton hop from one amine location of a grain to another in correspondence to the progressive binding of resulting carbonates formed from the CO₂ gas molecules and the hydroxyls of the liquid, from locations nearest to the ingress surface towards locations nearest to an egress surface of the grains. The protons then rejoin with counterpart hydroxls reforming the liquid, whilst the CO₂ gas molecules each are released at the egress surface into a sequestration container.

L'invention concerne un procédé de détection et de lecture automatique qui débute par l'acquisition d'un nuage de points 3D et d'un flux vidéo de l'environnement ferroviaire à l'aide de capteurs montés sur le véhicule. Les rails sont détectés à partir de ce nuage de points, suivis par la création d'une représentation numérique tridimensionnelle des rails. Cette représentation est ensuite superposée sur les images vidéo pour créer des images enrichies. Une zone d'intérêt, correspondante à au moins une portion d'une zone prenant la forme de « U » inversée autour des rails projetés, est identifiée sur chaque image pour la détection de panneaux. Les panneaux détectés sont suivis et un panneau spécifique, associé à la voie, est sélectionné par analyse des trajectoires. Enfin, le procédé lit l'information lumineuse du panneau sélectionné, permettant la régulation de la marche du véhicule.

L'invention concerne un procédé de génération de consignes de validation de conduite d'un véhicule ferroviaire (1) circulant sur une voie ferroviaire (10) et équipé d'un capteur (2.1), de détection et/ou de lecture de la signalisation ferroviaire (5) destinée à réguler la marche dudit véhicule ferroviaire (1), le procédé comprenant les étapes : - une étape (P1) de détection et/ou de lecture de la signalisation ferroviaire (5) ; - une étape (E1) de génération d'une consigne de conduite (CC1) du véhicule ferroviaire ; - une étape (P2) d'acquisition d'au moins une donnée (d) relative à une grandeur physique de l'environnement de la voie ferroviaire (10), - une étape (E2) de détermination d'une consigne (C) de validation de conduite dudit véhicule ferroviaire (1).

Industrial hazard alert and visualized audit includes the receipt of sensor data from different sensors positioned in a geographic zone of interest at an industrial site, the computation of a position of one or more objects in the geographic zone of interest and the determination whether or not a hazardous condition has arisen based upon a proximity of a worker and the computed position. In response to the hazardous condition, an alert is generated in connection with the worker, an identity of the hazardous condition is stored along with the sensor data and the computed position within an audit record in an audit data store. Further, a graphical visualization is generated of the hazardous condition from the computed position and at least a portion of the sensor data. Finally, the graphical visualization is stored in the audit record for retrieval in visualizing the hazardous condition.

Spatial upscaling for greenhouse gas flux quantification over a sparsely sensed geographically bounded region includes configuring a data structure to include a number of uniform spatial units, each representing a location within a geographically bounded area. Greenhouse gas flux data are received from different sensors disposed within the area and are stored in the corresponding uniform spatial units of the data structure. For each uniform spatial unit not associated with a disposed sensor, environmental context data for that location are selected. A flux model is queried with the retrieved environmental context data to estimate the greenhouse gas flux for that spatial unit. A token is then generated from the data structure indicative of a total mass of greenhouse gas emitted/sequestered across all locations within the larger geographically bounded area.

Collision regulation of non-rigid objects conveyed for processing in a machine includes a selection of a collision model for a specified object type of a non-rigid object. Thereafter, an arrangement of objects of the specified object type is sensed on a conveyance for a machine adapted to process the objects. The collision model is then queried for a collision state of the objects prior to conveyance into the machine and, in response to the querying, a collision metric is received from the collision model. Finally, the collision metric is matched to a regulated set of machine configuration parameters and so that the regulated set is applied to the machine.

The dynamic demarcation of danger zones in a factory floor includes remote sensing an arrangement of objects on the factory floor, such as a proximity of one object to another object on the factory floor, or a proximity of an object on the factory floor to a location at which a human is proximate. Dynamic demarcation also includes determining a risk factor for the arrangement. Dynamic demarcation additionally includes comparing the risk factor to a threshold value. Finally, dynamic demarcation includes responding to the risk factor exceeding the threshold value by defining a boundary.

A cathode regeneration system for the regeneration of a lithium-ion battery cathode includes a relithiation tank comprising spent lithium-ion battery cathode material immersed in a lithium aqueous electrolyte with a redox mediator and lithium containing salt, an electrochemical reactor coupled to the relithiation tank and regenerating the redox mediator in the electrolyte, a counter tank coupled to the reactor and receiving accumulated lithium ferricyanide from the reactor while supplying the electrolyte to the reactor, an electrochemical cell coupled to the counter tank and regenerating the electrolyte for the counter tank and a waste tank coupled to the electrochemical cell and receiving oxygen waste from the electrochemical cell.

The quantification and persistence of imaged food includes the acquisition of imagery by an optical sensor of a digital camera such as that included within a smart phone. The optically sensed imagery is then loaded into memory and a food portion can be identified therewithin. Subsequently, a food waste value is computed of the identified food portion and the food waste value is encapsulated within a digital artifact to be written into the memory. Finally, the digital artifact is uploaded into a secure ledger entry from over a computer communications network, such as an entry in a blockchain ledger.

Artificial Intelligence (Al)-assisted model selection for a social interaction engine includes the establishment of a communications link to an agent-based model (ABM) from over a computer communications network and the generation of a network of social interactivity amongst actors in the network. Al-assisted model selection additionally includes a selection in the fixed storage of the host computing platform of a social interaction model for social interactions on the generated network of social interactivity, based upon a characteristic of the generated network, that include at least an opinion dynamics model or a psychological/behavioral model. Thereafter, the ABM is configured with agent and network parameters according to the selected social interaction model in order for the ABM to simulate mediated agent interactions representative of interactions amongst the actors of the generated network. Finally, an ABM based simulation is simulated for the generated network with the outcome of the simulation recorded in the fixed storage.