Systems and methods of optimizing enhanced oil recovery fluids in the form of a hydrocarbon foam, an emulsion based foam, an emulsion, and a gelled enhanced oil recovery fluid, each comprising Y-Grade NGL, which is an unfractionated hydrocarbon mixture that comprises ethane, propane, butane, isobutane, and pentane plus, wherein the unfractionated hydrocarbon mixture is a byproduct of a condensed and demethanized hydrocarbon stream.

This control device of a machine tool is provided with: a storage unit which stores in advance a nominal diameter and a nominal length of a blade part of a rotary tool; an image-capturing instruction unit which outputs an image-capturing instruction to an image-capturing device; a model creation unit which generates model data of the blade part of the tool on the basis of the nominal diameter and the nominal length stored in the storage unit, generates model data of a tool shank and holder on the basis of an image stored in the image-capturing device, and creates model data of the rotary tool on the basis of the generated model data of the blade part and the generated model data of the tool shank and holder.

A method for cementing a borehole includes pumping a collection of fluids into the borehole through a tubular string in the borehole, flowing the collection of fluids up an annulus positioned between the tubular string and a sidewall of the borehole, monitoring a volume of the fluids pumped into the borehole, performing a first estimation of a position of the fluids based on the volume of the collection of fluids pumped into the borehole, and an initial estimate of an average diameter of the sidewall of at least a portion of the borehole, calculating a corrected estimate of the average diameter based on the first estimation and a pressure of the fluids measured at an inlet of the tubular string, and performing a second estimation of the position of the fluids based on the volume of the fluids pumped into the borehole and the corrected estimate of the average diameter.

A system and approach for catalyst model parameter identification with modeling accomplished by an identification procedure that may incorporate a catalyst parameter identification procedure which may include determination of parameters for a catalyst device, specification of values for parameters and component level identification. Component level identification may be of a thermal model, adsorption and desorption, and chemistry. There may then be system level identification to get a final estimate of catalyst parameters.

Disclosed is a computer-based method for automatically detecting characteristics of a complex software system. This system can be implemented with networked physical devices such as workstations, using portable devices and smaller IoT devices, and on devices that are virtualized. The method includes receiving machine-readable information about the computers, including information services and software, and building and storing a machine-readable model based on the received information. The model can be a stratified machine-readable model of the software, services, and further computer aspects. The method can also include updating the model and responding to user commands to access both stored and updated models, and/or displaying tagged and/or filtered visual representations of the model to the user. A learning method can be applied to the network using the machine-readable model, with the applying accessing artificial intelligence tags for the model, and associating artificial intelligence tags to elements of the model based on the application of the learning model to the network.

Disclosed is a computer-based method for automatically detecting characteristics of a complex software system. This system can be implemented with networked physical devices such as workstations, using portable devices and smaller IoT devices, and on devices that are virtualized. The method includes receiving machine-readable information about the computers, including information services and software, and building and storing a machine-readable model based on the received information. The model can be a stratified machine-readable model of the software, services, and further computer aspects. The method can also include updating the model and responding to user commands to access both stored and updated models, and/or displaying tagged and/or filtered visual representations of the model to the user. A learning method can be applied to the network using the machine-readable model, with the applying accessing artificial intelligence tags for the model, and associating artificial intelligence tags to elements of the model based on the application of the learning model to the network.

A beer making system may modify a beer ingredient/process recipe to adjust sensory characteristics of a desired beer. With a given ingredient list and starting recipe, a performance model of a brewing system may be used to generate an updated recipe when given a set of desired sensory characteristics of a desired beer. A user interface may permit a user to adjust characteristics such as thin/thick mouthfeel, dryness/maltiness, hops bitterness, hops flavor, hops aroma, and other characteristics. An updated recipe may change mashing schedules, boiling schedules, or other programmatically controlled aspects of a brewing system. The performance model may include heuristics as well as performance metrics derived from observing previous brewing sessions on one or multiple devices.

Method and apparatus for mechanical sex-sorting of mosquitoes by extracting a class of mosquitoes from unsorted mosquitoes comprises obtaining unsorted mosquitoes, obtaining images of individual mosquitoes in a stationary phase, electronically classifying the individuals from the images into male mosquitoes and/or female mosquitoes, and possibly also unclassified objects; obtaining co-ordinates of individuals of at least one of the male mosquito and female mosquito classifications, and using a robot arm to reach an individual identified by the obtained coordinates to store or remove the individuals, thereby to provide sex-sorted mosquitoes.

Apparatus for automatic loading of pupae into cartridges for growing, hatching into adults and dispersal of the adults, comprises: a pupa tray of pupae in liquid. A cartridge hatches the pupae into adults and may be placed in a dispersal machine for dispersal of the adults. The cartridge has a drainage hole covered in netting at a lower end, and when filled with pupae and needing water, may be placed in a water tray to retain water in the cartridge. Then, following hatching of the pupae, the cartridge is lifted from the water tray to drain via the drainage hole to provide a dry environment for the adults.

A virtual training system includes a computing processor, a virtual reality (VR) headset and a sensor to determine a VR hand position. The processor is configured according to computing instructions in a memory device for displaying a first VR scene that includes a first VR object. A second VR scene is displayed within a visual portal in the first VR scene that includes a second VR object. A user VR hand image is displayed in at least one of the first VR scene and the second VR scene based upon the determined VR hand position.