Abstract: There is provided a method and system for communication network management. There is provided an active TE architecture and procedure that rely on the epistemic uncertainty obtained from traffic forecasting models. According to embodiments, the traffic forecasting models can predict the mean of the network traffic demand and can extract one or more of the features relating epistemic uncertainty and the aleatoric uncertainty. According to embodiments, the epistemic uncertainty is used to vary the sampling frequency of network statistics in TE applications, for specific times or specific flows. A time-window can be used to predict network traffic can be varied (e.g. increased or decreased) to adjust the epistemic uncertainty.

Abstract: A method of enhanced oil recovery in a carbonate rock formation including injecting a mixture into the carbonate rock formation containing an oil composition and extracting the oil composition from the carbonate rock formation. The mixture includes 90-99.99 vol % of an aqueous solution and 0.01-10 vol % of a gemini cationic surfactant based on a total volume of the mixture and 1-2000 parts per million (ppm) of methylene blue, based on a total weight of the mixture. During the injecting at least a portion of the gemini cationic surfactant is adsorbed onto the carbonate rock formation, and at least 50% less by volume of the gemini cationic surfactant adsorbs onto the carbonate rock formation compared to a method under the same conditions but without the methylene blue.

Abstract: A method of enhanced oil recovery in a carbonate rock formation including, injecting a mixture into the carbonate rock formation containing an oil composition, and extracting the oil composition from the carbonate rock formation. The mixture contains 89-98.9 vol % of an aqueous solution, 0.01-1 vol % of a gemini cationic surfactant, and 0.1-10 vol % of formic acid based on a total volume of the mixture. During the injecting at least a portion of the gemini cationic surfactant is adsorbed onto the carbonate rock formation, and wherein at least 90% less by volume of the gemini cationic surfactant adsorbs onto the carbonate rock formation compared to a method under the same conditions but without the formic acid.

Abstract: A method of enhanced oil recovery in a carbonate rock formation including, injecting a mixture into the carbonate rock formation containing an oil composition, and extracting the oil composition from the carbonate rock formation. The mixture contains 89-98.9 vol % of an aqueous solution, 0.01-1 vol % of a gemini cationic surfactant, and 0.1-10 vol % of formic acid based on a total volume of the mixture. During the injecting at least a portion of the gemini cationic surfactant is adsorbed onto the carbonate rock formation, and wherein at least 90% less by volume of the gemini cationic surfactant adsorbs onto the carbonate rock formation compared to a method under the same conditions but without the formic acid.

Abstract: A method of enhanced oil recovery in a carbonate rock formation including, injecting a mixture into the carbonate rock formation containing an oil composition, and extracting the oil composition from the carbonate rock formation. The mixture contains 89-98.9 vol % of an aqueous solution, 0.01-1 vol % of a gemini cationic surfactant, and 0.1-10 vol % of formic acid based on a total volume of the mixture. During the injecting at least a portion of the gemini cationic surfactant is adsorbed onto the carbonate rock formation, and wherein at least 90% less by volume of the gemini cationic surfactant adsorbs onto the carbonate rock formation compared to a method under the same conditions but without the formic acid.

Abstract: A method of enhanced oil recovery in a carbonate rock formation including, injecting a mixture into the carbonate rock formation containing an oil composition, and extracting the oil composition from the carbonate rock formation. The mixture contains 89-98.9 vol % of an aqueous solution, 0.01-1 vol % of a gemini cationic surfactant, and 0.1-10 vol % of formic acid based on a total volume of the mixture. During the injecting at least a portion of the gemini cationic surfactant is adsorbed onto the carbonate rock formation, and wherein at least 90% less by volume of the gemini cationic surfactant adsorbs onto the carbonate rock formation compared to a method under the same conditions but without the formic acid.

Abstract: A method for predicting a blowdown rate of one or more boilers includes generating output data with a first model that specifies an empirical relationship between multiple input temperatures, multiple plant gas feed rates, and multiple outputs of the boilers. The method further includes collecting an ambient operating temperature and a current steam demand of the boilers and comparing the ambient operating temperature and the current steam demand to the output data to determine a current required blowdown rate. Once determined, the blowdown rate of the boilers is adjusted according to the current required blowdown rate.

Abstract: A variable orifice flow meter system includes a housing defining a flow passage and at least one plate extending into the flow passage and defining an orifice. The at least one plate is movably supported such that a size of the orifice may be adjusted. Upstream and downstream pressure sensors may measure fluid pressures upstream and downstream of the orifice and a drive mechanism may move the at least one plate. A controller may instruct the drive mechanism to move the at least one the plate such that a predetermined orifice size is defined in response to detecting an upstream pressure within a predetermined pressure range, determine a pressure differential across the orifice and calculate a flow rate through the flow passage based on the pressure differential when the pressure differential meets a predetermined threshold.

Abstract: There are provided a method, system and computer program product for preventing unauthorized use of a deep reinforcement learning agent. The DRL agents are trained to behave as expected only when they observe the one or more required secret operational keys. In some embodiments, the DRL agents are further trained to operate at a diminished capacity when the one or more required secret operational keys are unused.

Abstract: An automated vacuum sampling system comprising: a compressor in fluid communication with an upstream process line; downstream of the compressor, an inlet control valve; downstream of the inlet control valve, a sampling cylinder that includes an inlet quick-fitting valve and an outlet quick-fitting valve at either end of the cylinder, wherein an inlet quick-fitting valve is in fluid communication with the inlet control valve and the outlet quick-fitting valve is in fluid communication with an outlet control valve; a downstream tubing line fluidly connects the outlet control valve to a downstream process line; and, a control system communicably coupled to and programmed to operate the compressor, the inlet control valve, and the outlet control valve.

Abstract: Methods and systems that enable communication network traffic engineering functions or application functions using combinations of neural network (NN) encoders and NN decoders are provided. A first network element has a NN encoder deployed thereat and receives input data based on which the NN encoder generates a latent representation. The latent representation is provided to a second network element that has a NN decoder deployed thereat and is configured to process the latent representation in accordance with a traffic engineering function to produce a traffic engineering output, which may be used to modify an operational state variable of the communication network. The input data are values of operational state variables of the communication network obtained at the first network element.

Abstract: A method of automatic optimization of ROP. The method obtains a plurality of drilling surface parameters for a field of interest, and determines an UCS data and a MSE data for a targeted formation based on well logs. The method further trains a ML model using the drilling surface parameters as inputs, and outputs a plurality of weights for drilling parameters in a ROP equation and in a Teale's MSE equation for the field of interest. The method further combines the ML ROP equation with the Teale's MSE equation to determine a plurality of optimum drilling parameters by simultaneously solving the set of ML ROP equation and the Teale's MSE equation. Furthermore, the method generates a work order to adjust the drilling parameters and cause display of the work order and the determined optimum drilling parameters in a user interface of a client device.

Abstract: Intelligent query routing may be performed across shards of a scalable database table. A router of a database system may receive an access request directed to one or more database tables. The router may evaluate the access request with respect to metadata obtained for the database tables to determine an assignment distribution of computing resources of the database system to data that can satisfy the access request. The router can select planning locations to perform the access request based on the assignment distribution of the computing resources. The router can cause the access request to be performed according to planning at the selected planning locations.

Abstract: Disclosed is a method for detecting the numerology types and bands in the received signal without using any control information in the systems using mixed numerology (e.g. 5G standard) and to a signal receiving unit operating according to the method.

Abstract: A method for predicting a blowdown rate of one or more boilers includes generating output data with a first model that specifies an empirical relationship between multiple input temperatures, multiple plant gas feed rates, and multiple outputs of the boilers. The method further includes collecting an ambient operating temperature and a current steam demand of the boilers and comparing the ambient operating temperature and the current steam demand to the output data to determine a current required blowdown rate. Once determined, the blowdown rate of the boilers is adjusted according to the current required blowdown rate.

Abstract: A two-tier in vitro growth apparatus and method for cultivating Oestridae larvae and maggots is provided. The growth apparatus includes a top tier container and a bottom tier container where the top tier container has a growth container residing within the volume of the top tier container. The growth container is constructed of a semipermeable material and facilitates cultivating Oestridae larvae and maggots within an interior space of the growth container.

Abstract: Systems and methods include a computer-implemented method for determining risks of injector wells. Inputs for multiple risk criteria are received through an injector riskiness score (IRS) user interface for processing risks posed by an injector well to a new well being drilled in proximity to the injector well. A weighted sum of values corresponding to inputs for the risk multiple criteria is determined based on the inputs. An IRS score is determined based on the weighted sum. A determination is made whether the injector well has an IRS score above a predefined threshold. A shut-down recommendation for the injector well is identified in response to determining that the injector well has an IRS score above the predefined threshold.

Abstract: There is provided a method and system for communication network management. There is provided an active TE architecture and procedure that rely on the epistemic uncertainty obtained from traffic forecasting models. According to embodiments, the traffic forecasting models can predict the mean of the network traffic demand and can extract one or more of the features relating epistemic uncertainty and the aleatoric uncertainty. According to embodiments, the epistemic uncertainty is used to vary the sampling frequency of network statistics in TE applications, for specific times or specific flows. A time-window can be used to predict network traffic can be varied (e.g. increased or decreased) to adjust the epistemic uncertainty.

Abstract: There are provided a method, system and computer program product for preventing unauthorized use of a deep reinforcement learning agent. The DRL agents are trained to behave as expected only when they observe the one or more required secret operational keys. In some embodiments, the DRL agents are further trained to operate at a diminished capacity when the one or more required secret operational keys are unused.

Abstract: Some implementations of the present disclosure provide a computer-implemented method that includes: accessing measurement data obtained from a drilling operation, wherein the measurement data show multiple measurements during the drilling operation when a drilling bit is located at a range of depths; based on the measurement data, using machine learning analytics to construct a model that predicts a formation top when the drilling bit reaches a depth; determining a correlation between the measurement data and the predicted formation top; and in response to determining the correlation exceeds a pre-determined threshold, applying the model to predict a formation top when the drilling bit reaches the depth.