Abstract: Systems and methods to provide contactless cards for transactions are disclosed. In an exemplary transaction provisioning system, an authentication server receives, from a backend server, a session creation request for provisioning a contactless card and transmits, to the backend server, a session creation response and a session token. The authentication server receives, from the backend server, an authentication process function request that includes encrypted data associated with the contactless card, decrypts the encrypted data to yield a decrypted authentication code, and compares the decrypted authentication code to an expected authentication code. After an unsuccessful comparison, the authentication server transmits, to the backend server, a notification indicating an unsuccessful authentication to the backend server.

Abstract: This disclosure relates generally to method and system for providing data privacy in service operations. Identifying risk arising from processing of user request in service operations is time consuming and monitoring insider threats is a difficult task. The method includes receiving a user request for a service comprising a plurality of sensitive attributes and further a vulnerability rating is assigned to each sensitive attribute. To mitigate the risk, the method estimates a disclosure proportion for the plurality of sensitive attributes and a masking operation is performed. Further, a sensitivity score is computed to allocate the user request to an agent associated with an agent registry with enabled data privacy and minimal data exposure. The agent is monitored by computing an agent mis-usability score to assess an insider threat risk. Additionally, a feedback alert is notified to autotune the plurality of privacy settings.

Abstract: A reconciliation engine and data reconciliation techniques are disclosed that partially use machine learning and natural language processing techniques to overcome challenges associated with traditional manual reconciliation engines and data reconciliation techniques without compromising the accuracy and handle the complexity of the features. In one aspect, a computer-implemented method is provided that includes: accessing a source and target table, performing intra-reconciliation on the source table, grouping the source and target table based on system configurations, reconciling data is iterated over each group, where the reconciling data includes: finding, using a machine learning model, a closest match for each group, and outputting the closest match for each group.

Abstract: Embodiments disclosed are directed to a computing system that performs steps for automatically capturing images. The computing system receives an automatic image capture control signal from an application installed on a device and captures, by a camera of the device during a predetermined time interval, preview frames of an object and a background. For each of the preview frames, the computing system identifies an outline of the object in the preview frame, removes the background of the preview frame based on the outline to generate a modified preview frame, and determines a focus value of the modified preview frame. Subsequently, the computing system determines whether a predetermined amount of focus values are greater than a threshold focus value corresponding to the device and, if so, automatically captures, via the camera, an image of the object.

Abstract: Carbon Capture, Utilization, and Storage (CCUS) is a relatively new technology directed to mitigating climate change by reducing greenhouse gas emissions. Current and new government requirements require proof that carbon dioxide (CO2) is either sequestered in a stable form or safely stored for long periods of time. In instances when the CO2 is sequestered through mineral formation, the need for long-term monitoring can be reduced, as the stability of the sequestered CO2 is inherent based on a chemical change in subterranean rocks. The reactions between CO2 and rock formations are influenced by numerous factors, including temperature, pressure, fluid composition, and the mineralogy of the formation. Furthermore, these reactions occur over large spatial areas and long timescales, making them difficult to monitor directly.

Abstract: Current approaches for identifying accretion in rotary kiln lack access to information regarding the internal condition of the rotary kiln such as temperatures of the wall, gas or solid bed and specific methodology that is required to calculate accretion and hence forecast. Present disclosure provides method and system for forecasting and diagnosing accretion in rotary kiln. The system first takes historical data associated with rotary kiln, real-time data, and a future time horizon information. Then, system predicts accretion scores for future time horizon based on received data using a pretrained accretion forecasting model which are further utilized to estimate a rate of accretion. Thereafter, the system identifies high accretion (HA) operating regime and low accretion (LA) operating regime over predefined time period. Further, system identifies one or more accretion variables responsible for causing each of the HA operating regime and the LA operating regime using an accretion diagnostic model.

Abstract: A system and method may update network policies by determining, among a set of hosts, a subset of hosts to have network policies updated; for each host in the subset of hosts, determining a set of policies relevant to the host; and for each of the subset of hosts, installing the set of policies relevant to the host. The subset of hosts may be determined based on a category or division such as the time zone corresponding to the location of each host in the subset of hosts. The policies relevant to the host may be received from a database and saved to a file with the set of policies relevant to the host; the host may then access the file.

Abstract: Systems and methods for a dual-pathway model that includes a deterministic word graph that operates in parallel with a semantic autocomplete model. The system generates outputs first using the deterministic word graph, and the system then uses the output of the deterministic word graph to determine whether to invoke the functionality of the semantic autocomplete model. By doing so, the semantic autocomplete model is used only sparingly, thus reducing aggregate latency in the system, but still allowing for increased scalability and customizability in the overall system as the deterministic word graph and the semantic autocomplete model may be updated and trained in parallel in the dual-pathway model.

Abstract: The present invention is a load transfer device and method of use comprising a pulley system attached to a universal pipe mount with a rope retention device. The load transfer device of the present invention allows for the maneuvering of appurtenances, such as antennas or other equipment from a load line rigged to a the main structure of a vertical infrastructure installation, to a desired installation location, such as on a standoff mount. The load transfer device helps to suspend the equipment or antenna in place above the desired installation location, enabling operators to use both hands to install the appurtenance.

Abstract: A tube plug for securely sealing a tube to be plugged. The tube plug has a housing member with a non-cylindrical body and a deformable wall. An insert member having a threaded shank and a ramped ferrule can be threaded into the body to deform the deformable wall outwardly and into engagement with the tube to be sealed. The non-cylindrical body allow the plug to be inserted into and used to plug a tube that is in a difficult to reach location and whose diameter may not be precisely known.

Abstract: Systems and methods for a dual-pathway model that includes a deterministic word graph that operates in parallel with a semantic autocomplete model. The system generates outputs first using the deterministic word graph, and the system then uses the output of the deterministic word graph to determine whether to invoke the functionality of the semantic autocomplete model. By doing so, the semantic autocomplete model is used only sparingly, thus reducing aggregate latency in the system, but still allowing for increased scalability and customizability in the overall system as the deterministic word graph and the semantic autocomplete model may be updated and trained in parallel in the dual-pathway model.

Abstract: A aerosol-generating system includes a liquid storage portion, a liquid pressure sensor within the liquid storage portion, and a control unit that is in communication with the pressure sensor. The aerosol-generating system further includes an atmospheric pressure sensor in communication with the control unit. The atmospheric pressure sensor is configured to sense the atmospheric pressure of the environment. The control unit is configured to receive the pressure signals from the liquid pressure sensor and the atmospheric pressure sensor. The control unit is further configured to determine the fill level of the liquid aerosol-forming substrate based on a comparison of the pressure signals from the liquid pressure sensor and the atmospheric pressure sensor.

Abstract: Existing Magnetic Resonance (MR) analysis approaches are either manual, which is time consuming and error prone, or automatic yet fail to identify correct landmarks. The disclosure herein generally relates method and system for MR image analysis. The system trains and uses a Generative adversarial network (GAN) for the MR image analysis. A generator network of the GAN generates a heatmap of a plurality of landmarks, by processing input data. Further, a discriminator network of the GAN, which has gradients updated based on a Modified Discriminator Loss (MDL) calculated based on a foreground pixel loss function and a standard discriminator loss, predicts each of a plurality of patches in a second input data as one of real and fake, based on presence of the one or more foreground pixel regions in the landmark heatmap in the ground-truth heatmap identified based on the foreground pixel loss function.

Abstract: A soluble fiber lozenge includes a body that is partially or wholly receivable in an oral cavity. The body includes a soluble-fiber matrix and one or more additives in the soluble-fiber matrix. A soluble fiber lozenge provided herein includes at least 40 weight percent of soluble fiber. Soluble fiber in soluble fiber lozenge can include maltodextrin. The soluble fiber lozenge is adapted to release one or more additives from the body when the body is received within the oral cavity of a consumer and exposed to saliva. A method of making soluble fiber lozenges includes forming a molten mixture of at least 40 weight percent soluble fiber, one or more additives, and less than 15 weight percent water while maintaining a mixture temperature of less than 200° C. and portioning the molten mixture into a plurality of soluble fiber lozenges.

Abstract: According to the present invention there is provided a composition for treating plant seeds for improvement of germination rate and/or improvement of early stage plant growth wherein the composition comprises at least one bioflavonoid and at least one organic acid. Preferably, the composition includes at least one wetting agent. More preferably, the at least one wetting agent is a natural plant extract. The at least one bioflavonoid may be a natural plant extract. Further, the organic acid may be a naturally produced organic acid.

Abstract: As discussed earlier, accretion happens to be the most critical problem faced by users of the rotary kiln as it leads to shutdown of the rotary kiln which ultimately leads to reduction in production. Currently available accretion monitoring systems require expensive equipment and sensors which increases the production cost. Present disclosure provides method and system for monitoring accretion happening inside the rotary kiln. The system first takes real-time data associated with a rotary kiln as input. The system then localizes accretion clusters present in the rotary kiln using an accretion localization model. Thereafter, the system estimates the accretion probability score based on the HTM statistics calculated based on the accretion cluster information and real-time data using an accretion scoring model. Further, the system compute accretion score representative of real-time accretion condition of the rotary kiln based on the accretion probability score and the inputs.

Abstract: At least some embodiments are directed to a prediction system of software objects. The prediction system predicts a first aspect of a user profile utilizing a categorization machine learning model and a user activity profile, the user profile and the user activity profile are associated with a user. The user activity profile comprises a plurality of values associated with demographics and historical activity data of the user. The prediction system predicts a software object associated with the user profile utilizing an optimization machine learning model, the first aspect of the user profile, and a second aspect of the user profile. The software object is optimized with respect to at least one competitive interest between the user associated with the user profile and an entity associated with the software object. The prediction system outputs the software object to a client computing device of the user.

Abstract: Graphene metasurface based linear to circular polarization converters in THz band plays a crucial role in beyond 5G/THz wireless systems. However, conventional converters suffer a trade-off between “high bandwidth”, “compact size” and “high field confinement”. The present disclosure provides a graphene metasurface based tunable linear to circular polarization converter to minimize the trade-off by operating at a large bandwidth of 800 GHz with considerable compact size and high field confinement. The linear to circular polarization converter of the present disclosure includes a metasurface comprising two-dimensional periodic array of unit cells along x-axis and y-axis, wherein each unit cell is a three-layered stacked structure with a predefined periodicity. The three-layered stacked structure includes a top layer, a middle layer and a bottom layer. The top layer is a single layer graphene. The middle layer is a dielectric substrate, and the bottom layer comprises thin layer of gold.

Abstract: Systems and methods for remotely closing a switch that is downhole in a wellbore are disclosed. The switch has a body with a first connector and a movable piston assembly with a second connector configured to mate with the first connector. The piston assembly has a first position wherein the first and second connectors are separated and a second position wherein the first and second connectors are mated. A spring is disposed between the body and the piston assembly and configured to urge the piston assembly toward the first position. When the fluid in the wellbore reaches a pressure above a threshold, the piston assembly will move to the second position thereby closing the switch.

Abstract: Systems and methods for a dual-pathway model that includes a deterministic word graph that operates in parallel with a semantic autocomplete model. The system generates outputs first using the deterministic word graph, and the system then uses the output of the deterministic word graph to determine whether to invoke the functionality of the semantic autocomplete model. By doing so, the semantic autocomplete model is used only sparingly, thus reducing aggregate latency in the system, but still allowing for increased scalability and customizability in the overall system as the deterministic word graph and the semantic autocomplete model may be updated and trained in parallel in the dual-pathway model.