Abstract: An inflow control valve hammer system may include a ram disposed adjacent a valve feature, a hammer device configured to drive the ram into the valve feature, and a retention feature configured to hold the hammer device in a loaded position. The retention feature is configured to release the hammer device to impact the ram in response to a threshold force being exerted on the hammer device, and the impact drives the ram to jerk the valve feature. Additionally, the inflow control valve hammer system may include a spring and an actuator. The spring may be disposed adjacent the hammer device. The spring is configured to exert the threshold force on the hammer device in an energized state. Further, the actuator is configured to energize the spring into the energized state.

Abstract: Multi-object tracking (MOT) in video sequences plays a critical role in various computer vision applications. The primary objective of MOT is to accurately localize and track objects across consecutive frames. However, existing MOT approaches often suffer from computational limitations and low frame rates in commodity machines, which hinders real-time performance. Present disclosure provides method and system for performing content aware multi-object tracking. The system first classifies video into slow and fast moving object content videos depending on features of objects to be tracked in frames. Then, system applies a computationally intensive deep sort algorithm to perform tracking of objects by selectively skipping frames.

Abstract: State of art techniques, need a decoder following the encoder to encode EEG signals, whose morphology is undefined. Embodiments herein disclose a method and system for a Spiking Neural Network (SNN) based low power cognitive load analysis using electroencephalogram (EEG) signal. The method receives a raw EEG signal from multichannel EEG set up, wherein each of the raw EEG signal is re-referenced and encoded into a spike train using a Light-Weight-Lossless-Decoder less-Peak-based (LWDLP) encoding. Further, the spike trains are processed by the SNN architecture using backpropagation based supervised approach, wherein the spatial information and the temporal information are learnt by the SNN in form of neuronal activity and synaptic weights. Post learning the SNN architecture applies an activation function on the neuronal activity for classifying a cognitive load level experienced by a subject from among a plurality of predefined cognitive load levels using a SNN classifier.

Abstract: Apparatuses, methods, and systems for detecting the presence of a beacon are disclosed. An embodiment includes a vehicle that includes a load arm configured to receive a bin, a first detector configured to receive a first wireless signal when the load arm is in a first position, and receive a second wireless signal when the load arm is in a second position, a second detector configured to receive a third wireless signal when the load arm is in the first position, and receive a fourth wireless signal when the load arm is in the second position, and a controller configured to detect presence of the beacon attached to an object within the bin based on the received signal strengths of the first wireless signal, the second wireless signal, the third wireless signal and the fourth wireless signal.

Abstract: Methods and systems are described herein for minimizing development time in artificial intelligence models by automating model selection based on dataset fittings of time-series data prior to hyperparameter optimization. For example, the system may apply a profiling model using a time-series embedding of the dataset combined with the aggregate statistical profile. In either case, the profiling model may be trained on the scoring policy and/or a time-series embedding of the dataset combined with the aggregate statistical profile to determine a likelihood of the effectiveness of a given model on the given dataset and/or likely hyperparameters for the given model.

Abstract: Systems and methods for minimizing development time in artificial intelligence models by automating model selection based on dataset fittings of time-series data prior to hyperparameter optimization. The systems and methods use a scoring policy based on a plurality of labeled datasets that score one or more results contained within the aggregate statistical profile. The system may dynamically identify particular criteria in statistical data that indicates an effectiveness of a given model on a given dataset. These criteria (e.g., the scoring policy) may then be updated over time as new datasets, statistical analyses, and/or aggregated statistical profiles are developed within affecting the underlying models and/or datasets.

Abstract: The invention provides an isolated and purified nucleic acid sequence encoding a chimeric antigen receptor (CAR) directed against B-cell Maturation Antigen (BCMA). The invention also provides host cells, such as T-cells or natural killer (NK) cells, expressing the CAR and methods for destroying multiple myeloma cells.

Abstract: Aspects of the subject disclosure may include, for example, deploying UAVs to a geographic area based on a need to offload traffic from a terrestrial base station, instructing the base station to enforce a UE served by the base station to determine a DoA of a received pilot signal emitted from each neighboring cell and to provide determined DoAs in a measurement report to the base station, obtaining the report from the base station, wherein the report includes DoA information for a plurality of neighboring cells, analyzing the DoA information to determine, for each neighboring cell of the plurality of neighboring cells, a probability of that neighboring cell being an aerial cell, resulting in determined probabilities, and controlling an ability of the base station to perform a handover of the UE to one or more of the plurality of neighboring cells based on the probabilities. Other embodiments are disclosed.

Abstract: The uncertainty of availability and risk associated with the cost of power procurement hinders the consumer from using new sources of supply/storage devices or taking part in the competitive power markets or procuring power from green energy resources. Present disclosure provides a method and a system for optimal scheduling of power sources for meeting electricity demand of enterprise. In particular, the system performs portfolio optimization formulation for cost, risk and carbon emission minimization for the enterprise. The portfolio optimization formulation simulates market scenario and guides in providing effective power purchase strategy for enterprise along with real-time adjustments. In particular, the level of risk to be considered along with cost of power procurement and carbon footprint determine portfolio allocation for each time block in portfolio optimization formulation.

Abstract: A method, a system, and a computer program product for transmission of information over a network. A validity token is generated based on a received contactless card identifier associated with a contactless card. The validity token is generated upon validating the contactless card using the contactless card identifier, and transmitted to a first computing device. A second computing device is identified based on an information request received from the first computing device. The information request includes a first public key associated with the first computing device and the validity token. An encrypted response to the request and a second public key associated with the second computing device are sent to the first computing device. The second computing device generates the encrypted response and encrypts it using a shared key generated using the first public key. The first computing device decrypts the response upon generation of the shared key using the second public key.

Abstract: Methods and systems are described herein for minimizing development time in artificial intelligence models by automating model selection based on dataset fittings of time-series data prior to hyperparameter optimization. The system may select a statistical profile type to identify in a first dataset. The system may retrieve a statistical model corresponding to the statistical profile type. The system may select, based on a first statistical profile, a first untrained model from a first plurality of untrained models for training, wherein the first plurality of untrained models comprises respective algorithms for time-series forecasting and wherein each of the first plurality of untrained models comprises default hyperparameter tuning. The system may, based on selecting the first untrained model, tune a first hyperparameter of the first untrained model using the first dataset.

Abstract: A method includes receiving, by aggregator platform computer from a user device of first user, remittance message including at least a service amount for service rendered by second user to the first user; identifying, by the aggregator platform computer, that the remittance message includes an additional amount that accompanies the service amount; upon identifying that the remittance message includes the additional amount, forwarding, by the aggregator platform computer to a plug-in computer, the remittance message including the service amount and the additional amount; identifying, by the plug-in computer in the remittance message, the service amount and the additional amount; and separating, by the plug-in computer, the service amount from the additional amount. The plug-in computer facilitates transfer of the additional amount from an account of the first user to an account of the second user and sends, to the aggregator platform computer, a service remittance message including the service amount.

Abstract: Disclosed are compounds of Formula (I), pharmaceutically acceptable salts thereof, and methods of preparation thereof, wherein R1, Xa, Xb, Xc, and Xd are as described in the specification. Further disclosed is an isotopic mixture of a compound of Formula (I), as well as a pharmaceutical composition containing a hyperpolarized compound of Formula (I). Also disclosed is a method of diagnosing or monitoring a patient suffering from cancer, the method including administering a pharmaceutical composition comprising an effective amount of a hyperpolarized ketoglutarate compound or a pharmaceutically acceptable salt thereof, and measuring the hyperpolarization of a compound of interest in the patient. Further disclosed is a method of preparing hyperpolarized ketoglutarate compounds for use in the above methods.

Abstract: One or more surface features (e.g., capacitive buttons, fingerprint sensor) may be exposed on a surface of a card (e.g., chi payment card). The card may store multiple applications/accounts of a user. The card receives a selection of one of the accounts by the user placing a finger on or pressing on a surface feature associated with the selected account. The card provides credentials associated with the selected account to a terminal. The multi-application card may disable credentials associated with the remaining accounts thereby appearing as a single-application card to the terminal during a transaction.

Abstract: Methods and systems are described herein for minimizing development time in artificial intelligence models by automating model selection based on dataset fittings of time-series data prior to hyperparameter optimization.

Abstract: The disclosure relates generally to methods and systems for predicting water quality of a river having a varying river ecosystem. Due to multiple and diverse factors, understanding and estimating the water quality of the river stream (river itself) is extremely and technically challenging. The present disclosure discloses a development of a river digital twin model utilizing a multi-modeling approach to comprehensively model the river and its varying ecosystems. The agents encompass entities that directly or indirectly introduce effluents or withdraw water from the river. Agents and their interactions are defined using a combination of behavior rules, correlations, and physics principles, creating the digital twin model that closely mimics the real river system. Physics-based equations are also employed in the present disclosure to capture the dynamics of the river, while relationships between different agents are established.

Abstract: Methods and systems are described herein for updating cybersecurity enforcement rules in real-time over disparate computer networks. A rule enforcement system may receive a real-time data stream. The real-time data stream may include real-time communications requiring cybersecurity verification. Real-time data communications are processed through a first rule repository. In response to determining that rule updates to rules within the first rule repository are available, a second rule repository is retrieved and brought online. Previously received real-time communication data is processed with the first rule repository and new real-time communication data is routed to the second rule repository. When previously received real-time communication data has been processed, the first rule repository is disabled.

Abstract: Current OT security solutions mostly provide defensive security involving monitoring and network segmentation. However, offensive security, proven effective in IT systems, is not easily applicable to OT systems due to its sensitive nature and high availability requirements. To conduct offensive security measures in OT networks, the concept of Digital Twins emerges as a viable solution but with limited progress in developing virtual replicas that accurately simulate real environments. Further, the process of creating such replicas is inherently complex and time-consuming, often involving extensive manual work. The present invention discloses an environment named as “Battle Twin,” a specialized playground designed for breach and attack simulations specifically designed for OT networks. Battle Twin focuses on mimicking the security posture of the underlying network rather than replicating its production or behavioral aspects.

Abstract: Embodiments of the present invention are directed to methods and systems for managing a cryptocurrency payment network comprising one or more issuer nodes and one or more distributor nodes. Issuer nodes may be granted different rights from distributor nodes with respect to the issuance and distribution of digital currency within the cryptocurrency payment network. A management system server computer may generate unique node verification key pairs for each node in the cryptocurrency payment network, where the node verification key pairs may be used to identify and authenticate issuer nodes and distributor nodes.

Abstract: Methods and devices for vaporization with a device comprising a liquid input, a gas output, and one or more plates arranged below the liquid input. The one or more plates are configured to receive liquid in droplet form from the liquid input and generate gas by vaporizing the droplets, and the generated gas exits the device via the gas output. The device may include a conduit, such as a pipe carrying a fluid such as engine coolant or other heat source, where the one or more plates are mounted on the conduit or heat source.