Abstract: A system for monitoring and improving social agent interaction quality includes a computing platform having processing hardware and a system memory storing a software code. The processing hardware is configured to execute the software code to receive, from a social agent, interaction data describing an interaction of the social agent with a user, and to perform an assessment of the interaction, using the interaction data, as one of successful or including a flaw. When the assessment indicates that the interaction includes the flaw, the processing hardware is further configured to execute the software code to identify an interaction strategy for correcting the flaw, and to deliver, to the social agent, one or both of the assessment and the interaction strategy to correct the flaw in the interaction.

Abstract: Systems and methods for using a differentiable multi-agent Actor-Critic (DiMAC) for multi-step radiology report summarization. The tasks of extracting salient sentences and phrases are divided across two collaborating agents that are trained end-to-end using reinforcement learning (RL).

Abstract: Evaluating examination scoring performance of exam evaluators is provided. Simulated examination sheets are generated that include new answer versions corresponding to examination questions regarding a particular subject matter for scoring by an exam evaluator. Each new answer version is generated based on a selected answer type comprised of a plurality of levels of a plurality of answer generating factors. A score is generated for each respective new answer version based on manipulation of model answers to the examination questions. An exam evaluation model of the exam evaluator scoring the new answer versions to the examination questions on the simulated examination sheets is formulated based on detected scoring deviations between computer-generated scores and evaluator-assigned scores for the new answer versions. Scores assigned by the exam evaluator to answers provided by a group of examinees to questions on the particular subject matter are adjusted based on the detected scoring deviations.

Abstract: A wireless communication network serves a wireless User Equipment (UE). The wireless UE exchanges user data over a data session of a Dynamic Network Name (DNN) while exchanging other user data over other data sessions of other DNNs. An Access and Mobility Management Function (AMF) receives a DNN message for the wireless UE and the DNN and responsively transfers a reattach message for the data session of the DNN to the wireless UE. The wireless UE receives the reattach message and responsively terminates the data session of the DNN and transfers a session message for the DNN to the AMF. The AMF receives the session message for the DNN and the wireless UE and responsively establishes a new data session for the DNN. The wireless UE exchanges new user data over the new data session of the DNN while exchanging additional user data over the other data sessions of the other DNNs.

Abstract: The present disclosure, in some embodiments, relates to a data protection method comprising: determining a file comprising content data on a computing system; generating index information for the file; transmitting the index information to a cloud system; executing a corruption operation on the file comprising: dividing the content data of the file into a plurality of data chunks; executing a first encryption operation based on an encryption protocol, on the first data chunk; executing a second encryption operation based on the encryption protocol, on the second data chunk; generating or assigning a first name for the first data and a second name for the second data chunk; and generating a key associated with an order of the first data chunk and the second data chunk.

Abstract: The present invention relates to solid oral pharmaceutical compositions comprising dexamethasone or its pharmaceutically acceptable salts or solvates thereof. The present invention also relates to a process for preparing solid oral pharmaceutical compositions comprising dexamethasone or its pharmaceutically acceptable salts or solvates thereof. The preferred drug load in the compositions of the present invention is from about 0.01% to 15% by weight based on the total weight of the composition. The prepared compositions of dexamethasone as per the present invention exhibit desirable technical attributes.

Abstract: An end-to-end trainable grouped mathematically differentiable non-maximal suppression (NMS) technique is presented for monocular 3D object detection. First, formulate NMS as a matrix operation and then group and mask the boxes in an unsupervised manner to obtain a simple closed-form expression of the NMS. This technique addresses the mismatch between training and inference pipelines and, therefore, forces the network to select the best 3D box in a differentiable manner. As a result, the proposed technique achieves state-of-the-art monocular 3D object detection results on the KITTI benchmark dataset performing comparably to monocular video-based methods.

Abstract: A system to detect quality of a silk cocoon is disclosed. The plurality of subsystems includes an image processing subsystem, configured to process the captured image of the one or more silk cocoons for noise. The plurality of subsystems includes an object detection subsystem, configured to detect cocoon contours from processed image. The plurality of subsystems also includes a cocoon analysing subsystem, configured to identify shape of the cocoon from the detected cocoon contours by using a shape function, compute a set of the parameters, validate the set of parameters with prestored parameters and determine the quality of each of the one or more silk cocoons based on the results of validation. The system uses OpenCV functions of python to do such complex work of grading silk cocoons. Such process reduces manual labour all together.

Abstract: Systems and methods of the present disclosure are directed to a computer-implemented method. The method can include obtaining a first image depicting a first object and a second image depicting a second object, wherein the first object comprises a first feature set and the second object comprises a second feature set. The method can include processing the first image with a machine-learned image transformation model comprising a plurality of model channels to obtain a first channel mapping indicative of a mapping between the plurality of model channels and the first feature set. The method can include processing the second image with the model to obtain a second channel mapping indicative of a mapping between the plurality of model channels and the second feature set. The method can include generating an interpolation vector for a selected feature.

Abstract: A system and method for learning human activities from video demonstrations using video augmentation is disclosed. The method includes receiving original videos from one or more data sources. The method includes processing the received original videos using one or more video augmentation techniques to generate a set of augmented videos. Further, the method includes generating a set of training videos by combining the received original videos with the generated set of augmented videos. Also, the method includes generating a deep learning model for the received original videos based on the generated set of training videos. Further, the method includes learning the one or more human activities performed in the received original videos by deploying the generated deep learning model. The method includes outputting the learnt one or more human activities performed in the original videos.

Abstract: This disclosure provides systems, devices, apparatus, and methods, including computer programs encoded on storage media, for an ML model training procedure. A network entity may receive a trigger to activate an ML model training procedure based on at least one of an indication from an ML model repository or a protocol of the network entity. The network entity may transmit an ML model training request to activate the ML model training at one or more nodes. The one or more nodes may be associated with a RAN that may transmit, based on receiving the ML model training request, ML model training results indicative of a trained ML model. In aspects, an apparatus, such as a UE, may train the ML model based on an ML model training configuration received from the RAN, and transmit an ML model training report indicative of the trained ML model.

Abstract: A target user equipment (UE), which may be a vehicle or UE carried by a pedestrian, may receive sequentially broadcast ranging signals from a set of ranging source entities (SEs), which may be road side units or other vehicles. The target UE further receives location information separately broadcast by each SEs. The location information, for example, may include the position for the SE, the time of transmission of the ranging signals transmitted by the SE and/or a sequence identifier for the SE. The target UE may determine ranges to the SEs using time of arrival measurements for the ranging signals and the time of transmissions of the ranging signals or the sequence identifier received in the location information. The position of the target UE may be determined using the determined ranges to the SEs and the positions of the SEs received in the location information.

Abstract: A levelling laser for generating a laser projection line on a surface is disclosed. The levelling laser includes an optical projection lens with a three-dimensional lens surface. The projection lens can be described in a three-dimensional coordinates system having three axes, X, Y and Z, arranged orthogonally to one another. The Z-axis coincides with the optical axis of the projection lens. The lens surface of the projection lens has a shape with a surface inclination angle rising monotonically along the X-axis. A corresponding projection lens is also disclosed.

Abstract: In certain aspects, the disclosure provides multispecific binders (e.g., ActRIIA:T?RII heteromultimers comprising an ActRIIA polypeptide and a TfiRU polypeptide). The disclosure further provides that such multispecific binders (e.g., ActRIIA:T?RII heteromultimer) may be used to treat various disorders or conditions.

Abstract: Method and apparatus for controlling loads connected to a distributed energy generation system. The method and apparatus display a list of loads, load status, load control state, where the load control state is manipulated through a user interface displayed on a user device. The load control state defines the operation of a load depending upon the operational status of the distributed energy generation system.

Abstract: A coating on a substrate is disclosed having layers including yttrium aluminum garnet (YAG) and yttrium aluminum monoclinic (YAM).

Abstract: In one embodiment, a device obtains data regarding routing decisions made by a machine learning-based predictive routing engine for a network. The device determines, based on the data regarding the routing decisions, a behavior of the machine learning-based predictive routing engine. The device compares the behavior of the machine learning-based predictive routing engine to a behavioral policy for the machine learning-based predictive routing engine. The device adjusts operation of the machine learning-based predictive routing engine, when the behavior of the machine learning-based predictive routing engine violates the behavioral policy.

Abstract: A request to execute a workload is received from a client device. The request includes identification information associated with one or more containers of multiple containers supported by one or more host systems of multiple host systems, where the one or more containers are to execute the workload. Corresponding communication endpoints associated with the one or more containers are identified in view of the identification information. One or more network connections are configured between the corresponding communication endpoints of the one or more containers and the client device while bypassing configuring other network connections between other containers of the multiple containers and the one or more containers and further network connections between the one or more containers that do not communicate with one another when executing the workload.

Abstract: Methods, systems and computer program products for data protection across computing infrastructure comprising a plurality of geographically distant computing clusters. The geographically distant computing clusters form a distributed system comprising clusters that are assigned into availability zones. Disaster recovery policies are maintained in each of the availability zones. A first cluster detects a modification of a disaster recovery policy. The modification of the disaster recovery policy that occurred at the first cluster is to be communicated over a wide area network. Synchronization of the disaster recovery policy is accomplished by carrying out a peer-to-peer communication protocol over the wide area network.

Abstract: Techniques that provide link establishment between a radio equipment controller (REC) and a radio equipment (RE) in a fronthaul network are described herein. In one embodiment, a method includes performing, Common Public Radio Interface (CPRI) Layer 1 (L1) link auto-negotiation operations to establish a CPRI link between the REC and RE. A proxy slave may achieve a hyper frame number (HFN) synchronization with the REC at a link bit rate for a first CPRI bit stream and communicate the first CPRI bit stream and the link bit rate to a proxy master. The proxy master may communicate a second CPRI bit stream to the proxy slave to transmit to the REC. The L1 link auto-negotiation operations are completed and CPRI link is established between the REC and the RE when the REC achieves a HFN synchronization for the second CPRI bit stream.