Abstract: Systems, methods, and other embodiments for supporting high availability by using in-memory cache as a database are disclosed. In one embodiment, a system includes an application server that is configured to select a sub-set of data from a remote database that is predicted to be accessed by an application server, wherein the application server includes an in-memory cache. The sub-set of data is reformatted to reduce the size. The in-memory cache is configured to act as a backup database by pre-populating the reformatted sub-set of data into the in-memory cache. In response to detecting the remote database is in an off-line state: the in-memory cache is assigned as a primary database to replace the remote database and subsequent data requests are re-directed from being processed using the remote database to being processed using the in-memory cache.

Abstract: Cooperative session orchestration includes devising a crypt for pre-distribution of tokens, distributing the tokens to member nodes of the network, based on a request from a delegate node of the network for brokerage of a session between the delegate node and a supplier node of the network, creating and sending, for each of a plurality of potential supplier nodes of the network, a respective individual puzzle, receiving, from each of one or more potential supplier nodes of the plurality of potential supplier nodes, a respective result obtained by the potential supplier node from solving the individual puzzle using the token distributed to the potential supplier, identifying, based on the receiving, candidate supplier node(s) of the one or more potential supplier nodes as a potential supplier for the session with the delegate node, and identifying to the delegate node the candidate supplier node(s) for the session with the delegate node.

Abstract: Prioritizing a work request pertaining to a physical asset can include generating a data structure that encodes the work request as a multidimensional representation indicating at least one classification, each at least one classification including at least one sub-category. In response to identifying multiple work requests encoded as multidimensional representations with respect to the physical asset, each multidimensional representation can be reduced to a one-dimensional (1-D) representation that preserves a variance factor of each sub-category of each multidimensional representation. Each 1-D structure can be input to a machine learning model trained to prioritize each of the work requests. The work requests can be prioritized in accordance with the machine learning model based on the 1-D structures. The priorities of each of the work requests can be output.

Abstract: A logical graph is generated using at least a portion of log data received from a set of agents executing on one or more nodes in one or more data centers. The logical graph is augmented using data obtained from one or more agents executing in containerized environments, including by representing communications between pods within the logical graph. The augmented logical graph is used to detect an anomaly.

Abstract: Detecting anomalous behavior using a browser extension, including: gathering first information describing activity associated with a user and generated by a browser extension on a user device; gathering second information describing activity associated with the user and generated by an application executed on the user device; and determining, based on the first information and the second information, whether the user has deviated from normal activity.

Abstract: In implementations of context-based copy-paste systems, a computing device implements a context system to receive input data describing a selection of a vector object. The context system detects vicinity vector objects based on a bounding box of the vector object and bounding boxes of the vicinity vector objects. A transformation is identified based on similarities between the vicinity vector objects and target vector objects. The context system generates a modified vector object for display in a user interface by transforming the vector object using the transformation and reproducing the transformed vector object relative to a particular target vector object of the target vector objects.

Abstract: A request to perform a secure erase operation for a memory component can be received. A voltage level of a pass voltage that is applied to unselected wordlines of the memory component during a read operation can be determined. A voltage pulse can be applied during a program operation to at least one wordline of the memory component to perform the secure erase operation. The voltage pulse can exceed the pass voltage applied to the unselected wordlines of the memory component during the read operation.

Abstract: A module of a processing system for flipping a substrate in vacuum includes a clamp assembly for securing the substrate, a first motor assembly coupled to the clamp assembly for rotating the clamp assembly, and a second motor assembly coupled to the first motor assembly for raising and lowering the first motor assembly and the clamp assembly.

Abstract: A processing device detects a read operation at a memory device that is directed at a word line group from among multiple word line groups of the memory device. The processing device increments a read counter associated with the word line group based on the read operation being directed at the word line group. The processing device determines the read counter exceeds a read-disturb threshold and performs read-disturb handling on the word line group in response to determining the read counter exceeds the read-disturb threshold.

Abstract: A processing device, operatively coupled with a memory device, is configured to perform a write operation on a page of a plurality of pages of a data unit of a memory device. The processing device further generates a parity page for data stored in the page of the data unit and associates the parity page with parity data associated with the data unit. Responsive to determining that a first size of the parity data is larger than a first threshold size, the processing device compresses the parity data. Responsive to determining that a second size of the compressed parity data is larger than a second threshold size, the processing device releases at least a subset of the parity data corresponding to a subset of the data that is free from defects.

Abstract: An approach for assessing terms and conditions (TnC)s of a legal agreement is provided. A block of text, which contains a TnC of the set of TnC, in the legal agreement is identified using a cognitive system. A standardized significance value is assigned to the TnC by the cognitive system by applying the TnC to a TnC model containing corresponding industry TnCs from industry standard documents. A block currency that indicates a significance of an impact of the TnC to a contract party is computed for the TnC by the cognitive system. Based on the standardized significance value and the block currency, a personal impact of the TnC to the contract party is assessed by the cognitive system. The contract party is alerted to the TnC and the personal impact corresponding to the TnC.

Abstract: The present invention relates to compositions comprising clofazimine and methods for treating cancer. In various embodiments, the compositions and methods further comprise a proteasome inhibitor and/or immunomodulatory drug. The compositions and methods of the present invention may be used for naïve cancers as well as those that have developed resistance to proteasome inhibitors and/or immunomodulatory drugs.

Abstract: Embodiments are disclosed for identifying and generating symmetrical repeat edits to similar objects in an image. A selection of a first object and an edit to the first object in an image is received. The image is searched for a plurality of candidate objects that have a similar shape to the first object and the plurality of candidate objects are filtered to include one or more objects that are symmetrical with the first object. A symmetric object is selected from the plurality of candidate objects. An axis of symmetry is computed between the symmetric object and the first object. The edit is applied to the symmetric object and to the first object.

Abstract: Setting a primary server within a business density cluster when the business density location changes. A new primary edge provisioning server replaces a current primary edge provisioning server when the business density cluster is determined not to include the current primary edge provisioning server. An edge provisioning framework handles the associations and dissociations of the edge network(s) to build the new primary server within the business density cluster. The former primary server is respawned as a new secondary node to the new primary server.

Abstract: Provisioning business functions is provided. A runtime binary activation code is sent to a nodal edge server that has a needed runtime binary for a set of edge devices to perform a business function. A secure shell protocol connection with root operating system access is established to the nodal edge server that has the needed runtime binary to execute the runtime binary activation code.

Abstract: Systems and methods for video representation learning using triplet training are provided. The system receives a video file and extracts features associated with the video file such as video features, audio features, and valence-arousal-dominance (VAD) features. The system processes the video features, audio features, and VAD features using a hierarchical attention network to generate a video embedding, an audio embedding, and a VAD embedding, respectively. The system concatenates the video embedding, the audio embedding and VAD embedding to create a concatenated embedding. The system processes the concatenated embedding using a non-local attention network to generate a fingerprint associated with the video file. The system then processes the fingerprint generate one or more of a mood prediction, a genre prediction, and a keyword prediction.

Abstract: In implementations of systems for visual reordering of partial vector objects, a computing device implements an order system to receive input data describing a region specified relative to a group of vector objects that includes a portion of a first vector object and a portion of second vector object. A visual order as between the portion of the first vector object and the portion of the second vector object within the region is determined. The order system computes a modified visual order as between the portion of the first vector object and the portion of the second vector object within the region based on the visual order. The order system generates the group of vector objects for display in a user interface using a render surface and a sentinel value to render pixels within the region in the modified visual order.

Abstract: A variety of applications can include apparatus and/or methods to preemptively detect defect prone memory blocks in a memory device and handle these memory blocks before they fail and trigger a data loss event. Metrics based on memory operations can be used to facilitate the examination of the memory blocks. One or more metrics associated with a memory operation on a block of memory can be tracked and a Z-score for each metric can be generated. In response to a comparison of a Z-score for a metric to a Z-score threshold for the metric, operations can be performed to control possible retirement of the memory block beginning with the comparison. Additional apparatus, systems, and methods are disclosed.

Abstract: Generating user-specific polygraphs for network activity, including: gathering information describing network activity associated with a user and generating, based on the information, a user-specific polygraph that includes one or more destinations associated with the network activity.

Abstract: Detecting deviations from typical user behavior, including: identifying a geographic location of a device that is associated with a user; determining device activity associated with the user; and detecting, based on a profile associated with the user, that the device activity associated with the user deviates from normal activity for the user.