Abstract: The present embodiments relate to detecting malware in a document management system (DMS). File stubs representing files remotely stored in a DMS can be presented in file managers at local computing devices for review/interaction on the local computing devices. A file stub for a specific file can be selected in the file manager, and a request to download the file can be provided to the DMS. The process in requesting the download of the file can be processed to determine whether the process is user-initiated or programmatic-initiated. If the process is user-initiated (e.g., initiated by a user on the local computing device), the file can be provided to the local computing device. Programmatic-initiated processes can be a result of software or malware, and mitigating actions can be taken if the request to download the file is a programmatic-initiated process.

Abstract: A method includes determining a picture type of a current picture, determining, based on the picture type of the current picture, whether to write the current picture in a dedicated chip memory or whether to write the current picture a non-dedicated system memory, and writing the current picture in the dedicated chip memory or the non-dedicated system memory based on the determining of whether to write the current picture in the dedicated chip memory or whether to write the current picture in the non-dedicated system memory.

Abstract: Methods, apparatus, and processor-readable storage media for predicting task execution efforts using artificial intelligence techniques are provided herein. An example computer-implemented method includes determining intent information associated with at least a portion of a task by processing data related to the task using at least a first set of artificial intelligence techniques; determining task execution workflow data based at least in part on the intent information associated with at least a portion of the task; predicting one or more efforts associated with executing the task by processing at least a portion of the task execution workflow data using at least a second set of artificial intelligence techniques; and performing one or more automated actions based at least in part on at least one of the one or more predicted efforts associated with executing the task.

Abstract: A computer implemented method of training a model, using a machine learning process, to predict whether a transaction of a digital currency stored in a blockchain is fraudulent, comprises: obtaining (202) transaction data for a first transaction of first funds in the digital currency, wherein the transaction data further comprises information related to a second transaction of the first funds that preceded the first transaction. The method further comprises labelling (204) the transaction data for the first transaction according to whether the first transaction was fraudulent and using (206) the transaction data and the label as training data with which to train the model.

Abstract: Disclosed are systems and methods for improving interactions with and between computers in content providing, searching and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel framework for compiling, updating and dynamically managing a confidence graph for a user that leads to generation of a scored interest profile for the user that content providers can utilize as a basis for disseminating their proprietary digital content. The disclosed confidence graph provides a scored interest profile for each user that is based on authenticated user data derived from an inbox of the user. The confidence graph is not only derived from authenticated data, but is also dynamic and evolves simultaneously with changing user interests. Thus, digital content is selected and transmitted to users based on the current, real-time digital data reflecting their current interests as reflected by their inbox activity.

Abstract: A computer implemented method of decomposing a blockchain comprising transactions in digital currency for analysis and display is described. The method comprises first determining a range of blocks in the blockchain. Each block in the range of blocks in the blockchain is then unpacked into a table comprising one or more rows of input and output data for each transaction stored in the block. For the range of blocks in the blockchain, entity information and transaction information are then aggregated into a block analysis table. A node of a computing network and a computer program product adapted for implementation of such a method are also described.

Abstract: Embodiments relate to a method for forming a three-dimensional structure. The method includes determining one or more locations for positioning a sensing device based on structural coordinate information relating to a three-dimensional structure to be formed. The method further includes forming a portion of the three-dimensional structure based on the structural coordinate information. The method further includes positioning the sensing device at a location of the one or more locations.

Abstract: An E2EO module stores action data which is linked to a condition relating to a combination of an operation status of a specific type of element and an operation status of another type of element linked to the specific type of element, and which indicates an action to be executed on the specific type of element that satisfies the condition. The E2EO module identifies, based on the current status indicated by the inventory data, a combination of a current operation status of the specific type of element included in the communication system and a current operation status of another type of element linked to the specific type of element. The E2EO module executes, when the identified combination satisfies the condition linked to the action data, the action indicated by the action data on the specific type of element.

Abstract: A processor-implemented method of pre-processing for deep neural network compilation comprising receiving a representation of an artificial neural network (ANN) model. The ANN includes multiple nodes coupled by edges. Position information is determined for each node of the ANN. An operator embedding is generated to represent operators of the ANN model in an embedding space based on the position information. A graph neural network (GNN) processes the operator embedding to generate a graph embedding corresponding to the ANN model according to a learned distance metric and based on the position information. The GNN determines a set of hyperparameters for the ANN model based on the graph embedding.

Abstract: A processor-implemented method of pre-processing for deep neural network compilation comprising receiving a representation of an artificial neural network (ANN) model. An operator embedding is generated to represent operators of the ANN model in an embedding space. A graph neural network (GNN) processes the operator embedding to generate a graph embedding corresponding to the ANN model according to a learned distance metric. The GNN determines a set of hyperparameters for the ANN model based on the graph embedding.

Abstract: Processing circuitry includes a selectively powered domain having a communications interface to communicate with power management circuitry via a bus in accordance with a bus protocol, and a processing core to control the communications interface, wherein the selectively powered domain is not powered when the processing circuitry is operating in any one of multiple low power modes. The processing circuitry also includes an always on power domain having a set of pins to communicate a set of handshake signals with the power management circuitry and a power management sequencer to control power mode transitions of the processing circuitry. When the processing circuitry is operating in one of the multiple low power modes such that the communications interface and the processing core are not powered, the power management sequencer generates a signature on the set of handshake signals to control power mode transitions from one of the multiple low power modes.

Abstract: A device access management server may facilitate secure access of a target device by an accessing device. The secure remote access of the target device by the accessing device may be facilitated by a public key infrastructure (PKI) certificate issued and/or validated by the device access management server.

Abstract: Data associated with a source system is ingested. After the data is ingested, a post-processing metadata conversion process is performed including by selecting an entry of a chunk metadata data structure and determining that a data chunk associated with the selected entry is not referenced by at least a threshold number of objects. In response to determining that the data chunk associated with the selected entry is not referenced by at least the threshold number of objects, metadata of a tree data structure node corresponding to a chunk identifier associated with the data chunk is updated to store a reference to a chunk file storing the data chunk and the selected entry is removed from the chunk metadata data structure.

Abstract: A plurality of portions of a content file are stored. It is determined that the content file has a size that is greater than a threshold size. In response to determining that the content file has the size that is greater than the threshold size, a plurality of component file metadata structures are generated for each of the plurality of portions of the content file. A component file metadata structure of the plurality of component file metadata structures corresponds to one of the portions of the content file. Each of the plurality of component file metadata structures includes corresponding metadata that enables data chunks associated with a corresponding portion of the content file to be located.

Abstract: Backup data associated with a primary storage system is received. At least a view of the received backup data associated with the primary storage system is generated. The view of the of the received backup data associated with the primary storage system includes a tree data structure comprising a root node, a first plurality of child nodes, and a first plurality of leaf nodes. At least some of the first plurality of leaf nodes include corresponding pointers to a corresponding binary large object. A read request for data exposed by the view of the received backup data associated with the primary storage system is received from an external system. In response to receiving the read request, the view of the received backup data associated with the primary storage system is exposed to a requesting system utilizing a protocol associated with the external system.

Abstract: The lease-purchase system gives consumers access to numerous products at merchants through a flexible lease-purchase transaction. The lease-purchase system allows merchants to grow their customer bases and allows them to move inventory through another consumer payment method. A parsing engine is utilized to automatically determine which merchant items are eligible to transaction via the lease system. At any time throughout the life of the lease-purchase transaction, the consumer can purchase the leased product or return it.

Abstract: Methods for site-specific risk evaluation of foodborne pathogens and/or fecal indicator bacteria contamination. Methods for generating a heat map of a field showing contamination concentrations integrated with environmental data are also provided.

Abstract: An implant for insertion into a patient is provided. The implant includes a three-dimensionally printed structure of layers. Each layer comprises an infill pattern of the three-dimensionally printed structure, the infill pattern of each layer comprising a set of infill lines. The implant includes a plurality of hollow channels. The layers are arranged on top of one another such that the plurality of hollow channels are formed within the implant, wherein the walls of each channel are formed by sections of the infill lines of a plurality of layers of the printed structure of layers. At least one hollow channel extends between a first outer surface of the implant and a second outer surface of the implant. At least one hollow channel is oriented in a direction which is tilted with respect to a reference axis perpendicular to the first outer surface of the implant.

Abstract: A door includes an inner wall, an outer wall, and a window assembly including a window. The inner wall is configured to engage with a cab of a vehicle. The outer wall is coupled to the inner wall and spaced apart from the inner wall to form an interior cavity. The door is configured to move between a closed position in which the inner wall is engaged with the cab and an open position in which the inner wall is separated from the cab. In the closed position, at least a portion of the interior cavity is configured to be disposed outboard from the cab in a lateral direction. The window is slidably engaged to the door and configured to move between an extended position and a retracted position. In the retracted position, the window is at least partially disposed in the portion of the interior cavity.

Abstract: Provided are a network service construction system and a network service construction method which are capable of flexibly constructing network services that satisfy various needs. A purchase management module receives service requirement data indicating a service requirement. An E2EO module and an inventory management module identify, based on the service requirement data, a configuration of a functional unit group that achieves a network service. Based on the identified configuration and template data in which the configuration is acceptable as a parameter, a CMaaS module, a service manager module, and a slice manager module identify a construction procedure of the functional unit group. The CMaaS module, the service manager module, the slice manager module, and a container management module construct the functional unit group by executing the identified construction procedure.