Abstract: A system designed for increasing network communication speed for users, while lowering network congestion for content owners and ISPs. The system employs network elements including an acceleration server, clients, agents, and peers, where communication requests generated by applications are intercepted by the client on the same machine. The IP address of the server in the communication request is transmitted to the acceleration server, which provides a list of agents to use for this IP address. The communication request is sent to the agents. One or more of the agents respond with a list of peers that have previously seen some or all of the content which is the response to this request (after checking whether this data is still valid).

Abstract: In one embodiment, a method includes training a target machine-learning model iteratively by accessing training data of content objects, training an intermediate machine-learning model that outputs contextual evaluation measurements based on the training data, generating state-indications associated with the training data, wherein the state-indications comprise user-intents, system actions, and user actions, training the target machine-learning model based on the contextual evaluation measurements, the state-indications, and an action set comprising possible system actions, extracting rules based on the target machine-learning model by a sequential pattern-mining model, generating synthetic training data based on the rules, updating the training data by adding the synthetic training data to the training data, determining if a completion condition is reached for the training, and if the completion condition is reached returning the target machine-learning model, else repeating the iterative training of the tar

Abstract: A system designed for increasing network communication speed for users, while lowering network congestion for content owners and ISPs. The system employs network elements including an acceleration server, clients, agents, and peers, where communication requests generated by applications are intercepted by the client on the same machine. The IP address of the server in the communication request is transmitted to the acceleration server, which provides a list of agents to use for this IP address. The communication request is sent to the agents. One or more of the agents respond with a list of peers that have previously seen some or all of the content which is the response to this request (after checking whether this data is still valid).

Abstract: An operations management apparatus includes: a memory; and a processor coupled to the memory, the processor being configured to execute an acquiring processing that includes acquiring operations management information in communications with one or more devices, execute a monitoring processing that includes monitoring conditions of the one or more devices by transmitting or receiving a condition monitoring packet to or from the one or more devices, execute a judging processing that includes judging whether the operations management information has been worsened at the time of transmitting or receiving the condition monitoring packet, and execute a determining processing that includes determining a method of transmitting or receiving the condition monitoring packet depending on a result of judgment made by the judging processing.

Abstract: Systems and methods are provided for determining if an e-mail originating from an external source is deemed malicious and thereby preventing an out of office e-mail reply. One example method includes receiving, at a computing device of a service provider, an e-mail identified as originating from an external source, scanning the e-mail to identify at least one parameter only when an out of office reply is setup by a recipient of the e-mail, comparing the at least one scanned parameter to a set of known parameters, calculating a score of the e-mail based on the comparison of the at least one parameter to a set of known parameters, determining the e-mail to be a malicious e-mail if the score exceeds a threshold value and blocking an out of office reply based on the threshold value.

Abstract: A network device may receive configuration data identifying resource subscription thresholds associated with a plurality of respective endpoint devices and may receive traffic from the plurality of endpoint devices. The network device may process the traffic and the configuration data, with a resource allocation model, to determine that processing traffic associated with a first endpoint device requires allocating a resource of the network device, and may process the configuration data, with the resource allocation model, to identify the resource of the network device from a particular resource of the network device that is currently allocated to traffic associated with a second endpoint device. The network device may allocate the particular resource of the network device to the traffic associated with the first endpoint device, and may process the traffic associated with the first endpoint device with the particular resource to generate processed traffic.

Abstract: A loyalty switch for examining loyalty messages and routing the loyalty messages to one or more loyalty hosts and examining responses and routing the responses back to stores. Such a switch has configurable number of selector handlers pool, and the switch accepts a connection from stores and reads loyalty host information from master data to establish the connection with a loyalty host and to route messages. Each selector handler in the switch has multiple store objects that contain a routing map and connection information from companies' sites and the loyalty host.

Abstract: A system designed for increasing network communication speed for users, while lowering network congestion for content owners and ISPs. The system employs network elements including an acceleration server, clients, agents, and peers, where communication requests generated by applications are intercepted by the client on the same machine. The IP address of the server in the communication request is transmitted to the acceleration server, which provides a list of agents to use for this IP address. The communication request is sent to the agents. One or more of the agents respond with a list of peers that have previously seen some or all of the content which is the response to this request (after checking whether this data is still valid).

Abstract: A plurality of computing devices are communicatively coupled to each other via a network, and each of the plurality of computing devices is operably coupled to one or more of a plurality of storage devices. The computing devices may use local caches and storing snapshots in a coherent manner when accessing the plurality of storage devices spread across multiple data centers.

Abstract: A system and method of managing user engagement with a musical playlist provides feedback for a host and allows attendees to directly engage with the host to adjust a playlist for an event or social gathering. The system includes at least one remote server, a corresponding user personal computing (PC) device, and a corresponding host PC device. The method begins by prompting the at least one host account to initiate an event session for a plurality of attendee accounts and then to designate a plurality of playlist songs with the corresponding host PC device. The event session is managed in between the host account and the plurality of attendee accounts through the remote server. A current song is played during the event session and feedback is relayed for the current song with the corresponding user PC device. The feedback is then outputted with the corresponding host PC device.

Abstract: Throughput is preserved in a distributed system while maintaining concurrency by pushing a commit wait period to client commit paths and to future readers. As opposed to servers performing commit waits, the servers assign timestamps, which are used to ensure that causality is preserved. When a server executes a transaction that writes data to a distributed database, the server acquires a user-level lock, and assigns the transaction a timestamp equal to a current time plus an interval corresponding to bounds of uncertainty of clocks in the distributed system. After assigning the timestamp, the server releases the user-level lock. Any client devices, before performing a read of the written data, must wait until the assigned timestamp is in the past.

Abstract: A data analysis device 10 comprises: a frequency analysis unit 11 that performs frequency analysis, under a predetermined condition, on each piece of a plurality of training data pieces including a plurality of class training data pieces some of which have been assigned a label indicating the data class; a cluster analysis unit 12 that clusters the frequency analyzed training data pieces into a number of classes of frequency analyzed training data; a computation unit 13 that computes, on the basis of the clusters, the degree to which frequency analyzed training data pieces assigned the same label are not included in the same cluster; and a selection unit 14 that selects, as a clustering model for assigning a label to a training data piece, clustering results according to the cluster analysis unit 12 when the smallest degree was computed, from among the plurality of computed degrees.

Abstract: Neural networks can be used for time series data classification. However, in a K-shot scenario in which sufficient training data is unavailable to train the neural network, the neural network may not produce desired results. Disclosed herein are a method and system for training a neural network for time series data classification. In this method, by processing a plurality of task specific data, a system generates a set of updated parameters, which is further used to train a neural network (network) till a triplet loss is below a threshold. The network is trained on a diverse set of few-shot tasks sampled from various domains (e.g. healthcare, activity recognition, and so on) such that it can solve a target task from another domain using only a small number of training samples from the target task.

Abstract: A search query can be received. User parameters can be identified based on the search query. The search query can be refined to include the user parameters. A search result from a search for media content using the refined search query can be received. Based on at least one search result received from the search and based on the user parameters, an augmented media content can be generated. Playing of the augmented media content can be synchronized with a user's activity by controlling playing of the augmented media content while detecting the user's activity pace.

Abstract: A query directed to database data stored across a set of files is received. The query includes predicates and each file from the set of files is associated with metadata stored in a metadata store that is separate from a storage platform that stores the set of files. One or more files are removed from the set of files whose metadata does not satisfy a predicate of the plurality of predicates to generate a pruned set of files. One or more predicates are removed that are satisfied by the metadata of the pruned set of files to generate a modified query.

Abstract: A model-based industrial security policy configuration system implements a plant-wide industrial asset security policy in accordance with security policy definitions provided by a user. The configuration system models the collection of industrial assets for which diverse security policies are to be implemented. An interface allows the user to define zone-specific security configuration and event management policies for a plant environment at a high-level based on a security model that groups the industrial assets into security zones. Based on the model and these policy definitions, the system generates asset-level security setting instructions configured to set appropriate device settings on one or more of the industrial assets to implement the security event management policies, and deploys these instructions to the appropriate assets in order to implement the defined policies.

Abstract: A method for predicting one or more events includes generating, for features of each of at least two feature types, an intermediate representation using a representation learning model for the at least two feature types. The intermediate representations of the at least two feature types are analyzed using a neural network and at least one neural network model so as to provide a joint representation for predicting certain events. One or more actions to be taken can be determined based on the one or more events predicted by the joint representation.

Abstract: Methods, systems and apparatuses to enable an optimum bin selection by implementing a neural network with a network scheduling and configuration tool (NST), the method includes: configuring an agent with a critic function from neural networks wherein the agent neural network represents each bin of the collection of bins in the network that performs an action, and a critic function evaluates a criteria of success for performing the action; processing, by a scheduling algorithm, the VLs by the NST; determining one or more reward functions using global quality measurements based on criteria comprising: a lack of available bins, a lack of available VLs, and successfully scheduling operations of a VL into a bin; and training the network based on a normalized state model of the scheduled network by using input data sets to arrive at an optimum bin selection.

Abstract: Systems, devices, and methods of classifying encrypted network communications. A Traffic Monitoring Unit operates to monitor network traffic, and to capture HTTPS-encrypted packets that are exchanged over an HTTPS connection between an end-user device and a web server. An HTTPS Traffic Classification Unit operates to detect discrete HTTPS-encrypted objects within that HTTPS connection, and to classify those discrete HTTPS-encrypted objects based on at least one of: a first Analysis Model that classifies HTTPS-encrypted objects based on a type of content that is represented in the HTTPS-encrypted object; a second Analysis Model that classifies HTTPS-encrypted objects based on a type of server-side application that is associated with the HTTPS-encrypted object. Each Analysis Model utilizes Machine Learning (ML), Deep Learning (DL), Artificial Intelligence (AI), or Statistical and Mathematical Analysis (SMA).

Abstract: A method of orchestrating one or more radio resources among various services executing within a container. The method includes obtaining, by an orchestration engine executing on a network device, a request, from a first service of a plurality of services, for use of a physical/hardware resource that connects a container running on the network device to a network. The request from the first service has a particular priority. The plurality of services execute within the container. The method further includes determining whether to connect the first service to the network via the physical/hardware resource based on the priority and an availability status of the physical/hardware resource and establishing, at a kernel level, a connection between the first service and the physical/hardware resource based on the determining.