Abstract: A computer-implemented method, non-transitory, computer-readable medium, and computer-implemented system are provided for deploying a smart contract in a blockchain network. The computer-implemented method includes: receiving, by a blockchain node in a blockchain network, a transaction for creating a smart contract, wherein the transaction comprises a machine code of the smart contract, and the machine code of the smart contract is obtained by Ahead of Time (AoT) compilation of a bytecode of the smart contract in a first trusted execution environment (TEE); determining, by the blockchain node, that the machine code of the smart contract is obtained in a trusted TEE; and in response to determining that the machine code of the smart contract is obtained by the trusted TEE, completing, by the blockchain node, a deployment of the smart contract.

Abstract: In an approach, a process intercepts a deployment resource associated with software prior to deploying the software to a node, where the deployment resource configures how the software is deployed and operates. A processor verifies authenticity of a digital signature present within the deployment resource. A processor, responsive to verifying the authenticity of the digital signature, deploys the software to the node in accordance with the deployment resource.

Abstract: Systems and methods are provided for improving compute job distribution using federated computing nodes. This includes identifying a plurality of independently controlled computing nodes which then receive a token such that they can each be identified as being authorized to participate in a federated computing node cluster. Metrics associated with the particular nodes are then received and based on the received metrics compute jobs are assigned to the particular node by assembling a compute job data packet comprising the one or more compute jobs and transmitting the assembled compute job data packet to the particular node. Other features are also described in which assigned compute jobs and/or unrelated compute tasks can be dynamically modified in order to optimize compute job completion based on the received metrics.

Abstract: A computer architecture for geolocation spoofing/meaconing detection is disclosed. According to some aspects, a computer accesses an incoming geolocation positioning signal. The computer determines, using a signal characteristics calculation subsystem, geolocation positioning signal characteristics for the incoming geolocation positioning signal. The computer provides, using a geolocation positioning spoofing/meaconing detection subsystem, the geolocation positioning signal characteristics as an input vector to a neural network, wherein the neural network determines whether the incoming geolocation positioning signal is legitimate or fake. If the incoming geolocation positioning signal is determined to be fake: the computer computes, using a Bayesian inference subsystem, a likelihood and a severity of a geolocation positioning technology based attack. The computer provides, as a digital transmission, an indication of whether the incoming geolocation positioning signal is legitimate or fake.

Abstract: A process for management of Internet-of-Things (IoT) devices includes a management system for identifying, interrogating, and updating devices connected to one or more networks. The management system can include a data store for storing various data related to the devices and the various processes of the management system. The management system can include a controller for executing processes such as interrogation processes, firmware change processes, credential change processes, and other processes. The controller can determine versions of firmware and other configuration properties of a device and generate various profiles for updating the firmware and other configuration properties. The controller can determine upgrade paths for updating the firmware and other configuration properties from a first version to a second version, the upgrade paths including one or more intermediary versions for facilitating the upgrade path.

Abstract: A robot-connected IoT-based sleep-caring system includes a sleep-caring robot and an IoT system. The sleep-caring robot includes environment monitoring, physiology monitoring, sleep monitoring, sound, lighting and electricity control, a smart storage compartment, central data processing, and machine arms. The IoT system senses and executes instructions from the sleep-caring robot, thereby catering to bedroom activities of the user.

Abstract: A method for analyzing a computer program ecosystem includes performing a static analysis, including identifying static dependencies among elements of the ecosystem based on values of parameters in one or more parameter sets associated with the ecosystem, the elements of the ecosystem including the computer programs of the ecosystem and data resources associated with the computer programs. The method includes performing a runtime analysis, including identifying elements of the ecosystem that were utilized during execution of the ecosystem to process data records. The method includes performing a schedule analysis, including identifying a computer program of the ecosystem that has a schedule dependency from another computer program of the ecosystem. The method includes identifying a subset of the elements of the ecosystem as an ecosystem unit based on the results of the static, runtime, and schedule analyses. The method includes migrating the ecosystem unit, testing the ecosystem unit, or both.

Abstract: Embodiments of the invention are directed to systems, methods, and computer program products for an electronic system for management of image processing model database. The system is configured for versioning machine-learning neural-network based image processing models and identifying and tracking mutations in hyper parameters amongst versions of image processing models. The system is configured to determine that a second image processing model is a version of a first image processing model. The system is further configured to map the mutations in hyper parameters between the first plurality of hyper parameters of the first image processing model and the second plurality of hyper parameters associated with the second image processing model.

Abstract: Disclosed is a method of operating an air purifier by executing an artificial intelligence (AI) algorithm and/or a machine learning algorithm in a fifth generation (5G) environment connected for the Internet of Things. A method for operating an air purifier comprises determining whether an indoor situation is a situation in which protection of a filter is necessary based on sensor information from at least one sensor, in response to a determination that the indoor situation is the situation in which protection of the filter is necessary, suspending an air purifying function, and operating one or more ventilation devices. According to the present disclosure, it is possible to protect the air purifier from a situation in which a life of the filter of the air purifier can be drastically shortened.

Abstract: Aspects of the present disclosure provide systems for managing product development that include receiving development data. The systems record an amount of time spent developing one or more project features; calculate, based at least in part on development data and the amount of time spent developing the feature, business momentum; and calculate, based on certain development data, project agility and market agility.

Abstract: A host application installed on a computing device detects that the computing device is in proximity of a location associated with another application that can be installed onto the computing device. As a result of the computing device being in proximity of the location, the host application obtains, from an application vending server, application code for the application. The host application uses the application code to install the other application onto the computing device. If the host application detects that the computing device is no longer in proximity of the location, the host application uninstalls the other application from the computing device.

Abstract: Configuring distributed control in an industrial system comprises building an asset model representative of a process control installation of the industrial system and creating an asset library of distributed control assets according to a distributed control programming standard. The asset model includes modeled assets defined according to levels of a physical model standard and representing physical devices of the industrial system. The distributed control assets each have one or more predefined, built-in facets. One of the distributed control assets in the asset library is mapped to each of the modeled assets to configure the process control installation of the industrial system and generate an asset-based control application for providing distributed control of the industrial system. Additional aspects relate to auto-creation of control applications based on an information model, either through the use of machine learning or an asset configurator tool.

Abstract: A system may forecast a plurality of workload measurements for a database management system (DBMS) at respective times based on a workload model. The system may determine, based on the forecasted workload measurements, configuration parameter sets optimized for the DBMS at the respective times. The system may generate a reconfiguration plan. The system may determine a performance gain that would result from reconfiguring nodes of the DBMS with the configurations parameter sets. In addition, the system may determine a performance loss that would result from the respective databases of the nodes being inaccessible during reconfiguration with the configuration parameter sets. The system may select a reconfiguration plan in response to the performance gain and the performance loss satisfying a fitness criterion. The system may cause, at the reconfiguration times, the nodes to begin reconfiguration with the configuration parameter sets included in the selected reconfiguration plan.

Abstract: A mobile device app may be provided with a communications registry describing network-based resources with which the app would like to communicate, including Internet Protocol (IP) addresses and Universal Resource Locators URLs of the network-based resources, for example. A local firewall on the mobile device allows the app to only communicate with the defined network-based resources in the communications registry. A user is presented with the communications registry prior to accepting download or installation. The user is thus alerted to which external resources are necessary to operate the app and which ones are not. Users would be warned when requested communication permissions are overly broad or relate to known threat locations. A threat score may be provided to users for self-mitigation.

Abstract: The disclosure includes methods, systems and apparatus for predictive management of efficient selecting and receiving of retail electric utility service to a facility for a period, by automated selecting of a retail utility service provider corresponding to a selected least cost path of predicted rate plan choices across the period, wherein costs of all possible, viable time-bounded predicted rate plan choices are determined for predicted consumer usage where a predicted market of retail rate formulas for the period are predicted in relation to at least one variable, such as weather.

Abstract: A server includes a memory configured to store a software update for a vehicle; and a processor configured to responsive to receiving first usage data from the vehicle indicative of a usage pattern of the vehicle, analyze the first usage data to identify an entity associated with the vehicle; receive second usage data from the entity indicative of a usage pattern of the entity; predict the entity and the vehicle to be within a predefined distance for establishing a wireless connection based on the usage pattern of vehicle and the usage pattern of the entity; responsive to verifying a capability of the wireless connection, divide the software update into multiple partitions; and transmit one or more partitions to the entity for sharing with the vehicle over the wireless connection.

Abstract: A processor includes a plurality of cores configured to perform operations independently, a memory, and a control circuit electrically connected to the plurality of cores and the memory. The control circuit is configured to acquire one or more instructions associated with a task, store data corresponding to the task based on the one or more instructions, transmit the instructions to the at least some cores, check one or more cores that have responded to the instructions among the at least some cores, prevent the task from being allocated to the cores except for one core if the task is allocated to the one core, and allocate the task to one of the cores, the allocation of the task including changing state information associated with the allocation and setting other cores not allocated the task among the plurality of cores not to access the data corresponding to the task.

Abstract: Disclosed embodiments relate to adjusting vehicle Electronic Control Unit (ECU) software versions. Operations may include receiving a prompt to adjust an ECU of a vehicle from executing a first version of ECU software to a second version of ECU software; configuring, in response to the prompt and based on a delta file corresponding to the second version of ECU software, the second version of ECU software on the ECU in the vehicle for execution; and configuring, in response to the prompt, the first version of ECU software on the ECU in the vehicle to become non-executable.

Abstract: A computer-implemented method, computer program product and computing system for: defining a threat mitigation platform for a client, wherein the threat mitigation platform includes a plurality of threat detection capability modules; defining a rollout schedule for at least a portion of the plurality of threat detection capability modules; and presenting the rollout schedule to the client.

Abstract: Disclosed are systems, methods, and computer readable media for automatically assessing and allocating virtualized resources (such as central processing unit (CPU) and graphics processing unit (GPU) resources). In some embodiments, this method involves a computing infrastructure receiving a request to perform a workload, determining one or more workflows for performing the workload, selecting a virtualized resource, from a plurality of virtualized resources, wherein the virtualized resource is associated with a hardware configuration, and wherein selecting the virtualized resources is based on a suitability score determined based on benchmark scores of the one or more workflows on the hardware configuration, scheduling performance of at least part of the workload on the selected virtualized resource, and outputting results of the at least part of the workload.