Abstract: The disclosed technology is generally directed to network security for processors. In one example of the technology, a device includes: hardware, including a network interface; a memory; and a processor. The memory is adapted to store run-time data for the device. The memory includes at least a first memory region and a second memory region. The processor that is adapted to execute processor-executable code including a first binary in the first memory region and a second binary in the second memory region. The first binary includes at least one application and a kernel. The kernel is configured to control the hardware. The second binary is configured to operate, upon execution, as a network stack. The device is configured such that the first memory region is protected such that the first memory region is inaccessible to the second binary.

Abstract: Systems and methods are described for processing ingested pipeline metrics and ingested logs in an asynchronous manner as the data is being ingested to explain anomalies detected in the pipeline metrics using the ingested logs. For example, one or more streaming data processors can convert data as the data is ingested into a comparable data structure, determine whether the comparable data structure should be assigned to an existing data pattern or a new data pattern, and determine whether the logs corresponding to the comparable data structure is anomalous. Separately, the streaming data processor(s) can perform an outlier detection on the pipeline metrics to detect outliers. The streaming data processor(s) can then window the anomalous logs and the pipeline metric outliers to surface explanations for the pipeline metric outliers using the anomalous logs.

Abstract: A load control system may comprise load control devices for controlling respective electrical loads, and a system controller operable to transmit digital messages including different commands to the load control devices in response to a selection of a preset. The different commands may include a preset command configured to identify preset data in a device database stored at the load control device and/or a multi-output command configured to define the preset data for being stored in the device database. The system controller may decide which of the commands to transmit to the load control devices in response to the selection of the preset.

Abstract: Embodiments facilitate efficient and flexible handling of metadata for processing in a microservice architecture (MSA) environment. A consumer service and a provider service both utilize a data model having metadata. A central repository stores metadata information that is being called for by a consumer service. A dedicated meta service manages the metadata repository by listening to a message queue to obtain model-relevant metadata information from a provider service. That model-relevant metadata information may be static in nature, or may be dynamic (e.g., varying as between different tenants). The meta service recognizes the static/dynamic nature of the model-relevant metadata information (e.g., based upon content such as a tenant ID or other information) in a message from the provider service, and stores the metadata accordingly. Once stored in the central repository, the model-relevant metadata information may be communicated directly to the consumer service.

Abstract: A virtual server includes at least one processor to retrieve a user layer from a user's personalization container, and initiate mounting of the user layer to a target operating system. During the mounting, the at least one processor determines that the user layer did not originate with the target operating system. The user layer is modified so that file system objects and registry objects are compatible with the target operating system. Mounting of the modified user layer is completed to create a single composited layered image.

Abstract: Provided are a method and apparatus for operating a blockchain system, a device and a storage medium. The method is described below. To-be-processed blockchain data is acquired through a kernel engine of a blockchain system. The to-be-processed blockchain data is processed through the kernel engine, and a kernel component interface provided by a component adaptor is called during the processing process of the to-be-processed blockchain data to call a kernel component.

Abstract: Methods and apparatus are disclosed for providing emulation of quantized precision operations in a neural network. In some examples, the quantized precision operations are performed in a block floating-point format where values of a tensor share a common exponent. Techniques for selecting higher precision or lower precision can be used based on a variety of input metrics. When converting to a quantized tensor, a residual tensor is produced. In one embodiment, an error value associated with converting from a normal-precision floating point number to the quantized tensor is used to determine whether to use the residual tensor in a dot product calculation. Using the residual tensor increases the precision of an output from a node. Selection of whether to use the residual tensor can depend on various input metrics including the error value, the layer number, the exponent value, the layer type, etc.

Abstract: A method for operating a control system of a technical installation, wherein an operator station server transfers visualization information to an operator station client, and the operator station client generates a graphical presentation for an operator via the visualization information, where the method includes adjusting the graphical presentation via the operator station client in response to an instruction of the operator to the operator station client, transmitting the information regarding the adjustment of the graphical presentation to the operator station server via the operator station client, recording the information received from the operator station client regarding the adjustment of the graphical presentation in a memory of the operator station server, transmitting the information regarding the adjustment of the graphical presentation to the engineering station server via the operator station server, and presenting the information regarding the adjustment of the graphical presentation to a proje

Abstract: Disclosed herein are related to a system, a method, and a non-transitory computer readable medium for controlling a central plant. In one aspect, the system obtains a control envelope for a device controlled by the controller. The control envelope comprises boundaries of a plurality of control regions in a multidimensional operating space for the device. Each control region is enclosed by a corresponding boundary. The system counts a number of times that a ray of the device crosses the boundary of a control region. The system determines whether an operating point of the device is within the control region based on the counted number. The system operates the device according to a predetermined control technique corresponding to the control region, in response to determining that the operating point of the device is within the control region.

Abstract: A method of managing a medical suction device through a network may be embodied by the management server through the steps of: storing operation information of at least one medical suction device in a storage unit provided in the management server, generating an operation start determination reference value of the medical suction device based on the operation information, receiving information on conditions of a patient from a medical suction device installed at an outside, and determining whether to start an operation of the medical suction device that has transmitted the information on conditions of the patient based on the operation start determination reference value and the information on conditions of the patient.

Abstract: According to an example, an autonomous novel behavior detection apparatus may receive network, user, application and device events; partition the network, user, device and application behavior events to plurality of partitions; extract features from the events based on fieldnames, type of data and type of values stored in the corresponding fields in an unsupervised manner; transform the data in the events from all data types to numerical values; normalize the data in the events; utilize training neural networks to learn the network, user, device and application behavior from the events; evaluate network, user, device and application events for novel behavior events using evaluation models; learn the novel behaviors using a plurality of neural networks, filter out novel behavior events that are similar to learned novel behaviors, identify novel behaviors and summarize novel behaviors into meaningful aggregation of novel behaviors.

Abstract: A reinforcement learning method executed by a computer includes calculating a degree of risk for a state of a controlled object at a current time point with respect to a constraint condition related to the state of the controlled object, the degree of risk being calculated based on a predicted value of the state of the controlled object at a future time point, the predicted value being obtained from model information defining a relationship between the state of the controlled object and a control input to the controlled object; and determining the control input to the controlled object at the current time point, from a range defined according to the calculated degree of risk so that the range becomes narrower as the calculated degree of risk increases.

Abstract: Systems and methods for unsupervised training and evaluation of anomaly detection models are described. In some embodiments, an unsupervised process comprises generating an approximation of a data distribution for a training dataset including varying values for a metric of a computing resource. The process further determines, based on the size of the training dataset, a first quantile probability and a second quantile probability that represent an interval for covering a prescribed proportion of values for the metric within a prescribed confidence level. The process further trains a lower limit of the anomaly detection model using a first quantile that represents the first quantile probability in the approximation of the data distribution and an upper limit using a second quantile that represents the second quantile probability in the approximation. The trained upper and lower limits may be used to monitor input data for anomalous behavior and, if detected, trigger responsive action(s).

Abstract: Semantic feature values of notification messages in different applications are obtained, and notification messages that are in different applications and whose semantic feature values match are associated. This associates notification messages that are of associated events of a mobile terminal and that are from different channels (for example, different applications). A user can view notification messages that are of associated events and that are from different channels.

Abstract: A system and method include digitally determining a virtual insertion path of a digital dental restoration.

Abstract: Various embodiments are provided for decentralized distributed deep learning by one or more processors in a computing system. Asynchronous distributed training of one or more machine learning models may be performed by generating a list of neighbor nodes for each node in a plurality of nodes and creating a first thread for continuous communication according to a weight management operation and a second thread for continuous computation of a gradient for each node. One or more variables are shared between the first thread and the second thread.

Abstract: Systems and method for generating a base design and corresponding layout based on client data and an electrical load list. The electrical load list may include any number of electrical components for an industrial device assembly. A processor may determine parameters that define levels of operations for each of the electrical components based on the client data and subsequently identify a set of base designs based on the parameters. Additionally, supporting modules that assist operations of at lead one of the electrical components may be added to the base design. In turn, the set of base designs and corresponding supporting modules may be displayed to a user as a set of visualizations. In response to receiving a selection of a particular visualization that represents a particular base design, the processor may generate and display a layout corresponding to the particular base design.

Abstract: Systems, methods, and computer-readable media for cybersecurity are disclosed. The systems and methods may involve receiving, by an application capable of JavaScript execution, code for execution; executing, before execution of the received code, an intercepting code, wherein the intercepting code is configured to intercept at least one application programming interface (API) invocation by the received code; intercepting, by the intercepting code, an API invocation by the received code; determining that the intercepted API invocation results in a manipulation of a backing store object; and modifying an execution of the intercepted API invocation, wherein the modified execution results in at least one of: a non-predictable memory layout, a non-predictable memory behavior, or a non-predictable property of an object.

Abstract: The present disclosure relates to a method for parameterizing an automation field device which is communicatively connected to a server, having the following steps: initiating the method by transmitting a command to parameterize the field device on the server; transmitting identification information of the field device to the server; ascertaining a digital image of the field device stored on the server using the transmitted identification information, said digital image containing configuration settings of the field device and measurement location-relevant information and being designed to reproduce the behavior of the field device in a simulated or emulated manner; generating and proposing a parameter set for the field device using the field device information; selecting and confirming the proposed parameter set by a user; and transmitting the confirmed parameter set to the field device and parameterizing the field device using the transmitted parameter set.

Abstract: The present invention relates to the technical field of high performance computing (HPC). In particular, the invention relates to a heterogeneous computing system, particularly a computing system including different modules, which can freely be assigned to jointly process a computation tasks. A control entity, referred to as module computing abstraction layer (MCAL), is provided which allows dynamic assignment of various resources provided by the different modules. Due to its flexibility in adjusting to varying demands in computing, the present invention is also applicable as an underlying system for providing cloud computing services, which provides shared computer processing resources and data to computers and other devices on demand, mostly via the Internet.