982 results about "System configuration" patented technology

A system for identifying and preventing Advanced Persistent Threats (APTs) using big data analytics, including: a data collection module [100] configured to collect real-time data from network devices, endpoints, security applications and external threat data feeds; a data preprocessing module [101] configured to normalize and filter the collected data; a big data analytics engine [102] that uses both supervised and unsupervised machine learning models and is configured to detect anomalous behaviors and known attack patterns from the preprocessed data; a classification module [103] configured to categorize detected threats based on identified behaviors and characteristics of APTs; a real-time threat response module [104] configured to automatically initiate countermeasures based on the classified threat, the countermeasures including isolating compromised systems, blocking malicious traffic and adjusting network security configurations; a continuous learning module [105] configured to update the machine learning models using feedback from past threats and external threat data to ensure adaptability to evolving APT strategies; and a management dashboard [106] configured to provide security administrators with real-time alerts, visualizations and control over system configurations and responses.

Various embodiments of a system and method for a smart work zone are described. In one example, the system includes smart cone devices configured to transmit smart cone device localization data, a wearable device comprising a processor configured to transmit worker localization data of a worker wearing the garment device and to receive an alert, and a base station. The base station includes an internal edge computing system configured to process the smart cone device localization data to define a virtual geofence boundary of a safe area, process the worker localization data, broadcast a location of the worker wearing the wearable device, and in response to a vehicle or the worker approaching the virtual geofence boundary, provide an alert to at least one of: the worker wearing the wearable device, a passing motorist, or a connected and automated vehicle (CAV).

The invention discloses a comprehensive algorithm for distribution and scheduling of AGV (Automatic Guided Vehicle) carrying tasks. S1: an SCADA system; equipment communication, data acquisition and storage, protocol analysis and logic processing; s11, the communication protocol, the address and the communication rhythm of the equipment are configured through the system, data acquisition data are stored in ES (ElasticSearch), the data acquisition data are stored for one year and backed up regularly, and the system achieves service logic processing through an LUA script. The carrying efficiency of the AGV is integrally improved, and the execution time of carrying a single task by the AGV is shortened by 10%; the production capacity of a workshop is improved, and the carrying rate exceeds 96% under the condition of no interference; the workshop logistics cost is reduced, and the overall number of AGVs is reduced by 10%; and the first pass yield of material carrying is improved by 15%. The deep fusion data analysis capability enables the whole system to predict demands more accurately, avoid conflicts, optimize the overall production efficiency, optimize the production process, reduce waiting and resource waste, and improve the flexibility of path planning and the reliability of task completion.

A system and method including receiving a prompt specifying at least one task type; determining a system prompt based on the received prompt, the system prompt including artificial intelligence (AI) system configuration details corresponding to the at least one task type; pre-processing the system prompt to generate a pre-processed prompt including code referenced in the system prompt; transmitting, as an input prompt, the pre-processed prompt to an AI system; receiving, in response to the AI system executing the pre-processed prompt, a result from the AI system; and storing a record of the result from the AI system in a data repository.

A machine learning system configured to map an input data instance to an output according to a system mapping. The system mapping may be composed from multiple functions. A latent input vector may be determined in a second latent space for the input data instance, from latent reference vectors related to a number of reference data instances identified as parents.

A method of operating an IDS for a device includes performing a fuzzing operation on a software program being executed on a system under test, the software program corresponding to a deployed software program on the device monitored by the IDS and the system under test being configured to emulate at least one system of the device, the fuzzing operation including supplying fuzzing inputs to the software program, monitoring outputs of the software program, and detecting, based on the outputs, a vulnerability to intrusion in the software program caused by supplying the fuzzing inputs to software program. The method further includes generating and storing a vulnerability entry corresponding to the detected vulnerability, the vulnerability entry including information identifying the detected vulnerability, and updating, based on the vulnerability entry, at least one of a component of the IDS and a code portion of the deployed software program.

A system for translating source code in a first programming language to a target language is provided. The system is configured to receive source code for converting to target code; determine an abstract syntax tree from the source code; determine program specifications from the source code; determine a dependency graph from the source code; determine a plurality of chunks based at least in part on the abstract syntax tree, the program specifications, and the dependency graph; determine a plurality of converted chunks based at least in part on the plurality of chunks and a deep learning model, the deep learning model converting the plurality of chunks from the language of the source code to the language of the target code; post-process the plurality of converted chunks to obtain intermediate code; and provide the intermediate code as the target code.

The invention relates to the technical field of dynamic system configuration, and discloses a dynamic system configuration and state change notification method and system, and the method comprises the steps: obtaining a system initialization parameter set; constructing an information communication center based on the system initialization parameter set, and generating a protocol routing set and a topological connection diagram of the information communication center; constructing a multi-modal state monitoring channel based on the protocol routing set of the information communication center and the topological connection diagram, initializing a detection engine, and obtaining an engine state set of the detection engine; constructing a subscription relation mapping matrix based on the topological data set and the application subscription request set, and generating a path optimization strategy set; generating a cross-protocol event set based on the state change event set, generating transmission quality based on the cross-protocol event set, and dynamically scheduling the detection engine path according to the transmission quality; and generating an exception handling independent channel based on the dynamic scheduling condition. According to the invention, the reliability and maintainability of the system are improved.

The invention relates to the technical field of data security, and discloses a data security risk assessment method based on model construction, and the method comprises the steps: firstly collecting historical data security events and related system configuration, network architecture and other multi-dimensional data, and carrying out the preprocessing to form a standardized data set; and then, constructing a data security risk prediction model, and predicting future possible data security events and potential influences thereof in combination with multi-dimensional factors. And obtaining a risk prediction result by obtaining data such as a system state and network flow in real time and inputting the data into the prediction model. Meanwhile, a risk influence assessment framework is established, the severity, occurrence frequency and business influence of the risk are comprehensively considered, and a risk comprehensive score is calculated. And finally, sorting and classifying the risks according to the scores, and formulating and implementing corresponding risk relief measures and emergency response plans for high-risk and medium-risk data assets. According to the invention, the accuracy and timeliness of data security risk assessment are improved.

Methods and apparatus are provided for automated analysis of airflow objectives in architectural design plans using artificial intelligence (AI). A controller evaluates design plans, such as floor plans or architectural drawings, to identify, classify, and assess the placement, type, and configuration of airflow components, including air supply and exhaust vents, ducts, and HVAC systems. The controller examines these components against relevant building deployment objectives and preferred practices, evaluating spatial relationships, airflow patterns, and system configurations. When non-compliance is detected, the system generates automated suggestions for design revisions and optimizations, in order to facilitate adherence to building deployment objectives and functional efficiency before construction begins. The apparatus includes interactive tools for real-time simulation and collaboration, allowing designers, architects, and others to make informed adjustments to the design to achieve optimal airflow management and compliance with building deployment objectives.

The invention discloses a multi-zone-area interconnection model prediction control system and method based on side-end interoperation, relates to the technical field of power distribution automation, and comprises the steps of designing an interconnection system, configuring equipment to realize system architecture construction, optimizing a communication architecture, realizing real-time information interaction, and performing collaborative optimization based on model control prediction. According to the method, by adopting a model predictive control (MPC) strategy, energy dynamic distribution and load balancing between transformer areas are achieved, and the power quality problem caused by load fluctuation and distributed energy access can be effectively solved; the optimized communication architecture enables the real-time information interaction to be more efficient, and the cooperative control capability among the transformer areas is improved; through the flexible direct current interconnection technology, the problems of difficulty in capacity increase and point distribution and voltage quality difference of a traditional power distribution network are solved, and the stability and the safety of the power distribution network are improved. And meanwhile, the flexibility of cooperative operation of multiple transformer areas is improved, and the self-recovery capability of the system under the fault condition is enhanced.

A system is configured to: (a) provide a deep learning model; (b) receive a concept, the concept including text; (c) determine a word embedding representing the concept using the deep learning model; (d) determine a centroid for the concept, the centroid representing an average position of concept characteristics in a high-dimensional word embeddings space; (e) determine Euclidean distances for each of the concept characteristics; (f) determine cosine similarities for each of the concept characteristics; (g) determine a prominence index for each of the concept characteristics based on the determined Euclidean distances and the determined cosine similarities; and (h) provide, to a client device, a ranking of the concept characteristics based on the prominence index.

Systems and methods for stereotactic localization of components include a system for stereotactic localization of a component during a surgical procedure. In some cases, the system includes one or more of an instrument, a plurality of markers disposed on the instrument, one or more sensors configured to detect a position of each of the markers, and an output device. In some cases, the system is configured to calculate a digital 3-dimensional array based on the position of at least some of the plurality of markers, compute a location of the instrument, and communicate the location of the instrument to a user of the system through the output device. Other implementations are described.

A hybrid traffic flow testing method and system based on digital twin and virtual-physical integration includes steps as follows. Data of a realistic testing site is collected, and a virtual scene is created based on the digital twin, interactions between a realistic environment and a virtual environment are set up to achieve a system configuration of a system based on the virtual-physical integration. Virtual human-driven vehicles are generated based on a data set of the system configuration, and realistic human-driven vehicles are generated based on data collected by driving simulators operated by realistic human drivers. Human-driven vehicles are formed by combining the virtual and realistic human-driven vehicles, and status and location information of the human-driven vehicles are acquired. A set of sensing, positioning, planning, control, and V2X communication methods are set up based on the status and the location information for CAVs, thereby achieving autonomous driving.

The invention provides an audio and video system data comprehensive analysis and processing method based on a virtual distributed architecture, and the method comprises the steps: collecting a heterogeneous audio and video data set of a target region through a multi-source audio and video collection assembly cluster deployed in a virtual resource pool, and carrying out the distributed task decomposition according to a preset time-space correlation constraint condition; the method comprises the following steps: generating a feature extraction task set, then dynamically allocating tasks to a processing unit group based on real-time resource availability parameters of virtual computing nodes, triggering a parallel feature extraction process, then carrying out fusion operation on an intermediate feature data set through a cross-node communication interface, generating a global state description vector of a target area, and finally, carrying out feature extraction on the global state description vector. And a resource regulation and control instruction set is generated according to a mapping relation between the global state description vector and a preset system configuration strategy, and is transmitted to a scheduling management node of the virtualized resource pool, so that efficient and accurate comprehensive analysis and processing of the audio and video data are realized, and the overall performance and stability of the system are improved.

The present invention discloses a patrol system configuration method based on a standard point library, relates to the technical field of drone patrol, and is used to solve the problem of inflexible drone patrol requirements; the present invention establishes an intelligent standard point library and automated point management, and can flexibly generate and dynamically adjust equipment point configurations according to different equipment types, functional requirements and spatial distributions, thereby achieving more accurate and efficient equipment patrol, and introduces intelligent perception and multi-modal joint patrol technology, which improves the accuracy of fault detection through sensor data fusion and intelligent analysis, and optimizes patrol paths and task scheduling to ensure that high-risk equipment is patrolled first and maintained in a timely manner. In addition, the point optimization and dynamic adjustment mechanism can adjust the patrol path and task priority in real time according to the equipment health status, environmental changes and fault warning information, thereby improving the timeliness of patrols and the accuracy of equipment maintenance.

The invention relates to the technical field of power systems, and discloses a power distribution area energy storage parameter configuration method and system, and the method comprises the steps: obtaining power supply range information and power demand density information, and dividing a power supply area; identifying out-of-limit nodes, and generating voltage out-of-limit parameters; determining a voltage out-of-limit influence weight according to the topological connection relationship between the out-of-limit node and the transformer, the voltage out-of-limit parameter and the voltage regulation capability matrix, and generating a voltage out-of-limit responsibility quantification result; based on the voltage out-of-limit responsibility quantification result, load distribution characteristics are extracted, and energy storage system access points are determined; according to the voltage sensitivity and the load characteristics of the energy storage system access point, the capacity of the energy storage system is optimally configured, the energy storage system access point is optimized, a global optimal energy storage system configuration scheme is obtained, the technical problem of optimizing the energy storage system access point is solved, the power supply quality is ensured, and meanwhile, the energy storage system access point is optimized. And the economic benefit of the energy storage system is maximized.

A system configuration significantly reduces the number of interconnections needed between an electromechanical actuator (EMA) and an EMA controller (EMAC) while maintaining redundancy and other safety aspects needed by the target application without adding second or third independent redundant position sensors to the EMA for use with backup channel of the controller. The system configuration extends the sensor architecture used by COM-COM controllers with an additional sensor channel used by a backup controller without the need for adding a separate physical position sensor for the backup controller, which saves implementation effort, space, and weight that would otherwise be needed for integration of additional redundant sensors into the EMA.

The invention discloses an intelligent early warning system for laboratory hazardous gas leakage, and the system comprises a system initialization and configuration module which is used for carrying out sensor deployment, system configuration and network connection; the real-time monitoring and data acquisition module is used for continuously monitoring sensor data and preprocessing the data; the data analysis and judgment module is used for threshold comparison and trend analysis to obtain alarm information and notification information; the alarm and notification module is used for sending out alarm information and notification information; the linkage control and emergency response module is used for automatically closing a dangerous source and starting a ventilation system; the recording and reporting module is used for recording events and generating reports; and the system recovery and evaluation module is used for alarm release, system inspection and safety evaluation. According to the invention, more comprehensive and intelligent laboratory hazardous gas leakage early warning can be carried out.

The invention discloses a nuclear power DCS signal distribution method, device and equipment, a medium and a product, and relates to the technical field of industrial automation. The method comprises the following steps: acquiring information data; the information data comprises input data acquired by the input layer; the input data comprises signal configuration information data, hardware resource state data, DCS system configuration data and historical operation data; based on the core processing layer, performing data association interaction and constraint optimization processing according to the information data to obtain a processing result; based on the decision layer, determining a resource allocation scheme according to the processing result; the resource allocation scheme is used for representing a mapping relation between signals and resources in the nuclear power DCS system. According to the invention, nuclear power DCS signal distribution is realized, and the reliability and safety of the system are improved.

In some embodiments, a computer mouse comprises a housing, a depressible keyplate disposed within the housing, a carrier platform including a top side and disposed within the housing, a haptic element coupled to a top side of the carrier platform, a biasing system configured to couple the carrier platform to the housing and provide a pre-loading force that pushes the haptic element coupled to the carrier platform against a bottom surface of the depressible keyplate, and a limiter element operable to physically limit a movable range of the keyplate in one direction that prevents a top surface of the keyplate to deflect past an adjacent top surface of the housing due to the pre-loading force, the top surface of the keyplate and the adjacent top surface of the housing forming a continuous contour when the depressible keyplate is in a non-depressed, neutral position.

The present application provides a method and device in a node for wireless communications. A first node receives a first CSI (Channel Status Information) report configuration set; transmits a first information block. The first CSI report configuration set comprises a first CSI report configuration, the first CSI report configuration is used to determine a first CSI report, and the first CSI report comprises a first compress CSI; the first information block comprises the first CSI report; the first CSI report configuration is associated with a first index; the first CSI report occupies a first-type processing unit starting from a first symbol, and a number of the first-type processing unit(s) occupied by the first CSI report is related to the first index. The above method satisfies the demands for processing capability for AI / ML-based CSI report, while avoiding the waste of processing capability and optimizing the system configuration.

The invention relates to an operation method of an unattended intelligent mobile emergency cabin. Comprising the steps of system initialization, material information configuration, authority verification, order generation, material warehouse-in and warehouse-out, inventory monitoring, intelligent prediction, decision support, data processing and synchronization and the like. Various parameters are obtained and configured through the system configuration module, material information is managed through the material detail directory tree module, accuracy of access authority is ensured through the face recognition and authority verification module, and automatic order generation and inventory updating are achieved through the automatic order generation and inventory updating module. A gravity sensing unit is used for monitoring warehouse-in and warehouse-out of materials, an inventory alarm and decision-making auxiliary module is used for monitoring an inventory state and sending an alarm signal, an intelligent prediction unit is used for predicting a material use trend and generating a replenishment plan, and finally data processing and synchronous management are realized through a data processing module. Manual operation is reduced, management efficiency is improved, timeliness and reliability of material supply are ensured, and the method is suitable for the fields of electric power engineering and the like.

A DC-SCM composable BIOS system includes a DC-MHS computing device having a DC-SCM device with a BIOS subsystem and a BIOS configuration database. During initialization operations for the DC-SCM device that are part of an initialization of the DC-MHS computing device, the DC-SCM device determines that the DC-SCM device requires a BIOS image to be composed in order to operate with the DC-MHS computing device, and identifies a DC-MHS computing device processing system configuration and a DC-MHS computing device hardware configuration of the DC-MHS computing device. The DC-SCM device then retrieves BIOS modules from the BIOS configuration database based on the DC-MHS computing device processing system configuration and the DC-MHS computing device hardware configuration of the DC-MHS computing device, and uses them to compose the BIOS image. The DC-SCM device then provides the BIOS image in the BIOS subsystem, and causes a second initialization of the DC-MHS computing device.

Height adjustable angled desks are disclosed herein. An example height adjustable table includes three legs, each of the three legs including an upper section, a lower section, and an actuator; a connection system to couple the three legs; a height adjust system including drive system; a first gearbox coupled to the drive system; second gearboxes coupled to respective ones of the actuators, the first gearbox and the second gearboxes to change a transmission direction; and transmission shafts connected to the drive system and to the first and second gearboxes; and wherein the drive system is configured to drive the transmission shafts to drive the legs together to rise and fall, and wherein the drive system includes a motor, a worm connected to the motor, and a worm wheel engaged with the worm.

The invention discloses an energy storage optimal configuration method and system based on data-driven model fusion. The method comprises the following steps: extracting feature data with important influence in load data and operation and maintenance data for data fusion; constructing a load prediction model for predicting the load state of the energy storage equipment and a predictive maintenance model for predicting the health state and the remaining service life state of the energy storage equipment; training a load prediction model and a predictive maintenance model of the energy storage system through iteration; and the load state, the health state and the remaining service life state of the energy storage equipment are predicted in real time, an energy storage system configuration optimization model is constructed, and the overall configuration of the energy storage system is optimized. The method is not only used for short-term power load prediction, but also used for health state prediction and residual service life prediction of the energy storage system, through the accurately predicted energy storage equipment state, an energy storage system configuration optimization model is cooperatively constructed in a complex power grid scene, a maintenance plan is reasonably arranged, and efficient and stable operation of the energy storage system is ensured; and the reliability and the economical efficiency of power supply are improved.

An anomaly detection system uses configuration-related activity profiles, generated in course of threat samples analysis in a secure testing environment, consisting of features of system events and system configurations of endpoints and shared network assets. Backup archives and activity monitors are used to collect system events and system configurations from corporate networks to analyze them with threat pattern databases including configuration-related activity profiles.

A device for reversibly blocking activities of a target region of a subject includes a microfluidic system configured to route a fluid around the target region to change a local temperature of the target region; and an electronic system coupled with the microfluidic system for providing a real-time feedback.

The invention relates to the technical field of water pollutant concentration detection, and discloses a water pollutant concentration detection system and method based on big data analysis, and the water pollutant concentration detection method based on big data analysis comprises the following steps: constructing a multi-level sensing network, the multi-layer sensing network comprises a fixed monitoring station layer, a water surface unmanned ship layer and an underwater robot layer; carrying out multi-modal data fusion by utilizing a knowledge constraint data assimilation algorithm to generate consistent water quality parameter estimation; a double-layer cognitive structure combining a knowledge graph and a causal model is constructed, and water pollutant propagation understanding and tracing are achieved; continuous optimization of system configuration is realized through a multi-objective reinforcement learning framework; through collaborative optimization of a multi-layer sensing network, the system realizes three-dimensional monitoring of a water body, the monitoring coverage range is expanded, and meanwhile, the high-precision detection capability is kept.

The invention discloses a configuration recovery method of a storage system, electronic equipment, a program and a storage medium, and is applied to the technical field of storage. The configuration data comprises hardware information, logic information and network information; packaging the configuration data to obtain a configuration file in a standard format and storing the configuration file; when the configuration of the storage system is recovered, reading the configuration file, and for any configuration item of the storage system, generating an execution command for the configuration item; for the service configuration items, sorting execution commands of the service configuration items based on service dependency rules in the logic information; the execution commands of all the configuration items are sorted according to the execution sequence of the configuration items, an executable logic module is generated, and the executable logic module is executed to conduct configuration recovery on the storage system. By means of the scheme, configuration recovery of the storage system can be effectively achieved, and universality and reliability are guaranteed.