31 results about "Cybernetics" patented technology

Holistic cybernetic vehicle control enables the results of machine sensing and decision making to be communicated to a vehicle operator through the various senses of the operator. By providing machine advice to the operator through various vehicle functions and by integrating the machine advice with what the operator senses and perceives, holistic cybernetic control can result in much better and safer vehicle operation. The invention integrates human and machine vehicle control action to improve vehicle operation and, particularly, to avoid collision events.

The invention integrates emerging applications, tools and techniques for machine learning in medicine with videoconference networking technology in novel business methods that support rapid adaptive learning for medical minds and machines. These methods can leverage domain knowledge and clinical expertise with networked cognitive collaboration, augmented clinical intelligence and cybernetic workflow streams for learning health care systems. The invention enables multimodal clinical communications, collaboration, consultation and instruction between and among heterogeneous networked teams of persons, machines, devices, neural networks, robots and algorithms. It provides for both synchronous and asynchronous cognitive collaboration with multichannel, multiplexed imagery data streams during various stages of medical disease and injury management—detection, diagnosis, prognosis, treatment, measurement, monitoring and reporting, as well as workflow optimization with operational analytics for outcomes, performance, results, resource utilization, resource consumption and costs. The invention enables cognitively-enriched, annotation and tagging, as well as encapsulation, saving and sharing of collaborated imagery data streams as packetized clinical intelligence.

The invention integrates emerging applications, tools and techniques for machine learning in medicine with videoconference networking technology in novel business methods that support rapid adaptive learning for medical minds and machines. These methods can leverage domain knowledge and clinical expertise with cognitive collaboration, augmented medical intelligence and cybernetic workflow streams for learning health care systems. The invention enables multimodal cognitive communications, collaboration, consultation and instruction between and among cognitive collaborants, including heterogeneous networked teams of persons, machines, devices, neural networks, robots and algorithms. It provides for both synchronous and asynchronous cognitive collaboration with multichannel, multiplexed imagery data streams during various stages of medical disease and injury management—detection, diagnosis, prognosis, treatment, measurement and monitoring, as well as resource utilization and outcomes reporting. The invention acquires both live stream and archived medical imagery data from network-connected medical devices, cameras, signals, sensors and imagery data repositories, as well as multiomic data sets from structured reports and clinical documents. It enables cognitive curation, annotation and tagging, as well as encapsulation, saving and sharing of collaborated imagery data streams as packetized medical intelligence. The invention augments packetized medical intelligence through recursive cognitive enrichment, including multimodal annotation and [semantic] metadata tagging with resources consumed and outcomes delivered. Augmented medical intelligence can be saved and stored in multiple formats, as well as retrieved from standards-based repositories. The invention provides neurosynaptic network connectivity for medical images and video with multi-channel, multiplexed gateway streamer servers that can be configured to support workflow orchestration across the enterprise—on platform, federated or cloud data architectures, including ecosystem partners. It also supports novel methods for managing augmented medical intelligence with networked metadata repositories [inclduing imagery data streams annotated with semantic metadata]. The invention helps prepare streaming imagery data for cognitive enterprise imaging. It can be incorporate and combine various machine learning techniques [e.g., deep, reinforcement and transfer learning, convolutional neural networks and NLP] to assist in curating, annotating and tagging diagnostic, procedural and evidentiary medical imaging. It also supports real-time, intraoperative imaging analytics for robotic-assisted surgery, as well as other imagery guided interventions. The invention facilitates collaborative precision medicine, and other clinical initiatives designed to reduce the cost of care, with precision diagnosis [e.g., integrated in vivo, in vitro, in silico] and precision targeted treatment [e.g., precision dosing, theranostics, computer-assited surgery]. Cybernetic workflow streams—cognitive communications, collaboration, consultation and instruction with augmented medical intelligence—enable care delivery teams of medical minds and machines to ‘deliver the right care, for the right patient, at the right time, in the right place’ - and deliver that care faster, smarter, safer, more precisely, cheaper and better.

The invention discloses a system for planning, addressing and optimizing the value of an entity channel. The system is characterized by comprising a planning function, an addressing function and a value optimization function, wherein the planning function is used for planning a layout design of a regional entity channel based on urban planning and market analysis; the addressing function is used for analyzing and estimating a candidate address of the entity channel to obtain business prediction and benefit prediction of the candidate address; and the value optimization function is used for evaluating the value of the current entity channel and designing an optimal configuration scheme of personnel and equipment. Based on a system theory and a control theory, the system for planning, addressing and optimizing the value of the entity channel performs system analysis on all important factors relevant to the planning and the addressing of the entity channel and provides a key factor, so the transformation from a model to actual operation is realized and effective decision basis is provided for scientific addressing and adjustment on value optimization of the entity channel. Moreover, the system has high operability and practicality.

A method for performing a biological experiment includes accessing a protocol that specifies operations and prescribes a plurality of conditions for carrying out the biological experiment in a defined space. The method includes performing the sequence of operations according to the protocol; and periodically before or as the sequence of operations are performed, obtaining observations of particular conditions of the plurality, and comparing the particular conditions as observed to the particular conditions as prescribed. When a particular condition as observed deviates from the as prescribed by more than a predetermined threshold for the particular condition, the method includes interrupting the sequence of operations, accessing a corrective protocol that specifies an operation for remediating the particular condition as observed to within the predetermined threshold of the particular condition as prescribed, performing the operation to remediate the particular condition according to the corrective protocol, and resuming the sequence of operations.

The invention integrates emerging applications, tools and techniques for machine learning in medicine with videoconference networking technology in novel business methods that support rapid adaptive learning for medical minds and machines. These methods can leverage domain knowledge and clinical expertise with cognitive collaboration, augmented medical intelligence and cybernetic workflow streams for learning health care systems. The invention enables multimodal cognitive communications, collaboration, consultation and instruction between and among heterogeneous networked teams of persons, machines, devices, neural networks, robots and algorithms. It provides for both synchronous and asynchronous cognitive collaboration with multichannel, multiplexed imagery data streams during various stages of medical disease and injury management—detection, diagnosis, prognosis, treatment, measurement, monitoring and reporting, as well as workflow optimization with operational analytics for outcomes, performance, results, resource utilization, resource consumption and costs. The invention enables cognitive curation, annotation and tagging, as well as encapsulation, saving and sharing of collaborated imagery data streams as packetized medical intelligence.

The invention discloses an emergency optimization control method for nuclear chemical accidents based on natural cybernetics, which belongs to the field of hazard control. The invention first predicts and warns the hazards of nuclear chemical accidents, and then formulates an optimal control scheme based on natural cybernetics on the basis of predicting the consequences of nuclear chemical accidents. An emergency optimization control method for nuclear chemical accidents based on natural cybernetics proposed by the present invention can not only achieve the goal of emergency control of nuclear chemical accidents, but also minimize the cost of control and accident losses, and realize emergency response to nuclear chemical accidents best control.

The invention relates to a human-in-loop machine learning application development method and system, a machine learning application development process is regarded as a control process, a data flow isa signal flow, and according to a negative feedback adjustment principle in a control theory, a negative feedback loop comprising an online stage and an offline stage and three artificial assistantsis designed. Data of the on-line loop can enrich basic data samples, fault feedback of the on-line loop is matched with manual processing to position the off-line data or the model stage, then the problem is solved, and finally the model data flow is uploaded to the on-line state to form a continuous iterative development process. The invention provides a solution for developing a complete set ofprocesses of machine learning application. According to the method, based on the negative feedback adjustment principle in the control theory, manual experience and knowledge are applied to loops of all development stages at a relatively low cost, iterative and incremental development is supported, and the development quality of all components and stages is improved, so that the performance of thewhole application is improved.

The invention discloses a dynamic arc model construction method considering the random variation of arc length, and belongs to the field of power system fault detection and protection. The invention establishes a dynamic arc model by randomly changing the arc length and combining with the cybernetic arc model. The dynamic arc model constructed by the present invention takes into account the random variation of arc length. It can be seen from the simulation waveform generated by applying the model of the present invention to the simulation that the arc voltage and arc current are changing in different power frequency cycles, and the volt-ampere characteristic curve of the It is not completely coincident, so the difference between it and the actual waveform is narrowed compared with some traditional methods, thus indicating the effectiveness of this method to build a model.

A system and method is provided for constructing optimal cybernetic based systems. The method is based on a process of formalized rational inquiry, measurement and planned action. More particularly, the method relies upon the precise determination of alternatives through inquiry, a formal logical model of measurement, and the subsequent matching of information obtained through measurement to possible courses of action to arrive at a realizable and useful cybernetic system architecture

The invention discloses an adaptive shunting decision method based on cybernetics and data-driven. By defining a suitable network environment as the state input of an intelligent body module, and then through the training and testing process of a machine learning model, the intelligent body can be adaptive action decision; distribute the corresponding amount of video data to the transmission terminal after deciding the optimal split ratio of the multi-path; at the same time calculate the rate control range based on the dynamic change model of the buffer, and adjust the video bit rate to adapt to the buffer occupancy. changes to ensure the smoothness of video playback; through the control system, the accuracy of the application of the machine learning algorithm decision model in the actual system is further optimized; in the system testing stage, the optimal split ratio is used to transmit the corresponding video data, and calculate the video data The code rate range, the control system selects an appropriate value to match the dynamically changing buffer occupancy length.

The present invention discloses systems and methods for protecting technical systems (TS) from cyber-attacks. Exemplary methods include: acquiring the actual state of the technical system; initializing the cybernetic control system (CCS) by synchronizing the cybernetic control system (CCS) with the technical system; State comparison; based on the comparison, identifying the deviation of the actual state of the technical system from the ideal state of the technical system; when a deviation is identified, checking the integrity of at least the functional interconnection of the state of one or more units of the technical system; based on the technical system Based on one or more proven maintained functional interconnections between the units of the technical system, determining whether the ideal state of the technical system is a modeling error; and based on one or more disturbed functional interconnections between the units of the technical system, Identify anomalies in technical systems.

The invention discloses a control and management method for tuberculosis on the basis of a disease control theory. The method accords with the objective law of occurring and developing of the tuberculosis. Through effect evaluation of the control and management of the tuberculosis, performance of the control and management of the tuberculosis is analyzed, new suggestions for improvement are proposed for control and management of the tuberculosis, disease control of the tuberculosis is achieved gradually, and the control and management of the tuberculosis tending to a perfect medical condition is achieved.

The invention relates to a car-following control model, method and system based on optimized transmission information. In the vehicle-following control model, the influence of wireless transmission of estimated optimal speed difference information on traffic flow is considered, modern control theory is used, and the idea of ​​cybernetics is used. Realize the stability analysis of the control model, determine the parameters of the feedback gain of the control, so as to solve the problem that the existing car-following control model does not take into account the influence of the estimated and optimized speed difference information on the vehicle operation, which leads to the stability of the car-following control of the vehicle problem of poor sex.

The invention relates to a ball screw grinding chatter stability limit graph determining method, comprising the steps: 1) establishing a dynamics model of a grinding process via an experimental method; 2) according to the stability criterion of cybernetics, determining a grinding chatter stability limit graph; and 3) according to the grinding chatter stability limit graph, determining the parameters of the grinding technique for ensuring the grinding stability. The invention mainly aims at solving the chatter inhibition problem of a numerical control thread grinder in the grinding process of a ball screw, adopts the experimental design method to accurately identify the parameters of the grinding dynamics model, determines the grinding chatter stability limit graph according to the parameters, and provides the parameters of the grinding technique to ensure the grinding stability, thereby effectively solving the chatter inhibition problem in grinding process. The curve can be used to determine the parameters of the grinding technique, namely the abrasion wheel main shaft speed n and the grinding depth h to avoid flutter, thus the invention can improve the grinding quality and efficiency of the ball screw.