93 results about "Continuous analysis" patented technology

The invention discloses a landslide geological disaster deduction method and system based on an MPM method, and the method comprises the steps: collecting the multi-source data of a disaster scene, and synchronously constructing a digital twinborn model; a qualitative and quantitative two-stage inversion calibration model is adopted; a qualitative layer combines a monitored displacement direction and a deformation mode, and preliminarily inverts key parameters such as slip band cohesive force and an internal friction angle; the quantitative layer comparison model calculates the actual deformation range, collapse position and displacement, and parameters are optimized to match the actual landslide state; in landslide long-term evolution deduction, a rock-soil body aging characteristic model is embedded, an exponential function is used for describing annual scale parameter deterioration, prediction is divided into continuous analysis steps, MPM calculation is carried out based on a material point method, full-cycle simulation from the current year to the future years is completed, and deformation range, displacement and outburst risk results are output. And reliable decision support is provided for disaster prevention and reduction.

The invention discloses an automatic ship collision avoidance decision-making system, and relates to the technical field of ships, and the technical scheme is characterized in that the method comprises the steps: collecting environment data of a target ship in a navigation region and target ship dynamic data of the target ship in a navigation process; dividing the navigation area into navigation area blocks according to the risk level and the environmental data, and performing feature extraction on the dynamic data of the target ship to obtain dynamic feature parameters; analyzing and determining the normal variation range of the influence coefficients of the navigation region blocks with different risk levels to obtain a reference interval value; according to the reference interval value, performing statistics on influence coefficients between the current target ship and the surrounding environment and between the current target ship and other ships in the sailing process to obtain a statistical result, and comparing the statistical result with the reference interval value to obtain a collision avoidance risk early warning or continuous analysis instruction; the method has the effects of reducing the occurrence rate of collision accidents and improving the safety and orderliness of marine navigation.

According to the building intelligent monitoring method and system provided by the invention, the same target person is locked through target detection / target tracking, and continuous analysis is carried out in a detection period, so that the misjudgment risk caused by other persons, shielding and instantaneous noise can be remarkably reduced, and the evaluation stability is improved. By fusing the deviation (abnormal sight value during walking) of the sight, the head orientation and the walking direction with abnormal gravity center and upper limb action (abnormal walking value), an early risk signal can be captured before the abnormal behavior is upgraded, and the sensitivity and the recognition timeliness of the abnormal state are improved. And an abnormal total value is formed by using weighted average and is compared with a threshold value, so that the balance of false alarm and missing alarm can be realized in different building scenes, and the alarm result has higher availability and credibility. Finally, by marking the target personnel and pushing the warning command, security personnel can obtain clear risk objects and early warning prompts in the first time, the response time is shortened, and the field disposal efficiency and the overall security level are improved.

A system for at least partial closed-loop control of a medical condition is disclosed. The system includes at least one medical fluid pump. The medical fluid pump including a sensor for determining the volume of fluid pumped by the pump. Also, at least one continuous analyte monitor, and a controller. The controller is in communication with the medical fluid pump and the at least one continuous analyte monitor. The controller includes a processor. The processor includes instructions for delivery of medical fluid based at least on data received from the at least one continuous analyte monitor.

The invention discloses an intelligent log analysis and fault diagnosis system for distributed software, and relates to the technical field of software fault diagnosis, and the system comprises a data acquisition module which is used for acquiring a business log flow and an arrangement event flow, each log in the business log flow comprises a service name and a first timestamp, and the first timestamp is a first timestamp; the arrangement event flow comprises discrete events of all containers under the corresponding service names and operation nodes deployed by all the containers. According to the method, fault analysis is changed from traditional instantaneous discrete static deployment fault analysis to dynamic continuous analysis through the generated enhanced trajectory, and the real trajectory of the service request in the execution process can be accurately restored, so that a series of novel hidden faults directly caused by container dynamics can be detected; and the fault detection accuracy is effectively improved.

The invention discloses a multi-source data business travel service collaborative decision-making method and system, and relates to the technical field of business travel services, and the technical scheme is characterized in that the method comprises the steps: collecting business travel demand scene information of a current user, and calculating the resource matching complexity according to the business travel demand scene information; comparing and judging the resource matching complexity to obtain a first-level collaborative decision signal or a continuous analysis signal; if the resource matching complexity is compared and judged as a continuous analysis signal, extracting historical behavior data of the user, and constructing a resource relation model associated with the current scene according to the historical behavior data; analyzing calling time sequence characteristics of the user to the resource nodes based on the resource relation model; wherein the calling time sequence characteristic comprises an abnormal calling duration proportion and a continuous abnormal calling frequency; generating a time sequence exception index according to the exception call duration ratio and the continuous exception call frequency; the effect is that resources and service power can be flexibly allocated.

The invention discloses a protocol dynamic adaptation method for a stock power Internet of Things terminal, and relates to the technical field of power Internet of Things and information communication computers. Comprising the steps of collecting communication message data and generating a standardized message data set in combination with a protocol mode analysis method based on an interaction process of side equipment and a stock power Internet of Things terminal; performing preprocessing based on the standardized message data set, and performing feature extraction to form a feature set adapted to model training; constructing a protocol recognition model according to the feature set, and realizing online incremental training and self-adaptive modeling of a newly added unknown protocol through a dynamic updating mechanism; and deploying the protocol identification model to an edge side, performing reasoning identification on stock power Internet of Things terminal communication message data acquired in real time, and if an identification result is not in a local registry, triggering a federal learning update process to realize protocol dynamic adaptation and continuous analysis of the stock power Internet of Things terminal.

The application discloses a kind of underground space optical cable high fidelity sound restoration method based on DAS system, comprising: the real-time signal collected to optical cable is carried out data demodulation, identify whether it contains energy impact signal generated by the optical cable after being padded and being hit, if it contains, the energy abnormal distribution position in energy impact signal is positioned, obtains positioning point;Continuous analysis time domain signal of positioning point, after filtering low-frequency interference signal, phase anomaly signal is rejected;The sound signals of a plurality of equivalent sensing nodes adjacent to the positioning point are superimposed and averaged to suppress additive noise, and then the sound signal is restored.The application can realize rapid positioning according to the spatial distribution mapping relationship of optical cable, and after filtering background noise from the collected signal, the highly correlated signals of multiple spatial sensing nodes near the positioning position are linearly superimposed to suppress additive random noise, and high-fidelity sound signal restoration is realized.

In an embodiment, a method of dynamically adapting analyte rate-of-change determination to a current patient context includes receiving, from a continuous analyte monitoring system, a plurality of analyte measurements of a patient. The method also includes automatically determining a current context for the patient based on the plurality of analyte measurements. The method also includes automatically configuring an analyte rate-of-change determination based on the current context. The method also includes generating a context-adapted rate-of-change measurement based on the automatically configured analyte rate-of-change determination and the plurality of analyte measurements.

There is provided a technique of generating MAP message for V2X intersection. The technique comprises: obtaining road-informative data related to the vicinity of the intersection and collected by one or more sensor-based (SB) source-modalities and one or more V2X source-modalities monitoring the vicinity of the intersection and operatively connected to the control unit, wherein the obtained road-informative data comprises vehicle-related data informative of vehicles and of parameters thereof detected by the source-modalities in the vicinity of the intersection; separately for each of the detected vehicles aggregating the obtained road-informative data; processing the resulted data to obtain lane-level geometry of the intersection; and encoding the generated geometry to generate the MAP message. The MAP message is automatically regenerated responsive to detecting an anomaly event (e.g. anomaly event can be detected by continuously analyzing the collected and stored timestamped road-informative data and TLC-informative data to detect changes indicative of the anomaly event).

In an embodiment, one general aspect includes a method of optimizing data transmission from a device to a remote target. The method includes receiving analyte measurements from a continuous analyte monitoring (CAM) system. The method also includes determining a current status of a connection between the device and the CAM system. The method also includes conditionally transmitting data related to the analyte measurements over a network to a remote target based on the current status of the connection.

Systems and methods for operating a continuous analyte monitoring (CAM) device are provided. In one example, a method includes converting a first stream of analyte data to an analyte value that reflects a biological concentration of an analyte; obtaining one or more additional streams of data from one or more auxiliary sensors; inferring, based on the first stream of data and the one or more additional streams of data, that a conversion of the first stream of data to the analyte value is predicted to be inaccurate; and taking a mitigation measure to avoid reporting the inaccurate analyte value to a user. In this way, corrective measures can be taken to improve overall CAM device operation, the quality of data provided via the CAM device can be improved, and user health and safety characteristics associated with the continuous analyte monitoring device can be improved.

This invention discloses a log intelligent analysis and fault diagnosis system for distributed software, relating to the field of software fault diagnosis technology. It includes a data acquisition module for acquiring business log streams and orchestration event streams. Each log entry in the business log stream includes a service name and a first timestamp. The orchestration event stream includes discrete events for each container under the corresponding service name and the running nodes deployed by each container. This invention transforms fault analysis from traditional instantaneous, discrete, static deployment fault analysis to dynamic, continuous analysis through the generated enhanced trajectory. It can accurately reconstruct the true trajectory of business requests during execution, thereby detecting a series of novel, hidden faults directly caused by container dynamism, effectively improving the accuracy of fault detection.

A continuous analysis method comprising generating microfluidic droplets comprising multiple copies of a same antigen, multiple copies of a same primary antibody potentially capable of specifically binding to said antigen, a multivalent crosslinking agent being a biomolecule or a support, and a fluorescent labeling agent, said continuous microfluidic analysis being a fluorescence-based sorting.

Systems, devices, and methods are provided for dynamic determination and presentation of inter-feature correlation insights. In one embodiment, a non-transitory computer-readable storage medium storing a program is provided, the program including instructions that, when executed by at least one processor of a computing device, cause the at least one processor to perform operations including: identifying at least one analyte feature using an analyte feature selection user interface (UI), identifying at least one correlated feature using a correlated feature selection UI, determining an analyte feature trend for the at least one analyte feature, determining a correlation feature trend for the at least one correlated feature, determining at least one inter-feature correlation insight based on the analyte features and the correlated feature trend, determining a correlation magnitude profile for the at least one inter-feature correlation, and displaying the at least one inter-feature correlation insight using the at least one insight UI.

The present invention relates to a specialized AI-driven data analytics platform tailored for optimizing engineered T cell therapies in patients, particularly those undergoing treatment for cancer, autoimmune diseases, and inflammatory conditions. Unlike general-purpose AI systems, this platform integrates advanced machine learning, deep learning, and fuzzy logic algorithms to continuously analyze and prioritize real-time data from multiple sources, including patient monitoring systems, laboratory tests, imaging modalities, wearable devices, and genomic profiles. The platform is specifically designed to predict and manage adverse events unique to T cell therapies, such as Cytokine Release Syndrome (CRS) and Tumor Lysis Syndrome (TLS), offering clinicians real-time, personalized guidance that dynamically adjusts treatment protocols during and after T cell infusion. The system's adaptive learning capabilities allow it to evolve by incorporating clinical feedback and patient outcomes, continuously refining its predictive models to enhance precision and effectiveness. By providing robust support for managing complex side effects and delivering actionable recommendations, this invention marks a significant advancement in the application of AI to oncology, offering a highly specialized, innovative approach to enhancing the safety and efficacy of engineered T cell therapies.

The invention relates to the technical field of soil environment monitoring, in particular to a forest soil carbon sink dynamic monitoring and data acquisition device which comprises a shell and a probe used for measuring soil carbon content data in real time, a roller mechanism is arranged at the bottom of the shell, and a processor, a power supply module, a communication module and a storage module are arranged in the shell; a shielding mechanism is arranged at the top of the shell and comprises a plurality of detachable arc-shaped plates, the arc-shaped plates are annularly arranged with the shell as the center, solar power generation modules are further arranged on the concave faces of the arc-shaped plates, a rotating mechanism used for driving the arc-shaped plates to rotate is arranged on the shell, and the solar power generation modules are electrically connected with the power supply module. A drilling mechanism used for soil drilling is arranged at the bottom of the shell and comprises a lifting mechanism used for adjusting the drilling depth and a cutting mechanism used for cutting off tree roots in soil. The method is used for meeting the data transmission requirement under the forest complex environment, and continuous analysis of the carbon sink data is guaranteed.

The invention relates to the field of material analytical chemistry and biochemistry, and provides a continuous batch pretreatment device and method for proteomics, glycoproteomics and phosphorylated proteomics samples. According to the continuous batch pretreatment device for the proteomics, glycoproteomics and phosphorylated proteomics samples, under the assistance of the filler, the whole process of protein denaturation, aggregation capture, enzymolysis and complete glycopeptide and phosphorylated peptide enrichment in biological samples can be achieved. Compared with a free solution method conventionally used in proteomics, the sample pretreatment method based on the device has the advantages that the sample treatment time can be effectively shortened, and continuous analysis of mass proteome, glycoprotein group and phosphorylated proteome of trace protein samples can be realized; the method is expected to be widely applied to the aspects of disease occurrence mechanisms, drug action mechanisms, clinical detection, biomarker discovery and the like.

In an embodiment, a method of optimizing analyte event identification includes receiving, from a continuous analyte monitoring system, first analyte measurements determined for a patient during a first time period. The method also includes transforming the first analyte measurements into first relevance metrics that each indicate a probability of an occurrence of a defined analyte event during the first time period. The method also includes generating a personalized analyte signature for the patient for the first time period based on the first relevance metrics. The method also includes automatically identifying one or more analyte events for the patient based on an evaluation of additional analyte measurements determined for the patient relative to the personalized analyte signature for the patient.

The invention relates to the technical field of medical data analysis, in particular to an endocrine detection data real-time analysis system, which comprises a multi-objective optimization classification module, an endocrine detection data real-time analysis module and a health classification module, according to the method, the dynamic health state classification boundary is generated by collecting the endocrine detection data in real time and analyzing the change relation between the data, and the real-time change of the endocrine state can be accurately reflected. By analyzing the association strength between the data and generating the association matrix, the potential interaction between the data is effectively mined, and a scientific basis is provided for health status assessment. In continuous analysis of the time sequence, abnormal changes are recognized and future trends are predicted in combination with the incidence matrix, and early warning is provided for health risk assessment. And the fluctuation trend and key trend inflection points of the data are identified, and the dynamic evaluation capability of the health state is optimized.

A method of displaying continuous analyte data including receiving analyte data through a communication interface, wherein the analyte data comprises a plurality of analyte readings; determining a numerical value corresponding to a current analyte level based on the analyte data; and displaying the numerical value on a display screen.

A method of providing performance reports to persons associated with the monitoring of an analyte level, such as blood glucose concentrations in a host, is provided. The performance reports can indicate a measure of an analyte variability of the host over a first analysis time period compared to a measure of analyte variability of the host over one or more other analysis time periods. The analyte level of the host can be received in each of a plurality of sensor readings from a continuous analyte sensor, such as multiple sensor readings per hour, so that the analyte variability that is used in determining the performance report of the host can be based on not just a few metered readings taken by the host, but a plurality of intermittent readings that are taken by a continuous analyte sensor, for example. Various types of performance reports can be generated, such as reports that comprise charts, graphs, tables, and / or other visual indicia of a host's performance during one analysis period versus another analysis period.

The application discloses a battery pack charging energy consumption equalization optimization method, and relates to the technical field of battery management. The method establishes a charging energy consumption contribution function for each battery monomer in the battery pack in the charging process dimension, which is used for describing the energy consumption intensity and its change rule at different charging process positions; based on the energy consumption contribution function of each monomer, a battery pack energy consumption distribution state is constructed at each position of the charging process, and the energy consumption distribution dispersion is calculated to quantify the charging energy consumption equalization degree among the monomers; further, the energy consumption distribution dispersion is continuously analyzed in the charging process range, and it is determined whether the energy consumption imbalance presents a convergence trend or an amplification trend; when it is determined that there is an amplification trend, a charging process reconstruction mapping is generated with the target of reducing the energy consumption distribution dispersion, and the distribution structure of the energy consumption contribution in the charging process is controlled and adjusted; finally, the energy consumption distribution dispersion is recalculated based on the reconstructed energy consumption contribution function, and when it satisfies the preset equalization condition, the charging energy consumption equalization optimization is determined to be completed.

The invention discloses a gesture recognition method and program product for a vehicle, and the method comprises the steps: obtaining the video information of a target user through a target interaction device in the vehicle, and enabling the video information to comprise a plurality of video frames; a static gesture queue of the target user is determined according to the multiple video frames, and the static gesture queue comprises hand arrays of the multiple video frames; the hand array at least records hand initial examination data and hand key point data; the hand initial detection data comprises a hand detection state and hand position data; the hand detection state is used for indicating whether hand information exists in the video frame; and determining a dynamic gesture of the target user according to the static gesture queue, and controlling the vehicle to execute a response operation corresponding to the dynamic gesture. Therefore, by performing continuous analysis on multiple groups of video frames, consumed cache resources are effectively reduced, and the calculation amount of data is reduced, so that the method and the device can be deployed in more application scenes.

The invention relates to the technical field of model construction, in particular to a construction method of a garbage classification model based on data analysis and machine learning. The method comprises the following steps: determining a garbage discharge area through a GIS (Geographic Information System) visualization system, and discretely dividing the garbage discharge area into three-dimensional discharge units with height, area and adjacency relations; then, aiming at each three-dimensional discharge unit, the discharge concentration characteristic of the garbage in the horizontal direction and the accumulation and diffusion characteristic of the garbage in the vertical direction are analyzed, so that the garbage discharge composition state is determined; on the basis, a corresponding relation between the garbage physical composition and the garbage classification proportion is established, and a garbage classification prediction model is constructed; and finally, carrying out classification prediction on the garbage discharge area by utilizing the model, and carrying out visual display on a prediction result through a GIS (Geographic Information System). According to the invention, garbage discharge and migration characteristics are described through three-dimensional GIS and time continuous analysis, and precise prediction and visual management of garbage source classification are realized in combination with machine learning.

The application provides a whole calculation method and system of a cross-fixed pulley continuous cable structure and a calculation device, and relates to the technical field of bridge engineering and structural mechanics. The method comprises the following steps: acquiring system parameters and target state parameters; solving initial unstressed cable length; performing continuous calculation in multiple construction stages, updating the structure state based on the result of the previous stage in each stage, cyclically traversing the pulley, calculating the sliding stiffness and sliding amount, adjusting the unstressed cable length, directly updating the cable force by using a cable force-cable length change relationship, and storing the result after the system balance converges; and outputting the calculation results of all stages, which realizes automatic parameter updating and multi-stage continuous analysis, avoids manual modeling and repeated input between stages, has the advantages of high precision, high efficiency and strong reliability, and is suitable for construction control of a large-span cable system.