96 results about "Abnormal results" patented technology

The invention discloses an automatic electrocardiogram recognition system. The system comprises an electrocardiogram acquisition device, a wireless/wired network transmission module, an electrocardiogram collection and time domain feature recognizer, an electrocardiogram dominant wave interphase recognizer, an electrocardiogram QRS wave group similarity recognizer and an electrocardiogram queuing recognizer, the electrocardiogram acquisition device inputs acquired data to the electrocardiogram collection and time domain feature recognizer via the transmission module, the electrocardiogram collection and time domain feature recognizer recognizes to obtain positions of peak points of P waves, QRS waves and T waves on a 12-lead, the electrocardiogram dominant wave interphase recognizer recognizes heart rate to obtain normal and abnormal results of the heart rate, the electrocardiogram QRS wave group similarity recognizer recognizes whether an electrocardiogram probably has premature beat or not, and the electrocardiogram queuing recognizer sequences and outputs. The system performs real-time computer-aided analysis of clinically acquired 12-lead electrocardiograms to automatically recognize arrhythmia and premature beat electrocardiograms, and accordingly efficiency of electrocardiogram analysis is improved while a priority processing means is provided for emergency electrocardiograms.

The invention relates to the technical field of computers, in particular to a computer server cluster log monitoring method and monitoring platform. The monitoring method includes step A of monitoringmassive machine code commands generated by a main board during the running of each server in a computer server cluster, and using a real-time stream data collection frame in a big data technology tocollect the machine code commands generated by the main board in real time; step B of performing data classification and transfer operations on the collected data, including real-time filtering, processing and storage; step C of performing real-time analysis and display of the data processed in step B to obtain real-time analysis results and store the results; step D of performing analysis by combination with the real-time analysis results and stored historical analysis results, obtaining potential abnormal results of the computer server, and performing early warning and notification. The computer server cluster log monitoring method and monitoring platform have the advantages of real time, expandability, automation, high availability and rich API extension.

The invention relates to an industrial control system anomaly detection method based on a dual-contour model. Involved industrial control network equipment comprises a security gateway, a programmable logic controller (PLC), onsite sensor equipment, a security management platform, and an engineer station. The method comprises the following steps of S1, the engineer station configures and operates a system, the PLC of each region discriminates controlled equipment connected to an IP module of the PLC, an information list is distributed to the controlled equipment, and a periodic communication mode is formed for master and slave stations; S2, the PLC timely feeds back data information to the security gateway, a data packet deep analysis system of the security gateway extracts data features and eliminates superfluous attribute features, and only features related to a system behavior mode are left, wherein the features related to the system behavior mode comprises protocol features, data packet transmission direction features and register value variation rules based on the communication frequency; and S3, an anomaly detection subsystem carries out anomaly detection and sends an alarm to the security management platform for an abnormal result.

The invention provides a utility tunnel inspection system based on a robot and an interactive system. The utility tunnel inspection system based on the robot comprises a remote infrared monitoring anddiagnosis module, a remote image monitoring and diagnosis module, a remote sound monitoring and diagnosis module, a navigation positioning and motion control module, and a database. The remote infrared monitoring and diagnosis module is used for detecting the temperature of equipment in a utility tunnel, and sending equipment information exceeding an alarm value to the database after judgement ismade; the remote image monitoring and diagnosis module is used for collecting images of the equipment and moving bodies in the utility tunnel, analyzing the images and sending abnormal results to thedatabase; the remote sound monitoring and diagnosis module is used for collecting noise of electrical equipment in the utility tunnel, analyzing the noise and sending the noise to the database; and the navigation positioning and motion control module is used for obtaining the operating path of the robot. According to the utility tunnel inspection system, known targets and unknown targets can be detected through surrounding environment information obtained through sensors and treatment on the environment information, and treatment results are displayed on a system interface.

The invention provides a self-inspection control method of a robot, the robot and a dispatch server. The self-inspection control method comprises the steps that when a starting instruction or a wakeupinstruction is obtained, all components of the robot are controlled to start self-inspection treatment; when it is confirmed that a self-inspection result of any one component is abnormal, the identification of the component and the abnormal result are sent to the dispatch server; and an abnormal handling instruction issued by the dispatch server is received and executed. According to the self-inspection control method of the robot, after the robot is started or waken up, all the components of the robot are controlled to conduct self-inspection treatment, when the self-inspection result is abnormal, the abnormal handling instruction is received, and abnormal handling is conducted according to the abnormal handling instruction, it is achieved that abnormal detection is conducted before therobot executes a task, the fault probability of the robot in the task execution process is lowered, and therefore the reliability of the robot is improved.

The invention relates to a medical expense information processing method. The method is characterized by comprising the steps of receiving medical information; judging whether the medical information conforms to a case classification standard or not, if so, querying a first expense information threshold range corresponding to a first case category to which the medical information conforms, judging whether the medical information conforms to rational drug use regulations or not, if so, extracting medical expense information from the medical information, judging whether the medical expense information is contained in the first expense information threshold range or not, if not, outputting abnormal result information; if the medical information does not conform to the rational drug use regulations, outputting abnormal result information; if the medical information does not conform to the case classification standard, bringing the medical information into a new second disease category, and setting a second expense information threshold range for the second disease category; and extracting medical expense information from the medical information, judging whether the medical expense information is contained in the second expense information threshold range or not, and if not, outputting abnormal result information.

The invention discloses a method for detecting the status of the default gateway and corresponding device which can be used in the network system with default gateway. The said default gateway is directly connected to the physical ports of the devices in the network, and these devices have loop checks on the physical ports with default gateway connected directly. If the physical ports is under the status of UP, the working status of the default gateway connected directly with the physical ports is Normal; if the detected status is DOWN, then get the Abnormal result of the status of the default gateway.

The invention is suitable for the technical field of software testing, and provides a program debugging method and device, terminal equipment and a storage medium, and the method comprises the steps:judging whether a preset pause condition is met or not before each operation instruction of a to-be-debugged program runs; If a preset pause condition is met, pausing to run the operation instruction,and monitoring whether a debugging instruction sent by a preset debugger is received or not; if a debugging instruction sent by a preset debugger is received, executing the debugging instruction, andusing the debugging instruction for obtaining a first debugging result; after the debugging instruction is executed, the operation instruction is operated, and monitoring whether an abnormal result is generated or not in the operation instruction operation process; and if it is monitored that an abnormal result is generated in the process of operating the operation instruction, reporting the abnormal result as a second debugging result to the preset debugger. Through the method, the debugging efficiency of the program can be effectively improved.

Investigation is made into a cause by which an abnormal result is obtained from an arterial stiffness evaluation apparatus for evaluating a degree of arteriosclerosis based on pulse waves and blood pressures which are detected from an ankle and an upper arm. Provided is an arterial stiffness evaluation apparatus capable of calculating an index of accurate vascular stiffness. A vascular stiffness evaluation apparatus (60) includes: a pulse wave detecting unit (10) including a strain sensor (13); a pulse wave velocity determining unit (30); a blood pressure detecting unit (10); and a vascular stiffness index calculating unit (50) for calculating a vascular stiffness index which serves as an index of vascular stiffness of a living body based on the pulse wave velocity and the blood pressures. The pulse wave detecting unit (10) includes a brachial pulse wave detecting unit (11) for detecting a brachial pulse wave of the living body and a popliteal pulse wave detecting unit (21) for detecting a popliteal pulse wave of the living body. The blood pressure detecting unit (40) includes a strain sensor (13).

A clinical data processing system systematically organizes and analyzes clinically significant information of a patient using a result flag indicating a critical or abnormal result to automate display of a view of clinical data in various contexts including diagnosis, insurance, medical complaint assessment and others to improve patient care. A system for use in processing patient clinical data for access by a user includes a repository associating an observation with a clinical significance indicator and with data indicating observations relevant to evaluation of the observation having the associated clinical significance indicator. A clinical data processor uses the repository for automatically providing data for display in response to receiving data representing an input observation and an associated clinical significance indicator. The data for display supports a user in making a patie nt assessment and includes the input observation and associated relevant clinical data items. A display processor initiates generation of data representing an image including the data for display.

A method for testing stability of a server includes the following steps. Providing a first user input interface for a user to input test parameters. Generating a control signal according to the input test parameters and transmitting the control signal to the BMC of the server. Controlling the server to start and shut down via the BMC. Detecting whether the tested characteristics are within specified ranges during each start and shutting down operation. Generating a SEL if any abnormal result is obtained and records a test time when the abnormal result is obtained in the SEL. Storing the generated SEL in a storage unit. Providing a second user input interface on the display for the user to input conditions to filter test results. And responding to the input conditions and outputting corresponding test results to the display.

The invention discloses an equipment intelligent inspection method for a large hydropower station, and the method comprises the following steps: 1, determining the inspection content according to theequipment characteristics of the large hydropower station; 2, determining adopted inspection equipment; 3, determining an inspection route of each inspection robot, and determining an installation position and an acquisition content; step 4, centrally uploading the data to a background server; 5, enabling the background system to perform image recognition on the images and the video streams; performing temperature identification on the infrared thermogram; carrying out characteristic quantity analysis on the sound; 6, automatically judging whether the inspection equipment is normal or not; 7,enabling the background server to send the abnormal result to the mobile phone of the user in a short message mode and give an alarm for reminding; and step 8, automatically generating an inspection report. Compared with the prior art, the visible light camera, the infrared thermal imaging, the inspection robot, the sound acquisition instrument and other devices are adopted to replace manual inspection, so that the inspection efficiency is effectively improved, and the working intensity of personnel is reduced.

The present invention provides a warning method based on specific illegal building identification in a land resource video monitoring system. The method comprises: by setting up cameras in field monitoring points, capturing pictures periodically at fixed points, and returning the pictures to an information center server. Based on the traditional land resource monitoring network, the method provided by the present invention uses an R-CNN (Fast RegionConvolutional Neural Networks) framework based on the convolution neural network to carry out target detection on the building in the information center server; identification results in the pictures within a continuous period of time are compared and analyzed to determine whether the building is an illegal building, and abnormal results are submitted to carry out manual audit so as to achieve the purpose of intelligent and automated monitoring of land resources; and according to the method provided by the present invention, de-atomization treatment based on a dark channel is carried out on the returned captured pictures so as to reduce the influence of the haze weather on the detection result.

The invention discloses a method for monitoring an electrocardio intelligent control and data processing system using IoT smart cloud, and belongs to the field of smart medical. The method includes electrocardio vest hardware, an intelligent mobile terminal, and a cloud server. The electrocardiogram vest is used for measuring electrocardiogram data and sending the electrocardiogram data to the intelligent mobile terminal. The cloud server performs automatic monitoring and big data analysis according to an existing expert database and user historical pathography data based on the electrocardiogram condition data and the electrocardiogram index in the electrocardiogram data, and automatically give an alarm in the case of an abnormal result. The data generated by automatic monitoring and bigdata analysis in the cloud server is used by doctors. The doctors make decisions with reference with the data in order to provide remote diagnosis for patients. Treatment timeliness and success rate of heart diseases and cardiovascular diseases can be improved by using big data technology.

The embodiment of the invention relates to the field of Fintech, in particular to a method and device for monitoring a smart contract in a block chain, which is used for improving the safety of the smart contract. The method comprises the steps of obtaining a transaction request; calling the corresponding smart contract according to the transaction request; during the process that the smart contract executes the transaction request, if it is determined that the called operation code is an operation code needing to be paid attention to, judging whether the operation code needing to be paid attention to meets the error condition of a monitoring rule or not; and if yes, outputting an abnormal result of the called operation code according to the monitoring rule, and executing a blocking operation for the operation code.

In an automotive radio wave radar, a center frequency of a transmitted wave is shifted at a certain cycle, and position information of an obstacle detected at three or more center frequencies is subjected to decision by majority to determine whether detection results of the obstacle are erroneous with the occurrence of jamming. If any of the detection results is determined to be abnormal, the abnormal result is discarded. An automotive radio wave radar is realized which can correctly perform the obstacle detection even in the event of jamming without causing erroneous obstacle detection or omission of the detection.

The invention discloses a real-time human face attitude estimation method based on depth video streaming. The real-time human face attitude estimation method comprises two stages of sampling and training and estimating in real time. The sampling and training stage comprises the following steps of obtaining filed depth images of all human face angles; then conducting random sampling on the filed depth images of all angles and obtaining a training sample set; and using a supervised learning method to conduct training, and obtaining a classifier. The real-time estimation stage comprises the following steps of firstly extracting real-time human face filed depth images in the depth video streaming output by collection equipment and converting the real-time human face filed depth images into integral images; conducting random slice sampling on the integral images, utilizing the classifier obtained by training to conduct classification on samples, and obtaining a plurality of estimation results; and removing abnormal results for the results and conducting weighted average, and obtaining final human face attitude results. The real-time human face attitude estimation method based on the depth video streaming avoids influences of factors like illumination on the final results, and is good in instantaneity and precision.

The invention discloses an abnormal driving behavior detection method based on machine vision. The method comprises the following steps that: a step of preparing a precursor;in hardware model selection 2, the selectionan image acquisition module 4 acquires is selected to acquire face information and hand posture information of a driver; then heart rate detection and hand posture detection of the driver are completed on the face of the driver through an algorithm design 1, and then an abnormal result processing module 15 integrates a heart rate result of heart rate detection and a result of hand posture abnormal detection, so that abnormal behavior stopping detection of the driver is achieved, and corresponding measures are taken. According to the invention, driving behavior classificationis carried out on the acquired driver motion characteristics by integrating the two detection results and designing the classifier, so that the abnormal driving behavior is identified, and the abnormal result processing module processes the abnormal result.