27 results about "Panic" patented technology

A device relating to a floater for use by a non-swimmer for buoyancy comprising a floating flatbed with coded descriptions (lateral ends: front end 14, back end 12) and a plurality of paired straps with buckles (20,22) to secure the floater flatbed (10) fixed in the swimmer’s body. This is designed to keep the non-swimmer afloat while concentrating on their hand and leg exercises. The floating flatbed is wrapped either at the upper limbs posterior or anterior portion of the body; a webbing belt with safety mechanisms buckled around the body which can be fixed at the levels; waist, abdominal, and upper back (posterior) or chest part (anterior). An adjustable strap is buckled across shoulders (24, 26) to fasten the device in place below the jaw with a plane surface of a floater which allows use purposely for either supine or prone floating mechanics fundamental in learning the basic skills for any appropriate floating position. Apparently, problems like drowning and other water accidents happen in just any part of the globe usually caused by panic and water anxiety. The device contains characteristics easy for use by non-swimmers at any age level for water safety and training device for non-swimmers particularly those who manifest water anxiety. Acquired skill in floating somehow creates mental alertness as a greater opportunity for survival during atrocities.

The invention relates to a real-time crowd panic probability identification method and system based on multi-modal fusion. The method comprises the following steps: collecting video data and audio data and carrying out data preprocessing; inputting the preprocessed video data into the CDNet to obtain a density map; candidate panic areas in the density map are extracted; identifying a target person in the candidate panic area in the video data frame by frame to obtain a motion trail sequence; obtaining the motion trail panic probability of the target person according to the high-order time sequence characteristics of the motion trail sequence; converting the preprocessed audio data into a frame-by-frame text sequence, and identifying panic language content; fusing the spatial structure features of the density map, the feature vector of the panic probability of the motion track and the context semantic features of the panic language content into a unified representation vector; and inputting the unified representation vector into a multi-layer perceptron to obtain a crowd panic probability identification result. Compared with the prior art, the method has higher adaptability and robustness.

The invention relates to the technical field of emergency rescue equipment, in particular to a compressed oxygen self-rescuer with a hand-free wearing function, which comprises a protective shell, an oxygen bottle, a switch hand wheel, an air storage bag, an extension soft bag, an air distribution layer, an absorption tank, an exhalation pipe and a split plate, by prolonging the closed space jointly formed by the soft bag and the air storage bag, it is ensured that the finally formed closed space can still be rapidly filled with oxygen-enriched air output by the low-pressure air supply end of the oxygen bottle, the situation that the inflation time is prolonged due to the too large volume can be avoided, and the situation that breathing resistance is increased due to the too small volume can also be prevented; according to the utility model, the soft material is prevented from collapsing and twisting due to insufficient inflation, the airflow channel is ensured to be always unblocked, and a user can feel obvious airflow support when inhaling the first breath, so that the panic emotion is effectively relieved.

The invention discloses a security activity scheme generation method and system based on machine learning, and relates to the technical field of security. The method comprises the steps of data acquisition and preprocessing, psychological feature quantitative model training, risk assessment, scheme generation and adjustment and model updating. A psychological feature quantitative model is constructed through machine learning, the real-time anxiety index and panic probability of participants are accurately predicted, and a secondary risk level is calculated in combination with site parameters, so that a security scheme is highly matched with an actual risk, and'one-step 'is avoided. Real-time data are collected every five minutes, the scheme is dynamically adjusted, and it is ensured that on-site changes are quickly responded. Data collection dimensions are comprehensive, data quality is guaranteed through preprocessing, a sliding window divides a data set, a random forest builds a model, new data is fused regularly to update the model, and prediction reliability is improved. The grading scheme pertinently prevents and controls secondary risks, guarantees activity safety, and meanwhile, differentially configures resources, optimizes the utilization of the resources and reduces the security cost.

The invention discloses a pedestrian dynamic modeling method and device considering panic emotion and a medium, and the method comprises the steps: firstly completing spatial discretization, static field calculation and obstacle processing through scene initialization, determining the distance from a grid to an exit through Euclidean distance, generating a static field value, and determining the spatial constraint of pedestrian motion; then, in a pedestrian motion calculation link, a multi-dimensional dynamic coupling panic factor quantification system is innovatively constructed, crowd density, environmental stimulation intensity, distances between pedestrians and stimulation sources and the like are synthesized, accurate quantification of panic emotions is achieved through a distance attenuation and time attenuation mechanism, and the panic emotions are deeply bound with motion parameters. According to the method, through deep fusion of the panic emotion and the OSM model, irrational behaviors and differentiated movement tracks of pedestrians in an emergency scene are effectively reproduced, the simulation precision of a complex evacuation scene is remarkably improved, a scientific quantitative basis can be provided for evacuation scheme optimization and crowd management and control strategy formulation, and the method is of great significance in improving the public safety management level.

The invention relates to the technical field of mental health assessment, in particular to a medical scene-oriented non-contact mental health assessment and intervention method, which comprises the following steps of: performing data enhancement on expression data and physiological data, and screening out enhanced expression data and enhanced physiological data; performing emotion recognition according to the enhanced expression data by using an emotion classification model to obtain an emotion recognition result of the detected object; and establishing a contact type psychological health assessment model by using a neural network, and carrying out transfer learning on the contact type psychological health assessment model to obtain a non-contact type psychological health assessment model. According to the method, the defects of the collected physiological data and expression data are repaired by utilizing the repair network, the quality of analysis data is improved, meanwhile, a contact type psychological assessment process based on the physiological data is converted into a non-contact type psychological assessment process by utilizing a transfer learning mode, external equipment does not need to be added to make contact with the body of a tumor patient, and the workload of the tumor patient is reduced. And unease and panic of tumor patients are avoided.

The application relates to the technical field of patient accompanying, and specifically provides an intelligent multi-dimensional management system for critical patients, which comprises an intelligent display terminal, an accompanying program is built in the intelligent display terminal, a fingertip controller, the accompanying program is controlled by the fingertip controller through acquisition of finger actions to select corresponding functions, wherein the fingertip controller comprises a direction control module, finger actions are acquired to control a cursor in the intelligent display terminal to move up, down, left and right along a screen, and a determination button module is used for acquiring actions of another finger to input confirmation and power-on / off instructions; the accompanying program in the intelligent display terminal enables the critical patient to make a video call with family members, watch videos and play small games, a rehabilitation mode with full participation of the family members is created to relieve the fear and anxiety of the critical patient, and thus problems such as anxiety, panic and delirium of the patient in an intensive care unit are prevented.

The invention discloses an emergency broadcasting method, a terminal and a storage medium. The method comprises the following steps: receiving an environment audio and video stream; separating human voice and environment voice categories based on the prompt vector; performing audio-visual cooperative positioning based on human voice, and extracting a face image; performing anti-shielding tracking on the target, and outputting continuous coordinates; human voice and human face features are fused to analyze emotion, and a panic index is output; in combination with the coordinates, the panic index and the environmental sound category, generating a safety guidance instruction through neural symbol reasoning; generating voice according to the instruction and performing psychoacoustic modulation based on the panic index; and finally generating beam forming parameters based on the coordinates. According to the method, the technical problem that the traditional broadcast cannot generate and precisely project the voice instruction with the psychological pacifying effect according to the specific position and the real-time psychological state of the target in a complex disaster site is solved.

The application discloses a sound stimulation self-adaptive regulation system based on abnormal state identification, wherein a signal acquisition and calculation module calculates an anxiety index by acquiring various physiological and motion sensing data of a user in real time; a panic identification and alarm module first corrects a motion state according to the motion sensing data, then runs a rapid threshold path and an unsupervised model path in parallel, and outputs a panic attack alarm signal and an abnormal intensity score; a sound stimulation control module selects a sound stimulation mode according to the output of the panic identification and alarm module and the anxiety index, and outputs corresponding sound stimulation according to an individualized file of the user; and a parameter optimization learning module evaluates the effect of sound stimulation in real time during the stimulation intervention process of the sound stimulation control module each time, optimizes stimulation parameters in the next step, and files and learns whole-process data after the intervention ends. According to the application, early and accurate identification and timely intervention of a panic attack state can be realized.

By detecting panic situations and providing a host device detailed panic data and mitigation options before the panic situation condition occurs, failure of data storage devices may be reduced. Several mitigation options may be presented to the host device upon detection of a future panic situation, such as adjusting read performance; increasing device power; performing evacuation and management operations; and / or redirecting host commands to another data storage device for command completion. When the other data storage device is in the same PCIe tree and reachable, the command may be directed with PRPs / SGLs that point back to the same host device. In some embodiments, the data storage devices may have a submission queue between them. In some embodiments, the data storage device comprises a panic early detection module and a panic control module.

The utility model relates to the technical field of mortar, and provides a frontier defense portable mortar shell anti-refilling detection device which comprises a mortar body. The sleeve shell is arranged on the gun barrel in a sleeving manner; the centering clamping assembly is arranged on the sleeve shell; the fixing assemblies are symmetrically arranged on the centering clamping assembly and used for fixing the sleeve shell; a power switch is manually pressed to activate a detection mechanism in a sleeve shell, then a system self-inspection indicator light is lightened after two seconds, so that whether the detection mechanism is normal or not is checked, then when a filling safety indicator light turns green, a driving assembly drives a blade of an iris closing assembly to retract, and shells can be normally filled; on the contrary, when the red is bright, the driving assembly does not work, the iris closing assembly continues to be closed, and shell filling is stopped, so that the shell filling condition in the mortar barrel can be displayed in real time, soldiers can conveniently and accurately recognize whether the bullets are excited or not, the panic psychology of live shell shooting training of the soldiers is relieved, and shooting safety accidents are prevented.

The invention relates to the technical field of crowd evacuation guiding, in particular to a crowd dynamic evacuation guiding method based on an emotional infection model, which comprises the following steps: acquiring multi-source sensing data such as a crowd density thermodynamic diagram, panic scream frequency distribution and real-time passage counting of gates at entrances and exits of a target place; after carrying out space-time alignment on the crowd density thermodynamic diagram and panic scream frequency distribution, inputting an emotional infection propagation model to generate a dynamic emotional field distribution diagram; calculating an instantaneous evacuation potential value of a candidate evacuation channel in combination with real-time passage counting, and screening a priority evacuation channel set; and extracting channel surrounding environment constraint parameters to generate a path weight matrix with physical capacity limitation, superposing emotional excitement indexes to remove conflict paths, and determining a final guide path set. According to the method, more accurate and more efficient crowd dynamic evacuation guidance can be realized.

By detecting panic situations and providing detailed panic data and mitigation options to the host device before the panic situation occurs, data storage device failure can be reduced. Upon detection of an impending panic situation, the host device can be offered several mitigation options, such as adjusting read performance; increasing device performance; performing swapping and management operations; and / or redirecting host commands to another data storage device for command execution. If the other data storage device is in the same PCIe tree and reachable, the command can be redirected using PRPs / SGLs that point back to the same host device. In some embodiments, the data storage devices can have a transmission queue between them.In some embodiments, the data storage device includes a panic early warning module and a panic control module.

A panic behavior recognition method and system based on a panic semantic model, and a medium. The method comprises the following steps: invoking an AI interface to perform real-time recognition on an audio stream to obtain semantic information, and by means of the semantic information and a basic concept, performing hierarchical division, and recognizing key speech segments; on the basis of a locating coordinate matrix, determining the specific hierarchical level and position of each key speech segment; and on the basis of the specific hierarchical level and position, using a description matrix to obtain the weight of the key speech segment, performing consistency matching on the degree of panic in a scenario, and determining whether a panic behavior has occurred, wherein the construction steps of a panic semantic reasoning network model are as follows: selecting a panic scenario as a description object; using a web ontology language to define a basis concept in the selected panic scenario; supplementing knowledge elements in the panic scenario, in order to improve a panic semantic model; and defining a reasoning rule, and constructing the panic semantic reasoning network model. Compared with the prior art, the method improves the accuracy of pedestrian panic behavior recognition.

This invention relates to a method and apparatus for identifying audio features of panicked pedestrians screaming. The method includes: extracting audio from a video; extracting audio features from a first frequency band of the audio and calculating the audio energy distribution; dividing the audio energy into intervals and establishing a panic behavior audio feature identification matrix model; and determining the behavior type and gender in the audio based on the audio feature identification matrix model. Compared with existing technologies, this invention identifies the screaming behavior of panicked pedestrians by analyzing audio features and establishing a panic behavior audio feature identification matrix model, exhibiting robustness and environmental adaptability.

The invention discloses a sound stimulation adaptive regulation and control system based on abnormal state recognition, and the system is characterized in that a signal collection and calculation module calculates an anxiety index through obtaining various physiological and motion sensing data of a user in real time; the panic recognition alarm module firstly performs motion state correction according to the motion sensing data, then runs a fast threshold path and an unsupervised model path in parallel, and outputs a panic attack alarm signal and an abnormal intensity score; the sound stimulation control module selects a sound stimulation mode according to the output of the panic recognition alarm module and the anxiety index, and outputs corresponding sound stimulation according to the individualized file of the user; the parameter optimization learning module evaluates the effect of sound stimulation in real time in each stimulation intervention process of the sound stimulation control module, and optimizes stimulation parameters of the next step; and meanwhile, archiving and learning the whole-course data after the intervention is finished. According to the invention, early accurate identification and timely intervention of the panic attack state can be realized.

The utility model relates to a bird transportation heat preservation box which comprises a box body, a heat preservation box body and a heat preservation box body. The lighting device is used for lighting the activity room; and the tooth grinding piece is used for being pecked and bitten by birds and protrudes from the inner wall of the movable chamber to the inside of the movable chamber. As the birds like pecking and biting protruding objects, the tooth grinding piece can attract the birds to peck and bite other places in the activity room, and the heat preservation box is not prone to being damaged due to pecking and biting of the birds. Besides, the lighting device can light the activity room, so that the panic emotion of the birds due to darkness is avoided, and the birds can clearly see the molar pieces in the activity room, so that the birds can peck and bite the molar teeth.

This utility model provides an anti-panic device for descent devices, belonging to the technical field of high-altitude installation devices. It solves the problem that existing descent devices, due to incorrect installation or operational errors, can cause a sudden, explosive fall that easily triggers panic. This anti-panic device includes a descent device body with an internal rope reel; a drive shaft is located at the center of the rope reel; an anti-panic device is located on the side wall of the descent device body; the anti-panic device has a follower turntable and a locking disc; the follower turntable is engaged with the drive shaft; the follower turntable has several locking pawls; the follower turntable also has a shaft with several limiting locking ratchet teeth; the inner wall of the locking disc has several concave teeth; a counterweight protrusion is located at one end of each locking ratchet tooth, and a limiting groove is located at the other end; a spring is located between the limiting groove and the follower turntable. This utility model has the advantages of being easy to use, preventing panic, and preventing sudden impacts.

The invention relates to the technical field of safety intelligent guidance, and particularly discloses a safety intelligent guidance method based on scene analysis and emergency plan triggering. Comprising the steps of situation awareness data stream generation, combined crisis state model construction, cooperative guidance instruction generation, field effect guidance environment deployment, physical feedback signal generation, closed loop validity verification result generation and guidance environment adaptive adjustment. According to the method, situation awareness data streams are generated through fusion of a multi-source sensor, a composite crisis state model is constructed, congestion and panic levels are quantitatively evaluated, then spatial differentiation cooperative guidance instructions are generated, an acousto-optic linkage field effect guidance environment is deployed, and the guidance strategy effectiveness is verified by monitoring the physical response of a crowd, so that the guidance efficiency of the crowd is improved. The guide environment is adaptively adjusted; according to the invention, the conversion from post-event response to pre-warning is realized, the evacuation efficiency and the system reliability are improved, and an innovative solution is provided for the safety management of large public places.

This invention discloses an emotion training system and method based on multi-sensory intervention and AI dialogue, belonging to the field of computer application and artificial intelligence technology. The system achieves proactive intervention throughout the entire cycle of panic attacks or acute anxiety attacks through the collaborative work of a multi-sensory intervention module, an AI dialogue system, a user data recording and feedback subsystem, and a peak detection state machine. The method includes: initiating AI dialogue and collecting multi-source evidence data; presenting dynamic storm visual effects, playing audio and vibration stimuli; calculating the emotion intensity curve I(t) based on real-time physiological proxy data (heart rate HR, skin conductance response GSR) and interaction data; automatically switching the stimulation parameters between peak and non-peak periods when the multi-source evidence score meets the threshold condition; calculating the amygdala sensitivity index (ASI), prefrontal control index (PCI), growth score (G), and courage index (CI) after the session ends, and generating a training report. This invention overcomes the limitations of traditional psychological applications that rely on a single sensory focus and passive relief, achieving closed-loop training with real-time detection, dynamic intervention, and effect quantification during the attack period.

A method for recognizing panic behavior based on panic semantic analysis includes: calling an AI interface to recognize audio streaming as semantic information in real-time, and performing, based on the semantic information and a basic concept, layered division to recognize key phrases; determining a specific layer and a position of each key phrase according to a position coordinate matrix; and obtaining a weight of each key phrase according to the specific layer and position using a description matrix, and performing consistency matching on a panic degree in a scene to determine whether the panic behavior occurs. Establishment steps of the panic semantic reasoning network model include: selecting a panic scene as a description object; defining a basic concept in the panic scene by using OWL; supplementing knowledge elements in the panic scene to improve the panic semantic model; and defining reasoning rules to establish the panic semantic reasoning network model.

This invention discloses a multi-agent reinforcement learning method and apparatus based on a panic attention mechanism. It includes: constructing the local state space, action space, and deterrence effect index of the drones based on local observations; constructing individual policy networks for each drone; constructing individual value networks for each drone; and, with the objective of maximizing the expected cumulative reward of the deterrence effect index over the entire optimization period, jointly optimizing the network parameters of the policy networks and value networks of all drones using experience replay and target network mechanisms, so that each policy network learns the optimal cooperative deterrence strategy. This invention provides a specialized reinforcement learning training method for drone swarm psychological deterrence formations, achieving improvements in training efficiency, strategy quality, security, and deployability.

The application discloses a simulation method for emotional contagion in a sudden public event based on an improved SIRS model, gives a function for quantifying the panic emotion of pedestrians, and gives a calculation method for related time-varying parameters of panic emotion contagion in a crowd based on the contagion mechanism of an infectious disease.The application comprises the following steps: a three-dimensional simulation modeling of a public place with a sudden accident is performed by using a computer simulation software; an emotion function for quantifying the risk perception of pedestrians is proposed, and the emotion values of the pedestrians to be evacuated are randomly set; the emotion states are divided according to the risk perception degrees of the pedestrians; the calculation method for related time-varying parameters of panic emotion contagion in a crowd is determined; an SIRS state transition relationship considering the risk perception and self-emotion regulation of the pedestrians is established; the evacuation speed of the pedestrians under the emotional contagion is determined, and simulation is performed; and the application can reflect the phenomenon that the pedestrians have panic emotions when a sudden event occurs and the panic emotions spread in a crowd, thereby providing decision support for preventing and managing the sudden event, especially simulating the crowd evacuation process after the event and formulating an evacuation scheme.

The utility model discloses a special anti-splashing face mask for a bronchoscope. The special anti-splashing face mask comprises a face mask main body, an eye protection piece and a protective cover, wherein the eye protection piece is arranged at the upper part of the face mask main body and is used for preventing splashing and relieving the panic psychology of a patient; the nose bronchoscope insertion hole is formed in the mask body and used for selectively inserting a bronchoscope during bronchoscopy; the mouth bronchoscope insertion hole is located below the nose bronchoscope insertion hole and used for selectively inserting the bronchoscope during bronchoscopy; the sputum suction tube insertion hole is formed in the mask body. The anti-splashing mask special for the bronchoscope can cover the face of a patient, is convenient to wear, can prevent cross infection between the patient and medical staff, can prevent hypoxia of the patient during bronchoscope operation, can prevent water from dripping into eyes of the patient during bronchus lavage operation, and can prevent a light source of the bronchoscope from being dazzling. A patient can experience a more comfortable bronchoscopy process, the bronchoscopy can be selected to enter through the nose or the mouth according to the condition of the patient during examination, and the clinical application range is wide.

According to the evacuation guidance system and method based on local station re-planning, the medium, the program product and the terminal provided by the invention, each station is only responsible for bringing personnel to a next safer position, so that an overlong instruction is prevented from being given in a complex environment, and the understanding cost and the execution cost are reduced. According to the method, the evacuation guidance information is played in a personification and emotion pacifying mode through the virtual digital human, the method has better compliance compared with a pure sound and light alarm, and panic diffusion can be effectively reduced especially under high-pressure situations (such as smoke, crowding and tension). According to the invention, each station recalculates the next route during evacuation guidance through the local re-planning module, dynamically shields danger and congestion and adjusts the evacuation path in real time, so that the robustness and reachability of the evacuation path are obviously superior to those of one-time global planning. According to the invention, after the evacuation personnel confirm to enter the safe area, the system can automatically stop the further guiding state of the evacuation personnel, and redundant tracking is avoided.

The invention relates to the technical field of vehicle safety, and provides a vehicle de-trapping method and device, electronic equipment and a vehicle, and the method comprises the steps: obtaining the image data and voice data of an environment where the vehicle is located, and determining a target intention response vector in response to the situation that the vehicle state is determined to be a trapped state according to the environment image data and the voice data; obtaining a vehicle signal label, and determining a target trapped type according to the environment image data, the voice data and the vehicle signal label; fusing the vehicle state, the target intention response vector and the target trapped type to obtain a target fusion vector; and inputting the target fusion vector into a pre-trained de-trapping processing model, and obtaining a target de-trapping control strategy through the de-trapping processing model. Therefore, the user can control the vehicle to get out of trouble according to the target getting-out control strategy, the situation that the user masters the vehicle in a limited degree and does not know how to control the vehicle to get out of trouble when the vehicle is in a trapped scene, and consequently the panic emotion is caused is avoided, and the driving safety and the vehicle using experience of the user are improved.