Abstract: A gas purification assembly for an air-conditioning indoor unit, the gas purification assembly comprising: a filter device arranged at or near an air inlet end of the air-conditioning indoor unit, for filtering particles entrained in the gas entering through the air inlet end; an ion generator located downstream of the filter device along the gas flow direction, for increasing the content of positive and/or negative ions in the gas flow; an atomizing device located downstream of the ion generator along the gas flow direction, for increasing the humidity and the amount of ions of the gas flow, and eliminating the ozone generated by the ion generator; and a photocatalytic device located downstream of the atomizing device along the gas flow direction, for performing a photocatalytic reaction on the humidified gas flow. An air-conditioning indoor unit equipped with the gas purification assembly is also disclosed.

Abstract: An electronic device includes one or more processors comprising processing circuitry, and memory comprising one or more storage media storing instructions that, when executed individually or collectively by the one or more processors, cause the electronic device to determine a first spectrum comprising a plurality of frequency components for an image containing noise determined at each of a plurality of levels by transforming the image into a frequency domain at the plurality of levels, determine a plurality of tokens for a plurality of patches by segmenting the first spectrum into the plurality of patches and encoding the plurality of patches based on positions of corresponding patches, denoise the plurality of tokens based on the image, determine a second spectrum obtained by denoising the first spectrum, based on the plurality of denoised tokens, and generate a high-resolution (HR) image with an increased resolution of the image by inversely transforming the second spectrum into a spatial domain at the plu

Abstract: An apparatus includes one or more processors comprising processing circuitry, and memory comprising one or more storage media storing instructions that, when executed individually or collectively by the one or more processors, cause the apparatus to generate a feature map from an input image, generate a coordinate combined feature map by concatenating the feature map and a coordinate map indicating a location of a feature point of the feature map, predict noise of the feature map using a noise prediction model, based on the coordinate combined feature map, generate a denoised feature map by denoising the feature map based on the predicted noise, and generate a target image based on the denoised feature map.

Abstract: Provided are a human-factors intelligence user gaze analysis method, apparatus, and system, and an edge computing device, which belong to the technical field of computer vision. The method includes: collecting visual data of a user's field of view through a camera of a head-mounted device, and collecting eye movement data of the user within the field of view through an eye tracker of the head-mounted device; identifying a target object in the visual data; determining target eye movement data associated with gaze on the target object in the eye movement data; and sending the target eye movement data to a target screen to correspondingly present the target eye movement data on the target object displayed on the target screen. Embodiments of the present disclosure improve efficiency of user visual behavior analysis.

Abstract: Provided is a multimodal trajectory information processing and analysis system based on a man-machine interaction terminal. The system includes a collection device and an information processing device. The collection device is configured to collect, analyze and process finger operation trajectory information and send it to the information processing device, and the information processing device is configured to receive a display interface of a device under test in real time, and is configured to fuse and display the collected finger operation trajectory information corresponding to the display interface of the device under test, and obtain an evaluation system of man-machine interaction experience by analyzing a finger operation trajectory. The system achieves the simultaneous collection of the movement trajectory data and interaction data of the target object, which is convenient for accurately analyzing the rules and habits of the interactions between the users and the information systems.

Abstract: The present disclosure provides a human factor data storage method and analysis method, an electronic device and a storage medium. The storage method includes: acquiring a data packet from a sensor, the data packet containing human factor data; and storing the human factor data in a human factor data file in a predetermined data format, wherein the predetermined data format has a file header and a data body, the file header includes a frame header, a length value and a check value, the human factor data from the sensor is stored in the data body, and the check value in the file header is obtained based on a predetermined check algorithm. The human factor data storage method according to the present disclosure can keep data integrity and has a high data storage efficiency, and correspondingly, the analysis method has a high analysis efficiency. Data safety can be further improved.

Abstract: A semantic segmentation method based on point cloud data and a device using the same are provided. The method includes generating an input feature corresponding to input point cloud data, generating a global feature by performing global feature extraction based on the input feature, generating a bird's eye view (BEV) feature by compressing the global feature in a depth direction corresponding to the BEV, generating a merged feature by merging the global feature with the BEV feature, and generating a semantic segmentation result for the input point cloud data based on the merged feature.

Abstract: The present disclosure relates to a device and method of detecting a key point. The method includes obtaining an initial detection result and first variance information of a key point of a target object in an image, performing key point verification on the initial detection result based on the first variance information, and determining a detection result of the target object based on a verification result of the key point.

Abstract: Provided are an HRV-data preprocessing method and apparatus, and an electronic device. The method includes: obtaining HRV data corresponding to a sliding window; determining a variance of a plurality of target peaks corresponding to the HRV data, and determining HRV data having the variance that falls within a predetermined variance range as first target HRV data; determining an RR interval sequence of the first target HRV data based on the plurality of target peaks, determining whether each RR interval in the RR interval sequence falls within a predetermined heartbeat time interval range, and determining second target HRV data; and extracting a time-domain feature, a frequency-domain feature, and a nonlinear feature of the second target HRV data.

Abstract: Provided are a method, and an apparatus for processing a personnel workload state based on multimodal data, and a device. The method includes: acquiring state information of a first user; determining workload information of the first user according to the acquired state information, the state information includes at least two of: physiological information, eye movement information, electroencephalogram information, brain function imaging information, motion capture information, spatiotemporal acquisition information, behavior acquisition information, and facial expression and state information; and feeding back the workload information to a first management account, and formulating a training scheme matching the workload information. According to the embodiments of the present disclosure, the workload of the user can be recognized based on the multimodal data of the user.

Abstract: Provided in the embodiments of the present application are a training method and apparatus for a human-factor intelligence state monitoring model, and a human-factor intelligence state monitoring method and apparatus. The training method comprises: collecting physiological signals and video signals of persons to construct a training sample set, wherein an initial neural network model comprises a data preprocessing module, a common feature extraction module, a multi-head feature extraction module, etc.; and using the training sample set to train the initial model, to finally obtain a human-factor intelligence state monitoring model. In the present application, multivariate time-series data is fused with two-dimensional image data to construct and train a human-factor intelligence state monitoring model.

Abstract: Provided are a device and method for acquiring and processing an electroencephalogram signal. The device includes: an analog front-end processing circuit including an analog front-end chip configured to take a clock signal with the first clock frequency from an external clock as a clock input, acquire an EEG signal to obtain an analog EEG signal, convert the analog EEG signal into a digital EEG signal, and transmit the digital EEG signal to the control unit; a frequency division circuit connected to the external clock and configured to perform N-fold frequency division on a clock crystal oscillator of the external clock to obtain a clock signal with a target clock frequency; and a control unit configured to take the clock signal with the target clock frequency as a clock input, and perform data processing on the digital EEG signal from the analog front-end chip.

Abstract: The present application provides a method and apparatus for generating a group eye movement trajectory, a computing device, and a storage medium, belonging to the technical field of vision tracking. The method includes: acquiring eye movement data of each individual in a target group on a fixation object; generating an individual fixation trajectory of each individual on a plurality of areas of interest in the fixation object based on the eye movement data; and performing similarity fitting on the plurality of individual fixation trajectories to generate the group eye movement trajectory.

Abstract: Provided is a method for multi-terminal communication based on a virtual reality model, and the method relates to the field of expanded reality technologies. According to the method, a terminal device searches for a first communication address in a local area network, broadcasts a second communication address through the local area network when the first communication address is not searched out, receives a plurality of requests from a plurality of terminal devices, and sends a plurality of virtual reality models to the plurality of terminal devices based on the plurality of requests. The plurality of terminal devices have one-to-one correspondence with the plurality of virtual reality models. The technical solution according to the present disclosure can avoid the problem of poor maintainability caused by all terminal devices in the local area being bound to a single server, thereby improving the usage experience.

Abstract: A human-factor intelligent driving behavior prediction method, a terminal device and a storage medium are provided.

Abstract: Provided are a method for training a human-factors intelligent physiological state recognition model which includes: obtaining a first physiological signal, a first state label of the first physiological signal, a second physiological signal corresponding to the first physiological signal, and a second state label of the second physiological signal, in which the second physiological signal is a physiological signal generated based on the first physiological signal, the first physiological signal is a collected physiological signal, the first state label indicates a physiological state corresponding to the first physiological signal, and the second state label indicates a physiological state corresponding to the second physiological signal; and training a physiological state recognition model based on the first physiological signal, the second physiological signal, the first state label, and the second state label.

Abstract: Provided are a method for processing human-machine-environment data, an edge computing device and system and a storage medium. According to the method, the first process writes the first message into the first memory, and reads the second message from the first memory to obtain the message type and the method identifier that are carried in the second message after detecting that the second message is written into the first memory. When the value of the message type carried in the second message is a response, and the method identifier carried in the second message matches the identifier of the method that the first process requests to call, the first process determines that the second message is a response message of the first message, and then processes the second message, thereby realizing efficient and reliable inter-process communication on the same machine, and reducing the communication latency and resource consumption.

Abstract: Provided are a method and a system for real-time artifact processing and feature extraction of an electroencephalogram signal.

Abstract: Provided are a multi-parameter group biofeedback training method, apparatus, and system, and a storage medium. The method includes: receiving a predetermined training program and a predetermined training prescription that are set in a training management module, the training program being a combination of individual trainings, and the training prescription being a combination of long-term, time-sequenced phased trainings or training programs; and presenting the training scenario to a subject based on the training or the training prescription to execute the training, and collecting in real-time physiological data and/or target indicator data selected for the training. The training prescription includes predetermined training programs for a plurality of phases and a transition rule between the training programs for the plurality of phases. The training program includes one or more training tasks in a predetermined execution sequence. Each training task has a corresponding training scenario.

Abstract: Provided are an electroencephalography dry electrode and an electroencephalography measurement apparatus having the same. The electroencephalography dry electrode includes a substrate and a plating layer. The substrate includes a base and a plurality of columnar members. An end of each of the plurality of columnar members is fixed to the base. At least a surface of each of the plurality of columnar members is provided with the plating layer. The plating layer on the surface of each of the plurality of columnar members is electrically connected to the base.