Abstract: Provided is a patient data visualization method and system for assisting decision making in chronic diseases. According to the present application, a management data model diagram of a patient on a hyperplane is constructed by constructing a chronic disease knowledge graph, and combining static data and dynamic data of the patient, and then the management data model diagram is projected onto a two-dimensional plane. The difference of the Euclidean distance between features of a patient information model on a two-dimensional plane graph from the distance of standard features is compared, and a management plan is generated and recommended in combination with path node concepts and an attribute relationship between the concepts.

Abstract: Disclosed are an automatic compression method and platform for a pre-trained language model based on multilevel knowledge distillation. The method includes the following steps: step 1, constructing multilevel knowledge distillation, and distilling a knowledge structure of a large model at three different levels: a self-attention unit, a hidden layer state and an embedded layer; step 2, training a knowledge distillation network of meta-learning to generate a general compression architecture of a plurality of pre-trained language models; and step 3, searching for an optimal compression structure based on an evolutionary algorithm.

Abstract: The present invention relates to the technical field of network communication, in particular to a method and system for controlling ID identifier network mobility based on a programmable switch. The system includes mobile terminal nodes, mobile access points, programmable switching nodes and control nodes, wherein the control nodes include local control nodes and a global control node, the mobile terminal nodes are connected and communicated with the mobile access points through wireless data links, the mobile access points are connected and communicated with the programmable switching nodes through wired data links, and the programmable switching nodes, the local control nodes and the global control node are connected and communicated in order through control links.

Abstract: The present invention discloses a speech emotion recognition method and system based on fused population information. The method includes the following steps: S1: acquiring a user's audio data; S2: preprocessing the audio data, and obtaining a Mel spectrogram feature; S3: cutting off a front mute segment and a rear mute segment of the Mel spectrogram feature; S4: obtaining population depth feature information through a population classification network; S5: obtaining Mel spectrogram depth feature information through a Mel spectrogram preprocessing network; S6: fusing the population depth feature information and the Mel spectrogram depth feature information through SENet to obtain fused information; and S7: obtaining an emotion recognition result from the fused information through a classification network.

Abstract: Provided is a time series deep survival analysis system combined with active learning. The system includes: a data collection module, an active learning module, and a time series deep survival analysis module; the data collection module is used for obtaining survival data of objects to be analyzed; combined with an active learning method, the active learning module selects a part of right censored data to label a survival time; and the time series deep survival analysis module constructs a time series deep survival analysis neural network model, and takes uncensored data and right censored data as model inputs, so as to obtain survival time prediction results of the objects to be analyzed. The present application can make full use of the right censored data in the survival data and time series features.

Abstract: Provided is a multi-center synergetic cancer prognosis prediction system based on multi-source migration learning. The system includes a model parameter setting module, a data screening module, and a multi-source migration learning module, wherein the model parameter setting module is responsible for setting cancer prognosis prediction model parameters; the data screening module is arranged at a clinical center, and a management center transmits the set model parameter to each clinical center, such that each clinical center inquires a sample feature and prognosis index data from a local database according to the model parameter, so as to preprocess the data; and the multi-source migration learning module includes a source model training unit, a migration weight calculation unit, and a target model calculation unit.

Abstract: An optimal power flow computation method based on multi-task deep learning is provided, which is related to the field of smart power grids.

Abstract: Disclosed is a reliable resilient router for a wide-area phasor measurement system of a power grid. The reliable resilient router includes a Data-type data packet processing module, a RetransReq data packet processing module, a RetransReport data packet processing module, a basic data packet processing module, a multi-path forwarding state table module, a content storage queue module and a physical port. The reliable resilient router of the present invention realizes active detection of a lost data packet and a single or batch retransmission mechanism, so that the lost data packet can be directly recovered in the grid from an upstream router through which the lost data packet passes, which improves the recovery time success rate and the high efficiency of the lost data packet, and guarantees the safe and stable operation of the wide-area phasor measurement system of the power grid.

Abstract: The present invention relates to the technical field of computer networking, in particular to an ID/location hybrid forwarding method based on source routing, including a message format based on an extension header of a MobilityFirst protocol, a source routing forwarding mechanism based on ID identifiers and a source routing forwarding mechanism based on location identifiers.

Abstract: The present invention discloses a real-time evaluation method and evaluation system for group emotion homogeneity. The method comprises the steps as follows: enabling testees to be in the same emotion induction environment, and collecting the original electroencephalograph (EEG) signals of multiple persons at the same time through online multichannel EEG equipment; and based on the average instantaneous phase per second of the beta frequency band and the energy value per second of the alpha frequency band obtained after wavelet transformation, calculating the time synchronization degree and the valence consistency degree in real time, and finally obtaining a group emotion homogeneity index for the objective evaluation of group emotion homogeneity.

Abstract: Disclosed is a meta-knowledge fine tuning method and platform for a multi-task language model. The method is to obtain highly transferable shared knowledge, that is, meta-knowledge, on different data sets of tasks of the same category, perform interrelation and mutual reinforcement on the learning processes of the tasks of the same category that correspond to different data sets and are in different domains, so as to improve the fine tuning effect of downstream tasks of the same category on data sets of different domains in the application of the language model, and improve the parameter initialization ability and the generalization ability of a general language model for the tasks of the same category.

Abstract: Provided is a method and a platform for compressing a pre-training language model based on knowledge distillation. According to the method, a universal knowledge distillation strategy of feature migration is firstly designed, and in the process of knowledge distillation from the teacher model to the student model, the feature mapping of each layer of the student model is approaching the teacher's features, focusing on the ability of small samples to express features in the intermediate layer of the teacher model, and guiding the student model by using these features; then, a knowledge distillation method based on self-attention cross is constructed; finally, a linear transfer strategy based on Bernoulli probability distribution is designed to gradually complete the knowledge transfer of feature mapping and self-attention distribution from teachers to students.

Abstract: A method and a device for measuring light field distribution are provided; including steps of utilizing the optical trap to stably levitating particles, moving the optical trap to bring the particles close to the light field to be measured, and utilizing the photodetector to collect the scattered light signals of the particles at different positions in the three-dimensional space of the light field to be measured, and calculating the light field distribution of the light field to be measured according to the scattered light intensity which is proportional to the light intensity at that position. The device for measuring the optical field distribution includes a laser, an optical trapping path, particles, a photodetector, a control system and an upper computer; the laser emits a laser, passes through the optical trapping path, and emits highly focused captured light B to form an V optical trap to capture particles.