Schizophrenia is a serious mental disease whose pathogenesis has not been fully elucidated. Its clinical evaluation and diagnosis still highly depend on the clinical experience of doctors. It is of great scientific value and clinical significance to study the inducing factors and neuropathological mechanism of schizophrenia. Based on the four research problems of schizophrenia, this paper analyzes the data types that need to be stored in clinical trials and scientific research, including basic information, case report data, neuropsychological and cognitive function (...) evaluation, magnetic resonance data, electroencephalogram data, and intestinal flora data. Through the demand analysis of the system, including the data management part, data analysis part, the functional demand of the system management part, and the overall nonfunctional demand of the system, the overall architecture design, functional module division, and database table structure design of the system are completed. Adopting Browser/Server architecture and front-end and back-end separation mode and applying Java and Python programming language, based on spring framework and database, a multidimensional information management system for schizophrenia is designed and implemented, which includes four modules: data analysis, data management, system management, and security control. In addition, each functional module of the system is designed and implemented in detail, and the software operation flow of each module is illustrated with the sequence diagram. Finally, the multidimensional data of schizophrenia collected in our laboratory were used for system test to verify whether the system can meet the needs of clinical big data management of schizophrenia and the multidimensional information management system of schizophrenia can meet the needs of clinical big data management. The information management system helps schizophrenic researchers to carry out data management and data analysis. It also has advantages that are easy to use, safe, and efficient and has strong scalability in data management, data analysis, and scalability. It reflects the innovation of the system and provides a good platform for the management, research, and analysis of clinical big data of schizophrenia. (shrink)

Actuator saturation phenomenon often exists in the actual control system, which could destroy the closed-loop performance of the system and even lead to unstable behavior. Our main contribution is to provide an antiwindup recursive dynamic surface control for a discrete-time system with an unknown state and actuator saturation. The fuzzy compensator is added to perform as an active disturbance rejection term in the feedforward path to avoid windup caused by input saturation. To construct output feedback control, the system is transformed (...) into the form of pure-feedback and an improved HOSM observer is designed to carry out future output prediction. Based on which RDSC is synthesized, only one fuzzy logic system is used and the controller singularity is completely avoided. In addition, the simulation and numeral examples using a continuous stirred tank reactors system with actuator saturation are provided and the results show that the strategy owns good robustness and effectively compensates for the disturbance caused by actuator saturation in the presence of a discrete-time system with an unmeasurable state. (shrink)

How to enable the computer to accurately analyze the emotional information and story background of characters in Qin opera is a problem that needs to be studied. To promote the artistic inheritance and cultural emotion color dissemination of Qin opera, an emotion analysis model of Qin opera based on attention residual network is presented. The neural network is improved and optimized from the perspective of the model, learning rate, network layers, and the network itself, and then multi-head attention is added (...) to the ResNet to increase the recognition ability of the model. The convolutional neural network is optimized from the internal depth, and the fitting ability and stability of the model are enhanced through the ResNet model. Combined with the attention mechanism, the expression of each weight information is strengthened. The multi-head attention mechanism is introduced in the model and a multi-head attention ResNet, namely, MHAtt_ResNet, is proposed. The network structure can effectively identify the features of the spectrogram, improve the weight information of spectrogram features, and deepen the relationship between distant information in long-time series. Through experiments, the proposed model has high emotional classification accuracy for Qin opera, and with the increase of the number of data sets, the model will train a better classification effect. (shrink)