Research on intelligent controller design for MIMO spatially -Distributed systems with applications

Spatially dynamic distributed systems have been attracting increasing attention from researchers in the field of system modelling and control since their introduction as an alternative to simple systems to meet the ever-greater requirements to make industrial systems more precise and energy-efficient and to overcome process complexities. An approach whereby complex systems with multi-dimensional parameters, inputs or outputs are simply disregarded or simplified with the help of convenient mathematical models is no longer feasible. Therefore, the purpose of the present study is to contribute to the advancement of both theoretical and empirical knowledge in this field through the means of theoretical analysis, application simulations and case studies. From a theoretical perspective, this study focuses primarily on the design methodology of control systems. To this end, the first step is identification of requirements from the applications, followed by the implementation of an original approach underpinned by data prediction for type-2 T-S fuzzy control with the purpose of making the control system design more convenient. With this aim in mind, the study creates an interface/platform to link or anticipate spatially dynamic distributed system output from lumped system data by taking advantage of the threedimensional character of type-2 fuzzy sets. Moreover, on the basis of a decoupled spatially dynamic distributed system, this study applies Mamdani-type and interval type-2 T-S type fuzzy control, and extends a discussion about the results of simulation and analysis. With regard to application examination, the study contributes to primarily with system analysis and modelling. Along with the progress of physical analysis, a MIMO model is customized for the plant by expanding from the lumped physical character to a distributed system. Furthermore, the coupling feature of the object is addressed based on the decoupling approach and the pole placement approach, while the SISO approach is expanded to a universally acknowledged MIMO approach and Matlab is used to produce the simulation results.As a conclusion, in this research, firstly a state space model was established to expand the SISO system into a MIMO system and the interacted inputs and outputs have been decoupled using decoupling method; and then a Mamdani-type fuzzy control was designed for temperature control and an Interval Type-2 fuzzy control was designed for pressure control, using a simple state-space model instead of a fuzzy model, accordance with the practical plant in use, and very satisfied, very robust control performances were obtained

Experimental Study on the Effectiveness of Extracurricular Football Training for Improving Primary Students Physical Fitness

The purpose of this study is to examine the effectiveness of after-school football training in improving the physical fitness of primary school students, so as to provide corresponding Suggestions for carrying out after-school football training in primary schools. A total of 72 students from the experimental primary school of Mouping district, Yantai city, Shandong province, participated in this experimental study, including 36 in the experimental group and 36 in the control group.The experiment was conducted for two semesters. During the experiment period, the experimental group conducted one-hour football training after school from Monday to Thursday afternoon every week, and two hours of football training on Saturday morning every week. The control group conducted sports teaching and extracurricular activities as usual without other intervention. Before and after the experiment, both the experimental group and the control group underwent physical fitness tests according to the physical fitness test standards of Chinese students, including lung capacity, 50-meter run, one-minute skipping rope, sitting forward flexor, and one-minute sit-ups. The test results were all converted to the 100-point system according to the scoring standards. Before the experiment, there was no significant difference between the experimental group and the control group in various physical fitness indicators (p \u3e 0.05). After the experiment, the lung capacity score (T = 3.108, p \u3c 0.05), the 50-meter run score (T = 6.593, p \u3c 0.05), the skipping score (T = 9.227, p \u3c 0.05), the sitting forward flexor score (T = 3.742, p \u3c 0.05), and the sit-up score (T = 5.210, p \u3c 0.05) of the experimental group were significantly higher than that of the control group. This study shows that the physical fitness of primary school students can be improved by football training in their spare time. It is suggested to carry out after-school football training activities in primary schools so as to effectively improve the physical fitness of pupils

Volatility spillovers across NFTs news attention and financial markets

The aim of this study is to investigate the volatility spillover connectedness between NFTs attention and financial markets. This paper firstly proposes a new direct proxy for the public’s attention in the NFT market: the non-fungible tokens attention index (NFTsAI), based on 590m news stories from the LexisNexis News & Business database and applies the historical decomposition to assess the historical variations of the NFTsAI. Then the empirical analysis is performed via a TVP-VAR volatility spillover connectedness model. The empirical results show that NFTsAI indicates NFT markets are dominated by cryptocurrency, DeFi, equity, bond, commodity, F.X. and gold markets. And NFT markets are volatility spillover receivers. In addition, NFT assets could impede financial contagion and have significant diversification benefits. Employing a panel pooled OLS regression model as a supplementary analysis and a GARCH-MIDAS model as a robustness test. This study reveals that NFTsAI has sufficient power to explain the return of NFT assets from a fixed effect perspective, and NFTsAI contains useful forecasting information for both short and long-term volatility of NFT markets, separately. The new NFTsAI and the empirical findings contain useful insights for risk-averse investors, portfolio managers, institutional investors, academics and financial policy regulators

The Impact of Stigmatizing Language in EHR Notes on AI Performance and Fairness

Today, there is significant interest in using electronic health record data to generate new clinical insights for diagnosis and treatment decisions. However, there are concerns that such data may be biased and result in accentuating racial disparities. We study how clinician biases reflected in EHR notes affect the performance and fairness of artificial intelligence models in the context of mortality prediction for intensive care unit patients. We apply a Transformer-based deep learning model and explainable AI techniques to quantify negative impacts on performance and fairness. Our findings demonstrate that stigmatizing language written by clinicians adversely affects AI performance, particularly so for black patients, highlighting SL as a source of racial disparity in AI model development. As an effective mitigation approach, removing SL from EHR notes can significantly improve AI performance and fairness. This study provides actionable insights for responsible AI development and contributes to understanding clinician EHR note writing