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A Fusion Kalman Filter and UFIR Estimator Using the Influence Function Method

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IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 709-718页

作者： Wei Xue Xiaoli Luan shunyi zhao Fei Liu IEEE the Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) Institute of AutomationJiangnan University

In this paper,the Kalman filter(KF)and the unbiased finite impulse response(UFIR)filter are fused in the discrete-time state-space to improve robustness against uncertainties.To avoid the problem where fusion filters may give up some advantages of UFIR filters by fusing based on noise statistics,we attempt to find a way to fuse without using noise statistics.The fusion filtering algorithm is derived using the influence function that provides a quantified measure for disturbances on the resulting filtering outputs and is termed as an influence finite impulse response(IFIR)filter.The main advantage of the proposed method is that the noise statistics of process noise and measurement noise are no longer required in the fusion process,showing that a critical feature of the UFIR filter is inherited.One numerical example and a practice-oriented case are given to illustrate the effectiveness of the proposed method.It is shown that the IFIR filter has adaptive performance and can automatically switch from the Kalman estimate to the UFIR estimates according to operating conditions.Moreover,the proposed method can reduce the effects of optimal horizon length on the UFIR estimate and can give the state estimates of best accuracy among all the compared methods.

关键词： Fusion filter influence function Kalman filter(KF) robustness unbiased finite impulse response(FIR)

Enhancing the Effectiveness of Trimethylchlorosilane Purification Process Monitoring with Variational Autoencoder

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Computer Modeling in Engineering & Sciences 2022年第8期132卷 531-552页

作者： Jinfu Wang shunyi zhao Fei Liu Zhenyi Ma Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) Jiangnan UniversityWuxi214122China Hangzhou JASU Environmental Monitoring Co. Ltd.Hangzhou311999China

In modern industry,process monitoring plays a significant role in improving the quality of process conduct.With the higher dimensional of the industrial data,the monitoring methods based on the latent variables have been widely applied in order to decrease the wasting of the industrial database.Nevertheless,these latent variables do not usually follow the Gaussian distribution and thus perform unsuitable when applying some statistics indices,especially the T^(2) on them.Variational AutoEncoders(VAE),an unsupervised deep learning algorithm using the hierarchy study method,has the ability to make the latent variables follow the Gaussian distribution.The partial least squares(PLS)are used to obtain the information between the dependent variables and independent variables.In this paper,we will integrate these two methods and make a comparison with other methods.The superiority of this proposed method will be verified by the simulation and the Trimethylchlorosilane purification process in terms of the multivariate control charts.

关键词： Process monitoring variational autoencoders partial least square multivariate control chart

Introduction to the Special Issue on Advances on Modeling and State Estimation for Industrial Processes

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Computer Modeling in Engineering & Sciences 2023年第4期135卷 1-3页

作者： shunyi zhao Xiaoli Luan Jinfeng Liu Ruomu Tan Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) Jiangnan UniversityWuxi214122China University of Alberta EdmontonT6G 2R3Canada ABB Corporate Research Germany Ladenburg68526Germany

In the past few years,significant progress has been made in modeling and state estimation for industrial processes to improve control performance,reliable monitoring,quick and accurate fault detection,diagnosis,high product quality,fule and resource consumption,etc.However,with the fast development of information technology,numerous essential issues are faced in modeling and state estimation,which generates the new need for novel modeling and or state estimation methodologies and in-depth studies of them.Therefore,this special issue is dedicated to innovative modeling and state estimation from applicability,computational efficiency,and effectiveness.

关键词： estimation state diagnosis

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超分子主客体作用调控电化学熵变

科学通报 2024年第10期69卷 1251-1252页

作者：高顺意赵杰华东理工大学化学与分子工程学院上海200237

在生产生活中常伴随着大量低级废热的产生,如光伏、太阳能、地热、燃料电池等,其转化和再利用在应对全球能源问题方面非常有前途.在各种收集热量的方法中,热电的研究最为广泛,它是基于塞贝克效应,利用温度梯度下导电材料上产生的电压.... 详细信息

在生产生活中常伴随着大量低级废热的产生,如光伏、太阳能、地热、燃料电池等,其转化和再利用在应对全球能源问题方面非常有前途.在各种收集热量的方法中,热电的研究最为广泛,它是基于塞贝克效应,利用温度梯度下导电材料上产生的电压.在电化学中存在类似的效应,由温度差可以引起电极电位的变化.一些电化学热机可以通过氧化还原过程伴随的熵变化实现热量与电力的转化.

关键词：燃料电池导电材料塞贝克效应氧化还原过程电极电位电化学主客体作用温度梯度

Bayesian estimation for nonlinear stochastic hybrid systems with state dependent transitions

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Journal of Systems Engineering and Electronics 2012年第2期23卷 242-249页

作者： shunyi zhao Fei Liu Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) Institute of AutomationJiangnan UniversityWuxi 214122P.R.China

The Bayesian approach is considered as the most general formulation of the state estimation for dynamic systems. However, most of the existing Bayesian estimators of stochastic hybrid systems only focus on the Markov jump system, few liter- ature is related to the estimation problem of nonlinear stochastic hybrid systems with state dependent transitions. According to this problem, a new methodology which relaxes quite a restrictive as- sumption that the mode transition process must satisfy Markov properties is proposed. In this method, a general approach is presented to model the state dependent transitions, the state and output spaces are discreted into cell space which handles the nonlinearities and computationally intensive problem offline. Then maximum a posterior estimation is obtained by using the Bayesian theory. The efficacy of the estimator is illustrated by a simulated example .

关键词： Bayesian estimation nonlinear stochastic hybrid sys- tem state dependent transition cell space.

Efficacy of Daoyin combined with lower limb robot as a comprehensive rehabilitation intervention for stroke patients: a randomized controlled trial

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Journal of Traditional Chinese Medicine 2024年第3期44卷 530-536页

作者： TIAN Haolin YANG Yuanbin ZHANG Hu zhao Wenjing ZHOU Jing TIAN Jingfeng HE Long LI Xuechao SHEN Qinxuan SHUAI Mei Department of First Rehabilitation Wangjing Hospital of China Academy of Chinese Medical Sciences Department of Rehabilitation Shunyi HospitalBeijing Traditional Chinese Medicine Hospital School of Biological Science and Medical Engineering Beihang University

OBJECTIVE: To assess the effectiveness of a comprehensive rehabilitation approach combining Traditional Chinese Medicine Daoyin with lower limb robotics during the recovery phase of stroke patients.METHODS: Stroke patients meeting the specified criteria were randomly assigned to one of four groups using a random number table: Control group, Daoyin group, lower limb robot group(LLR group), and Daoyin and lower limb robot group(DLLR group). Each group received distinct treatments based on conventional rehabilitation training.The treatment duration spanned two weeks with two days of rest per week. Pre-and post-intervention assessments included various scales: Fugl-Meyer Assessment(FMA),Berg balance scale(BBS), Barthel index(BI), Fatigue Scale-14(FS-14), Pittsburgh sleep quality index(PSQI),Hamilton Anxiety Scale(HAMA), and Hamilton Depression Scale(HAMD).RESULTS: Statistically significant differences were observed in the lower limb function measured by FAM between the Control group(15 ± 5) and the DLLR group(18 ± 5)(P = 0.049). In the Barthel index, a statistically significant difference was noted between the Control group(54 ± 18) and the DLLR group(64 ± 11)(P = 0.041).Additionally, significant differences were found in the Berg balance scale between the Control group(21 ± 10)and the DLLR group(27 ± 8)(P = 0.024), as well as between the Control group(21 ± 10) and the LLR group(26 ± 10)(P = 0.048).CONCLUSION: The findings of this study suggest that the combined use of Daoyin and robotics not only enhances motor function in stroke patients but also has a positive impact on fatigue, sleep quality, and mood. This approach may offer a more effective rehabilitation strategy for stroke patients.

关键词： Daoyin lower limb robot randomized controlled trial rehabilitation stroke

免疫球蛋白在肝癌TACE治疗过程中的变化及预测疗效的价值

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昆明医科大学学报 2024年第4期45卷 128-134页

作者：闫兰竹乔顺义张艳丽赵二强杨虎林静付海艳武警河北总队医院检验与病理科河北石家庄050080 武警河北总队医院内二科河北石家庄050080 河北医科大学第一医院肿瘤科河北石家庄050030

目的分析免疫球蛋白(immunoglobulin,Ig)在肝细胞性肝癌(hepatocellular carcnoma,HCC)肝动脉化疗栓塞术(transcatheter arterial chemoembolization,TACE)治疗过程中的变化及预测疗效的价值。方法选取2022年1月至2023年1月武警河北总队医院100例HCC患者作为肝癌组,另选50例肝脏良性疾病患者作为良性组,50例健康志愿者作为对照组。比较3组一般资料、血清Ig(IgA、IgG、IgM)及常规肿瘤标志物[甲胎蛋白(alpha feto protein,AFP)、细胞角蛋白19(cytokeratin 19,CK19)、高尔基膜蛋白73(golgi protein 73,GP73)]水平,分析肝癌组血清Ig与常规肿瘤标志物水平的相关性。并比较肝癌组TACE治疗后不同疗效患者治疗前后血清Ig、常规肿瘤标志物水平及变化值,分析血清Ig及常规肿瘤标志物水平变化值与ACE疗效的相关性、预测疗效的价值,比较含与不含Ig预测方案对疗效的预测价值。结果肝癌组血清IgA、IgG、IgM水平低于良性组、对照组,AFP、CK19、GP73水平高于良性组、对照组,良性组血清IgA、IgG、IgM水平低于对照组,AFP、CK19、GP73水平高于对照组(P0(P<0.05)。结论HCC患者TACE治疗过程中血清IgA、IgG、IgM水平升高,各指标变化值可为临床预测TACE疗效提供可靠依据。

关键词：肝细胞性肝癌免疫球蛋白肝癌肝动脉化疗栓塞术疗效预测

生殖道GBS感染对妊娠晚期妇女阴道微生态环境及免疫因子的影响

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中国微生态学杂志 2024年第3期36卷 336-340页

作者：唐春艳赵洁北京市顺义区妇幼保健院/北京儿童医院顺义妇儿医院妇产科北京101300

目的探讨妊娠晚期生殖道B族溶血性链球菌(GBS)感染对阴道微生态环境及免疫因子的影响。方法收集2021年7月至2022年7月本院76例GBS筛查阳性妊娠晚期妊娠妇女(GBS阳性组),另选取同期GBS筛查阴性的76例妊娠晚期妊娠妇女(对照组),比较2组阴... 详细信息

目的探讨妊娠晚期生殖道B族溶血性链球菌(GBS)感染对阴道微生态环境及免疫因子的影响。方法收集2021年7月至2022年7月本院76例GBS筛查阳性妊娠晚期妊娠妇女(GBS阳性组),另选取同期GBS筛查阴性的76例妊娠晚期妊娠妇女(对照组),比较2组阴道微生态情况、血清免疫炎症因子(IL-1β、IL-6)水平及妊娠结局;另根据阴道微生态评价结果将GBS阳性组妊娠妇女进一步分为微生态失调组(n=56)和微生态正常组(n=20),比较2组妊娠结局。结果GBS阳性组和对照组研究对象的阴道pH值、细菌性阴道病(BV)发生率、外阴阴道假丝酵母菌病(VVC)发生率、阴道菌群密集度、阴道菌群多样性及微生态失调发生率比较差异均有统计学意义(χ2=8.550、5.842、5.156、4.682、5.339、14.341,均P0.05)。GBS阳性组血清IL-1β、IL-6水平显著高于对照组(t=16.711、19.388,均P0.05)。微生态失调组胎膜早破、胎儿窘迫发生率显著高于微生态正常组(χ2=4.113、4.113,均P0.05)。结论妊娠晚期GBS感染妊娠妇女易发生阴道微生态及炎症因子失调,增加不良妊娠结局发生风险。

关键词： B族溶血性链球菌感染妊娠晚期阴道微生态免疫炎症因子

超大特大城市人居环境质量时空动态评价——以北京市为例

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绿色科技 2024年第3期26卷 182-189页

作者：赵燊住房和城乡建设部政策研究中心北京100835 中国社会科学院大学北京102488

人居环境质量是衡量城市发展水平的重要指标。研究基于长时间序列多源数据构建了由温湿指数、风效指数等5个自然本底单因子指数和夜间灯光指数、医疗保健指数等5个人文社会单因子指数组成的超大特大城市人居环境质量综合评价体系,并以... 详细信息

人居环境质量是衡量城市发展水平的重要指标。研究基于长时间序列多源数据构建了由温湿指数、风效指数等5个自然本底单因子指数和夜间灯光指数、医疗保健指数等5个人文社会单因子指数组成的超大特大城市人居环境质量综合评价体系,并以北京市为例,分析评价了2012-2022年北京市人居环境质量时空分异情况。研究表明:(1)10年间北京市自然本底要素综合指数均值增长了41.87%,但全域均值仅为0.2531,自然环境宜居性不高;(2)10年间北京市中心六城区的人文社会要素综合指数均值涨幅(25.16%)低于其他10个区(39.28%),医疗、交通和教育等人文社会资源呈现中心向外围“外溢”态势;(3)北京市人居环境质量整体在逐步提高,但区域发展协调性不足。西城区、东城区、朝阳区和海淀区稳居第一梯队,丰台区和石景山区位居第二梯队,昌平区、大兴区、顺义区、通州区位处第三梯队,房山区、怀柔区、门头沟区、密云区、平谷区和延庆区处于第四梯队。

关键词：超大特大城市人居环境质量指标体系时空分析北京市