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| 1 | A knowledge reasoning Fuzzy-Bayesian network for root cause analysis of abnormal aluminum electrolysis cell condition显示文摘 | Weichao Yue Xiaofang Chen Weihua Gui Yongfang Xie Hongliang Zhang | 2017 | Frontiers of Chemical Science and Engineering2017，11，3： | 13 |
| 2 | Decentralized robust H-infinity descriptor output feedback control for value-bounded uncertain descriptor large-scale systems显示文摘为围住值的不明确的描述符的一个类大规模互连的系统,分散的柔韧的 H_ ∞描述符输出反馈控制问题被调查。Adesign 方法为一个分散的描述符基于围住的真实词根被开发动态输出反馈控制器,它为非线性的矩阵不平等(NLMI ) 被归结为一个可行性问题。由 homotopy 的想法反复地解决 NLMI 被建议,在一些变量在把 NLMI 归结为线性矩阵不平等(LMI ) 的每次重复或者被修理的地方。 | Yongfang XIE Weihua GUI Zhaohui JIANG | 2006 | 控制理论与应用(英文版)2006，4，2： | 6 |
| 3 | HMW glutenin subunits in multiploid Aegilops species: composition analysis and molecular cloning of coding sequences显示文摘The Aegilops genus contains species closely related to wheat. In common with wheat, Aegilops species accumulate high molecular weight (HMW) glutenin subunits in their endospermic tissue. In this study, we investigated the composition of HMW glutenin subunits in four multiploid Aegilops species using SDS-PAGE analysis. Furthermore, by working with Ae. ventricosa, we established an efficient ge-nomic PCR condition for simultaneous amplification of DNA sequences coding for either x- or y-type HMW glutenin sub-units from polyploid Aegilops species. Using the genomic PCR condition, we amplified and subsequently cloned two DNA fragments that may code for HMW glutenin subunits in Ae. ventricosa. Based on an analysis of the deduced amino acid sequences, we concluded that the two cloned sequences encode one x- and one y-type of HMW glutenin subunit, respectively. | Ruili Xie Yongfang Wan Yan Zhang Daowen Wang | 2001 | Chinese Science Bulletin2001，46，4： | 6 |
| 4 | A Data and Knowledge Collaboration Strategy for Decision-Making on the Amount of Aluminum Fluoride Addition Based on Augmented Fuzzy Cognitive Maps显示文摘In the aluminum reduction process, aluminum uoride (AlF3) is added to lower the liquidus temperature of the electrolyte and increase the electrolytic ef ciency. Making the decision on the amount of AlF3 addi- tion (referred to in this work as MDAAA) is a complex and knowledge-based task that must take into con- sideration a variety of interrelated functions;in practice, this decision-making step is performed manually. Due to technician subjectivity and the complexity of the aluminum reduction cell, it is dif cult to guarantee the accuracy of MDAAA based on knowledge-driven or data-driven methods alone. Existing strategies for MDAAA have dif culty covering these complex causalities. In this work, a data and knowl- edge collaboration strategy for MDAAA based on augmented fuzzy cognitive maps (FCMs) is proposed. In the proposed strategy, the fuzzy rules are extracted by extended fuzzy k-means (EFKM) and fuzzy deci- sion trees, which are used to amend the initial structure provided by experts. The state transition algo- rithm (STA) is introduced to detect weight matrices that lead the FCMs to desired steady states. This study then experimentally compares the proposed strategy with some existing research. The results of the comparison show that the speed of FCMs convergence into a stable region based on the STA using the proposed strategy is faster than when using the differential Hebbian learning (DHL), particle swarm optimization (PSO), or genetic algorithm (GA) strategies. In addition, the accuracy of MDAAA based on the proposed method is better than those based on other methods. Accordingly, this paper provides a feasible and effective strategy for MDAAA. | Weichao Yue Weihua Gui Xiaofang Chen Zhaohui Zeng Yongfang Xie | 2019 | Engineering2019，5，6： | 3 |
| 5 | Constrained voting extreme learning machine and its application显示文摘Extreme learning machine(ELM)has been proved to be an effective pattern classification and regression learning mechanism by researchers.However,its good performance is based on a large number of hidden layer nodes.With the increase of the nodes in the hidden layers,the computation cost is greatly increased.In this paper,we propose a novel algorithm,named constrained voting extreme learning machine(CV-ELM).Compared with the traditional ELM,the CV-ELM determines the input weight and bias based on the differences of between-class samples.At the same time,to improve the accuracy of the proposed method,the voting selection is introduced.The proposed method is evaluated on public benchmark datasets.The experimental results show that the proposed algorithm is superior to the original ELM algorithm.Further,we apply the CV-ELM to the classification of superheat degree(SD)state in the aluminum electrolysis industry,and the recognition accuracy rate reaches87.4%,and the experimental results demonstrate that the proposed method is more robust than the existing state-of-the-art identification methods. | MIN Mengcan CHEN Xiaofang XIE Yongfang | 2021 | Journal of Systems Engineering and Electronics2021，32，1： | 3 |
| 6 | THE ITERATIVE LINEAR MATRIX INEQUALITY SUBOPTIMAL DESIGN OF DECENTRALIZED H_∞ CONTROL显示文摘An approach is proposed to design decentralized state feedback H ∞ suboptimal controllers for LTI interconnected large scale systems. The parametrization theorem of decentralized robust state feedback controllers is developed in two steps and the design condition for the feedback gain is in the form of matrix inequalities. An iterative solution algorithm based on linear matrix inequality(LMI) techniques is proposed to obtain the decentralized feedback gain. The given examples are taken to show the application and the convergence of the algorithm. | Xie Yongfang Gui Weihua Liu Xiaoying Wu Min (College of Information Engineering, Central South University of Technology, Changsha 410083, China) | 1999 | Journal of Central South University1999，11，2： | 1 |
| 7 | Bis(9)-(−)-Meptazinol,a novel dual-binding AChE inhibitor,rescues cognitive deficits and pathological changes in APP/PS1 transgenic mice显示文摘Background:Alzheimer’s disease(AD)is a progressive and irreversible neurodegenerative brain disorder,which is the most common form of dementia.Intensive efforts have been made to find effective and safe treatment against AD.Acetylcholinesterase inhibitors(AChEIs)have been widely used for the treatment of mild to moderate AD.In this study,we investigated the effect of Bis(9)-(−)-Meptazinol(B9M),a novel potential dual-binding acetylcholinesterase(AChE)inhibitor,on learning and memory abilities,as well as the underlying mechanism in the APP/PS1 mouse model of AD.Methods:B9M(0.1μg/kg,0.3μg/kg,and 1μg/kg)was administered by subcutaneous injection into eight-month-old APP/PS1 transgenic mice for four weeks.Morris water maze,nest-building and novel object recognition were used to examine learning and memory ability.Aβ levels and Aβplaque were evaluated by ELISA and immunochemistry.Results:Our results showed that chronic treatment with B9M significantly improved the cognitive function of APP/PS1 transgenic mice in the Morris water maze test,nest-building test and novel object recognition test.Moreover,B9M improved cognitive deficits in APP/PS1 mice by a mechanism that may be associated with its inhibition of the AChE activity,Aβ plaque burden,levels of Aβ and the consequent activation of astrocytes and microglia in the brain of APP/PS1 transgenic mice.Most of important,the most effective dose of B9M in the present study is 1μg/kg,which is one thousand of the dosage of Donepezil acted as the control treatment.Furthermore,B9M reduced Aβ plaque burden better than Donepezil.Conclusion:These results indicate that B9M appears to have potential as an effective AChE inhibitor for the treatment of AD with symptom-relieving and disease-modifying properties. | Yuhuan Shi Wanying Huang Yu Wang Rui Zhang Lina Hou Jianrong Xu Zhuibai Qiu Qiong Xie Hongzhuan Chen Yongfang Zhang Hao Wang | 2018 | Translational Neurodegeneration2018，7，1： | 1 |
| 8 | Attention-based novel neural network for mixed frequency data显示文摘It is a common fact that data(features,characteristics or variables)are collected at different sampling frequencies in some fields such as economic and industry.The existing methods usually either ignore the difference from the different sampling frequencies or hardly take notice of the inherent temporal characteristics in mixed frequency data.The authors propose an innovative dual attention-based neural network for mixed frequency data(MID-DualAtt),in order to utilize the inherent temporal characteristics and select the input characteristics reasonably without losing information.According to the authors’knowledge,this is the first study to use the attention mechanism to process mixed fre-quency data.The MID-DualAtt model uses the frequency alignment method to trans-form the high--frequency variables into observation vectors at low frequency,and more critical input characteristics are selected for the current prediction index by attention mechanism.The temporal characteristics are explored by the encoder-decoder with attention based on long-short-term memory networks(LSTM).The proposed MID-DualAtt has been tested in practical application,and the experimental results show that it has better prediction ability than the compared models. | Xiangpeng Li Hong Yu Yongfang Xie Jie Li | 2021 | CAAI Transactions on Intelligence Technology2021，6，3： | 0 |
| 9 | LMI-Based Delay-Dependent Robust Control for Value Bounded Uncertain Systems with Time Delay显示文摘The present paper investigated the delay-dependent robust control for linear value bounded uncertain systems with state delay. By introducing the idea of matrix decomposition into the synthesis problem, incorporating with Lyapunov-Krasovskii functional method and adding 'zeros' matrix through the correla-tion of each item in Newton-Leibniz formula, we present a suffi-cient condition via the feedback stabilization based on linear ma-trix inequality (LMI). LMI is a new delay dependent condition that is much less conservative, and it guarantees that the system is robust asymptotically stable via state feedback controller. Neither the model transformation nor the bounding cross terms is em-ployed. Finally, a numerical example is presented and it demon-strates the effectiveness of the offered method. | DENG Yanni GUI Weihua XIE Yongfang | 2009 | Wuhan University Journal of Natural Sciences2009，14，2： | 0 |
| 10 | DECENTRALIZED H_∞ SUBOPTIMAL DESIGN:AN LMI APPROACH显示文摘inceZamesproposedtheH∞designmethodin1981,H∞controltheoryhasbecomeadesigntoolforcontrolsystem.Inrecentyears,Decentralizedcontr... | Weihua Gui Yongfang Xie Ning Chen Min Wu | 1999 | Journal of Central South University1999，11，1： | 0 |
| 11 | A Cell Condition-Sensitive Frequency Segmentation Method Based on the Sub-Band Instantaneous Energy Spectrum of Aluminum Electrolysis Cell Voltage显示文摘Cell voltage is a widely used signal that can be measured online from an industrial aluminum electrolysis cell.A variety of parameters for the analysis and control of industrial cells are calculated using the cell voltage.In this paper,the frequency segmentation of cell voltage is used as the basis for designing filters to obtain these parameters.Based on the qualitative analysis of the cell voltage,the sub-band instantaneous energy spectrum(SIEP)is first proposed,which is then used to quantitatively represent the characteristics of the designated frequency bands of the cell voltage under various cell conditions.Ultimately,a cell condition-sensitive frequency segmentation method is given.The proposed frequency segmentation method divides the effective frequency band into the[0,0.001]Hz band of lowfrequency signals and the[0.001,0.050]Hz band of low-frequency noise,and subdivides the lowfrequency noise into the[0.001,0.010]Hz band of metal pad abnormal rolling and the[0.01,0.05]Hz band of sub-low-frequency noise.Compared with the instantaneous energy spectrum based on empirical mode decomposition,the SIEP more finely represents the law of energy change with time in any designated frequency band within the effective frequency band of the cell voltage.The proposed frequency segmentation method is more sensitive to cell condition changes and can obtain more elaborate details of online cell condition information,thus providing a more reliable and accurate online basis for cell condition monitoring and control decisions. | Zhaohui Zeng Weihua Gui Xiaofang Chen Yongfang Xie Hongliang Zhang Yubo Sun | 2021 | Engineering2021，7，9： | 0 |
| 12 | Visual Perception-Based Fault Diagnosis in Froth Flotation Using Statistical Approaches显示文摘Froth flotation is an important mineral concentration technique.Faulty conditions in flotation processes may cause the huge waste of mineral resources and reagents,and consequently,may lead to deterioration in terms of benefits of flotation plants.In this paper,we propose a computer vision-aided fault detection and diagnosis approach for froth flotation.Specifically,a joint Gabor texture feature based on the Copula model is designed to describe froth images;a rejection sampling technique is developed to generate training sets from the quality distribution of real flotation products,and then an isolation forest-based fault detector is learned;and a fault diagnosis model based on spline regression is developed for root cause identification.Simulation experiments conducted on the historical industry data show that the proposed strategy has better performance than the alternative methods.Thereafter,the entire framework has been tested on a lead-zinc flotation plant in China.Experimental results have demonstrated the effectiveness of the proposed method. | Jin Zhang Zhaohui Tang Yongfang Xie Mingxi Ai Weihua Gui | 2021 | Tsinghua Science and Technology2021，26，2： | 0 |
| 13 | E674Q(Shanghai APP mutant),a novel amyloid precursor protein mutation,in familial late-onset Alzheimer's disease显示文摘Identified as the pathogenic genes of Alzheimer's disease(AD),APP,PSEN1,and PSEN2 mainly lead to early-onset AD,whose course is more aggressive,and atypical symptoms are more common than sporadic AD.Here,a novel missense mutation,APP E674Q(also named“Shanghai APP”),was detected in a Chinese index patient with typical late-onset AD(LOAD)who developed memory decline in his mid-70s.The results from neuroimaging were consistent with AD,where widespread amyloidβdeposition was demonstrated in 18 F-florbetapir Positron Emission Tomography(PET).APP E674Q is close to theβ-secretase cleavage site and the well-studied Swedish APP mutation(KM670/671NL),which was predicted to be pathogenic in silico.Molecular dynamics simulation indicated that the E674Q mutation resulted in a rearrangement of the interaction mode between APP and BACE1 and that the E674Q mutation was more prone to cleavage by BACE1.The in vitro results suggested that the E674Q mutation was pathogenic by facilitating the BACE1-mediated processing of APP and the production of Aβ.Furthermore,we applied an adeno-associated virus(AAV)-mediated transfer of the human E674Q mutant APP gene to the hippocampi of two-month-old C57Bl/6 J mice.AAV-E674Q-injected mice exhibited impaired learning behavior and increased pathological burden in the brain,implying that the E674Q mutation had a pathogenicity that bore a comparison with the classical Swedish mutation.Collectively,we report a strong amyloidogenic effect of the E674Q substitution in AD.To our knowledge,E674Q is the only pathogenic mutation within the amyloid processing sequence causing LOAD. | Yongfang Zhang Xinyi Xie Boyu Chen Lina Pan Jianping Li Wanbing Wang Jintao Wang Ran Tang Qiang Huang Xiaofen Chen Rujing Ren Zhentao Zhang Wei Fu Gang Wang | 2024 | Genes & Diseases2024，11，2： | 0 |
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