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Erratum to: Data-driven soft sensors in blast furnace ironmaking: a survey (Frontiers of Information Technology & Electronic engineering, (2023), 24, 3, (327-354), 10.1631/FITEE.2200366)

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Frontiers of Information Technology and Electronic engineering 2023年 1-1页

作者： Luo, Yueyang Zhang, Xinmin Kano, Manabu Deng, Long Yang, Chunjie Song, Zhihuan State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou310027 China Department of Systems Science Kyoto University Kyoto606-8501 Japan Research Institute Baoshan Iron & Steel Co. Ltd. Shanghai201900 China

The article "Data-driven soft sensors in blast furnace ironmaking: a survey," written by Yueyang LUO, Xinmin ZHANG, Manabu KANO, Long DENG, Chunjie YANG, and Zhihuan SONG, was originally published electronically on the publisher’s Internet portal on Mar. 27, 2023 without open access. With the authors’ decision to opt for Open Choice the copyright of the article changed on Sept. 14, 2023 to © The Authors 2023, and the article is forthwith distributed under a Creative Commons Attribution: This article is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License, which permits any non-commercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://***/licenses/by-nc/4.0/ © 2023 Zhejiang University Press.

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Towards Data-driven LQR with Koopmanizing Flows ⋆

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IFAC-PapersOnLine 2022年第15期55卷 13-18页

作者： Petar Bevanda Max Beier Shahab Heshmati-Alamdari Stefan Sosnowski Sandra Hirche Chair of Information-oriented Control (ITR) Department of Electrical and Computer Engineering Technical University of Munich D-80333 Munich Germany Department of Electronic Systems Aalborg University Fredrik Bajers Vej 7K 9220 Aalborg Denmark

We propose a novel framework for learning linear time-invariant (LTI) models for a class of continuous-time non-autonomous nonlinear dynamics based on a representation of Koopman operators. In general, the operator is infinite-dimensional but, crucially, linear. To utilize it for effcient LTI control design, we learn a finite representation of the Koopman operator that is linear in controls while concurrently learning meaningful lifting coordinates. For the latter, we rely on Koopmanizing Flows - a diffeomorphism-based representation of Koopman operators and extend it to systems with linear control entry. With such a learned model, we can replace the nonlinear optimal control problem with quadratic cost to that of a linear quadratic regulator (LQR), facilitating efficacious optimal control for nonlinear systems. The superior control performance of the proposed method is demonstrated on simulation examples.

关键词： Machine learning Koopman operators Learning for control Representation Learning Neural networks Learning systems

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Predicting the effectiveness of chemotherapy treatment in lung cancer utilizing artificial intelligence-supported serum N-glycome analysis

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Computers in Biology and Medicine 2025年 186卷 109681-109681页

作者： Torok, Rebeka Meszaros, Brigitta Gombas, Veronika Vathy-Fogarassy, Agnes Szabo, Miklos Csanky, Eszter Jarvas, Gabor Guttman, Andras Research Institute of Biomolecular and Chemical Engineering University of Pannonia Veszprem Hungary Horváth Csaba Memorial Laboratory of Bioseparation Sciences Research Center for Molecular Medicine Doctoral School of Molecular Medicine Faculty of Medicine University of Debrecen Debrecen Hungary Department of Computer Science and Systems Technology University of Pannonia Veszprem Hungary Department of Pulmonology Borsod Academic County Hospital Miskolc Hungary

An efficient novel approach is introduced to predict the effectiveness of chemotherapy treatment in lung cancer by monitoring the serum N-glycome of patients combined with artificial intelligence-based data analysis. The study involved thirty-three lung cancer patients undergoing chemotherapy treatments. Serum samples were taken before and after the treatment. The N-linked oligosaccharides were enzymatically released, fluorophore-labeled, and analyzed by capillary electrophoresis with laser-induced fluorescence detection. The resulting electropherograms were thoroughly processed and evaluated by artificial intelligence-based classifiers, i.e., utilizing a machine learning algorithm to categorize the data into two (binary) classes. The classifier analysis method revealed a strong association between the structural changes in the N-glycans and the outcomes of the chemotherapy treatments (ROC >0.9). This novel combination of bioanalytical and AI methods provided a precise and rapid tool for predicting the effectiveness of chemotherapy. © 2025 The Authors

关键词： Lung cancer

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Orthogonal least squares based fast feature selection for linear classification

arXiv

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arXiv 2021年

作者： Zhang, Sikai Lang, Zi-Qiang Department of Mechanical Engineering The University of Sheffield Sheffield United Kingdom Department of Automatic Control and Systems Engineering The University of Sheffield Sheffield United Kingdom

An Orthogonal Least Squares (OLS) based feature selection method is proposed for both binomial and multinomial classification. The novel Squared Orthogonal Correlation Coefficient (SOCC) is defined based on Error Reduction Ratio (ERR) in OLS and used as the feature ranking criterion. The equivalence between the canonical correlation coefficient, Fisher's criterion, and the sum of the SOCCs is revealed, which unveils the statistical implication of ERR in OLS for the first time. It is also shown that the OLS based feature selection method has speed advantages when applied for greedy search. The proposed method is comprehensively compared with the mutual information based feature selection methods and the embedded methods using both synthetic and real world datasets. The results show that the proposed method is always in the top 5 among the 12 candidate methods. Besides, the proposed method can be directly applied to continuous features without discretisation, which is another significant advantage over mutual information based methods. © 2021, CC BY-NC-ND.

关键词： Feature extraction

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Facile Fabrication of 2d/2d G-C3n4/Nh2-Mil-125(Ti) Mof Nanocomposite with Z-Scheme Heterojunction for Efficient Photocatalytic H2 Production and Co2 Reduction Under Visible Light

SSRN

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SSRN 2023年

作者： Ikreedeegh, Riyadh Ramadhan Tasleem, Sehar Hossen, Md. Arif School of Chemical and Energy Engineering Universiti Teknologi Malaysia Johor Johor Bahru81310 Malaysia Department of Analysis and Quality Control Sarir Oil Refinery Arabian Gulf Oil Company El Kish P.O. Box 263 Benghazi Libya Faculty of Civil Engineering Technology Universiti Malaysia Pahang Pahang Gambang26300 Malaysia Center for Environmental Science and Engineering Research Chittagong University of Engineering and Technology Chattogram4349 Bangladesh

A binary 2D/2D g-C3N4/NH2-MIL-125(Ti) MOF nanocomposite was fabricated through a facile sonochemical-assisted thermal approach for enhanced photocatalytic H2 production and CO2 reduction under visible light. Compared to pure g-C3N4, the g-C3N4/MOF photocatalyst showed enhanced visible light absorption with promoted charge carrier separation which increased the H2 production rate and the CO2 reduction into CH4 and CO. This enhancement was attributed to the successfully constructed Z-scheme heterojunction in addition to the visible-active, large surface area and highly CO2 adsorbable NH2-MIL-125(Ti) MOF. The highest H2 production of 480 µmol g−1 was exhibited over the g-C3N4/NH2-MIL-125(Ti) nanocomposite with 20 wt% MOF. Similarly, the highest CO production rate of 338 µmol g−1 was achieved with 20 wt% MOF composite. However, for the CH4 product gas, it was observed that the highest production rate was attained with pure g-C3N4 which reveals the NH2-MIL-125(Ti) MOF selectivity towards CO production instead of CH4. Among all the investigated sacrificial agents for H2 production, methanol was the best. The performance of CO2 reduction process was found to be increasing with the pressure increase. Furthermore, the stability investigations revealed continuous productions of H2, CO and CH4 over the C3N4/MOF photocatalyst in multiple cyclic runs without any significant photocatalyst deactivation. This study provides new ideas for the fabrication of cheap, efficient and easy-synthesized nanomaterials for energy production and environmental remediation applications. © 2023, The Authors. All rights reserved.

关键词： Solar fuels

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Exploring the Trans-Cleavage Activity with Rolling Circle Amplification for Fast Detection of miRNA

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BioDesign Research 2023年第1期5卷 72-79页

作者： Chenqi Niu Juewen Liu Xinhui Xing Chong Zhang MOE Key Laboratory for Industrial Biocatalysis Institute of Biochemical EngineeringDepartment of Chemical EngineeringTsinghua UniversityBeijing 100084China. Department of Chemistry Waterloo Institute for NanotechnologyUniversity of Waterloo200 University Avenue WestWaterlooON N2L 3G1Canada. Center for Synthetic and Systems Biology Tsinghua UniversityBeijing 100084China.

MicroRNAs(miRNAs)are a class of endogenous short noncoding *** regulate gene expression and function,essential to biological *** is necessary to develop an efficient detection method to determine these valuable biomarkers for the diagnosis of *** this paper,we proposed a general and rapid method for sensitive and quantitative detection of miRNA by combining CRISPR–Cas12a and rolling circle amplification(RCA)with the precircularized ***,the detection of miRNA-21 could be completed in 70 min with a limit of detection of 8.1 pM with high *** reaction time was reduced by almost 4 h from more than 5 h to 70 min,which makes detection more *** design improves the efficiency of CRISPR–Cas and RCA-based sensing strategy and shows great potential in lab-based detection and point-of-care test.

关键词： diagnosis specificity endogenous

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S2KAN-SLAM: Elastic Neural LiDAR SLAM with SDF Submaps and Kolmogorov-Arnold Networks

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IEEE Transactions on Circuits and systems for Video Technology 2025年

作者： Wang, Zhong Zhang, Lin Wang, Hesheng Shanghai Jiao Tong University State Key Laboratory of Avionics Integration and Aviation System-of-Systems Synthesis Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai200240 China Tongji University School of Computer Science and Technology National Pilot Software Engineering School with Chinese Characteristics Shanghai201804 China

Traditional LiDAR SLAM approaches prioritize localization over mapping, yet high-precision dense maps are essential for numerous applications involving intelligent agents. Recent advancements have introduced methods leveraging neural fields to enhance mapping capabilities;however, these approaches still face several limitations. Firstly, concerning scene representation, they typically employ neural fields with high-dimensional features and multi-layer perceptron decoders utilizing non-continuous activation functions. This results in low learning efficiency and challenges in capturing high-frequency signals. Secondly, in terms of scene organization, these methods often treat the entire scene as a singular neural field, leading to inefficiencies, inflexibility, and difficulties in rectifying accumulated errors when mapping large-scale environments over extended periods. To tackle the first issue, we propose a lightweight continuous SDF regression approach by encoding the scene in single-valued embeddings and decoding SDF values from a Kolmogorov-Arnold Network. By minimizing discrepancies in measuring range, sampling distance, and decoded SDF values, we facilitate iterative frame-to-model tracking and bundle adjustment neural mapping. To mitigate the second challenge, we propose structuring the whole scene into multiple neural SDF submaps. By establishing node-node, node-submap, and loop closure constraints into a global pose graph, the system can create dense neural maps with global consistency across large-scale scenes. Experimental evaluations in both real-world and simulated settings indicate that our system achieves superior mapping completeness and accuracy, enhanced learning efficiency, reduced memory consumption, and greater flexibility compared to its counterparts. © 2025 IEEE.

关键词： Mapping

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Networked Supervisory control Synthesis of Timed Discrete-Event systems

arXiv

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arXiv 2021年

作者： Rashidinejad, Aida Reniers, Michel Fabian, Martin The Control Systems Technology Group Department of Mechanical Engineering Eindhoven University of Technology Netherlands Department of Electrical Engineering Chalmers University of Technology Sweden

—Conventional supervisory control theory assumes full synchronization between the supervisor and the plant. This assumption is violated in a networked-based communication setting due to the presence of delays, and this may result in incorrect behavior of a supervisor obtained from conventional supervisory control theory. This paper presents a technique to synthesize a networked supervisor handling communication delays. For this purpose, first, a networked supervisory control framework is provided, where the supervisor interacts with the plant through control and observation channels, both of which introduce delays. The control channel is FIFO, but the observation channel is assumed to be non-FIFO so that the observation of events may not necessarily be received by the supervisor in the same order as they occurred in the plant. It is assumed that a global clock exists in the networked control system, and so the communication delays are represented in terms of time. Based on the proposed framework, a networked plant automaton is achieved, which models the behavior of the plant under the effects of communication delays and disordered observations. Based on the networked plant, the networked supervisor is synthesized, which is guaranteed to be (timed networked) controllable, nonblocking, time-lock free, (timed networked) maximally permissive, and satisfies control requirements for the plant. Copyright © 2021, The Authors. All rights reserved.

关键词： Discrete event simulation

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γ-MnO_(2) nanorod-assembled hierarchical micro-spheres with oxygen vacancies to enhance electrocatalytic performance toward the oxygen reduction reaction for aluminum-air batteries

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Journal of Energy Chemistry 2020年第12期29卷 81-89页

作者： Ge Huo Xue-Wan Wang Zhi-Bin Zhang Zhongxin Song Xiao-Min Kang Ming-Xing Chen Qi Wang Xian-Zhu Fu Jing-Li Luo College of Materials Science and Engineering Shenzhen UniversityShenzhen 518060GuangdongChina Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province College of Optoelectronic Engineering.Shenzhen UniversityShenzhen 518060GuangdongChina Department of Chemical and Materials Engineering University of AlbertaEdmontonAlberta T6G 2G6Canada

γ-MnO2 nanorod-assembled hierarchical micro-spheres with abundant oxygen defects are synthesized by a simple thermal treatment approach as oxygen reduction electrocatalysts for Al(aluminum)-air batteries. The rich oxygen vacancies on the surface of γ-MnO2 are verified by morphology, structure,electron paramagnetic resonance(EPR) and X-ray photoelectron spectroscopy(XPS) results. The oxygen reduction reaction(ORR) electrocatalytic activity of γ-MnO2 is significantly improved by the incoming oxygen vacancies. The γ-MnO2 nanorod-assembled hierarchical micro-spheres calcined under 300 °C in Ar atmosphere show the best ORR performance. The primary Al-air batteries using γ-MnO2 catalysts as the cathode, which demonstrates excellent peal power density of 318 m W cm^(-2) when applying theγ-MnO2 catalysts with optimal amount of oxygen vacancies.

关键词： γ-MnO2 Oxygen vacancy ORR electrocatalysts Al-air battery

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Enhancing adsorption capacity of nano-adsorbents via surface modification: A review

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South African Journal of chemical engineering 2020年 31卷 25-32页

作者： Manyangadze, M. Chikuruwo, N.H.M. Narsaiah, T.B. Chakra, C.S. Radhakumari, M. Danha, G. Chemical and Process Systems Engineering Department Harare Institute of Technology Harare Zimbabwe Industrial and Manufacturing Engineering Department Harare Institute of Technology Harare Zimbabwe Department of Chemical Engineering Jawaharlal Nehru Technological University Anantapur India Centre for Nano Science and Technology Institute of Science & Technology Jawaharlal Nehru Technological University Anantapur India Department of Chemical Engineering B.V. Raju Institute of Technology Narsapur India Department of Chemical Materials & Metallurgical Engineering Botswana International University of Science & Technology Private Bag 16 Palapye Botswana

In this review, the role of surface modification of nanoparticles to enhance their performance as adsorbents was explored. Performance was assessed by comparisons on adsorption capacities of differently modified nanoparticles (silica, iron, and alumina based nanoparticles) on different heavy metal ions (Cu, Cd, Co, Ni, Pb, As, Cr, Zn, Mn, and Hg). A comparison of pure and modified materials revealed that the modified materials gave superior adsorption capacities. A close relationship was observed between the various modification methods and the adsorption capacities of particles synthesized by hydrothermal methods giving the highest adsorption capacities. Surface modification also had a direct effect on the specific surface area which decreased with the degree of functionalization. The adsorption capacity was however generally observed to increase with the degree of functionalization. © 2019 The Authors

关键词： Adsorption capacity Functionalization Hydrothermal Nanoparticles Specific surface area Surface modification

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