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Effective ensemble learning approach for SST field prediction using attention-based PredRNN

Frontiers of Computer science 2023年第1期17卷 143-155页

作者： Baiyou QIAO Zhongqiang WU Ling MA Yicheng Zhou Yunjiao SUN School of Computer Science and Engineering Northeastern UniversityShenyang 110169China Key Laboratory of Intelligent Computing in Medical Image Ministry of EducationNortheastern UniversityShenyang 110169China

Accurate prediction of sea surface temperature (SST) is extremely important for forecasting oceanic environmental events and for ocean studies. However, the existing SST prediction methods do not consider the seasonal periodicity and abnormal fluctuation characteristics of SST or the importance of historical SST data from different times;thus, these methods suffer from low prediction accuracy. To solve this problem, we comprehensively consider the effects of seasonal periodicity and abnormal fluctuation characteristics of SST data, as well as the influence of historical data in different periods, on prediction accuracy. We propose a novel ensemble learning approach that combines the Predictive Recurrent Neural Network(PredRNN) network and an attention mechanism for effective SST field prediction. In this approach, the XGBoost model is used to learn the long-period fluctuation law of SST and to extract seasonal periodic features from SST data. The exponential smoothing method is used to mitigate the impact of severely abnormal SST fluctuations and extract the a priori features of SST data. The outputs of the two aforementioned models and the original SST data are stacked and used as inputs for the next model, the PredRNN network. PredRNN is the most recently developed spatiotemporal deep learning network, which simulates both spatial and temporal representations and is capable of transferring memory across layers and time steps. Therefore, we used it to extract the spatiotemporal correlations of SST data and predict future SSTs. Finally, an attention mechanism is added to capture the importance of different historical SST data, weigh the output of each step of the PredRNN network, and improve the prediction accuracy. The experimental results on two ocean datasets confirm that the proposed approach achieves higher training efficiency and prediction accuracy than the existing SST field prediction approaches do.

关键词： SST prediction ensemble learning XGBoost PredRNN attention mechanism

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Increase of chiral sensing ability in host-guest chemistry by magnetic anisotropy

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science China Chemistry 2024年第8期67卷 2775-2782页

作者： Jia-Liang Chen Bin Li Feng Yang Tiesheng Shi Xun-Cheng Su State Key Laboratory of Elemento-organic Chemistry Tianjin Key Laboratory of Biosensing and Molecular RecognitionCollege of ChemistryNankai UniversityTianjin 300071China College of Chemistry Chemical Engineering and Materials ScienceZaozhuang UniversityZaozhuang 277160China

Enantiomeric molecules generally play distinct functions in chemistry,biology,and *** physical and chemical properties of chiral analytes lay difficulty in discrimination and quantification of the *** report herein an efficient approach of increasing the chiral sensing ability ofβ-cyclodextrin(β-CD),a widely used host molecule,in the hostguest chemistry by magnetic anisotropy.A rigid and chiral lanthanide binding tag was attached to theβ-CD to amplify the changes of nuclear magnetic resonance(NMR)signals in the host-guest recognition *** installation of the paramagnetic lanthanide ion inβ-CD greatly enhances the enantiomeric discrimination up to 30-fold in comparison with the diamagneticβ-CD *** addition,the magnitude of the paramagnetic effects is tunable according to the diverse range of paramagnetic strength of the lanthanide *** reported method significantly increases the chiral sensing ability ofβ-CD,which can be applied to other host *** transferred paramagnetic effects,pseudocontact shifts(PCSs)and paramagnetic relaxation enhancements(PREs),from the host to the guest molecules,are valuable structural restraints to determine the absolute stereochemistry of the chiral *** strategy does not need modification of the analytes and is complementary to the reported analytical methods that rely on the functionalization of the chiral analytes.

关键词： chiral recognition nuclear magnetic resonance host-guest chemistry magnetic anisotropy lanthanide ions

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Optimization of LiB electrode with bi-diameter active particles using a microstructure-resolved model

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Particuology 2024年第12期95卷 49-61页

作者： Peng Zhang Junqi Weng Ping Li Guanghua Ye Wenli Du Xinggui Zhou Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of EducationEast China University of Science and TechnologyShanghai200237China BASF(China)Company Ltd. Shanghai200137China State Key Laboratory of Chemical Engineering School of Chemical EngineeringEast China University of Science and TechnologyShanghai200237China

The microstructure of electrodes significantly affects the performance of lithium-ion batteries(LiBs),and using bi-diameter active particles is a simple but effective way to regulate the microstructure of commercial LiB ***,to optimize the LiB cathode of bi-diameter active particles,a microstructure-resolved model is developed and *** results indicate that randomly packing of bi-diameter active particles is optimal when the electrolyte diffusion limitation is mild,as it provides the highest volume fraction of active *** strong electrolyte diffusion limitations,layered packing with small particles near the separator is *** is because particles near the current collector have a low lithiation ***,optimizing the random packing can further improve the energy *** energy-oriented LiBs,a low volume fraction of small particles(0.2)is preferred due to the higher volume fraction of active *** power-oriented LiBs,a high volume fraction of small particles(0.8)is better because it reduces diffusion *** work should serve to guide the optimal design of electrode microstructure for achieving high-performance LiBs.

关键词： Lithium-ion battery Electrode microstructure Bi-diameter particles Diffusion limitation Microstructure-resolved model

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MXene-based flexible pressure sensor with piezoresistive properties significantly enhanced by atomic layer infiltration

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Nano Materials science 2023年第4期5卷 439-446页

作者： Zilian Qi Tianwei Zhang Xiao-Dong Zhang Qing Xu Kun Cao Rong Chen State Key Laboratory of Digital Manufacturing Equipment and Technology School of Mechanical Science and EngineeringHuazhong University of Science and TechnologyHubei430074China State Key Laboratory of Materials Processing and Die&Mold Technology School of Materials Science and EngineeringHuazhong University of Science and TechnologyHubei430074China

The flexible pressure sensor has been credited for leading performance including higher sensitivity,faster response/recovery,wider detection range and higher mechanical durability,thus driving the development of novel sensing materials enabled by new processing *** atomic layer infiltration,Pt nanocrystals with dimensions on the order of a few nanometers can be infiltrated into the compressible lamellar structure of Ti3C2Tx MXene,allowing a modulation of its interlayer spacing,electrical conductivity and piezoresistive *** flexible piezoresistive sensor is further developed from the Pt-infiltrated MXene on a paper *** is demonstrated that Pt infiltration leads to a significant enhancement of the pressure-sensing performance of the sensor,including increase of sensitivity from 0.08 kPa^(-1)to 0.5 kPa^(-1),extension of detection limit from 5 kPa to 9 kPa,decrease of response time from 200 ms to 20 ms,and reduction of recovery time from 230 ms to 50 *** mechanical durability of the flexible sensor is also improved,with the piezoresistive performance stable over 1000 cycles of flexure *** atomic layer infiltration process offers new possibilities for the structure modification of MXene for advanced sensor applications.

关键词： MXene Atomic layer deposition Pt infiltration Piezoresistive Flexible pressure sensor

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NO_(x) reduction against alkali poisoning over Ce(SO_(4))_(2)-V_(2)O_(5)/TiO_(2) catalysts by constructing the Ce^(4+)-SO_(4)^(2−)pair sites

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Chinese Chemical Letters 2024年第5期35卷 355-360页

作者： Shuangxi Li Huijun Yu Tianwei Lan Liyi Shi Danhong Cheng Lupeng Han Dengsong Zhang State Key Laboratory of Advanced Special Steel School of Materials Science and EngineeringInternational Joint Laboratory of Catalytic ChemistryCollege of SciencesShanghai UniversityShanghai 200444China

Commercial V_(2)O_(5)-based catalysts have been successfully applied in NH_(3) selective catalytic reduction(NH_(3)-SCR)of NO_(x) from power stations,but their poor alkali-resistance restrains the wider application in nonelectrical *** this study,NO_(x) reduction against alkali poisoning over V_(2)O_(5)/TiO_(2) is greatly improved via Ce(SO_(4))_(2) *** has been originally demonstrated that Ce^(4+)-SO_(4)^(2−)pair sites play crucial roles in improving NO_(x) reduction against alkali poisoning over V_(2)O_(5)/TiO_(2) *** strong interaction between V species and Ce sites of Ce^(4+)-SO_(4)^(2−)pairs triggers the reaction between NH_(4)^(+) species and gaseous NO via Eley-Rideal(E-R)reaction *** K-poisoning,the SO_(4)^(2−)sites of Ce^(4+)-SO_(4)^(2−)pairs as protective sites strongly bond with K and thus maintain the high reaction efficiency via the E-R reaction *** work demonstrates an effective strategy to enhance NO_(x) reduction against alkali poisoning over catalysts via constructing Ce^(4+)-SO_(4)^(2−)pair sites,contributing to developing alkali-resistant SCR catalysts for practical application in nonelectrical industries.

关键词： Air pollution control Selective catalytic reduction NOx reduction Alkali poisoning Ce(SO_(4))_(2)

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Offline Reinforcement Learning with Constrained Hybrid Action Implicit Representation Towards Wargaming Decision-Making

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Tsinghua science and Technology 2024年第5期29卷 1422-1440页

作者： Liwei Dong Ni Li Guanghong Gong Xin Lin School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191ChinaState Key Laboratory of Virtual Reality Technology and SystemsBeihang UniversityBeijing 100191Chinaand also with Zhongguancun LaboratoryBeijing 100191China School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191Chinaand also with State Key Laboratory of Virtual Reality Technology and SystemsBeihang UniversityBeijing 100191China

Reinforcement Learning(RL)has emerged as a promising data-driven solution for wargaming ***,two domain challenges still exist:(1)dealing with discrete-continuous hybrid wargaming control and(2)accelerating RL deployment with rich offline *** RL methods fail to handle these two issues simultaneously,thereby we propose a novel offline RL method targeting hybrid action space.A new constrained action representation technique is developed to build a bidirectional mapping between the original hybrid action space and a latent space in a semantically consistent *** allows learning a continuous latent policy with offline RL with better exploration feasibility and scalability and reconstructing it back to a needed hybrid ***,a novel offline RL optimization objective with adaptively adjusted constraints is designed to balance the alleviation and generalization of out-of-distribution *** method demonstrates superior performance and generality across different tasks,particularly in typical realistic wargaming scenarios.

关键词： offline Reinforcement Learning(RL) wargaming decision-making hybrid action space

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Kelp-derived porous carbon for capacitive deionization: Trade-off effect of activation temperature

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Progress in Natural science:Materials International 2024年第5期34卷 907-912页

作者： Changle Li Shiwei Sun Wenjie Wu Dan Luo Kaidan Zheng Zhibin Pang Zeinhom M.El-Bahy Zhengtong Li Xingtao Xu Marine Science and Technology College Zhejiang Ocean University Key Laboratory of Xinjiang Coal Resources Green Mining Ministry of Education Xinjiang Institute of Engineering Key Laboratory of Marine Chemistry Theory and Technology Ministry of Education College of Chemistry and Chemical Engineering Ocean University of China Department of Chemistry Faculty of Science Al-Azhar University State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering Yangtze Institute for Conservation and Development Hohai University

In this paper, a series of kelp-derived porous carbon（KPC） materials were prepared from kelp by using a pyrolysisactivation method, where KOH with a fixed ratio was applied as the activator under varying activation temperature. Eventually, the KPC-based capacitive deionization（CDI） system showed excellent desalination performance, and the desalination capacity of KPC with an activation temperature of 800°C was highest, reaching 51.33 mgNaClg-1at 1.2 V. This work implies the trade-off effect of the activation temperature for the preparation and application of biomass-derived carbon materials, and provides some insights for carbon-based CDI materials.

关键词： Capacitive deionization Biomass-derived carbon Activation temperature Water desalination Trade-off effect

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Power Optimization for Low Transmission Delay in Software Defined Data Center Networks

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IEEE Transactions on Mobile computing 2025年第7期24卷 5716-5730页

作者： Zhao, Yong Cao, Jiannong Wang, Xingwei Li, Fuliang He, Qiang Liu, Xiaojie University of Electronic Science and Technology of China Trusted Cloud Computing and Big Data Key Laboratory of Sichuan Province Laboratory of Intelligent Collaborative Computing Chengdu611731 China Hong Kong Polytechnic University Department of Computing Hung Hom Hong Kong Northeastern University College of Computer Science and Engineering Shenyang110819 China Northeastern University College of Medicine and Biological Information Engineering Shenyang110819 China Pengcheng Laboratory Shenzhen518066 China

Software-Defined Data Center Networks (SDDCNs) utilizes Software Defined Networking (SDN) as a network architecture to achieve highly flexible, programmable, and automated management of Data Center Networks (DCNs). The high energy consumption of DCNs remains a persistent and significant challenge. Thus, the energy saving is crucial and imperative for DCNs. Current energy-efficient solutions primarily rely on flow consolidation and dynamic device sleeping techniques to reduce energy consumption. However, these approaches often yield long Flow Completion Time (FCT), potentially resulting in violations of service-level agreements, particularly for delay-sensitive applications. In this paper, we formulate the problem of minimizing the power consumption in SDDCNs as key objective while ensuring timely FCT for delay-sensitive applications. To solve this problem, we first introduce the Active Network Generation (ANG) approach, which generates a minimal active subnet with the least number of active devices while meeting the current traffic demand. Subsequently, we propose two algorithms based on the type of applications: the Delay-Tolerant Flow Route (DTFR) algorithm for delay-tolerant applications and the Delay-Sensitive Flow Route (DSFR) algorithm for delay-sensitive applications. Simulation results demonstrate that our propose solution achieves an energy-saving rate of up to 67.77% and significantly reduces FCT compared to benchmark solutions. © 2002-2012 IEEE.

关键词： Energy efficiency

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Research on Cross-site Scripting Attack Detection Technology Based on Few-shot Learning 6

Research on Cross-site Scripting Attack Detection Technology...

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6th IEEE Information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2023

作者： Lu, Dongzhe Liu, Long State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou China

ISBN: (纸本)9781665460033

With the intensification of informatization and mobility, various web security threats are emerging. Cross-site scripting (XSS) attack is the most common type of web attack. Most traditional detection methods have been difficult to adapt to the existing confusion variants of XSS attacks. In this paper, we extract features based on big data collected from 2017 to 2022. In order to improve the XSS detection effect of detection tools, we build machine learning models based on more than 210,000 positive and negative samples, among which CNN has the best performance. Furthermore, we propose a new algorithm that improves the traditional virtual sample generation technology based on prior knowledge in order to improve the generalization of the models. Experimental results show that in most cases, the performance of the algorithm in this paper is better than other VSG methods, and the ability to detect and discover unknown attacks is improved to a certain extent. © 2023 IEEE.

关键词： Informatization

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Iron recovery and dephosphorization behaviors from high-phosphorus oolitic hematite by gas-based direct reduction and magnetic separation

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Journal of Iron and Steel Research International 2025年第3期32卷 550-563页

作者： Fang Liu Yi-chi Zhang Wang Zeng Jun Ni Yun-peng Si Heng Zhou Tian-xiang Zhang Sheng-li Wu Ming-yin Kou State Key Laboratory of Advanced Metallurgy University of Science and Technology BeijingBeijing100083China School of Metallurgical and Ecological Engineering University of Science and Technology BeijingBeijing100083China School of Automation and Electrical Engineering University of Science and Technology BeijingBeijing100083China

With the depletion of high-quality iron ore resources,high-phosphorus oolitic hematite(HPOH)has attracted great attention due to its large reserve and relatively high iron ***,HPOH is very difficult to be used in ironmaking process due to its special structure.A two-step method of gas-based direct reduction and magnetic separation was thus proposed to recover iron and reduce *** results showed that the powdery reduced iron produced contained 92.31%iron and 0.1%phosphorus,and the iron recovery was 92.65%under optimum reduction condition,which is suitable for following *** apatite will be reduced under long reduction time and a large reducing gas flow rate,resulting in more phosphorus found in the metallic *** the hydrogen–carbon ratio will inhibit the formation and growth of iron particles and prevent the breakage of oolitic *** adjustment of reduction temperature is recommended as it affects the oolitic structure and reduction.

关键词： High-phosphorus oolitic hematite Iron recovery Dephosphorization Gas-based direct reduction Magnetic separation

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