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Dynamic performance and energy efficiency of reflective and insulative composite coating on building exterior wall

Building Simulation 2023年第12期16卷 2245-2259页

作者： Guangpeng Zhang Huijun Wu Jia Liu Jianming Yang Huakun Huang Yujie Ding Lei Xie School of Civil Engineering Guangzhou UniversityGuangzhou 510006China Guangdong Provincial Key Laboratory of Building Energy Efficiency and Application Technologies Guangzhou 510006China School of Automation Guangdong Polytechnic Normal UniversityGuangzhou 510665China School of Computer Science and Cyber Engineering Guangzhou UniversityGuangzhou 510006China

Reflective and insulative composite coatings are a new energy-saving material with high solar reflectance and extremely low thermal conductivity for *** optimization and impact of high solar reflectance and low thermal conductivity on the insulating capacity of walls remain *** work investigates the dynamic thermal performance and energy efficiency of a reflective and insulative composite coating in regions with hot summer and warm winter.A simplified thermal resistance-heat capacitance model of an exterior building wall is established to predict thermal *** dynamic temperature and heat flow of the wall are predicted to reduce heat loss through the interior surface of the wall and compared to the conventional *** specific impact of the thermal conductivity and solar reflectance of the coating on the heat loss is further investigated to minimize heat loss of the *** research shows that the composite coating shows better performance on adjusting outdoor climate change than the other *** with cement,it reduces the maximum temperature of the exterior surface of the wall by 7.45°C,and the heat loss through the interior surface of the wall by 38%.The heat loss is reduced with the increase of solar reflectance and the reduction of thermal *** results can provide a useful reference and guidance for the application of reflective and insulative composite coating on building exterior wall to promote their energy-saving use on building envelopes.

关键词： reflective and insulative composite coating exterior wall building insulation solar reflectance thermal conductivity

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Energy-Efficient Multi-Trip Routing for Municipal Solid Waste Collection by Contribution-Based Adaptive Particle Swarm Optimization

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Complex System Modeling and Simulation 2023年第3期3卷 202-219页

作者： Xiaoning Shen Hongli Pan Zhongpei Ge Wenyan Chen Liyan Song Shuo Wang Collaborative Innovation Center of Atmospheric Environment and Equipment Technology and also with the Jiangsu Key Laboratory of Big Data Analysis TechnologySchool of AutomationNanjing University of Information Science and TechnologyNanjing 210044China School of Automation Nanjing University of Information Science and TechnologyNanjing 210044China Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation the Department of Computer Science and EngineeringSouthern University of Science and TechnologyShenzhen 518055China School of Computer Science University of BirminghamBirminghamB152TTUK

Waste collection is an important part of waste management *** costs and carbon emissions can be greatly reduced by proper vehicle ***,each vehicle can work again after achieving its capacity limit and unloading the *** this,an energy-efficient multi-trip vehicle routing model is established for municipal solid waste collection,which incorporates practical factors like the limited capacity,maximum working hours,and multiple trips of each *** both economy and environment,fixed costs,fuel costs,and carbon emission costs are minimized *** solve the formulated model effectively,contribution-based adaptive particle swarm optimization is *** strategies named greedy learning,multi-operator learning,exploring learning,and exploiting learning are specifically designed with their own searching *** assessing the contribution of each learning strategy during the process of evolution,an appropriate one is selected and assigned to each individual adaptively to improve the searching efficiency of the ***,an improved local search operator is performed on the trips with the largest number of waste sites so that both the exploiting ability and the convergence accuracy of the algorithm are *** of the proposed algorithm is tested on ten waste collection instances,which include one real-world case derived from the Green Ring Company of Jiangbei New District,Nanjing,China,and nine synthetic instances with increasing scales generated from the commonly-used capacitated vehicle routing problem benchmark *** with five state-of-the-art algorithms show that the proposed algorithm can obtain a solution with a higher accuracy for the constructed model.

关键词： municipal solid waste collection energy conservation multi-trip contribution particle swarm optimization

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Text-Guided Attention is All You Need for Zero-Shot Robustness in Vision-Language Models 38

Text-Guided Attention is All You Need for Zero-Shot Robustne...

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38th Conference on Neural Information Processing Systems, NeurIPS 2024

作者： Yu, Lu Zhang, Haiyang Xu, Changsheng School of Computer Science and Engineering Tianjin University of Technology China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation University of Chinese Academy of Sciences China

Due to the impressive zero-shot capabilities, pre-trained vision-language models (e.g. CLIP), have attracted widespread attention and adoption across various domains. Nonetheless, CLIP has been observed to be susceptible to adversarial examples. Through experimental analysis, we have observed a phenomenon wherein adversarial perturbations induce shifts in text-guided attention. Building upon this observation, we propose a simple yet effective strategy: Text-Guided Attention for Zero-Shot Robustness (TGA-ZSR). This framework incorporates two components: the Attention Refinement module and the Attention-based Model Constraint module. Our goal is to maintain the generalization of the CLIP model and enhance its adversarial robustness: The Attention Refinement module aligns the text-guided attention obtained from the target model via adversarial examples with the text-guided attention acquired from the original model via clean examples. This alignment enhances the model's robustness. Additionally, the Attention-based Model Constraint module acquires text-guided attention from both the target and original models using clean examples. Its objective is to maintain model performance on clean samples while enhancing overall robustness. The experiments validate that our method yields a 9.58% enhancement in zero-shot robust accuracy over the current state-of-the-art techniques across 16 datasets. Our code is available at https://***/zhyblue424/TGA-ZSR. © 2024 Neural information processing systems foundation. All rights reserved.

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Independent Vector Analysis Based Blind Interference Reduction and Signal Recovery for MIMO IoT Green Communications

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China Communications 2022年第7期19卷 79-88页

作者： Zhongqiang Luo Mingchun Li Chengjie Li School of Automation and Information Engineering Sichuan University of Science and EngineeringYibin 644000China Artificial Intelligence Key Laboratory of Sichuan Province Sichuan University of Science and EngineeringYibin 644000China School of School of Computer Science and Technology Southwest Minzu UniversityChengdu 610041China

In application to time convolutive mixing model or frequency domain blind separation model for wireless receiving applications,frequency domain independent component analysis(FDICA)has been a very popular method but with adverse random permutation ambiguity *** order to solve this inherent problem in FDICA assisted multiple-input multiple-output orthogonal frequency-division multiplexing(MIMO-OFDM)based the Internet of Thing(IoT)systems,this paper proposes an new detection mechanism,named independent vector analysis(IVA),for realizing blind adaptive signal recovery in MIMO IoT green communication to reduce inter-carrier interference(ICI)and multiple access interference(MAI).IVA jointly implements separation work for different frequency bin data while the FDICA deals with it *** IVA,the dependencies of frequency bins can be exploited in mitigating the random permutation *** addition,multivariate prior distributions are employed to preserve the inter-frequency dependencies for individual sources,which can result in separation performance *** results and analysis corroborate the effectiveness of the proposed method.

关键词： independent vector analysis blind source separation MIMO green communications

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Hemodynamic Analysis and Diagnosis Based on Multi-Deep Learning Models

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Fluid Dynamics & Materials Processing 2023年第6期19卷 1369-1383页

作者： Xing Deng Feipeng Da Haijian Shao School of Automation Key Laboratory of Measurement and Control for CSEMinistry of EducationSoutheast UniversityNanjing210096China School of Computer Jiangsu University of Science and TechnologyZhenjiang212003China Department of Electrical and Computer Engineering University of NevadaLas Vegas89154USA

This study employs nine distinct deep learning models to categorize 12,444 blood cell images and automatically extract from them relevant information with an accuracy that is beyond that achievable with traditional *** work is intended to improve current methods for the assessment of human health through measurement of the distribution of four types of blood cells,namely,eosinophils,neutrophils,monocytes,and lymphocytes,known for their relationship with human body damage,inflammatory regions,and organ illnesses,in particular,and with the health of the immune system and other hazards,such as cardiovascular disease or infections,more in *** results of the experiments show that the deep learning models can automatically extract features from the blood cell images and properly classify them with an accuracy of 98%,97%,and 89%,respectively,with regard to the training,verification,and testing of the corresponding datasets.

关键词： Blood cell analysis deep learning models classification-detection

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Dynamic Modeling of Strip Rolling Process Using Probabilistic Neural Network

Dynamic Modeling of Strip Rolling Process Using Probabilisti...

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18th IEEE International Conference on Advanced Motion Control, AMC 2024

作者： Deng, Jifei Sierla, Seppo Sun, Jie Vyatkin, Valeriy Northeastern University State Key Laboratory of Rolling and Automation Shenyang China Aalto University Department of Electrical Engineering and Automation Espoo Finland Luleå University of Technology Department of Computer Science Electrical and Space Engineering Luleå Sweden

ISBN: (纸本)9798350342819

This paper proposes an intelligent dynamic modeling method for strip rolling process. Actuators of a cold rolling mill perform actions, including work roll bending, intermediate roll bending, and roll gap tilting, to regulate the product quality. Conventional first-principles modeling necessitates intricate mathematical equations derived from process analysis and action evaluation. However, the complexity of the model increases the difficulty of upgrading the model. To address this limitation, a novel approach involving a deep neural network with a Gaussian distribution layer is proposed to effectively capture the process dynamics. A negative log likelihood is established as the loss function for the model using real-world industrial data. Experiment outcomes demonstrate the efficacy of the proposed method in achieving an accurate dynamic model. © 2024 IEEE.

关键词： Deep neural networks

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Learning Robust Global-Local Representation From EEG for Neural Epilepsy Detection

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第11期5卷 5720-5732页

作者： Zhou, Xinliang Liu, Chenyu Yang, Ruizhi Zhang, Liangwei Zhai, Liming Jia, Ziyu Liu, Yang Nanyang Technological University School of Computer Science and Engineering 639798 Singapore Queen Mary University of London School of Electronic Engineering and Computer Science LondonE1 4NS United Kingdom Carnegie Mellon University School of Computer Science PittsburghPA15213 United States Central China Normal University Hubei Provincial Key Laboratory of Artificial Intelligence and Smart Learning Wuhan430079 China Central China Normal University School of Computer Science Wuhan430079 China Chinese Academy of Sciences Brainnetome Center Institute of Automation Beijing100190 China

Epilepsy is a life-threatening and challenging neurological disorder, and applying an electroencephalogram (EEG) is a commonly used clinical approach for its detection. Neuropsychological research indicates that epilepsy seizures are highly associated with distinct ranges of temporal EEG patterns. Although previous attempts to automatically detect epilepsy have achieved high classification performance, one crucial challenge still remains: how to effectively learn the robust global-local representation associated with epilepsy in the signals? To address the above challenge, we propose global-local neural epilepsy detection network (GlepNet), a novel architecture for automatic EEG epilepsy detection. We interleave the temporal convolution model together with the multihead attention mechanism within the GlepNet's encoder blocks to jointly capture the interlaced epilepsy seizure local and global features in EEG signals. Meanwhile, the interpretable method, gradient-weighted class activation mapping (Grad-CAM), is applied to visually confirm that the GlepNet acquires the ability to accord significant weight to EEG segments containing epileptiform abnormalities such as spike-wave complexes. Specifically, the Grad-CAM heatmaps are generated by backpropagating the gradients from the encoder blocks to highlight the epilepsy seizure-related parts. Extensive experiments show the superiority of the GlepNet over state-of-the-art methods on multiple EEG epilepsy datasets. The code will soon be open-sourced on GitHub. © 2024 IEEE.

关键词： Feature extraction

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Adaptive Tracking Control of an Omnidirectional Mobile Robot System with Uncertainties and Disturbances 49

Adaptive Tracking Control of an Omnidirectional Mobile Robot...

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49th Annual Conference of the IEEE Industrial Electronics Society, IECON 2023

作者： Zhang, Yaozhong Long, Jiang Bai, Zitong Wang, Wei School of Computer Science Northwestern Polytechnical University Xi'an China School of Automation Science and Electrical Engineering Beihang University Beijing China Zhongguancun Laboratory Beijing China

ISBN: (纸本)9798350331820

This paper addresses the tracking problem of an omnidirectional mobile robot (OMR), which is a second-order electromechanical system with unmatched uncertainties and disturbances. The control inputs are the currents of the motors, and the control objective is the tracking control of the real-time position and orientation for the robot. The main features of this paper are summarized as follows. (1) Both the kinematic and the dynamic models for a standard OMR are presented, which explicitly defines the unknown physical parameters of the system as well as the specific mathematical form of disturbances. (2) A new OMR control scheme is proposed based on adaptive back-stepping techniques. It is shown that the OMR can asymptotically track the desired trajectory with any orientation. (3) In addition to numerical simulations, a real OMR experiment platform is established. The effectiveness of the proposed control scheme has been verified with both simulation and experimental results. © 2023 IEEE.

关键词： Mobile robots

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PI-funnel and inverse hysteresis compensation cascade control of smart soft dielectric elastomer actuator

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Control Theory and Technology 2024年第4期22卷 552-567页

作者： Peng Huang Yawu Wang Yue Zhang Jundong Wu Chun-Yi Su School of Automation China University of GeosciencesWuhan430074HubeiChina Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074HubeiChina Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan430074HubeiChina Gina Cody School of Engineering and Computer Science Concordia UniversityMontrealQCH3G 1M8Canada

Smart soft dielectric elastomer actuators(SSDEAs)possess wide applications in soft robotics due to their properties similar to natural muscles,including large deformation ratio,high energy density,and fast response ***,the complicated asymmetric and rate-dependent hysteresis property,creep property and quadratic input property of the SSDEA pose enormous challenges to its dynamic modeling and motion *** this paper,first,we construct the dynamic model of the SSDEA by connecting a square module,a one-sided Prandtl–Ishlinskii(OSPI)model and a linear system in series to describe the above *** key and innovative aspect of the dynamic modeling lies in cascading the square module in series with the OSPI model to construct the asymmetric hysteresis ***,a PI-funnel and inverse hysteresis compensation(PIFIHC)cascade control method of the SSDEA is proposed to actualize its tracking control *** performing the inversion operation on the asymmetric hysteresis model,the inverse hysteresis compensation controller(IHCC)is designed to compensate the asymmetric hysteresis property and quadratic input property of the *** addition,a PI-funnel controller is designed to cascade with the IHCC to construct the PIFIHC cascade controller to obtain a good tracking ***,the stability analysis of the PIFIHC cascade control system of the SSDEA is performed to theoretically prove that the tracking error can be controlled within the performance funnel and the steady-state error converges to ***,several practical tracking control experiments of the SSDEA are conducted,and RRMSEs are less than 2.30%for all *** experimental results indicate the effectiveness and feasibility of the proposed PIFIHC cascade control method of the SSDEA.

关键词： Smart soft dielectric elastomer actuator Dynamic modeling Inverse hysteresis compensation controller PI-funnel controller Cascade controller

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Multi-View Dynamic Kernelized Evidential Clustering

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2435-2450页

作者： Jinyi Xu Zuowei Zhang Ze Lin Yixiang Chen Weiping Ding the Software Engineering Institute East China Normal UniversityShanghai 200062 Shanghai Key Laboratory of Trustworthy Computing East China Normal UniversityShanghai 200062China IEEE the School of Automation Northwestern Polytechnical UniversityXi’an 710072China the School of Artificial Intelligence and Computer Science Nantong UniversityNantong 226019 the Faculty of Data Science City University of MacaoMacao 999078China

It is challenging to cluster multi-view data in which the clusters have overlapping *** multi-view clustering methods often misclassify the indistinguishable objects in overlapping areas by forcing them into single clusters,increasing clustering *** solution,the multi-view dynamic kernelized evidential clustering method(MvDKE),addresses this by assigning these objects to meta-clusters,a union of several related singleton clusters,effectively capturing the local imprecision in overlapping *** offers two main advantages:firstly,it significantly reduces computational complexity through a dynamic framework for evidential clustering,and secondly,it adeptly handles non-spherical data using kernel techniques within its objective *** on various datasets confirm MvDKE's superior ability to accurately characterize the local imprecision in multi-view non-spherical data,achieving better efficiency and outperforming existing methods in overall performance.

关键词： Evidential clustering imprecision characterizing kernel technique multi-view clustering

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