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Dimension-controlled synthesis of BiOI for efficient visible light photodegradation of tetracycline: role of pore structure

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Environmental Science and Pollution research 2024年第20期31卷 29101-29112页

作者： Gao, Peng Qiu, Nanting Feng, Li Zhang, Liqiu Beijing Key Lab for Source Control Technology of Water Pollution College of Environmental Science and Engineering Beijing Forestry University Beijing100083 China Engineering Research Center for Water Pollution Source Control & amp Eco-Remediation College of Environmental Science and Engineering Beijing Forestry University Beijing100083 China

The transformation of photogenerated charge carriers (PC) in variable dimensional photocatalyst plays a pivotal role in unraveling the generation of reactive species (RS). However, the dimensional structure–activity relationship in photocatalysis remains elusive, with limited insights into its intricacies. Herein, we report a controlled synthesis strategy by using polyvinyl pyrrolidone (PVP)-assisted precipitation method for BiOI photocatalyst. Due to the steric hindrance of PVP, the 3D microsphere (3D-PVP0.5) and porous structure (3D-PVP1) of BiOI catalysts have been successfully prepared at room temperature. The 3D-PVP1 photocatalyst contains abundant mesopores and larger pores, which significantly shorten the diffusion distance of PC. Also, these PC in porous structure is beneficial for transferring from the inner phase to the surface of materials. Combined with optical property and radicals trapping experiments, the recombination rate of PC in porous structure performs a significant decrease, leading to the generation of more dominated ROS (•O2− and h+). The •O2− played a dominated role (86.98% of contribution rate) in photodegradation of tetracycline (TC) in 3D-PVP1 photocatalytic process. Compared with 2D nanosheet of BiOI (16.7% removal rate of TC), the as-prepared 3D porous structure of BiOI catalyst exhibits unique stable and high removal capacities (90.5%) for TC photodegradation under visible light irradiation. The kobs of 3D-PVP1 photocatalyst increased by 5.1 times than that of 2D nanosheet. To investigate its practical application, the effects of inorganic anions and pH have been systematically studied. This work sheds light on the design of variable dimension BiOI catalyst and provides more insight into the transfer mechanism of PC. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Bismuth compounds

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Understanding Socially Compliant Driving Behaviour at Real Uncontrolled Mid-Block Crosswalks

Understanding Socially Compliant Driving Behaviour at Real U...

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International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024

作者： Xu, Fei Huang, Liang Tian, Kai Zhang, Hui Ding, Naikan Wu, Jiaxun Yang, Chunhui Ma, Haoyu Intelligent Transportation Systems Center Wuhan University of Technology Wuhan430070 China Engineering Research Center of Transportation Information and Safety Ministry of Education Wuhan430070 China

ISBN: (纸本)9789819639564

Automated vehicles (AVs) have already been operating in cities. However, there is a significant lack of understanding of the social interactions between AVs and pedestrians at real uncontrolled intersections. Particularly, how do human drivers control vehicle dynamics to convey specific social values to pedestrians and passengers? To minimize this research gap, this study has conducted an in-depth analysis of pedestrian-vehicle interaction trajectory data at real uncontrolled mid-block intersections by combining vehicle dynamic parameters with pedestrian behavior, using the proposed Time-to-Conflict Point (TTCP) and Time-to-Arrival (TTA) diagrams. Based on the theory of social value orientation, the social compliant driving behaviors of vehicles are categorized into five types: egoistic, competitive (successful), competitive (unsuccessful), prosocial, and altruistic. Our results show that, in real scenarios, most driving behaviors fall under the egoistic and competitive (successful) modes, with the altruistic mode having the lowest percentage. This paper discusses the significance of the proposed quantitative methods and their research results in understanding social compliant interactive driving behaviors. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Emotional intelligence

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Robust estimation of sideslip angle for heavy-duty vehicles under payload conditions using a series-connected structure estimator

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on intelligent Vehicles 2024年 1-17页

作者： Gao, Lin Wu, Qing He, Yi Wu, Kang Shao, Pu School of Transportation and Logistics Engineering Wuhan University of Technology Wuhan China Intelligent Transportation Systems Research Center Wuhan University of Technology Wuhan China Sunward Intelligent Equipment Co. Ltd Changsha China Hubei Sanjiang Space Wanshan Special Vehicle Co. Ltd. Xiaogan China

The robust estimation of heavy-duty vehicles (HDVs) sideslip angle is crucial for vehicle stability controls. This paper aims to address the challenge of estimating the sideslip angle for HDVs when carrying cargo. We propose an innovative framework for estimating the sideslip angle of HDVs after loading. To address the problem of deviation in the inertial measurement unit (IMU) output acceleration signal during vehicle turning caused by the change of center of gravity (C.G.) position after loading cargo, we amalgamate the minimum model error (MME) criterion with the cubature Kalman filter (CKF) to accurately estimate the longitudinal C.G. position and carry out the IMU sensor position correction. On this basis, concerning the estimation of the sideslip angle for HDV when carrying cargo, a series-connected structure estimator is proposed, comprising a kinematic model estimator, a tire cornering stiffness estimator, and a dynamics model estimator. In this structure, the kinematic and dynamics model estimator employs CKF. Considering the characteristics of both kinematic and dynamics models, alongside HDVs' variable payload, an innovative adaptive weighted recursive least squares (AWRLS) method is designed for the adaptive estimation of tire cornering stiffness. This allows the series-connected structure estimator to dynamically adjust in real-time, achieving an accurate and robust estimation of the sideslip angle. Finally, through extensive simulations and real-world vehicle experiments, we validate the efficacy of the proposed framework. The results of the experiments show that the proposed method has a satisfactory level of estimation accuracy, significantly outperforming the estimation results of individual models. IEEE

关键词： Tires

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Real-Time Lightweight Convolutional Neural Network for Polyp Detection in Endoscope Images

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Journal of Shanghai Jiaotong University (Science) 2025年第3期30卷 521-534页

作者： Si, Bingqi Pang, Chenxi Wang, Zhiwu Jiang, Pingping Yan, Guozheng School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China Shanghai Engineering Research Center of Intelligent Drug Detoxification and Rehabilitation Shanghai200240 China College of Computer Science and Technology Jilin University Changchun130012 China

Colorectal cancer is the most common cancer with a second mortality rate. Polyp lesion is a precursor symptom of colorectal cancer. Detection and removal of polyps can effectively reduce the mortality of patients in the early period. However, mass images will be generated during an endoscopy, which will greatly increase the workload of doctors, and long-term mechanical screening of endoscopy images will also lead to a high misdiagnosis rate. Aiming at the problem that computer-aided diagnosis models deeply depend on the computational power in the polyp detection task, we propose a lightweight model, coordinate attention-YOLOv5-Lite-Prune, based on the YOLOv5 algorithm, which is different from state-of-the-art methods proposed by the existing research that applied object detection models or their variants directly to prediction task without any lightweight processing, such as faster region-based convolutional neural networks, YOLOv3, YOLOv4, and single shot multibox detector. The innovations of our model are as follows: First, the lightweight EfficientNetLite network is introduced as the new feature extraction network. Second, the depthwise separable convolution and its improved modules with different attention mechanisms are used to replace the standard convolution in the detection head structure. Then, the α-intersection over union loss function is applied to improve the precision and convergence speed of the model. Finally, the model size is compressed with a pruning algorithm. Our model effectively reduces parameter amount and computational complexity without significant accuracy loss. Therefore, the model can be successfully deployed on the embedded deep learning platform, and detect polyps with a speed above 30 frames per second, which means the model gets rid of the limitation that deep learning models must rely on high-performance servers. © Shanghai Jiao Tong University 2023.

关键词： Object detection

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Non-Convex Operating Zone Establishment and Alarm Limit Design for Multivariate Alarm Systems Based on Grid Clustering 43

Non-Convex Operating Zone Establishment and Alarm Limit Desi...

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43rd Chinese control Conference, CCC 2024

作者： Wei, Yujie Hu, Wenkai Li, Yupeng Cao, Weihua China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581581

Alarm systems are core components in large complex industrial facilities to ensure safe and efficient operation. Traditional univariate alarm system design methods ignore the correlation of process variables and thus may generate massive false alarms and missed alarms. An effective way of designing a multivariate alarm system is to establish the normal operating zones (NOZs) based on historical data under normal conditions. These NOZs serve as the basis for setting alarm limits in multivariate alarm systems. Given that the actual correlations between related variables are frequently unknown, a robust modeling approach is necessary to effectively handle both convex and non-convex NOZs. Thus, this paper presents a systematic method for nonconvex operating zone establishment and alarm limit design for multivariate alarm systems. A multivariate non-convex NOZ is established based on grid clustering. Then, the multidimensional grid boundary is extracted and used to determine the alarm limits for real-time samples. A numerical example is used to demonstrate the effectiveness of the proposed method. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Alarm systems

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A Lightweight Steel Strip Defect Detection Method Based on YOLO 43

A Lightweight Steel Strip Defect Detection Method Based on Y...

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43rd Chinese control Conference, CCC 2024

作者： Qian, Hao Xu, Chi China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China

ISBN: (纸本)9789887581581

As an essential component of modern industry, steel strips play an indispensable role in various fields and serve as a crucial raw material in industrial production. However, due to various factors such as production technology, the surface of steel strips often exhibits unavoidable defects like scratches and crazings. Therefore, implementing online surface quality inspection for steel strips is one effective way to enhance product quality and production efficiency. This paper proposes a detection method for surface defects in steel strips based on YOLO. By optimizing the network structure of YOLOv5s, the performance on the NEU-DET dataset has improved by nearly 4 % compared to the original network's mAP value. Experimental results indicate that the detection performance of this method is significantly superior to the current mainstream lightweight detection networks. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Strip metal

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Multi-Lever EarlyWarning forWind and Photovoltaic Power Ramp Events Based on Neural Network and Fuzzy Logic

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Energy engineering 2024年第11期121卷 3133-3160页

作者： Huan Ma Linlin Ma Zengwei Wang Zhendong Li Yuanzhen Zhu Yutian Liu Power Grid Technology Center State Grid Shandong Electric Power Research InstituteJinan250003China Shandong Electric Power Dispatching and Control Center State Grid Shandong Electric Power CompanyJinan250012China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong UniversityJinan250061China

With the increasing penetration of renewable energy in power system,renewable energy power ramp events(REPREs),dominated by wind power and photovoltaic power,pose significant threats to the secure and stable operation of power *** paper presents an early warning method for REPREs based on long short-term memory(LSTM)network and fuzzy ***,the warning levels of REPREs are defined by assessing the control costs of various power control ***,the next 4-h power support capability of external grid is estimated by a tie line power predictionmodel,which is constructed based on the ***,considering the risk attitudes of dispatchers,fuzzy rules are employed to address the boundary value attribution of the early warning interval,improving the rationality of power ramp event early *** results demonstrate that the proposed method can generate reasonable early warning levels for REPREs,guiding decision-making for control strategy.

关键词： Early warning machine learning power system security renewable energy power ramp event smart grid

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Animatable Human Neural Radiance Field from Sparse Images Captured by a Single Camera 43

Animatable Human Neural Radiance Field from Sparse Images Ca...

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43rd Chinese control Conference, CCC 2024

作者： Yang, Qingru Xu, Chi China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581581

Recently, the use of neural radiance fields (NeRF) for three-dimensional reconstruction of humans has achieved high-quality view rendering. However, existing methods often rely on multiple or single videos as input, requiring dense images, and the rendering quality tends to be poor with sparse image inputs. To address this issue, this paper proposes a novel method that solely utilizes sparse images captured by a single camera to create an animatable human neural radiance field, enabling the rendering of high-fidelity human images under arbitrary novel viewpoints and poses. Specifically, our method utilizes body poses and multi-view feature to build a deformable neural radiance field, and employs frequency-segmented positional encoding to mitigate overfitting during training process. Extensive quantitative and qualitative experiments demonstrate that our proposed method outperforms prior works. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Image reconstruction

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Multi user computation offloading decision in edge networks 43

Multi user computation offloading decision in edge networks

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43rd Chinese control Conference, CCC 2024

作者： Liu, Chang Yuan, Yan Cao, Weihua Hu, Yabin China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9789887581581

Computing offload is a key technology in mobile edge computing (MEC). By offloading tasks to the edge servers, it solves the problem that terminal devices in the edge network cannot handle high computing and time sensitive tasks. However, in multi-user scenarios, the resources of edge servers are very limited, and without good offloading decisions, the performance of MEC systems cannot be guaranteed. In this paper, the computation offloading problem of multi-user MEC system is analyzed and modeled and a batch offloading method is proposed. And in response to the shortcomings of the existing algorithms, a neural network combined with genetic algorithm for offloading decision is proposed. Simulation results show that the proposed algorithm performs better than existing algorithms in terms of time complexity and accuracy. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Computation offloading

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Alarm Prediction with Variational Output Dimension for Alarm Floods Using Transformer 43

Alarm Prediction with Variational Output Dimension for Alarm...

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43rd Chinese control Conference, CCC 2024

作者： Pang, Long Jiang, Wenbin Hu, Wenkai Wang, Zhuang Cao, Weihua China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China

ISBN: (纸本)9789887581581

Industrial alarm systems play crucial roles in assessing the production status and ensuring process safety. However, the presence of alarm floods can make alarm systems partially or fully fail, and thus would cause serious consequences. Alarm prediction, as an advanced approach to address alarm floods, offers operators decision supports when an alarm flood occurs. Existing alarm prediction methods requires that the output alarm sequences are of a fixed dimension, making such methods unable to adapt to the changing alarm rate. Accordingly, this paper proposes an alarm prediction model based on Transformer. The proposed model can predict alarm sequences with variational dimensions and can also achieve remarkable accuracy. The effectiveness of the proposed method is demonstrated by a case study with data from the Vinyl Acetate Monomer (VAM) simulation model. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Polyvinyl acetates

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