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2023 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2023

作者： Gigerl, B. Zhao, Y. Raminger, J. Bakakeu, J. Kern, R. Thalmann, S. Siemens Energy Department of Process Digitalization Weiz Austria Siemens Energy Department of Manufacturing Technology Nürnberg Germany Siemens Energy Department of Test Field Weiz Austria Alteryx Department of Sales Engineering München Germany Institute of Interactive Systems and Data Science Technical University of Graz Graz Austria Institute of Operations and Information Systems University of Graz Graz Austria

ISBN: (纸本)9798350323153

Partial discharges, mainly caused by an insufficient drying processes or different types of contamination, reduce the lifetime of a transformer, and thus lead to expensive rework costs. Herein, a decision support system for partial discharges of transformers occurring in oven and filling processes is introduced. Based on machine learning (ML), partial discharge results are evaluated in dependency of various manufacturing parameters and an automated prediction tool to guide the production with preventive actions is developed. The required data, obtained from sensors and manufacturing sources, is used to train supervised learning algorithms that aim to predict and classify partial discharges. To achieve adequate accuracy and reliability, multiple ML and data mining techniques are applied, including feature engineering, clustering, and final evaluation of performance by cost factors. The evaluation results show that the introduced ML models effectively detect and classify early test failures in oven and filling processes, resulting in a successful identification of key factors and consequently to more efficient action derivation. Overall, the potential of decision support systems as a valuable tool in the field of transformers is emphasized. © 2023 IEEE.

关键词： Decision Support System Machine Learning Partial Discharges Predictive Quality Control

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Substrate-independent nano-coating with persistent antibacterial and tooth whitening activities for dental health

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Chinese Chemical Letters 2025年

作者： Yi Liu Xiaolin Yu Wenyun Mu Minsi Meng Baixue Li Jie Liu Haixin Qian Lin Weng Tingting Yu Nan Hu Xin Chen Yi Hao College of Chemical Engineering Sichuan University of Science & Engineering Zigong 643000 China Institute of Precision Medicine Zigong Academy of Big Data and Artificial Intelligence in Medical Science Zigong Fourth People's Hospital Zigong 643000 China Department of Chemical Engineering Shaanxi Key Laboratory of Energy Chemical Process Intensification Institution of Polymer Science in Chemical Engineering School of Chemical Engineering and Technology Xi'an Jiaotong University Xi'an 710049 China Sichuan Clinical Research Center for Clinical Laboratory Zigong Fourth People's Hospital Zigong 643000 China Department of Laboratory Medicine Zigong Fourth People's Hospital Zigong 643000 China Department of Prosthodontics Shanghai Ninth People's Hospital College of Stomatology Shanghai Jiao Tong University School of Medicine National Clinical Research Center of Stomatology Shanghai Key Laboratory of Stomatology and Shanghai Research Institute of Stomatology Shanghai 200240 China

Bacteria and stains on tooth and various dental materials severely harm dental health and beauty and require feasible solutions. In this study, a simple strategy was developed to produce nano-coating on different substrates for persistent antibacterial and whitening. The coating is formed by the lysozyme (Lys), hemoglobin (Hb), and glucose oxidase (GOD) via co-assembly, in which the phase transition of Lys initiated the co-assembly to anchor other two proteins. During therapy, the GOD continuously oxidizes glucose in the oral environment to cut off the nutrition of bacteria meanwhile generating H 2 O 2 , which would be further catalyzed by the ferrous ions in Hb to produce reactive oxygen species (ROS) for effective decomposition of surrounding bacteria and stains. Moreover, the Hb can perform persistent release of oxygen, which not only enhances the efficiency of glucose oxidation to produce more ROS but directly suppresses anaerobic bacteria via reversing the local hypoxia environment in the mouth. The experimental results indicated that our strategy is able to form nano-film of proteins both on the surface of dental orthosis and human tooth, which further causes obvious reduction of the bacteria not only on the coated substrate but in the surrounding tissue with up to 100% of the bacteriostatic rate. In addition, both the dental orthosis and human tooth were also rapidly cleaned due to the local ROS generation, leading to a sustained anti-staining property in the long term.

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A Framework for Extracting and Encoding Features from Object-Centric Event data

arXiv

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arXiv 2022年

作者： Adams, Jan Niklas Park, Gyunam Levich, Sergej Schuster, Daniel van der Aalst, Wil M.P. Process and Data Science RWTH Aachen University Aachen Germany Fraunhofer Institute for Applied Information Technology Germany Information Systems Research University of Freiburg Freiburg Germany

Traditional process mining techniques take event data as input where each event is associated with exactly one object. An object represents the instantiation of a process. Object-centric event data contain events associated with multiple objects expressing the interaction of multiple processes. As traditional process mining techniques assume events associated with exactly one object, these techniques cannot be applied to object-centric event data. To use traditional process mining techniques, the object-centric event data are flattened by removing all object references but one. The flattening process is lossy, leading to inaccurate features extracted from flattened data. Furthermore, the graph-like structure of object-centric event data is lost when flattening. In this paper, we introduce a general framework for extracting and encoding features from object-centric event data. We calculate features natively on the object-centric event data, leading to accurate measures. Furthermore, we provide three encodings for these features: tabular, sequential, and graph-based. While tabular and sequential encodings have been heavily used in process mining, the graph-based encoding is a new technique preserving the structure of the object-centric event data. We provide six use cases: a visualization and a prediction use case for each of the three encodings. We use explainable AI in the prediction use cases to show the utility of both the object-centric features and the structure of the sequential and graph-based encoding for a predictive model. © 2022, CC BY.

关键词： Machine learning

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Heuristic Optimization of Bandwidth Reservation Cost for Vehicular Applications

Heuristic Optimization of Bandwidth Reservation Cost for Veh...

引用

GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Abdullah A. Al–khatib Muneeb Ul Hassan Klaus Moessner Institute for Data and Process Science Landshut University of Applied Sciences Landshut Germany Swinburne University of Technology Hawthorn Australia Professorship for Communications Engineering Technical University Chemnitz Germany

ISBN: (纸本)9781665435413

Safety-critical vehicular applications require significant computation and communication resources and have strict performance requirements. Therefore, individual bandwidth reservation schemes are used to support such processes. Such schemes allow vehicles to place a cost-efficient smart reservation request alongside providing guaranteed bandwidth resources. However, efficient reservation is difficult to achieve due to uncertainty in both; future reservation requirement (i.e., demand) and network operator (NO) bandwidth cost. In order to solve this problem, a Heuristic Greedy Update Smart Reservation algorithm (HG-USR) is proposed by formulating bandwidth reservation cost problem. The primary objective of this formulation is to minimize the total reservation cost in certain problem scenarios, such as exact-booking, under-booking, and over-booking over time as the vehicle moves through the driving path. Extensive numerical studies have been carried out with the help of our proposed model. The experimental outcomes show that vehicle can successfully minimize the total cost of bandwidth resources as compared to prediction-based bandwidth reservation cost and immediate reservation request based approaches.

关键词： Costs Uncertainty Heuristic algorithms Simulation Bandwidth Prediction algorithms Numerical models

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Stable and Selective Catalysts for M-Cresol Hydrogenolysis to Aromatics Via Tailoring the Encapsulation Methods

SSRN

引用

SSRN 2022年

作者： Zhang, Jimei Shi, Yanchun Wu, Bi Sun, Sihan Li, Guotao Xu, Weichao Ning, Pengge Cao, Hongbin Chemistry & Chemical Engineering Data Center National Basic Public Science Data Center National Engineering Research Center of Green Recycling for Strategic Metal Resources Institute of Process Engineering Chinese Academy of Sciences Beijing Engineering Research Centre of Process Pollution Control Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China

The removal of oxygen is an essential link for upgrading biomass phenolics to aromatics, which is achieved through catalytic hydrodeoxygenation way. Here, we designed and synthesized four encapsulated Ni@S-1 catalysts with similar sizes of S-1 crystals and Ni nanoparticles via tailoring the encapsulation methods. The highest hydrogenolysis activity of hydroxyl and hydrocarbons selectivity were obtained over Ni@S-1 via the in-situ encapsulation method (r[g aromatics •g Ni -1 •h -1 ] = 103.5 at 290 °C) in vapor hydrogenation of m -cresol as a model due to the average 2.5 nm Ni nanoparticles uniformly encapsulated within S-1 crystals for improving the shape selectivity with the vertical adsorption mode of phenolics. The appropriate porosities of Ni@S-1 catalysts are proven to play a crucial role in shape selective-catalysis for hydroxyl hydrogenolysis of m -cresol. Significantly, the outstanding stability of Ni@S-1 via the in-situ encapsulation method has been proven by the hydroxyl hydrogenolysis of vapor m -cresol for 200 h long-run without obvious deactivation. This work provided an insight into the tuning hydroxyl hydrogenolysis of phenolics by designing metal@zeolite catalysts with different microenvironment and well-dispersion of small metal nanoparticles. © 2022, The Authors. All rights reserved.

关键词： Hydrogenolysis

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A Spatial Baseline of China's Blue Carbon Stocks for Improved Monitoring, Management, and Protection

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Earth's Future 2025年第5期13卷

作者： Shaobo Sun Zhaoliang Song Laodong Guo Carlos M. Duarte Peter I. Macreadie Zhen Zhang Yunying Fang Baozhang Chen Zhengang Wang Weiqi Wang Yidong Wang Dongjie Fu Yuan Li Yafei Wang Hailong Wang Cong-Qiang Liu Institute of Surface-Earth System Science School of Earth System Science Tianjin University Tianjin China School of Freshwater Sciences University of Wisconsin-Milwaukee Milwaukee WI USA Biological and Environmental Sciences & Engineering Division Red Sea Research Center and Computational Bioscience Research Center King Abdullah University of Science and Technology Thuwal Saudi Arabia Centre for Integrative Ecology School of Life and Environmental Sciences Deakin University Burwood VIC Australia State Key Laboratory of Tibetan Plateau Earth System National Tibetan Plateau Data Center (TPDC) Environment and Resource (TPESER) Institute of Tibetan Plateau Research Chinese Academy of Sciences Beijing China Earth System Science Interdisciplinary Center University of Maryland College Park MD USA Australian Rivers Institute School of Environment and Science Griffith University Brisbane QLD Australia State Key Laboratory of Resources and Environment Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China School of Geography and Planning Sun Yat-Sen University Guangzhou China Key Laboratory of Humid Subtropical Eco-Geographical Process Ministry of Education Fujian Normal University Fuzhou China Tianjin Key Laboratory of Water Resources and Environment Tianjin Normal University Tianjin China CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation Yantai Institute of Coastal Zone Research Chinese Academy of Sciences Yantai China Key Laboratory of Regional Sustainable Development Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing China School of Environmental and Chemical Engineering Foshan University Foshan China

Blue carbon ecosystems (BCEs) exhibit remarkable capacities for organic carbon (C) storage, making them a promising nature-based climate solution. However, the lack of robust, spatially explicit estimates of C stocks in BCEs presents a major challenge to incorporating them into national and global C accounting and climate mitigation strategies. For the first time, we develop spatially explicit estimates of both soil and living biomass C stocks in BCEs across China by integrating open-access remote sensing, climate, and soil property data with 2,899 site measurements using a data-driven method. Our C stock estimates reveal that mean C stocks in BCEs significantly decrease with increasing latitude. We estimate the total C storage within China's BCEs at 121.1 ± 48.4 Tg C, with soil accounting for 90% of the total C storage. Tidal marshes and flats contribute a total of 64.7 ± 8.7 Tg C, while mangroves store a much smaller amount (4.4 ± 1.4 Tg C) due to their limited spatial extent. Seagrasses store a total of 52.0 ± 38.3 Tg C, which is significantly larger than previous estimates. These findings underscore the significant potential of BCEs protection and restoration for China's climate mitigation efforts. Our spatially explicit C stock estimates for China's BCEs provide essential data for national and global C accounting and can serve as baselines for quantifying the impacts of climate change and anthropogenic activities on BCEs C stocks. Additionally, this study offers a practical framework for comprehensively assessing C stocks in BCEs at the national scale. Spatial-explicit estimates of present blue C stocks in China are presented The mean C stocks of blue carbon ecosystems significantly decrease with increasing latitude A practical framework for a comprehensive assessment of blue C stocks at national scale is presented Blue carbon ecosystems (BCEs), including mangroves, tidal marshes and flats, and seagrasses, have remarkable capacities for organic carbon (C) stora

关键词： coastal wetlands blue carbon mangroves salt marshes tidal flats seagrasses

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Deep Coarse-grained Potentials via Relative Entropy Minimization

arXiv

引用

arXiv 2022年

作者： Thaler, Stephan Stupp, Maximilian Zavadlav, Julija Multiscale Modeling of Fluid Materials Department of Engineering Physics and Computation TUM School of Engineering and Design Technical University of Munich Germany Munich Data Science Institute Munich Institute for Integrated Materials Energy and Process Engineering Technical University of Munich Germany

Neural network (NN) potentials are a natural choice for coarse-grained (CG) models. Their many-body capacity allows highly accurate approximations of the potential of mean force, promising CG simulations at unprecedented accuracy. CG NN potentials trained bottom-up via force matching (FM), however, suffer from finite data effects: They rely on prior potentials for physically sound predictions outside the training data domain and the corresponding free energy surface is sensitive to errors in transition regions. The standard alternative to FM for classical potentials is relative entropy (RE) minimization, which has not yet been applied to NN potentials. In this work, we demonstrate for benchmark problems of liquid water and alanine dipeptide that RE training is more data efficient due to accessing the CG distribution during training, resulting in improved free energy surfaces and reduced sensitivity to prior potentials. In addition, RE learns to correct time integration errors, allowing larger time steps in CG molecular dynamics simulation while maintaining accuracy. Thus, our findings support the use of training objectives beyond FM as a promising direction for improving CG NN potential accuracy and reliability. © 2022, CC BY.

关键词： Coarse-grained modeling

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5-Safe: AI-Based Road Safety Enhancement for Schoolchildren Using 5G

5-Safe: AI-Based Road Safety Enhancement for Schoolchildren ...

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IEEE European Technology and Engineering Management Summit (E-TEMS)

作者： Dominic Scholze Abdullah Al-Khatib Ahmed Chebaane Tobias Ziegler Abdelmajid Khelil Henriette Röger Marcel Müller Michael Spateneder Ranothan Ravichandran Tim Laine Michael Luger Holger Timinger Bettina Kühbeck Institute for Data and Process Science Landshut University of Applied Sciences Germany T-Systems on site services GmbH Germany Office of Economy Marketing Tourism City of Landshut Germany Institute for Social Change and Cohesion Research Landshut University of Applied Sciences Germany

Protecting children from traffic hazards near schools is of essential importance. Emergent technologies present new possibilities for monitoring traffic more efficiently and a dequately warning road users. This paper presents a new approach, that integrates well-selected technologies to increase road safety for schoolchildren on their way to school. It delves into how utilizing multimodal sensing, 5G mobile communications infrastructure, Artificial Intelligence and Edge Computing can achieve timely situation awareness to prevent traffic h azards near schools. Five use cases are outlined to enhance school route safety, derive critical requirements for their solution, and reveal potential challenges.

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Evaluating patient readmission risk: A predictive analytics approach

arXiv

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arXiv 2018年

作者： Choudhury, Avishek Greene, Christopher M. Applied Data Science Syracuse University New York United States Process Improvement UnityPoint Health IA United States Systems Engineering Stevens Institute of Technology New Jersey United States Systems Science and Industrial Engineering Binghamton University NY United States

With the emergence of the Hospital Readmission Reduction Program of the Center for Medicare and Medicaid Services on October 1, 2012, forecasting unplanned patient readmission risk became crucial to the healthcare domain. There are tangible works in the literature emphasizing on developing readmission risk prediction models;However, the models are not accurate enough to be deployed in an actual clinical setting. Our study considers patient readmission risk as the objective for optimization and develops a useful risk prediction model to address unplanned readmissions. Furthermore, Genetic Algorithm and Greedy Ensemble is used to optimize the developed model constraints. Copyright © 2018, The Authors. All rights reserved.

关键词： Health care

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Enhanced Salt Removal Performance Using Nickel Hexacyanoferrate/Carbon Nanotubes as Flow Cathode in Asymmetric Flow Electrode Capacitive Deionization

SSRN

引用

SSRN 2023年

作者： Xu, Yang Duan, Feng Cao, Renqiang Chen, Chuang Ji, Wenyan Li, Yuping Cao, Hongbin National Engineering Research Center of Green Recycling for Strategic Metal Resources Chemistry & Chemical Engineering Data Center CAS Beijing Engineering Research Centre of Process Pollution Control Institute of Process Engineering Chinese Academy of Science Beijing100190 China School of Chemical Engineering University of Chinese Academy of Sciences Beijing100049 China

One of the most widely used CDI processes is flow electrode capacitive deionization (FCDI), which is preferred over conventional CDI with static electrode due to its continuous treatment of high-salt wastewater and ability to scale production. However, the discontinuous charge transport network in flow electrodes restricts the improvement of desalination performance. In this study, we prepared nickel hexacyanoferrate and carbon nanotubes composites (NiHCF@CNTs) by a simple ball-milling method and constructed an asymmetric FCDI (AFCDI) system using NiHCF@CNTs and AC as flow cathode and anode, respectively. Then the desalination performance of AFCDI was examined and compared with that of symmetric FCDI system using AC as both flow electrodes under different conditions. The stability was also investigated by a 20-cycle operation test. It was found that AFCDI system showed higher average salt removal rate and lower energy consumption compared with FCDI, owing to the enhancement of charge transport resulting from the couple of high specific capacitance of NiHCF and excellent electrical conductivity of CNTs. Moreover, AFCDI system has stable desalination performance in continuous operation. These results indicate that compositing Faradic materials and CNTs is an effective strategy for improving desalination performance of FCDI. © 2023, The Authors. All rights reserved.

关键词： Carbon nanotubes

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