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Causal reasoning in typical computer vision tasks

Science China(Technological Sciences) 2024年第1期67卷 105-120页

作者： ZHANG KeXuan SUN QiYu ZHAO ChaoQiang TANG Yang Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and TechnologyShanghai 200237China National Key Laboratory of Air based Information Perception and Fusion Luoyang 471000China Luoyang Institute of Electro Optical Equipment of Avic Luoyang 471000China

Deep learning has revolutionized the field of artificial *** on the statistical correlations uncovered by deep learning-based methods,computer vision tasks,such as autonomous driving and robotics,are growing *** being the basis of deep learning,such correlation strongly depends on the distribution of the original data and is susceptible to uncontrolled *** the guidance of prior knowledge,statistical correlations alone cannot correctly reflect the essential causal relations and may even introduce spurious *** a result,researchers are now trying to enhance deep learningbased methods with causal *** theory can model the intrinsic causal structure unaffected by data bias and effectively avoids spurious *** paper aims to comprehensively review the existing causal methods in typical vision and visionlanguage tasks such as semantic segmentation,object detection,and image *** advantages of causality and the approaches for building causal paradigms will be *** roadmaps are also proposed,including facilitating the development of causal theory and its application in other complex scenarios and systems.

关键词： causal reasoning computer vision tasks vision-language tasks semantic segmentation object detection

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An immune inspired approach to 802.11 Wireless LANs coverage optimization

An immune inspired approach to 802.11 Wireless LANs coverage...

引用

2010 International Conference on Information, Networking and Automation, ICINA 2010

作者： Zhou, Xuan Qi, Rongbin Li, Qian Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai China School of Electronics and Information Tongji University Shanghai China

ISBN: (纸本)9781424481057

Coverage optimization is a critical issue in 802.11 Wireless LANs planning problems. In this paper an immune network algorithm named opt-aiNet is studied in order to automatize the planning process by optimizing the BS's (Base Station) sites. Compared the results of opt-aiNet and genetic algorithms(GA) which have been used in radio coverage optimization before, we found that opt-aiNet could find the optimal solution all times while GA falling into local optimum solution sometimes, and opt-aiNet converged more quickly than GA in most cases. Experimental results show that optaiNet is an effective way to optimize the 802.11 Wireless LANs planning problems. © 2010 IEEE.

关键词： Genetic algorithms

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Recovering from Feedback Failure in Minimal Time

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IFAC-PapersOnLine 2016年第18期49卷 612-617页

作者： Yu, Zhaoxu Hammer, Jacob Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology No. 130 Meilong Road Shanghai City200237 China Department of Electrical and Computer Engineering University of Florida GainesvilleFL32611-6130 United States

It is well known that feedback failure increases operating errors in control systems. The objective here is to develop controllers that reduce such operating errors in minimal time, once feedback has been restored. It is shown that there are robust optimal feedback controllers that attain this objective, and that the performance of these controllers can be approximated as closely as desired by bang-bang controllers that are easy to derive and implement. © 2016

关键词： Feedback controllers Nonlinear systems optimization Bang bang controllers Operating errors Optimal controls Optimal Feedback

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Enantioselective effects of chiral antibiotics on antibiotic resistance gene dissemination and risk in activated sludge

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Bioresource Technology 2025年

作者： Fang Zhao Zhao Yang Jingjing Wang Mark Bartlam Yingying Wang Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education) Nankai International Advanced Research Institute (Shenzhen Futian) Tianjin Key Laboratory of Environmental Remediation and Pollution Control College of Environmental Science and Engineering Nankai University Tianjin 300350 China State Key Laboratory of Medicinal Chemical Biology College of Life Sciences Nankai International Advanced Research Institute (Shenzhen Futian) Nankai University Tianjin China

Misuse of antibiotics drives the spread of antibiotic resistance genes (ARGs). Although reducing residual antibiotic concentrations can help curb ARG proliferation, the biodegradation and transformation of antibiotic stereoisomers may exacerbate resistance development. However, the impact of antibiotic enantiomers on ARG proliferation remains poorly understood. This study employed metagenomic analysis to investigate the enantiomer-specific selection and resistance risks of chiral antibiotic ofloxacin (OFL) and its ( S )-enantiomer, levofloxacin (LEV), in activated sludge. Results showed that LEV primarily promoted the enrichment of ARGs related to aminoglycoside and mupirocin resistance by selecting for pathogenic bacteria carrying virulence factors under high toxicity stress. OFL-driven ARG proliferation involved more diverse mechanisms, including increased gene mobility, co-selection with heavy metals, broader host range, and elevated pathogenicity. The antibiotic resistome risk index (ARRI) further demonstrated a higher environmental risk under OFL treatment than LEV. These findings offer critical insights into the enantioselective resistance risks posed by chiral antibiotics.

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A Discrete Artificial Bee Colony Algorithm for Minimizing the Total Flow Time in the Blocking Flow Shop Scheduling

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Chinese Journal of chemical Engineering 2012年第6期20卷 1067-1073页

作者：邓冠龙徐震浩顾幸生 Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and Technology

A discrete artificial bee colony algorithm is proposed for solving the blocking flow shop scheduling problem with total flow time criterion. Firstly, the solution in the algorithm is represented as job permutation. Secondly, an initialization scheme based on a variant of the NEH (Nawaz-Enscore-Ham) heuristic and a local search is designed to construct the initial population with both quality and diversity. Thirdly, based on the idea of iterated greedy algorithm, some newly designed schemes for employed bee, onlooker bee and scout bee are presented. The performance of the proposed algorithm is tested on the well-known Taillard benchmark set, and the computational results demonstrate the effectiveness of the discrete artificial bee colony algorithm. In addition, the best known solutions of the benchmark set are provided for the blocking flow shop scheduling problem with total flow time criterion.

关键词： blocking flow shop scheduling artificial bee colony algorithm total flow time

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Self-adaptive iterative hybrid modeling and its application in acetylene hydrogenation process

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Huagong Xuebao/CIESC Journal 2018年第11期69卷 4814-4822页

作者： Guo, Jingjing Xu, Jinjin Du, Wenli Ye, Zhencheng State Key Laboratory of Chemical Engineering Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education East China University of Science and Technology Shanghai200237 China

The reaction mechanism of chemical process is complex. There is a modeling error between the mechanism model and the actual reaction system. At the same time, there are complex slow time-varying features, such as catalyst deactivation, fuel coking, etc. Thus there will be a mismatch between the process model and the actual process system. A self-adaptive iterative hybrid model (SAIHM) is established to reflect the dynamic characteristics of the process accurately over a long period. The mechanism model and the data-driven model are effectively combined to improve the prediction accuracy of the model;the data-driven model uses the deep recurrent neural network (DRNN) to fully exploit the timing relationship between adjacent conditions;the data-driven model is automatically updated based on the evaluation indicators to resolve the contradiction between accuracy and efficiency. The simulation and comparison results of the self-adaptive iterative hybrid model and the existing mechanism model established based on the historical operation data of an acetylene hydrogenation adiabatic reactor show that the self-adaptive iterative hybrid model can more effectively track the actual system. © All Right Reserved.

关键词： Dynamics

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Modeling of ethylene cracking furnace yields based on transfer learning

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Huagong Xuebao/CIESC Journal 2014年第12期65卷 4921-4928页

作者： Zhou, Shuheng Du, Wenli Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai200237 China

Ethylene cracker generally utilizes petroleum products as raw materials, and turn the long-chain hydrocarbon molecules into a variety of short chain hydrocarbons like gaseous hydrocarbons and a small amount of liquid hydrocarbons at high temperature, thereby obtaining ethylene, propylene and other products. Establishing the yield model for main products is of great significance to advanced control, operation optimization of the pyrolysis furnace in theory and practice. Due to the semi-continuous and periodic characteristics of cracking furnace, establishing a yield model for each condition is time-consuming. Considering the temperature, residence time and pressure have common effect on product yields, so this article uses these similarities exist in the new and old processes, supplemented with transfer learning to accomplish quick modeling for different conditions. Compared to previous studies, this method can be able to fully exploit the information contained in the historical data from a small amount of new data. Meanwhile, building a model of ethylene in the process of cracking furnace, case studies demonstrate the efficacy of the developed methodology. ©, 2014, chemical Industry Press. All right reserved.

关键词： Ethylene

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Furnace firing control: The key to extending your run length 27

Furnace firing control: The key to extending your run length

引用

27th Ethylene Producers Conference 2015 - Topical Conference at the 2015 AIChE Spring Meeting and 11th Global Congress on Process Safety

作者： Vervust, Alexander J. Zhang, Yu Qian, Feng Reyniers, Pieter A. Schietekat, Carl M. Van Geem, Kevin M. Marin, Guy B. Laboratory for Chemical Technology Ghent University Belgium Key Laboratory of Advanced Control and Optimization East China University of Science and Technology China

ISBN: (纸本)9781510806924

control and regulation of furnace firing is essential to extend the runiength of new and existing furnaces. Accurate Computational Fluid Dynamic simulations of the furnace are essential for this purpose. This requires among others accounting for the detailed geometry of the burners. Also the so-called "shadow effect" 6 arising from the projected shadows between adjacent reactors leads to significant heat flux non-uniformities. This phenomenon is important but its effect on product yields is often ignored as only a single reactor is simulated. For the USC furnace simulated in this work, shadow effects cause a maximum difference in COT of 29 K and a difference in P/E-ratioof 0.1 between two different U-coils in the furnace. In order to obtain more uniform TMT's, COTs and olefin yields for the individual reactors, different furnace optimization methods were compared and their results are discussed. Full furnace CFD simulations prove to be essential in design and during debottlenecking, when aiming for a more uniform COT distribution to the reactors by fuel distribution.

关键词： Furnaces

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Modeling and optimization for ethylene cracking furnace systems scheduling with consideration of changing feedstock

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Huagong Xuebao/CIESC Journal 2013年第12期64卷 4304-4312页

作者： Shang, Baopeng Du, Wenli Jin, Yangkun Qian, Feng Key Laboratory of Advanced Control and Optimization for Chemical Processes Ministry of Education East China University of Science and Technology Shanghai 200237 China

An ethylene plant employs multiple cracking furnaces in parallel to convert various hydrocarbon feedstocks to smaller hydrocarbon molecules. The continuous operational performance of cracking furnaces gradually decays because of coke formation in the reaction coils, which requires each furnace to be periodically shut down for decoking. Given multiple feeds and different cracking furnaces as well as various product prices and manufacturing costs, the operational scheduling for the entire furnace system should be optimized to achieve the best economic performance. In this paper, a new MINLP(mixed-integer nonlinear programming) model is developed to obtain cyclic scheduling strategies for cracking furnace systems. Compared to previous studies, the new model has more capabilities to address operation profitability of multiple feeds cracked in multiple furnaces. Meanwhile, solving the problem of the choice for the right time of changing feedstock in the process of cracking furnace, case studies demonstrate the efficacy of the developed methodology. © All Rights Reserved.

关键词： Feedstocks

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Synthesis and optimization of utility system using parameter adaptive differential evolution algorithm

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Chinese Journal of chemical Engineering 2015年第8期23卷 1350-1356页

作者：李泽秋杜文莉赵亮钱锋 Key Laboratory of Advanced Control and Optimization for Chemical Process Ministry of EducationEast China University of Science and Technology

Synthesis and optimization of utility system usually involve grassroots design, retrofitting and operation optimization, which should be considered in modeling process. This paper presents a general method for synthesis and optimization of a utility system. In this method, superstructure based mathematical model is established, in which different modeling methods are chosen based on the application. A binary code based parameter adaptive differential evolution algorithm is used to obtain the optimal con figuration and operation conditions of the system. The evolution algorithm and models are interactively used in the calculation, which ensures the feasibility of con figuration and improves computational ef ficiency. The capability and effectiveness of the proposed approach are demonstrated by three typical case studies.

关键词： Utility system synthesis MINLP Operation optimization

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