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Prospect Theory Based Individual Irrationality Modelling and Behavior Inducement in Pandemic Control

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Computer Modeling in Engineering & Sciences 2024年第7期140卷 139-170页

作者： Wenxiang Dong H.Vicky Zhao department of automation BNRistTsinghua UniversityBeijing100084China

Understanding and modeling individuals’behaviors during epidemics is crucial for effective epidemic ***,existing research ignores the impact of users’irrationality on decision-making in the ***,existing disease control methods often assume users’full compliance with measures like mandatory isolation,which does not align with the actual *** address these issues,this paper proposes a prospect theorybased framework to model users’decision-making process in epidemics and analyzes how irrationality affects individuals’behaviors and epidemic *** to the analysis results,irrationality tends to prompt conservative behaviors when the infection risk is low but encourages risk-seeking behaviors when the risk is ***,this paper proposes a behavior inducement algorithm to guide individuals’behaviors and control the spread of *** and real user tests validate our analysis,and simulation results show that the proposed behavior inducement algorithm can effectively guide individuals’behavior.

关键词： Disease spread behavior model irrationality prospect theory

Deciphering gastric inflammation-induced tumorigenesis through multi-omics data and AI methods

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Cancer Biology & Medicine 2024年第4期21卷 312-330页

作者： Qian Zhang Mingran Yang Peng Zhang Bowen Wu Xiaosen Wei Shao Li Institute for TCM-X MOE Key Laboratory of BioinformaticsBioinformatics DivisionBNRISTDepartment of AutomationTsinghua UniversityBeijing 100084China

Gastric cancer(GC), the fifth most common cancer globally, remains the leading cause of cancer deaths worldwide. Inflammation-induced tumorigenesis is the predominant process in GC development;therefore, systematic research in this area should improve understanding of the biological mechanisms that initiate GC development and promote cancer hallmarks. Here, we summarize biological knowledge regarding gastric inflammation-induced tumorigenesis, and characterize the multi-omics data and systems biology methods for investigating GC development. Of note, we highlight pioneering studies in multi-omics data and state-of-the-art network-based algorithms used for dissecting the features of gastric inflammation-induced tumorigenesis, and we propose translational applications in early GC warning biomarkers and precise treatment strategies. This review offers integrative insights for GC research, with the goal of paving the way to novel paradigms for GC precision oncology and prevention.

关键词： Gastric cancer inflammation-induced tumorigenesis multi-omics artificial intelligence network-based methods

Constrained reinforcement learning with statewise projection: a control barrier function approach

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Science China(Information Sciences) 2024年第3期67卷 136-154页

作者： Xinze JIN Kuo LI Qingshan JIA department of automation Tsinghua University

Safety is a critical issue for reinforcement learning(RL), as it may be risky for some actual applications if the learning process involves unsafe exploration. Instead of formulating constraints as expectationbased in constrained RL, considering statewise safety in constrained RL is more meaningful. This work aims to address the issue of safe projection in RL by introducing a control barrier function that inherently learns a safe policy through a set certificate. We seek to analyze some theoretical properties of safe projection in the learning process, including convergence and performance bound, and extend the discussion into ensembles and guided controllers. Moreover, we approach analytical solutions for deterministic and stochastic system dynamics. Experimental results in different tasks show that the proposed method achieves better effects in terms of both performance and safety.

关键词： reinforcement learning safe projection control barrier function

Automatic velocity picking based on optimal key points tracking algorithm

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Petroleum Science 2024年第2期21卷 903-917页

作者： Yong-Hao Wang Wen-Kai Lu Song-Bai Jin Yang Li Yu-Xuan Li Xiao-Feng Gu The Institute for Artificial Intelligence(THUAI) Tsinghua UniversityBeijing100084China State Key Laboratory of Intelligent Technology and Systems Tsinghua UniversityBeijing100084China Beijing National Research Center for Information Science and Technology(bnrist) Beijing100084China The department of automation Tsinghua UniversityBeijing100084China

Picking velocities from semblances manually is laborious and necessitates experience. Although various methods for automatic velocity picking have been developed, there remains a challenge in efficiently incorporating information from nearby gathers to ensure picked velocity aligns with seismic horizons while also improving picking accuracy. The conventional method of velocity picking from a semblance volume is computationally demanding, highlighting a need for a more efficient strategy. In this study, we introduce a novel method for automatic velocity picking based on multi-object tracking. This dynamic tracking process across different semblance panels can integrate information from nearby gathers effectively while maintaining computational efficiency. First, we employ accelerated density clustering on the velocity spectrum to discern cluster centers without the requirement for prior knowledge regarding the number of clusters. These cluster centers embody the maximum likelihood velocities of the main subsurface structures. Second, our proposed method tracks key points within the semblance volume. Kalman filter is adopted to adjust the tracking process, followed by interpolation on these tracked points to construct the final velocity model. Our synthetic data example demonstrates that our proposed algorithm can effectively rectify the picking errors of the clustering algorithm. We further compare the performances of the clustering method(CM), the proposed tracking method(TM), and the variational method(VM) on a field dataset from the Gulf of Mexico. The results attest that our method offers superior accuracy than CM, achieves comparable accuracy with VM, and benefits from a reduced computational cost.

关键词： Velocity picking Multi-object tracking Density clustering Kalman filter

NeoHunter:Flexible software for systematically detecting neoantigens from sequencing data

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Quantitative Biology 2024年第1期12卷 70-84页

作者： Tianxing Ma Zetong Zhao Haochen Li Lei Wei Xuegong Zhang MOE Key Lab of Bioinformatics Bioinformatics Division of BNRIST and Department of AutomationTsinghua UniversityBeijingChina School of Medicine Tsinghua UniversityBeijingChina School of Life Sciences Tsinghua UniversityBeijingChina

Complicated molecular alterations in tumors generate various mutant *** of these mutant peptides can be presented to the cell surface and then elicit immune responses,and such mutant peptides are called *** detection of neoantigens could help to design personalized cancer *** some computational frameworks for neoantigen detection have been proposed,most of them can only detect SNV-and indel-derived *** addition,current frameworks adopt oversimplified neoantigen prioritization *** factors hinder the comprehensive and effective detection of *** developed NeoHunter,flexible software to systematically detect and prioritize neoantigens from sequencing data in different *** can detect not only SNV-and indel-derived neoantigens but also gene fusion-and aberrant splicing-derived *** supports both direct and indirect immunogenicity evaluation strategies to prioritize candidate *** strategies utilize binding characteristics,existing biological big data,and T-cell receptor specificity to ensure accurate detection and *** applied NeoHunter to the TESLA dataset,cohorts of melanoma and non-small cell lung cancer *** achieved high performance across the TESLA cancer patients and detected 79%(27 out of 34)of validated neoantigens in ***-and indel-derived neoantigens accounted for 90%of the top 100 candidate neoantigens while neoantigens from aberrant splicing accounted for 9%.Gene fusion-derived neoantigens were detected in one *** is a powerful tool to‘catch all’neoantigens and is available for free academic use on Github(XuegongLab/NeoHunter).

关键词： cancer vaccine molecular alteration neoantigen neoantigen prioritization

On optimal charging scheduling for electric vehicles with wind power generation

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Fundamental Research 2024年第4期4卷 951-960页

作者： Junjie Wu Qing-Shan Jia Center for Intelligent and Networked Systems(CFINS) Department of AutomationBeijing National Research Center for Information Science and Technology(BNRist)TsinghuaUniversityBeijing100084China Huawei Technologies Co.Ltd Shenzhen 518129China

We consider the scheduling of battery charging of electric vehicles(EVs)integrated with renewable power *** increasing adoption of EVs and the development of renewable energies contribute importance to this *** optimization of charging scheduling is challenging because of the large action space,the multi-stage decision making,and the high *** solve this problem is time-consuming when the scale of the system is *** is urgent to develop a practical and efficient method to properly schedule the charging of *** contribution of this work is ***,we provide a sufficient condition on which the charging of EVs can be completely self-sustained by distributed *** algorithm is proposed to obtain the optimal charging policy when the sufficient condition ***,the scenario when the supply of the renewable power generation is deficient is *** prove that when the renewable generation is deterministic there exists an optimal policy which follows the modified least laxity and longer remaining processing time first(mLLLP)***,we provide an adaptive rule-based algorithm which obtains a near-optimal charging policy efficiently in general *** test the proposed algorithm by numerical *** results show that it performs better than the other existing rule-based methods.

关键词： Electric vehicle Charging scheduling Wind power Optimal policy Renewable energy

Camera,LiDAR,and IMU Based Multi-Sensor Fusion SLAM:A Survey

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Tsinghua Science and Technology 2024年第2期29卷 415-429页

作者： Jun Zhu Hongyi Li Tao Zhang department of automation Tsinghua UniversityBeijing 100084China

In recent years,Simultaneous Localization And Mapping(SLAM)technology has prevailed in a wide range of applications,such as autonomous driving,intelligent robots,Augmented Reality(AR),and Virtual Reality(VR).Multi-sensor fusion using the most popular three types of sensors(e.g.,visual sensor,LiDAR sensor,and IMU)is becoming ubiquitous in SLAM,in part because of the complementary sensing capabilities and the inevitable shortages(e.g.,low precision and long-term drift)of the stand-alone sensor in challenging *** this article,we survey thoroughly the research efforts taken in this field and strive to provide a concise but complete review of the related ***,a brief introduction of the state estimator formation in SLAM is ***,the state-of-the-art algorithms of different multi-sensor fusion algorithms are *** we analyze the deficiencies associated with the reviewed approaches and formulate some future research *** paper can be considered as a brief guide to newcomers and a comprehensive reference for experienced researchers and engineers to explore new interesting orientations.

关键词： multi-sensor fusion Simultaneous Localization And Mapping(SLAM) navigation localization

A Soft Sensor with Light and Efficient Multi-scale Feature Method for Multiple Sampling Rates in Industrial Processing

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Machine Intelligence Research 2024年第2期21卷 400-410页

作者： Dezheng Wang Yinglong Wang Fan Yang Liyang Xu Yinong Zhang Yiran Chen Ning Liao School of automation Southeast UniversityNanjing 210096China Software and Artificial Intelligence College Chongqing Institute of EngineeringChongqing 400056China Beijing National Research Center for Information Science and Technology(bnrist) Department of AutomationTsinghua UniversityBeijing 100084China Liangjiang International College Chongqing University of TechnologyChongqing 401135China Smart City College Beijing Union UniversityBeijing 100101China

In industrial process control systems,there is overwhelming evidence corroborating the notion that economic or technical limitations result in some key variables that are very difficult to measure *** data-driven soft sensor is an effective solution because it provides a reliable and stable online estimation of such *** paper employs a deep neural network with multiscale feature extraction layers to build soft sensors,which are applied to the benchmarked Tennessee-Eastman process(TEP)and a real wind farm *** comparison of modelling results demonstrates that the multiscale feature extraction layers have the following advantages over other ***,the multiscale feature extraction layers significantly reduce the number of parameters compared to the other deep neural ***,the multiscale feature extraction layers can powerfully extract dataset ***,the multiscale feature extraction layers with fully considered historical measurements can contain richer useful information and improved representation compared to traditional data-driven models.

关键词： Multi-scale feature extractor deep neural network(DNN) multirate sampled industrial processes prediction

Optimal Positioning Strategy for Multi-Camera Zooming Drones

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1802-1818页

作者： Manuel Vargas Carlos Vivas Teodoro Alamo department of System Engineering and automation University of SevilleSeville 41092Spain

In the context of multiple-target tracking and surveillance applications,this paper investigates the challenge of determining the optimal positioning of a single autonomous aerial vehicle or agent equipped with multiple independently-steerable zooming cameras to effectively monitor a set of targets of *** camera is dedicated to tracking a specific target or cluster of *** key innovation of this study,in comparison to existing approaches,lies in incorporating the zooming factor for the onboard cameras into the optimization *** enhancement offers greater flexibility during mission execution by allowing the autonomous agent to adjust the focal lengths of the onboard cameras,in exchange for varying real-world distances to the corresponding targets,thereby providing additional degrees of freedom to the optimization *** proposed optimization framework aims to strike a balance among various factors,including distance to the targets,verticality of viewpoints,and the required focal length for each *** primary focus of this paper is to establish the theoretical groundwork for addressing the non-convex nature of the optimization problem arising from these *** this end,we develop an original convex approximation *** paper also includes simulations of diverse scenarios,featuring varying numbers of onboard tracking cameras and target motion profiles,to validate the effectiveness of the proposed approach.

关键词： Convex optimization projective transformation unmanned aerial vehicle visual object tracking visual surveillance.