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Artificial intelligence in gastric cancer:applications and challenges

Gastroenterology Report 2022年第1期10卷 227-242页

作者： Runnan Cao Lei Tang Mengjie Fang Lianzhen Zhong Siwen Wang Lixin Gong Jiazheng Li Di Dong Jie Tian School of Artificial Intelligence University of Chinese Academy of SciencesBeijingP.R.China CAS Key Laboratory of Molecular Imaging Beijing Key Laboratory of Molecular Imagingthe State Key Laboratory of Management and Control for Complex SystemsInstitute of AutomationChinese Academy of SciencesBeijingP.R.China Key Laboratory of Carcinogenesis and Translational Research(Ministry of Education/Beijing) Radiology DepartmentPeking University Cancer Hospital&InstituteBeijingP.R.China College of Medicine and Biological Information Engineering School Northeastern UniversityShenyangLiaoningP.R.China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Engineering MedicineBeihang UniversityBeijingP.R.China Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education School of Life Science and TechnologyXidian UniversityXi’anShaanxiP.R.China

Gastric cancer(GC)is one of the most common malignant tumors with high *** diagnosis and treatment decisions for GC rely heavily on human experts’careful judgments on medical ***,the improvement of the accuracy is hindered by imaging conditions,limited experience,objective criteria,and inter-observer ***,the developments of machine learning,especially deep-learning algorithms,have been facilitating computers to extract more information from data *** are exploring the far-reaching applications of artificial intelligence(AI)in various clinical practices,including ***,we aim to provide a broad framework to summarize current research on AI in *** the screening of GC,AI can identify precancerous diseases and assist in early cancer detection with endoscopic examination and pathological *** the diagnosis of GC,AI can support tumor-node-metastasis(TNM)staging and subtype *** treatment decisions,AI can help with surgical margin determination and prognosis ***,current approaches are challenged by data scarcity and poor *** tackle these problems,more regulated data,unified processing procedures,and advanced algorithms are urgently needed to build more accurate and robust AI models for GC.

关键词： gastric cancer artificial intelligence radiomics endoscopy computed tomography pathology

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Skeleton-Based Multi-Stream Adaptive Graph Convolutional Network for Indoor Scene Action Recognition

Skeleton-Based Multi-Stream Adaptive Graph Convolutional Net...

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Chinese Automation Congress (CAC)

作者： Jiazhuo Li Luefeng Chen Min Li Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems and the Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation China University of Geosciences Wuhan China Department of Electrical and Computer Engineering University of Alberta Edmonton AB Canada Polish Academy of Sciences Systems Research Institute Warsaw Poland Department of Computer Engineering Istinye University Sariyer/Istanbul Turkey Tokyo Institute of Technology Yokohama Japan Tokyo Institute of Technology Tokyo Japan

With the rapid advances in computer vision, human action recognition has gradually received attention, but the current methods still exhibit some problems in indoor environments. The human skeleton, as the framework of human motion, contains high-quality actional feature information, and the skeleton-based action recognition method effectively avoid the interference of interior background noise and has advantages in indoor action recognition. The outstanding effect of graph convolutional networks on graph structure data processing has led to its rapid development and wide application in skeleton-based action recognition. Second-order skeletal information also contains a large number of actional features but is not effectively utilized. The artificial predefined topology of the human skeleton map has limitations, and cannot reflect the interaction between limbs. To solve the above problems, this article designs an adaptive weighted multi-stream graph convolutional network (AM-GCN) based on skeletal information, using an attention mechanism to enhance the network's ability to extract actional features, and an adaptive layer to make the construction graph more flexible, incorporating second-order skeletal features through a dual-stream architecture. In this article, the NTU-RGB+D dataset has been used for the experiments, the results show that the method in this article has good results.

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control System for Electric Drives of Plate Straightening Machines

Control System for Electric Drives of Plate Straightening Ma...

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International Russian Automation Conference (RusAutoCon)

作者： Andrey A. Radionov Andrey Yu. Semitko Boris M. Loginov Vadim R. Khramshin Aleksandra A. Filimonova Department of Automation and Control Moscow Polytechnic University Moscow Russia Department of Mechatronics and Automation South Ural State University Chelyabinsk Russia Magnitogorsk Iron and Steel Works Magnitogorsk Russia Power Engineering and Automated Systems Institute Nosov Magnitogorsk State Technical University Magnitogorsk Russia Department of Electric Drive Mechatronics and Electromechanics South Ural State University Chelyabinsk Russia

The essential quality parameter of rolled products is the flatness along the rolled stock length. The profile defects of the rolled stock, produced at the modern plate mill 5000, frequently occur in the course of intense cooling implied by the thermomechanical rolling technology. To eliminate them, the mill lines include cold straightening machines. The authors show typical flatness defects caused by the occurrence of longitudinal, central and edge waves. Further, the paper characterizes a cold straightening machine installed at the mill 5000 and provides the parameters of electric engines of straightening rollers. The key drawback of the design algorithm for electric drives’ control is setting engine constant moments regardless of the thickness and character of the defects in the rolled stock processed. This causes overloading of the electric and mechanical systems of certain rollers and unsatisfactory product quality. To eliminate the drawback, the authors developed a method for individual setting of engine moments closely coupled in the course of sheet processing. The authors present a functional block diagram for the control system to implement the method. The rationale is provided for the digital setting of moment controllers switched on the inputs of speed controllers. The authors conducted simulation modelling and comparative analysis of engine speeds and moments at the design and proposed settings. The paper provides the analysis of oscillograms obtained before and after the introduction of the control system developed. Its technical and economic feasibility was confirmed during operation.

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Sparse optimization of mutual synchronization in collectively oscillating networks

arXiv

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arXiv 2021年

作者： Nakao, Hiroya Yamaguchi, Katsunori Katayama, Shingo Yanagita, Tatsuo Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo152-8552 Japan Department of Engineering Science Osaka Electro-Communication University Neyagawa Osaka572-8530 Japan

We consider a pair of collectively oscillating networks of dynamical elements and optimize their internetwork coupling for efficient mutual synchronization based on the phase reduction theory developed in Ref. [H. Nakao, S. Yasui, M. Ota, K. Arai, and Y. Kawamura, Chaos 28, 045103 (2018)]. The dynamical equations describing a pair of weakly coupled networks are reduced to a pair of coupled phase equations, and the linear stability of the synchronized state between the networks is represented as a function of the internetwork coupling matrix. We seek the optimal coupling by minimizing the Frobenius and L1norms of the internetwork coupling matrix for the prescribed linear stability of the synchronized state. Depending on the norm, either a dense or sparse internetwork coupling yielding efficient mutual synchronization of the networks is obtained. In particular, a sparse yet resilient internetwork coupling is obtained by L1-norm optimization with additional constraints on the individual connection weights. Copyright © 2021, The Authors. All rights reserved.

关键词： Synchronization

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Assessment of the mineral potential of rocks using intelligent data analysis technologies

Assessment of the mineral potential of rocks using intellige...

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International Symposium on INFOTEH-JAHORINA (INFOTEH)

作者： Yadviga Tynchenko Vadim Tynchenko Ksenia Degtyareva Ekaterina Kalmykova Svetlana Kukartseva Artificial Intelligence Technology Scientific and Education Center Bauman Moscow State Technical University Moscow Russia Department of Technological Machines and Equipment of Oil and Gas Complex School of Petroleum and Natural Gas Engineering Siberian Federal University Krasnoyarsk Russia Information-Control Systems Department Reshetnev Siberian State University of Science and Technology Krasnoyarsk Russia Department of Systems Analysis and Operations Research Reshetnev Siberian State University of Science and Technology Krasnoyarsk Russia Center for Continuing Education Bauman Moscow State Technical University Moscow Russia Department of Applied Informatics Moscow Timiryazev Agricultural Academy Moscow Russia

ISBN: (数字)9798331515799

ISBN: (纸本)9798331515805

This paper presents a study aimed at developing and evaluating a classification model for the mineral potential of geological layers using machine learning methods. The main goal was to create an algorithm capable of predicting the categories of mineral potential — low, medium and high — based on key geological characteristics such as ore content, density, depth, permeability and rock type. The results obtained demonstrated the overall accuracy of the model at 98%, with an almost ideal classification for the categories of medium and high mineral potential. The analysis of the significance of the features showed that the ore content and density have the greatest impact on the classification. The work also revealed certain difficulties in classifying low mineral potential, which is due to limited data or the intersection of characteristics between classes. These results highlight the importance of further research in feature selection and improving data balance. The findings demonstrate the effectiveness of using machine learning methods in geological research and their potential for automating mineral resource assessment processes. The developed methodology can be adapted to solve other problems in the field of geology, such as forecasting deposits and optimizing mining.

关键词： Accuracy Machine learning algorithms Ores Machine learning Predictive models Rocks Minerals Permeability Decision trees Forecasting

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A Multiple Ant Colony System for the Electric Vehicle Routing Problem with Time Windows

A Multiple Ant Colony System for the Electric Vehicle Routin...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Michalis Mavrovouniotis Georgios Ellinas Changhe Li Marios Polycarpou Department of Electrical and Computer Engineering KIOS Research and Innovation Center of Excellence University of Cyprus Nicosia Cyprus School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China

ISBN: (纸本)9781665487696

Ant colony optimization (ACO) has been found to be useful on several vehicle routing problem variations. In this work, ACO is applied to the electric vehicle routing problem with time windows (E-VRPTW). The E-VRPTW has a hierarchical multiple objective function, which is to minimize the number of electric vehicles and the total distance traveled. A multiple ACO is applied to E-VRPTW in which two colonies cooperate to minimize the objectives in parallel. A local search is embedded in ACO to improve the quality of the output. The experimental results on a set of benchmark instances show that the multiple ACO is competitive with existing methods.

关键词： Ant colony optimization Vehicle routing Benchmark testing Electric vehicles Routing Search problems Linear programming

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Quasi-linear transfer function: A new method for frequency domain analysis of nonlinear systems

arXiv

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arXiv 2021年

作者： Wei, Hua-Liang Billings, S.A. Department of Automatic Control and Systems Engineering University of Sheffield Mappin Street SheffieldS1 3JD United Kingdom

A new concept, called quasi-linear transfer functions (QLTF), which can be used to characterize the output frequency behaviour of nonlinear systems, is introduced based on the well-known Volterra series representation. By using the new concept of QLTF, it can be proved that the input and output frequency behaviour of a given system can be expressed using a number of one-dimensional functions with a form similar to that of the traditional frequency response function for linear systems. Two algorithms, which can be used to determine the valid range of the associated output frequencies of arbitrary order nonlinear subsystems with both a multitone and general inputs, are provided. The results obtained provide a new important insight into the output frequency characteristics of nonlinear systems and have many potential applications in nonlinear systems analysis and nonlinear structure detection. © 2021, CC BY-NC-ND.

关键词： Nonlinear systems

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Convergence of sequences: A survey

arXiv

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arXiv 2021年

作者： Franci, Barbara Grammatico, Sergio Department of Data Science and Knowledge Engineering Maastricht University Maastricht Netherlands Delft Center for Systems and Control Delft University of Technology Delft Netherlands

Convergent sequences of real numbers play a fundamental role in many different problems in system theory, e.g., in Lyapunov stability analysis, as well as in optimization theory and computational game theory. In this survey, we provide an overview of the literature on convergence theorems and their connection with Féjer monotonicity in the deterministic and stochastic settings, and we show how to exploit these results. © 2021, CC BY.

关键词： Surveys

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Cufe2o4@Ncnts-Functionalized Ceramic Microfiltration Membrane for Antibiotic Oxidation and Fouling control Via Heterogeneous Electro-Fenton Reaction

SSRN

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SSRN 2024年

作者： Zhang, Zixin Huang, Guohe Li, Yongping Yao, Yao Zhang, Peng Chen, Xiujuan Ren, Shaojie Luo, Yifei Zhang, Yuanzheng State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Beijing Normal University Beijing100875 China State Key Joint Laboratory of Environmental Simulation and Pollution Control China-Canada Center for Energy Environment and Ecology Research UR-BNU School of Environment Beijing Normal University Beijing100875 China Environmental Systems Engineering Program University of Regina ReginaSKS4S 0A2 Canada Institute for Energy Environment and Sustainable Communities University of Regina ReginaS4S 0A2 Canada Department of Civil Engineering The University of Texas at Arlington ArlingtonTX United States Shandong Key Laboratory of Water Pollution Control and Resource Reuse School of Environmental Science and Engineering Shandong University Qingdao266237 China College of Environmental Science and Engineering North China Electric Power University Beijing102206 China

Herein, we reported an electrocatalytic ceramic microfiltration membrane functionalized with CuFe2O4 nanoparticles supported by nitrogen-doped carbon nanotubes (NCNTs). The synergistic catalysis between Fe and Cu induced a continuous ·OH generation. The active Fe(II) and Cu(I) sites decomposed the in-situ generated H2O2 into ·OH. The electron transfer from the external circuit and Cu(I) to Fe(III) drove the regeneration of Fe(II). The interfacial electron transfer from CuFe2O4 to NCNTs decreased the electron density of Fe and Cu, thus facilitating the redox cycles of Fe(III)/Fe(II) and Cu(II)/Cu(I). Furthermore, the Fe and Cu sites at the interface of CuFe2O4 and NCNTs displayed a superior ability to non-interface sites in producing ·OH. At near-neutral pH, the electrocatalytic membrane delivered excellent tetracycline removal kinetics (0.0134 min-1) and significantly alleviated the organic fouling occurring on the membrane. These findings shed new light on the development of new-generation membranes with catalytic oxidation capabilities for water treatment. © 2024, The Authors. All rights reserved.

关键词： Antibiotics

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Generative Artificial Intelligence Assisted Wireless Sensing: Human Flow Detection in Practical Communication Environments

arXiv

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arXiv 2024年

作者： Wang, Jiacheng Du, Hongyang Niyato, Dusit Xiong, Zehui Kang, Jiawen Ai, Bo Han, Zhu Kim, Dong In School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore China Ministry of Education Guangzhou510006 China State Key Laboratory of Rail Traffic Control and Safety Beijing Engineering Research Center of High-Speed Railway Broadband Mobile Communications Beijing Jiaotong University Beijing100044 China Department of Electrical and Computer Engineering University of Houston HoustonTX77004 United States Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Groundbreaking applications such as ChatGPT have heightened research interest in generative artificial intelligence (GAI). Essentially, GAI excels not only in content generation but also signal processing, offering support for wireless sensing. Hence, we introduce a novel GAI-assisted human flow detection system (G-HFD). Rigorously, G-HFD first uses the channel state information (CSI) to estimate the velocity and acceleration of propagation path length change of the human induced reflection (HIR). Then, given the strong inference ability of the diffusion model, we propose a unified weighted conditional diffusion model (UW-CDM) to denoise the estimation results, enabling detection of the number of targets. Next, we use the CSI obtained by a uniform linear array with wavelength spacing to estimate the HIR’s time of flight and direction of arrival (DoA). In this process, UW-CDM solves the problem of ambiguous DoA spectrum, ensuring accurate DoA estimation. Finally, through clustering, G-HFD determines the number of subflows and the number of targets in each subflow, i.e., the subflow size. The evaluation based on practical downlink communication signals shows G-HFD’s accuracy of subflow size detection can reach 91%. This validates its effectiveness and underscores the significant potential of GAI in the context of wireless sensing. © 2024, CC BY.

关键词： Artificial intelligence

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