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Energy saving design of the machining unit of hobbing machine tool with integrated optimization

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Frontiers of Mechanical Engineering 2022年第3期17卷 209-227页

作者： Yan LV Congbo LI Jixiang HE Wei LI Xinyu LI Juan LI State Key Laboratory of Mechanical Transmission College of Mechanical and Vehicle EngineeringChongqing UniversityChongqing400044China Department of Process technology Sichuan Aerospace Fenghuo Servo Control Technology CorporationChengdu611130China State Key Laboratory of Digital Manufacturing Equipment and technology Huazhong University of Science and TechnologyWuhan430074China

The machining unit of hobbing machine tool accounts for a large portion of the energy consumption during the operating *** optimization design is a practical means of energy saving and can reduce energy consumption ***,this issue has rarely been discussed in depth in previous research.A comprehensive function of energy consumption of the machining unit is built to address this *** models are established by using effective fitting *** integrated optimization model for reducing tool displacement and energy consumption is developed on the basis of the energy consumption function and surrogate models,and the parameters of the motor and structure are considered *** show that the energy consumption and tool displacement of the machining unit are reduced,indicating that energy saving is achieved and the machining accuracy is *** influence of optimization variables on the objectives is analyzed to inform the design.

关键词： energy saving design energy consumption machining unit integrated optimization machine tool

A malware propagation prediction model based on representation learning and graph convolutional networks

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Digital Communications and Networks 2023年第5期9卷 1090-1100页

作者： Tun Li Yanbing Liu Qilie Liu Wei Xu Yunpeng Xiao Hong Liu College of Computer Science and technology Chongqing University of Posts and TelecommunicationsChongqing400065China

The traditional malware research is mainly based on its recognition and detection as a breakthrough point,without focusing on its propagation trends or predicting the subsequently infected *** complexity of network structure,diversity of network nodes,and sparsity of data all pose difficulties in predicting *** paper proposes a malware propagation prediction model based on representation learning and Graph Convolutional Networks(GCN)to address the aforementioned ***,to solve the problem of the inaccuracy of infection intensity calculation caused by the sparsity of node interaction behavior data in the malware propagation network,a mechanism based on a tensor to mine the infection intensity among nodes is proposed to retain the network structure *** influence of the relationship between nodes on the infection intensity is also ***,given the diversity and complexity of the content and structure of infected and normal nodes in the network,considering the advantages of representation learning in data feature extraction,the corresponding representation learning method is adopted for the characteristics of infection intensity among *** can efficiently calculate the relationship between entities and relationships in low dimensional space to achieve the goal of low dimensional,dense,and real-valued representation learning for the characteristics of propagation spatial *** also design a new method,Tensor2vec,to learn the potential structural features of malware ***,considering the convolution ability of GCN for non-Euclidean data,we propose a dynamic prediction model of malware propagation based on representation learning and GCN to solve the time effectiveness problem of the malware propagation *** experimental results show that the proposed model can effectively predict the behaviors of the nodes in the network and discover the influence of different characteristics of nodes on the mal

关键词： Malware Representation learning Graph convolutional networks(GCN) Tensor decomposition Propagation prediction

Nitrogen cold plasma treatment stabilizes Cu^(0)/Cu^(+) electrocatalysts to enhance CO_(2) to C2 conversion

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Journal of Energy Chemistry 2023年第9期84卷 321-328页

作者： Qiang Zhang Jianlin Wang Fang Guo Ge He Xiaohui Yang Wei Li Junqiang Xu Zongyou Yin School of Chemistry&Chemical Engineering Chongqing University of TechnologyChongqing 400054China College of Biomass Science and Engineering Sichuan UniversityChengdu 610065SichuanChina chongqing Institute of Green and Intelligent technology Chinese Academy of SciencesChongqing 400714China Research School of Chemistry Australian National UniversityCanberraACT 2601Australia

Cu-based materials are ideal catalysts for CO_(2) electrocatalytic reduction reaction(CO_(2)RR) into multicarbon ***,such reactions require stringent conditions on local environments of catalyst surfaces,which currently are the global pressing ***,a stabilized activation of Cu^(0)/Cu^(+)-onAg interface by N_(2) cold plasma treatment was developed for improving Faradaic efficiency(FE) of CO_(2)RR into C2 *** resultant Ag@Cu-CuN_x exhibits a C2 FE of 72% with a partial current density of-14.9 mA cm^(-2) at-1.0 V ***(reversible hydrogen electrode).Combining density functional theory(DFT) and experimental investigations,we unveiled that Cu^(0)/Cu^(+) species can be co ntrollably tu ned by the incorporation of nitrogen to form CuN_x on Ag surface,i.e.,Ag@Cu-CuN_*** strategy enhances ^(*)CO intermediates generation and accelerates C-C coupling both thermodynamically and *** intermediates O^(*)C^(*)CO,^(*)COOH,and ^(*)CO were detected by in-situ attenuated total internal reflection surface enhanced infrared absorption spectroscopy(ATR-SEIRAS).The uncovered CO_(2)RR-into-C2 products were carried out along CO_(2)→^(*)COOH→^(*)CO→O^(*)C^(*)CO→^(*)C_(2)H_(3)O→^(*)C_(2)H_(4)O→ C_(2)H_(5)OH(or ^(*)C_(2)H_(3)O→^(*)O+C_(2)H_(4)) paths over Ag@Cu-CuN_x *** work provides a new approach to design Cu-based electrocatalysts with high-efficiency,mild condition,and stable CO_(2)RR to C2 products.

关键词： Nitrogen cold plasma Cu-based metal nitride Carbon dioxide electroreduction C2 products Stabilizes

ICS-SVM:A user retweet prediction method for hot topics based on improved SVM

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Digital Communications and Networks 2022年第2期8卷 186-193页

作者： Tianji Dai Yunpeng Xiao Xia Liang Qian Li Tun Li School of Software Engineering Chongqing University of Posts and TelecommunicationsChongqing400065China

In social networks,many complex factors affect the prediction of user forwarding *** paper proposes an improved SVM prediction method for user forwarding behavior of hot topics to improve prediction ***,we consider that the improved Cuckoo Search algorithm can select the optimal penalty parameters and kernel function parameters to optimize the SVM and thus predict the user's forwarding ***,this paper considers the factors that affect the user forwarding behavior comprehensively from the user's own factors and external ***,based on the characteristics of the user's forwarding behavior changing over time,the time-slicing method is used to predict the trend of hot *** show that the method can accurately predict the user's forwarding behavior and can sense the trend of hot topics.

关键词： Cuckoo search algorithm Support vector machine Hot topic User behavior prediction

RepDDNet:a fast and accurate deforestation detection model with high-resolution remote sensing image

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International Journal of Digital Earth 2023年第1期16卷 2013-2033页

作者： Zhipan Wang Zhongwu Wang Dongmei Yan Zewen Mo Hua Zhang Qingling Zhang Shenzhen Key Laboratory of Intelligent Microsatellite Constellation Sun Yat-sen UniversityShenzhenPeople’s Republic of China Land Satellite Remote Sensing application Center Ministry of Natural ResourcesBeijingPeople’s Republic of China Aerospace Information Research Institute Chinese Academy of SciencesBeijingPeople’s Republic of China Changsha University of Science&technology ChangshaPeople’s Republic of China

Forest is the largest carbon reservoir and carbon absorber on ***,mapping forest cover change accurately is of great significance to achieving the global carbon neutrality *** forest change information could be acquired by deep learning methods using high-resolution remote sensing ***,deforestation detection based on deep learning on a large-scale region with high-resolution images required huge computational ***,there was an urgent need for a fast and accurate deforestation detection *** this study,we proposed an interesting but effective re-parameterization deforestation detection model,named *** other existing models designed for deforestation detection,the main feature of RepDDNet was its decoupling feature,which means that it allowed the multi-branch structure in the training stages to be converted into a plain structure in the inference stage,thus the computation efficiency can be significantly improved in the inference stage while maintaining the accuracy unchanged.A large-scale experiment was carried out in Ankang city with 2-meter high-resolution remote sensing images(the total area of it was over 20,000 square kilometers),and the result indicated that the model computation efficiency could be improved by nearly 30%compared with the model without ***,compared with other lightweight models,RepDDNet also displayed a trade-off between accuracy and computation efficiency.

关键词： Carbon neutral deforestation detection high-resolution remote sensing image deep learning reparameterization

Exploring associations between streetscape factors and crime behaviors using Google Street View images

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Frontiers of Computer Science 2022年第4期16卷 45-58页

作者： Mingyu Deng Wei Yang Chao Chen Chenxi Liu School of Computer Science Chongqing UniversityChongqing400044China School of Management Science and Real Estate Chongqing UniversityChongqing400044China State Key Laboratory of Mechanical Transmission Chongqing UniversityChongqing400044China

Understanding the influencing mechanism of the urban streetscape on crime is fairly important to crime prevention and urban ***,the development of deep learning technology and big data of street view images,makes it possible to quantitatively explore the relationship between streetscape and *** study computed eight streetscape indexes of the street built environment using Google Street View images ***,the association between the eight indexes and recorded crime events was revealed with a poisson regression model and a geographically weighted poisson regression *** experiment was conducted in downtown and uptown Manhattan,New *** regression results show that the influences of Motorization Index on crimes are significant and positive,while the effects of the Light View Index and Green View Index on crimes depend heavily on the socioeconomic *** a local perspective,the Pedestrian Space Index,Green View Index,Light View Index and Motorization Index have a significant spatial influence on crimes,while the same visual streetscape factors have different effects on different streets due to the combination differences of socioeconomic,cultural and streetscape *** key streetscape elements of a given street that affect a specific criminal activity can be identified according to the strength of the *** results provide both theoretical and practical implications for crime theories and crime prevention efforts.

关键词： crime Google Street View streetscape spatial analysis geographically weighted poisson regression

The inducible secreting TLR5 agonist,CBLB502,enhances the anti-tumor activity of CAR133-NK92 cells in colorectal cancer

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Cancer Biology & Medicine 2023年第9期20卷 662-681页

作者： Xiaohui Wang Wei Qiu Haoyu Liu Min He Wei He Zhan Li Zhiqiang Wu Xiang Xu Ping Chen College of Biotechnology Southwest UniversityChongqing 400715China Department of Stem Cell&Regenerative Medicine State Key Laboratory of TraumaBurn and Combined InjuryDaping HospitalArmy Medical UniversityChongqing 400042China Department of Dermatology The First Affiliated Hospital of Wenzhou Medical UniversityWenzhou 325035China Department of Biotherapeutics The First Medical CenterChinese PLA General HospitalBeijing 100038China

Objective:CAR-T/NK cells have had limited success in the treatment of solid tumors,such as colorectal cancer(CRC),in part because of the heterogeneous nature of tumor-associated antigens that lead to antigen-negative relapse after the initial *** barrier might be overcome by enhancing the recruitment and durability of endogenous immune ***:Immunohistochemistry and flow cytometry were used to assess the expression of CD133 antigen in tissue microarrays and cell lines,*** vector transduction was used to generate CBLB502-secreting CAR133-NK92 cells(CAR133-i502-NK92).The tumor killing capacity of CAR133-NK92 cells in vitro and in vivo were quantified via LDH release,the RTCA assay,and the degranulation test,as well as measuring tumor bioluminescence signal intensity in mice ***:We engineered CAR133-i502-NK92 cells and demonstrated that those cells displayed enhanced proliferation(9.0×10^(4)cells vs.7.0×10^(4)cells)and specific anti-tumor activities in vitro and in a xenogeneic mouse model,and were ***,CBLB502 secreted by CAR133-i502-NK92 cells effectively activated endogenous immune ***,in hCD133+/hCD133−mixed cancer xenograft models,CAR133-i502-NK92 cells suppressed cancer growth better than the counterparts(n=5,P=0.0297).Greater T-cell infiltration was associated with greater anti-tumor potency(P<0.0001).Conclusions:Armed with a CBLB502 TLR5 agonist,CAR133-NK92 cells were shown to be capable of specifically eliminating CD133-positive colon cancer cells in a CAR133-dependent manner and indirectly eradicating CD133-negative colon cancer cells in a CBLB502-specific endogenous immune response *** study describes a novel technique for optimizing CAR-T/NK cells for the treatment of antigenically-diverse solid tumors.

关键词： TLR5 agonist CBLB502 CAR133 endogenous immune response colorectal cancer

Multi-agent reinforcement learning for edge information sharing in vehicular networks

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Digital Communications and Networks 2022年第3期8卷 267-277页

作者： Ruyan Wang Xue Jiang Yujie Zhou Zhidu Li Dapeng Wu Tong Tang Alexander Fedotov Vladimir Badenko School of Communication and Information Engineering Chongqing University of Posts and TelecommunicationsChongqing400065China Advanced Network and Intelligent Connection technology Key Laboratory of chongqing Education Commission of china Chongqing400065China Key Laboratory of Ubiquitous Sensing and Networking in chongqing Chongqing400065China Peter the Great St.Petersburg Polytechnic University Polytechnicheskaya29St.Petersburg195251Russia

To guarantee the heterogeneous delay requirements of the diverse vehicular services,it is necessary to design a full cooperative policy for both Vehicle to Infrastructure(V2I)and Vehicle to Vehicle(V2V)*** paper investigates the reduction of the delay in edge information sharing for V2V links while satisfying the delay requirements of the V2I ***,a mean delay minimization problem and a maximum individual delay minimization problem are formulated to improve the global network performance and ensure the fairness of a single user,respectively.A multi-agent reinforcement learning framework is designed to solve these two problems,where a new reward function is proposed to evaluate the utilities of the two optimization objectives in a unified ***,a proximal policy optimization approach is proposed to enable each V2V user to learn its policy using the shared global network *** effectiveness of the proposed approach is finally validated by comparing the obtained results with those of the other baseline approaches through extensive simulation experiments.

关键词： Vehicular networks Edge information sharing Delay guarantee Multi-agent reinforcement learning Proximal policy optimization

Incipient fault diagnosis on active disturbance rejection control

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Science china.Information Sciences) 2022年第9期65卷 301-302页

作者： Darong HUANG Xingxing HUA Bo MI Yang LIU Zhenyuan ZHANG College of Information Science and Engineering Chongqing Jiaotong University College of Mathematical and Statistics Chongqing Jiaotong University

Dear editor,The incipient fault diagnosis method has received great attention in recent decades owing to the increasing demand for reliability and safety in industrial processes [1, 2]. A controller of active disturbance rejection control (ADRC)can effectively separate the incipient fault from the disturbance. Therefore, studying the incipient fault estimation has become a necessarily imminent research topic in this new frontier.

关键词： Active disturbance rejection control Fault diagnosis Disturbance abrupt incipient fault soft incipient fault