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| 1 | A Hybrid Forecasting Framework Based on Support Vector Regression with a Modified Genetic Algorithm and a Random Forest for Traffic Flow Prediction显示文摘The ability to perform short-term traffic flow forecasting is a crucial component of intelligent transportation systems. However, accurate and reliable traffic flow forecasting is still a significant issue due to the complexity and variability of real traffic systems. To improve the accuracy of short-term traffic flow forecasting, this paper presents a novel hybrid prediction framework based on Support Vector Regression(SVR) that uses a Random Forest(RF) to select the most informative feature subset and an enhanced Genetic Algorithm(GA) with chaotic characteristics to identify the optimal forecasting model parameters. The framework is evaluated with real-world traffic data collected from eight sensors located near the I-605 interstate highway in California. Results show that the proposed RFCGASVR model achieves better performance than other methods. | Lizong Zhang Nawaf R Alharbe Guangchun Luo Zhiyuan Yao Ying Li | 2018 | Tsinghua Science and Technology2018，23，4： | 19 |
| 2 | Force-induced charge carrier storage:a new route for stress recording显示文摘Stress sensing is the basis of human-machine interface,biomedical engineering,and mechanical structure detection systems.Stress sensing based on mechanoluminescence(ML)shows significant advantages of distributed detection and remote response to mechanical stimuli and is thus expected to be a key technology of next-generation tactile sensors and stress recorders.However,the instantaneous photon emission in ML materials generally requires real-time recording with a photodetector,thus limiting their application fields to real-time stress sensing.In this paper,we report a force-induced charge carrier storage(FICS)effect in deep-trap ML materials,which enables storage of the applied mechanical energy in deep traps and then release of the stored energy as photon emission under thermal stimulation.The FICS effect was confirmed in five ML materials with piezoelectric structures,efficient emission centres and deep trap distributions,and its mechanism was investigated through detailed spectroscopic characterizations.Furthermore,we demonstrated three applications of the FICS effect in electronic signature recording,falling point monitoring and vehicle collision recording,which exhibited outstanding advantages of distributed recording,longterm storage,and no need for a continuous power supply.The FICS effect reported in this paper provides not only a breakthrough for ML materials in the field of stress recording but also a new idea for developing mechanical energy storage and conversion systems. | Yixi Zhuang Dong Tu Changjian Chen Le Wang Hongwu Zhang Hao Xue Conghui Yuan Guorong Chen Caofeng Pan Lizong Dai Rong-Jun Xie | 2020 | Light(Science & Applications)2020，9，1： | 10 |
| 3 | Identifying absorbable bioactive constituents of Yupingfeng Powder acting on COVID-19 through integration of UPLC-Q/TOF-MS and network pharmacology analysis显示文摘Objective:Yupingfeng Powder(YPF),a kind of preventative patent medicine,is chosen for treatment of coronavirus disease 2019(COVID-19)due to its high frequency application in respiratory tract diseases,such as chronic obstructive pulmonary disease,asthma,respiratory tract infections,and pneumonia,with the advantage of reducing the relapse rate and the severity.However,the active components of YPF and the mechanisms of components affecting COVID-19 are unclear.This study aimed to determine active constituents and elucidate its potential mechanisms.Methods:Ultra performance liquid chromatography-quadrupole-time of flight mass spectrometry(UPLCQ/TOF-MS)and liquid chromatography-triple quadrupole mass spectrometry(LC-QQQ-MS)were used to determine the components and absorbable constituents of YPF.Secondly,TCMSP,Drugbank,Swiss and Pharm Mapper were used to search the targets of absorbable bioactive constituents of YPF,and the targets of COVID-19 were identified based on Gene Cards and OMIM databases.STRING database was used to filter the possible inter-protein interactions.Thirdly,Gene Ontology(GO)enrichment analysis and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathways analysis were performed to identify molecular function and systemic involvement of target genes.Results:A total of 61 components of YPF and 36 absorbable constituents were identified through UPLC-Q/TOF-MS.Wogonin,prim-O-glucosylcimifugin,5-O-methylvisamminol,astragalosideⅣand 5-Omethylvisamminol(hydroxylation)were vital constituents for the treatment of COVID-19,and RELA,TNF,IL-6,MAPK14 and MAPK8 ere recognized as key targets of YPF.The major metabolic reactions of the absorbed constituents of YPF were demethylation,hydroxylation,sulfation and glucuronidation.GO and KEGG pathway analysis further showed that the most important functions of YPF were T cell activation,response to molecule of bacterial origin,cytokine receptor binding,receptor ligand activity,cytokine activity,IL-17 signaling pathway,Chagas disease,lipid and atherosclerosis,etc.Conclusion:The approach of combining UPLC-Q/TOF-MS with network pharmacology is an effective tool to identify potentially bioactive constituents of YPF and its key targets on treatment of COVID-19. | Linyan Wang Zhongyan Du Yang Guan Bo Wang Yanling Pei Lizong Zhang Mingsun Fang | 2022 | Chinese Herbal Medicines2022，14，2： | 3 |
| 4 | Mechanism design and simulation analysis of multifimctional nursing bed 显示文摘 | Lin Lizong Zhang Song Hu Xinglong | 2010 | Mechanical and Electronics Engineering2010，，： | 1 |
| 5 | c-Met upregulates aquaporin 3 expression in human gastric carcinoma cells via the ERK signalling pathway显示文摘 | Jianping Wang Zhifu Gui Longying Deng Maocai Sun Renhua Guo Weiming Zhang Lizong Shen | 2012 | Cancer Letters2012，，1： | 1 |
| 6 | Efficient Publication of Distributed and Overlapping Graph Data Under Differential Privacy显示文摘Graph data publication has been considered as an important step for data analysis and mining.Graph data,which provide knowledge on interactions among entities,can be locally generated and held by distributed data owners.These data are usually sensitive and private,because they may be related to owners’personal activities and can be hijacked by adversaries to conduct inference attacks.Current solutions either consider private graph data as centralized contents or disregard the overlapping of graphs in distributed manners.Therefore,this work proposes a novel framework for distributed graph publication.In this framework,differential privacy is applied to justify the safety of the published contents.It includes four phases,i.e.,graph combination,plan construction sharing,data perturbation,and graph reconstruction.The published graph selection is guided by one data coordinator,and each graph is perturbed carefully with the Laplace mechanism.The problem of graph selection is formulated and proven to be NP-complete.Then,a heuristic algorithm is proposed for selection.The correctness of the combined graph and the differential privacy on all edges are analyzed.This study also discusses a scenario without a data coordinator and proposes some insights into graph publication. | Xu Zheng Lizong Zhang Kaiyang Li Xi Zeng | 2022 | Tsinghua Science and Technology2022，27，2： | 0 |
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