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Application of smoothing technique on twin support vector hypersphere

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The Journal of China Universities of Posts and Telecommunications 2020年第3期27卷 31-41页

作者： Wu Qing gao xiaofeng Fan Jiulun Zhang Hengchang School of Automation Xi'an University of Posts and TelecommunicationsXi'an 710121China School of Telecom munication and Information Engineering Xi'an University of Posts and TelecommunicationsXi'an 710121China

In order to improve the learning speed and reduce computational complexity of twin support vector hypersphere(TSVH),this paper presents a smoothed twin support vector hypersphere(STSVH)based on the smoothing *** can generate two hyperspheres with each one covering as many samples as possible from the same class ***,STSVH only solves a pair of unconstraint differentiable quadratic programming problems(QPPs)rather than a pair of constraint dual QPPs which makes STSVH faster than the *** considering the differentiable characteristics of STSVH,a fast Newton-Armijo algorithm is used for solving *** experiment results on normally distributed clustered datasets(NDC)as well as University of California Irvine(UCI)data sets indicate that the significant advantages of the proposed STSVH in terms of efficiency and generalization performance.

关键词： twin support vector hypersphere Newton-Armijo algorithm smoothing approximation function unconstraint differentiable optimization

Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

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Frontiers of Medicine 2022年第3期16卷 496-506页

作者： Yaxin Chen Tianyi Yang xiaofeng gao Ajing Xu Department of Pharmacy Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai 200240China Shanghai Key Laboratory of Scalable Computing and Systems Department of Computer Science and EngineeringShanghai Jiao Tong UniversityShanghai 200240China Clinical Research Unit Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghai 200240China

The fracture risk of patients with diabetes is higher than those of patients without diabetes due to hyperglycemia,usage of diabetes drugs,changes in insulin levels,and excretion,and this risk begins as early as *** factors including demographic data(such as age,height,weight,and gender),medical history(such as smoking,drinking,and menopause),and examination(such as bone mineral density,blood routine,and urine routine)may be related to bone metabolism in patients with ***,most of the existing methods are qualitative assessments and do not consider the interactions of the physiological factors of *** addition,the fracture risk of patients with diabetes and osteoporosis has not been further studied *** this paper,a hybrid model combining XGBoost with deep neural network is used to predict the fracture risk of patients with diabetes and osteoporosis,and investigate the effect of patients’physiological factors on fracture risk.A total of 147 raw input features are considered in our *** presented model is compared with several benchmarks based on various metrics to prove its ***,the top 18 influencing factors of fracture risks of patients with diabetes are determined.

关键词： XGBoost deep neural network healthcare risk prediction

Compressive strength prediction and optimization design of sustainable concrete based on squirrel search algorithm-extreme gradient boosting technique

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Frontiers of Structural and Civil Engineering 2023年第9期17卷 1310-1325页

作者： Enming LI Ning ZHANG Bin XI Jian ZHOU xiaofeng gao ETSI Minas y Energía Universidad Politécnica de MadridMadrid 28003Spain Leibniz Institute of Ecological Urban and Regional Development(IOER) Dresden 01217Germany Department of Civil and Environmental Engineering Politecnico Di MilanoMilano 20133Italy School of Resources and Safety Engineering Central South UniversityChangsha 410083China Key Laboratory of the Three Gorges Reservoir Region’s Eco-Environment(Ministry of Education) College of Environment and EcologyChongqing UniversityChongqing 400045China

Concrete is the most commonly used construction ***,its production leads to high carbon dioxide(CO_(2))emissions and energy ***,developing waste-substitutable concrete components is *** the sustainability and greenness of concrete is the focus of this *** this regard,899 data points were collected from existing studies where cement,slag,fly ash,superplasticizer,coarse aggregate,and fine aggregate were considered potential influential *** complex relationship between influential factors and concrete compressive strength makes the prediction and estimation of compressive strength *** of the traditional compressive strength test,this study combines five novel metaheuristic algorithms with extreme gradient boosting(XGB)to predict the compressive strength of green concrete based on fly ash and blast furnace *** intelligent prediction models were assessed using the root mean square error(RMSE),coefficient of determination(R^(2)),mean absolute error(MAE),and variance accounted for(VAF).The results indicated that the squirrel search algorithm-extreme gradient boosting(SSA-XGB)yielded the best overall prediction performance with R^(2) values of 0.9930 and 0.9576,VAF values of 99.30 and 95.79,MAE values of 0.52 and 2.50,RMSE of 1.34 and 3.31 for the training and testing sets,*** remaining five prediction methods yield promising ***,the developed hybrid XGB model can be introduced as an accurate and fast technique for the performance prediction of green ***,the developed SSA-XGB considered the effects of all the input factors on the compressive *** ability of the model to predict the performance of concrete with unknown proportions can play a significant role in accelerating the development and application of sustainable concrete and furthering a sustainable economy.

关键词： sustainable concrete fly ash slay extreme gradient boosting technique squirrel search algorithm parametric analysis

A Distributed Design for Minimum 2-Connected m-Dominating Set in Bidirectional Wireless Ad-Hoc Networks

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Tsinghua Science and Technology 2012年第5期17卷 553-566页

作者： xiaofeng gao Bosheng Xu Jun Li Department of Computer Science and Engineering Shanghai Jiao Tong UniversityShanghai 200240China Department of Physics Shanghai Jiao Tong UniversityShanghai 200240China

Wireless ad-hoc network is widely used in many fields for its convenience and outstanding suitability. Because of the inherent lack of infrastructure and the nature of wireless channels, people select the k-Connected m-Dominating Set （（k,m）-CDS） in a network as a fault-tolerant virtual backbone to help the routing process, which will save the energy of non-dominators and improve the network performance significantly. Considering the economic cost and efficiency, we choose （2,m）-CDS as the object of this paper, which is helpful enough in practical applications and has a smaller size. We firstly study the existing algorithms for （k,m）- CDS and figure out the problems of these designs. Then we propose a new distributed algorithm named Dominating Set Based AIgorithm （DSBA） with three sub-routines： Dominating Set AIgorithm （DSA）, Connection Algorithm （CA）, and Connectivity Expansion Algorithm （CEA）. Instead of commonly used Maximal Independent Set （MIS）, we pick dominating set directly from the given graph, and then connect them by a two-step ring based connecting strategy to satisfy the 2-connectivity. We also provide the correctness and complexity analysis of DSBA. At last, we compare DSBA with the last construction Distributed Deterministic Algorithm （DDA） by several numerical experiments. The simulation results show that DSBA improves over 30 percent of the performance of DDA, proving that DSBA is more practical for real-world applications.

关键词： connected dominating set fault-tolerance distributed algorithm approximation

Ar-Ar geochronology of Late Mesozoic volcanic rocks from the Yanji area, NE China and tectonic implications

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Science China Earth Sciences 2007年第4期50卷 505-518页

作者： LI ChaoWen GUO Feng FAN WeiMing gao xiaofeng Key Laboratory of Marginal Sea Geology Guangzhou institute of GeochemistryChinese Academy of SciencesGuangzhou 510640China Graduate University of the Chinese Academy of Sciences Beijing 100039China

Ar-Ar dating results of late Mesozoic-Cenozoic volcanic rocks from the Yanji area, NE China provide a new volcano-sedimentary stratigraphic framework. The previously defined “Triassic-Jurassic” volcanic rocks (including those from Sanxianling, Tuntianying, Tianqiaoling and Jingouling Fms.) were erupted during 118―106 Ma, corresponding to Early Cretaceous. The new eruption age span is slightly younger than the main stage (130―120 Ma) of the extensive magmatism in the eastern Central Asian Orogenic Belt and its adjacent regions. Subduction-related adakites occurring in the previously defined Quanshuicun Fm. were extruded at ca. 55 Ma. Based on these new Ar-Ar ages, the late Mesozoic to Palaeocene volcano-sedimentary sequences is rebuilt as: Tuopangou Fm., Sanxianling/Tuntianying Fm. (118―115 Ma), Malugou/Tianqiaoling Fm. (K1), Huoshanyan/Jingouling Fm. (108―106 Ma), Changcai Fm. (K2), Quanshuicun Fm. (~55 Ma) and Dalazi Fm. Our results suggest that subduction of the Pa- laeo-Pacific Ocean beneath the East Asian continental margin occurred during 106 to 55 Ma, consistent with the paleomagnetic observations and magmatic records which indicated that the Izanagi-Farallon ridge subduction beneath the southwestern Japan took place during 95―65 Ma.

关键词： Ar-Ar geochronology Late Mesozoic volcanic rocks tectonic implications Yanji area

Molecular characterization and toxin quantification of Microcystis panniformis: A microcystin producer in Lake Taihu,China

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Journal of Environmental Sciences 2019年第2期31卷 359-367页

作者： Yilu Gu xiaofeng gao Yongguang Jiang Xin Peng Renhui Li Key laboratory of Algal Biology Institute of HydrobiologyChinese Academy of Sciences Department of Urban Engineering The University of Tokyo School of Environmental Studies China University of Geosciences

Microcystis panniformis is a bloom forming species with flat panniform-like colonies. This species was recently found in Lake Taihu, China. To specifically characterize M. panniformis based on isolated strains, morphological examination on colonial transition and genetic examination are needed. Three M. panniformis strains isolated from a water bloom sample in Lake Taihu were characterized by molecular analysis and toxin quantification. Phylogenetic analysis based on both 16S rRNA gene and internal transcribed spacer(ITS) between 16S and 23S rRNA genes were performed and compared to facilitate easy identification of the *** high similarities(98%–99%) were shown in 16S rDNA sequences between the strains of M. panniformis and those of other Microcystis species, whereas the similarities for ITS sequences were 88%–95%. In the phylogenetic tree based on the 16S rDNA sequences, the M. panniformis and M. aeruginosa strains were intermixed together with no clear division,whereas all of the M. panniformis strains were clustered together in a single clade based on the ITS sequences based phylogenyetic tree. The mcyE gene was detected in all three strains, and microcystin was determined by high-performance liquid chromatography. The molecular detection and toxin production of M. panniformis strains are of great significance for the environmental risk assessment of Microcystis blooms.

关键词： Microcystis panniformis Blooms ITS of 16S-23S rRNA mcyE Microcystin Taihu

A survey on barrier coverage with sensors

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Frontiers of Computer Science 2016年第6期10卷 968-984页

作者： Fan WU Yang GUI Zhibo WANG xiaofeng gao Guihai CHEN Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China School of Computer Wuhan University Wuhan 430072 China

For various applications, sensors are deployed to monitor belt regions to guarantee that every movement crossing a barrier of sensors will be detected in real-time with high accuracy and minimize the need for human support. The bartier coverage problem is introduced to model these requirements, and has been examined thoroughly in the past decades. In this survey, we state the problem definitions and systematically consider sensing models, design issues and challenges in barrier coverage problem. We also review representative algorithms in this survey. Furthermore, we provide discussions on some extensions and variants of barrier coverage problems.

关键词： sensor network barrier coverage

Uncovering the coupling effect with energy-related carbon emissions and human development variety in Chinese provinces

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Journal of Environmental Sciences 2024年第5期139卷 527-542页

作者： Liu Chen Yiqi Tan Gengpei Lv Weiguang Cai xiaofeng gao Rui Li School of Management Science and Real Estate Chongqing UniversityChongqing 400044China State Key Joint Laboratory of Environment Simulation and Pollution Control(SKLESPC) School of EnvironmentTsinghua UniversityBeijing 100084China Key Laboratory of the Three Gorges Reservoir Region’s Eco-Environment Ministry of EducationCollege of Environment and EcologyChongqing UniversityChongqing 400044China

Lessening energy-related carbon emissions has become a crucial measure to achieve Chinese carbon *** study is the first to construct a Difference in Carbon pressures-adjusted Human Development Index(DCHDI)model for the purpose of exploring the coupling effect between carbon emissions and human development variety from 2000 to 2019 in Chinese *** demonstrate the following.(1)The total energy-related carbon footprint of 30 provinces in China reached 10.2 billion tons in 2019,with an average annual growth rate of 6.93% over the past two decades;and the provinces with the highest carbon emissions per capita are InnerMongolia,Ningxia,and Shanxi.(2)At the provincial level,we observed that the Human Development Index(HDI),which includes life expectancy,education,and income,has been rising,while Beijing,Shanghai,and Tianjin entered the super-high HDI level before 2008.(3)The entire coupling effect of 30 Chinese provinces has been broadly fortified in the last 20 years,but the growth rate of DCHDI values in 2011-2019 has slowed down compared with that in 2000-2010;the clustering phenomenon demonstrated that this discovery is associated with historical peaks in total carbon emissions.(4)The co-ordination degree of carbon emissions per capita and HDI was verified,and 96% of the data points were found in the range of super high coupling coordination ***,this study provides the government with worthwhile guidance for decision-making and carbon reduction strategies for other countries struggling to advance human sustainable development.

关键词： Energy-related carbon emissions Human sustainable development DCHDI model Coupling effect Chinese provinces

Least squares twin support vector machine with asymmetric squared loss

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The Journal of China Universities of Posts and Telecommunications 2023年第1期30卷 1-16页

作者： Wu Qing Li Feiyan Zhang Hengchang Fan Jiulun gao xiaofeng School of Automation Xi'an University of Posts and TelecommunicationsXi'an 710121China School of Telecommunication and Information Engineering Xi'an University of Posts and TelecommunicationsXi'an 710121China

For classification problems,the traditional least squares twin support vector machine(LSTSVM)generates two nonparallel hyperplanes directly by solving two systems of linear equations instead of a pair of quadratic programming problems(QPPs),which makes LSTSVM much faster than the original *** the standard LSTSVM adopting quadratic loss measured by the minimal distance is sensitive to noise and unstable to *** overcome this problem,the expectile distance is taken into consideration to measure the margin between classes and LSTSVM with asymmetric squared loss(aLSTSVM)is *** to the original LSTSVM with the quadratic loss,the proposed aLSTSVM not only has comparable computational accuracy,but also performs good properties such as noise insensitivity,scatter minimization and re-sampling *** experiments on synthetic datasets,normally distributed clustered(NDC)datasets and University of California,Irvine(UCI)datasets with different noises confirm the great performance and validity of our proposed algorithm.

关键词： classification least squares twin support vector machine asymmetric loss noise insensitivity