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| 1 | A NON-PARAMETER BAYESIAN CLASSIFIER FOR FACE RECOGNITION显示文摘A non-parameter Bayesian classifier based on Kernel Density Estimation (KDE)is presented for face recognition, which can be regarded as a weighted Nearest Neighbor (NN)classifier in formation. The class conditional density is estimated by KDE and the bandwidthof the kernel function is estimated by Expectation Maximum (EM) algorithm. Two subspaceanalysis methods-linear Principal Component Analysis (PCA) and Kernel-based PCA (KPCA)are respectively used to extract features, and the proposed method is compared with ProbabilisticReasoning Models (PRM), Nearest Center (NC) and NN classifiers which are widely used in facerecognition systems. The experiments are performed on two benchmarks and the experimentalresults show that the KDE outperforms PRM, NC and NN classifiers. | Liu Qingshan Lu Hanqing Ma Songde (Nat. Lab of Pattern Recognition, Inst. of Automation, Chinese Academy of Sciences, Beijing 100080) | 2003 | Journal of Electronics(China)2003，20，5： | 9 |
| 2 | Field Modeling Method for Identifying Urban Sphere of Influence:A Case Study on Central China显示文摘With rapid development of urbanization and regional interaction and interdependence,regional urban agglomeration planning becomes more and more important in China,in order to promote integrated development of various cities with close interrelationship.However,it is still arguable academically on how to define the boundary or which cities to be included for the urban agglomeration of a region.This paper aims to shed lights on how to identify urban spheres of influence scientifically by introducing field modeling method and by practicing a case study on 168 cities in Central China.In our field modeling method,the influence intensities of cities were measured by a comprehensive index and urban spheres of influence were represented spatially by field intensity.Then,their classification and spatial distribution characteristics of study area in 2007 were identified and explored by using GIS and statistical methods.The result showed that:1) Wuhan is the absolute dominant city in Central China;2) the provincial capital cities dominate their own provinces and there are no other lower grade agglomeration centers;and 3) the basic types of organization form of urban sphere of influence are single-polar type,agglomeration type,close-related group type and loose-related group type. | DENG Yu LIU Shenghe WANG Li MA Hanqing WANG Jianghao | 2010 | Chinese Geographical Science2010，20，4： | 7 |
| 3 | Pan-sharpening:a fast variational fusion approach显示文摘A fast variational fusion model based on partial differential equations (PDEs) is presented for pansharpening. The functional framework consists of several energy terms. The gradient energy term is created by calculating the gradient vector field of the panchromatic image and the geometry of the pan is injected into the multi-spectral bands. The radiometric reduction energy term and the channel correlation energy term are defined to decrease the radiometric distortion and preserve the correlation of multi-spectral channels while enforcing the inter-bands coherence. Inspired by the shock-filtering model, an inverse diffusion term for image enhancement is put to PDEs which are deduced by minimizing the energy functional. In comparison with the state-of-the-art fusion approaches based on `a trous wavelet and non-sampled contourlet, our model can obtain the fused image with a high spatial or spectral quality by adjusting the weight coefficients of the energy terms. It can also achieve a rather good trade-off between the spatial resolution improvement and the spectral quality preserving. Our model's computational complexity for one time step is only O(N). | ZHOU ZeMing LI YuanXiang SHI HanQing MA Ning SHEN Ji | 2012 | Science China(Information Sciences)2012，55，3： | 2 |
| 4 | , Improving Kernel Fisher Discriminant Analysis for Face Recognition 显示文摘 | Qingshan Liu Hanqing Lu and Songde Ma | 2004 | IEEE Trans on Circuits and Sistems for Video Technlogy2004，14，1： | 1 |
| 5 | The flexible interrelation between AOX respiratory pathway and photosynthesis in rice leaves显示文摘 | Hanqing Feng Hongyu Li Xin Li Jiangong Duan Houguo Liang Dejuan Zhi Jun Ma | 2007 | Plant Physiology and Biochemistry2007，，3： | 1 |
| 6 | Improving kernel fisher discriminant analysis for face recognition 显示文摘 | Liu Qingshan Lu Hanqing Ma Songde | 2004 | IEEE Transactions on Cir- cuits and Systems for Video Technology2004，14，1： | 1 |
| 7 | Mosaic representations of videosequences based on slice image analysis显示文摘 | FENG SHAOLEI LU HANQING MA SONGDE | 2002 | Pattern Recognition Letters2002，23，： | 1 |
| 8 | Effect of 5 GPa Pressure Treatment on Nanoindentation Creep Property of TC6 Titanium Alloy显示文摘 | Ying Xiao Jinming Ma Zhaobin Li Hanqing Zhang Yan Chen | 2015 | 材料科学与工程(中英文A版)2015，5，1： | 1 |
| 9 | Improving kernel fisher discriminant analysis for face recognition 显示文摘 | LIU Qingshaa LU Hanqing MA Songde | 2004 | IEEE Transactions on Circuits and Systems for Video Technology2004，14，1： | 1 |
| 10 | Improving Kernel Fisher Discriminant Analysis for Face Recognition显示文摘 | Liu Qingshan Lu Hanqing Ma Songde | 2004 | IEEE Transactions on Circuits and Systems for Video Technology2004，14，1： | 1 |
| 11 | Identification of serum microRNAs for cardiovascular risk stratification in dyslipidemia subjects显示文摘 | Jia Wu Jiaxi Song Cheng Wang Dongmei Niu Hanqing Li Yuxiu Liu Lijuan Ma Ruijie Yu Xi Chen Ke Zen Qi Yang Chunni Zhang Chen-Yu Zhang Junjun Wang | 2014 | International Journal of Cardiology2014，，： | 1 |
| 12 | Evaluation of P 1 adhesin epitopes for the serodiagnosis of M ycoplasma pneumoniae infections显示文摘 | Guanhua Xue Ling Cao Luoping Wang Hanqing Zhao Yanling Feng Lijuan Ma Hongmei Sun | 2013 | FEMS Microbiol Lett2013，，： | 1 |
| 13 | Error analysis of CCD-based point source centroid computation under the background light显示文摘 | Ma Xiaoyu Rao Changhui Zheng Hanqing | 2009 | Optics Express2009，17，10： | 1 |
| 14 | Error analysis of CCD-based point source centroid computation under the background light显示文摘 | Xiaoyu Ma Changhui Rao Hanqing Zheng | 2009 | Opt Express2009，17，10： | 1 |
| 15 | Robust Quantzation Index Modulation VIA Adaptive Watermarking显示文摘In this paper,we suggest an adaptive watermarkingmethod to improve both transparence and robustnessof quantization index modulation(QIM)scheme.Instead of a fixed quantization step-size,we apply astep-size adapted to image content in each 8×8block to make a balance of robust extraction andtransparent embedding.The modified step-size isdetermined by contrast masking thresholds ofWatson’s perceptual model.From a normalizedcrossed-correlation value between the original watermarkand the detected watermark,we could observethat our method is robust to attacks of additivewhite Gaussian noise(AWGN),Salt and Peppernoise and Joint Photographic Experts Group(JPEG)compression than the original QIM.By taking intoaccount the contrast insensitivity and visible thresholdsof human visual system,the suggested improvementachieves a maximum embedding strength andan appropriate quantization step-size which is consistentwith local values of a host signal. | Wang, Guoxi Ma, Lihong Yu, Decong Cai, Kang Lu, Hanqing | 2008 | China Communications2008，5，2： | 0 |
| 16 | Quantum light source devices of In(Ga)As semiconductor self-assembled quantum dots显示文摘A brief introduction of semiconductor self-assembled quantum dots (QDs) applied in single-photon sources is given. Single QDs in confined quantum optical microcavity systems are reviewed along with their optical properties and coupling characteristics. Subsequently, the recent progresses in In(Ga)As QDs systems are summarized including the preparation of quantum light sources, multiple methods for embedding single QDs into different microcavities and the scalability of single-photon emitting wavelength. Particularly, several In(Ga)As QD single-photon devices are surveyed including In(Ga)As QDs coupling with nanowires, InAs QDs coupling with distributed Bragg reflection microcavity and the In(Ga)As QDs coupling with micropillar microcavities. Furthermore, applications in the field of single QDs technology are illustrated, such as the entangled photon emission by spontaneous parametric down conversion, the single-photon quantum storage, the chip preparation of single-photon sources as well as the single-photon resonance-fluorescence measurements. | Xiaowu He Yifeng Song Ying Yu Ben Ma Zesheng Chen Xiangjun Shang Haiqiao Ni Baoquan Sun Xiuming Dou Hao Chen Hongyue Hao Tongtong Qi Shushan Huang Hanqing Liu Xiangbin Su Xinliang Su Yujun Shi Zhichuan Niu | 2019 | Journal of Semiconductors2019，40，7： | 0 |
| 17 | Terrestrial carbon cycle model-data fusion:Progress and challenges显示文摘The terrestrial carbon cycle is an important component of global biogeochemical cycling and is closely related to human well-being and sustainable development.However,large uncertainties exist in carbon cycle simulations and observations.Model-data fusion is a powerful technique that combines models and observational data to minimize the uncertainties in terrestrial carbon cycle estimation.In this paper,we comprehensively overview the sources and characteristics of the uncertainties in terrestrial carbon cycle models and observations.We present the mathematical principles of two model-data fusion methods,i.e.,data assimilation and parameter estimation,both of which essentially achieve the optimal fusion of a model with observational data while considering the respective errors in the model and in the observations.Based upon reviewing the progress in carbon cycle models and observation techniques in recent years,we have highlighted the major challenges in terrestrial carbon cycle model-data fusion research,such as the“equifinality”of models,the identifiability of model parameters,the estimation of representativeness errors in surface fluxes and remote sensing observations,the potential role of the posterior probability distribution of parameters obtained from sensitivity analysis in determining the error covariance matrixes of the models,and opportunities that emerge by assimilating new remote sensing observations,such as solar-induced chlorophyll fluorescence.It is also noted that the synthesis of multisource observations into a coherent carbon data assimilation system is by no means an easy task,yet a breakthrough in this bottleneck is a prerequisite for the development of a new generation of global carbon data assimilation systems.This article also highlights the importance of carbon cycle data assimilation systems to generate reliable and physically consistent terrestrial carbon cycle reanalysis data products with high spatial resolution and longterm time series.These products are critical to the accurate estimation of carbon cycles at the global and regional scales and will help future carbon management strategies meet the goals of carbon neutrality. | Xin LI Hanqing MA Youhua RAN Xufeng WANG Gaofeng ZHU Feng LIU Honglin HE Zhen ZHANG Chunlin HUANG | 2021 | Science China Earth Sciences2021，64，10： | 0 |
| 18 | End-cloud collaboration method enables accurate state of health and remaining useful life online estimation in lithium-ion batteries显示文摘Though the lithium-ion battery is universally applied,the reliability of lithium-ion batteries remains a challenge due to various physicochemical reactions,electrode material degradation,and even thermal runaway.Accurate estimation and prediction of battery health conditions are crucial for battery safety management.In this paper,an end-cloud collaboration method is proposed to approach the track of battery degradation process,integrating end-side empirical model with cloud-side data-driven model.Based on ensemble learning methods,the data-driven model is constructed by three base models to obtain cloud-side highly accurate results.The double exponential decay model is utilized as an empirical model to output highly real-time prediction results.With Kalman filter,the prediction results of end-side empirical model can be periodically updated by highly accurate results of cloud-side data-driven model to obtain highly accurate and real-time results.Subsequently,the whole framework can give an accurate prediction and tracking of battery degradation,with the mean absolute error maintained below 2%.And the execution time on the end side can reach 261μs.The proposed end-cloud collaboration method has the potential to approach highly accurate and highly real-time estimation for battery health conditions during battery full life cycle in architecture of cyber hierarchy and interactional network. | Bin Ma Lisheng Zhang Hanqing Yu Bosong Zou Wentao Wang Cheng Zhang Shichun Yang Xinhua Liu | 2023 | Journal of Energy Chemistry2023，，7： | 0 |
| 19 | Application of deep learning for informatics aided design of electrode materials in metal-ion batteries显示文摘To develop emerging electrode materials and improve the performances of batteries,the machine learning techniques can provide insights to discover,design and develop battery new materials in high-throughput way.In this paper,two deep learning models are developed and trained with two feature groups extracted from the Materials Project datasets to predict the battery electrochemical performances including average voltage,specific capacity and specific energy.The deep learning models are trained with the multilayer perceptron as the core.The Bayesian optimization and Monte Carlo methods are applied to improve the prediction accuracy of models.Based on 10 types of ion batteries,the correlation coefficients are maintained above 0.9 compared to DFT calculation results and the mean absolute error of the prediction results for voltages of two models can reach 0.41 V and 0.20 V,respectively.The electrochemical performance prediction times for the two trained models on thousands of batteries are only 72.9 ms and 75.7 ms.Besides,the two deep learning models are applied to approach the screening of emerging electrode materials for sodium-ion and potassium-ion batteries.This work can contribute to a high-throughput computational method to accelerate the rational and fast materials discovery and design. | Bin Ma Lisheng Zhang Wentao Wang Hanqing Yu Xianbin Yang Siyan Chen Huizhi Wang Xinhua Liu | 2024 | Green Energy & Environment2024，9，5： | 0 |
| 20 | Epidemiological Characteristics of Maize Rough Dwarf Disease in Huang-Huai-Hai Plain显示文摘Maize rough dwarf disease is a common epidemic disease in large areas.Its epidemic and occurrence mechanism is a complex process.In this paper,the epidemiological characteristics and influencing factors of maize rough dwarf disease in Huang-Huai-Hai plain were elaborated based on the research results of maize rough dwarf disease at home and abroad for many years.The epidemic of maize rough dwarf disease is affected by many factors,such as the occurrence and virus carrying rate of the first generation small brown planthopper,accumulation of virus sources on gramineous crops and weed hosts,maize variety resistance,maize sowing date,maize growth period,crop layout,tillage system,climate and ecological environment.The key factors causing the outbreak and epidemic of maize rough dwarf disease are the planting of maize susceptible varieties,the meeting of maize seedling stage and the peak period of adult spread of the first generation of small brown planthopper. | Shengji WANG Bin WU Shanshan JIANG Mei ZHANG Liping MA Tinglin SUN Hanqing CUI | 2019 | Agricultural Biotechnology2019，8，4： | 0 |
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