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Application of pca and HCA to the Structure-activity Relationship(SAR) Study of Fluoroquinolones

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Chinese Journal of Structural Chemistry 2006年第11期25卷 1351-1358页

作者： LI Xiao-Hong ZHANG Rui-Zhou CHENG Xin-Lu YANG Xiang-Dong Institute of Atom and Molecular Physics Sichuan University Chengdu 610065 China Xinxiang Teacher＇s College Xinxiang 453000 China

Density functional theory （DFT） was used to calculate a set of molecular descri ptors （properties） for 14 fluoroquinolones with *** activity. Principal component analysis （pca） and hierarchical cluster analysis （HCA） were employed in order to reduce dimensionality and investigate which subset of variables should be more effective for classifying fluoroquinolones according to their *** activity degree. The pca shows that the variables of ELUMO, AEHL, μ, Q2, Q3, Q5, Q6, QB, LogP, MR and MP are responsible for the separation between compounds with higher and lower *** activities. The HCA results are similar to those obtained with pca. By using the chemometric results, 4 synthetic compounds were analyzed through pca and HCA, and 2 of them are proposed as active molecules against ***, which is consistent with the results of clinic experiments. The methodologies of pca and HCA provide a reliable rule for classifying new fluoroquinolones with *** activity.

关键词： structure-activity relationship DFT pca HCA

sEMG-Based Lower Limb Motion Prediction Using CNN-LSTM with Improved pca Optimization Algorithm

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Journal of Bionic Engineering 2023年第2期20卷 612-627页

作者： Meng Zhu Xiaorong Guan Zhong Li Long He Zheng Wang Keshu Cai School of Mechanical Engineering Nanjing University of Science and TechnologyNo.200XiaolingweiNanjing CityJiangsu ProvinceChina Department of Rehabilitation Medicine The First Affiliated Hospital of Nanjing Medical University300 Guangzhou RoadNanjing CityJiangsu ProvinceChina

In recent years,sEMG(surface electromyography)signals have been increasingly used to operate wearable *** development of mechanical lower limbs or exoskeletons controlled by the nervous system requires greater accuracy in recognizing lower limb *** is less research on devices to assist the human body in uphill ***,developing controllers that can accurately predict and control human upward movements in real-time requires the employment of appropriate signal pre-processing methods and prediction *** this purpose,this paper investigates the effects of various sEMG pre-processing methods and algorithms on the prediction *** investigation involved ten subjects(five males and five females)with normal knee *** relevant data of the subjects were collected on a constructed *** obtain feature values that reflect the gait characteristics,an improved pca algorithm based on the kernel method is proposed for dimensionality reduction to remove redundant ***,a new model(CNN+LSTM)was proposed to predict the knee joint *** approaches were utilized to validate the superiority of the improved pca method and CNN-LSTM *** feasibility of the method was verified by analyzing the gait prediction results of different ***,the prediction time of the method was 25 ms,and the prediction error was 1.34±0.25 *** comparing with traditional machine learning methods such as BP(backpropagation)neural network,RF(random forest),and SVR(support vector machine),the improved pca algorithm processed data performed the best in terms of convergence time and prediction accuracy in CNN-LSTM *** experimental results demonstrate that the proposed method(improved pca+CNN-LSTM)effectively recognizes lower limb activity from sEMG *** the same data input,the EMG signal processed using the improved pca method performed better in terms of prediction *** is the first step toward myoelectri

关键词： CNN LSTM Exoskeleton sEMG Knee trajectory pca Bionic robot

Variational pca fusion for Pan-sharpening very high resolution imagery

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Science China(Information Sciences) 2014年第11期57卷 100-109页

作者： ZHOU ZeMing MA Ning LI YuanXiang YANG PingL ZHANG Peng LI YunYing Institute of Meteorology and Oceanography PLA University of Science and Technology School of Aeronautics Shanghai JiaoTong University

The Pan-sharpening approach based on principle component analysis(pca) is affected by severe spectral distortion. To address this problem, a new pan-sharpening model based on pca and variational technique is proposed to construct the substitute image of the first principal component(PC1). The energy functional consists of three terms. The first term injects PC1 with the geometric structure of the panchromatic(Pan) image. The second term preserves the spectral pattern of the multi-spectral image in the merged *** the third term guarantees the smoothness of the functional optimization solution. The fusion result is given by the minimum of the energy functional, which is computed with the gradient descend flow. The experiments on QuickBird and IKONOS datasets validate the effectiveness of the proposed model. Compared with the stateof-the-art pan-sharpening approaches, this model exhibits a better trade-off between improving spatial quality and preserving spectral signature of the MS image.

关键词： pca variational pca fusion remote sensing image pan-sharpening gradient descend flow

Distribution and assessment of hydrogeochemical processes of F-rich groundwater using pca model:a case study in the Yuncheng Basin,China

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Acta Geochimica 2020年第2期39卷 216-225页

作者： Tao Liu Xubo Gao Xiaobo Zhang Chengcheng Li School of Environmental Studies and State Key Laboratory of Biogeology and Environmental Geology China University of GeosciencesWuhan 430074HubeiPeople's Republic of China Science and Technology Promotion Centre of Water Resources of Zhejiang Province HangzhouPeople's Republic of China

Hydrogeochemistry and factor analysis were conducted together to assess the distribution and the major geochemical processes in fluoride-contaminated shallow groundwater in the Yuncheng ***,fluoride concentration was low(<1.5 mg/L)in the southern piedmont plain,medium(<4 mg/L)in the central basin,and high(up to 14.1 mg/L)in Kaolao lowland areas in shallow aquifers.A three-factor principal component analysis model explained over 75.1%of the total *** weathering leaching and evapotranspiration were recognized as the first primary hydrochemical processes response for the groundwater chemistry and explained the largest portion(42.1%)of the total *** two reflects the negative influence of human activities,with a positive loading of NO3^-and HCO3^-,and negative loading of well ***-bearing mineral dissolution and alkaline condition was ranked as the third factors responding for groundwater chemistry and explained 11.2%of the total variance.

关键词： Fluoride Groundwater chemistry pca model Hydrogeochemical processes Yuncheng Basin

Heart Disease Classification Using Multiple K-pca and Hybrid Deep Learning Approach

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Computer Systems Science & Engineering 2022年第6期41卷 1273-1289页

作者： S.Kusuma Dr.Jothi K.R School of Computer Science and Engineering Vellore Institute of TechnologyVellore632014India

One of the severe health problems and the most common types of heartdisease (HD) is Coronary heart disease (CHD). Due to the lack of a healthy lifestyle, HD would cause frequent mortality worldwide. If the heart attack occurswithout any symptoms, it cannot be cured by an intelligent detection *** effective diagnosis and detection of CHD should prevent human ***, intelligent systems employ clinical-based decision support approachesto assist physicians in providing another option for diagnosing and detecting *** paper aims to introduce a heart disease prediction model including phaseslike (i) Feature extraction, (ii) Feature selection, and (iii) Classification. At first,the feature extraction process is carried out, where the features like a time-domainindex, frequency-domain index, geometrical domain features, nonlinear features,WT features, signal energy, skewness, entropy, kurtosis features are extractedfrom the input ECG signal. The curse of dimensionality becomes a severe *** paper provides the solution for this issue by introducing a new ModifiedPrincipal Component Analysis known as Multiple Kernel-based pca for dimensionality reduction. Furthermore, the dimensionally reduced feature set is thensubjected to a classification process, where the hybrid classifier combining bothRecurrent Neural Network (RNN) and Restricted Boltzmann Machine (RBM)is used. At last, the performance analysis of the adopted scheme is compared overother existing schemes in terms of specific measures.

关键词： Heart disease prediction ecg recurrent neural network pca restricted boltzmann machine

Performance evaluation of BPM system in SSRF using pca method

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Chinese Physics C 2014年第7期38卷 112-116页

作者：陈之初冷用斌阎映炳袁任贤赖龙伟 Shanghai Institute of Applied Physics Chinese Academy of Sciences Shanghai Synchrotron Radiation Facility Chinese Academy of Sciences

The beam position monitor （BPM） system is of most importance in a light source. The capability of the BPM depends on the resolution of the system. The traditional standard deviation on the raw data method merely gives the upper limit of the resolution. Principal component analysis （pca） had been introduced in the accelerator physics and it could be used to get rid of the actual signals. Beam related information was extracted before the evaluation of the BPM performance. A series of studies had been made in the Shanghai Synchrotron Radiation Facility （SSRF） and pca was proved to be an effective and robust method in the performance evaluations of our BPM system.

关键词： pca MIA SVD storage ring SSRF

Facial expression feature extraction using hybrid pca and LBP

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The Journal of China Universities of Posts and Telecommunications 2013年第2期20卷 120-124页

作者： LUO Yuan WU Cai-ming ZHANG Yi School of Optoelectronic Engineering Chongqing University of Posts and Telecommunications School of Automation Chongqing University of Posts and Telecommunications

In order to recognize facial expression accurately, the paper proposed a hybrid method of principal component analysis （pca） and local binary pattern （LBP）. Firstly, the method of eight eyes segmentation was introduced to extract the effective area of facial expression image, which can reduce some useless information to subsequent feature extraction. Then pca extracted the global grayscale feature of the whole facial expression image and reduced the data size at the same time. And LBP extracted local neighbor texture feature of the mouth area, which contributes most to facial expression recognition. Fusing the global and local feature will be more effective for facial expression recognition. Finally, support vector machine （SVM） used the fusion feature to complete facial expression recognition. Experiment results show that, the method proposed in this paper can classify different expressions more effectively and can get higher recognition rate than the traditional recognition methods.

关键词： facial expression recognition pca LBP eight eyes segmentation SVM

Photon discrimination simulation with the pca method

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Chinese Physics C 2010年第10期34卷 1632-1635页

作者：周静刘志毅孟秋英周书华 China Institute of Atomic Energy

The shower shape of n, n^-, p, p^-, K^＋, π^＋ and photons, generated by JPCIAE code for 5.5 TeV/A ^208pb＋^208pb collisions, incident on the ALICE photon spectrometer （PHOS）, is analyzed with the principal component analysis （pca） method. The efficiency dependence of purity for the photon discrimination is simulated for the deposited energy ranges 0.5-2 GeV, 2-10 GeV, 10-50 GeV and 50-100 GeV. The result shows that in the energy range of 0.5 to 100 GeV, the efficiency of the photon identification can reach 90% with purity of 90%.

关键词： photon discrimination pca ALICE PHOS

pca-SDG based Fault Diagnosis on CAPL Furnace Temperature System

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PCA-SDG based Fault Diagnosis on CAPL Furnace Temperature Sy...