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Assessment of temporal and spatial variations in water quality using multivariate statistical methods

Xue LI,Pengjing LI,Dong WANG,Yuqiu WANG

Frontiers of Environmental Science & Engineering 2014, Volume 8, Issue 6,   Pages 895-904 doi: 10.1007/s11783-014-0736-z

Abstract: temporal and spatial variations of water quality data sets for the Xin'anjiang River through the use of multivariatestatistical techniques, including cluster analysis (CA), discriminant analysis (DA), correlation analysis, and principal component analysis (PCA).electricity conductivity, total nitrogen, chemical oxygen demand and total phosphorus) for spatial variation analysis

Keywords： Xin'anjiang River     multivariable statistical analysis     temporal variation     spatial variation     water quality    

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Modeling of unconfined compressive strength of soil-RAP blend stabilized with Portland cement using multivariate

Ali Reza GHANIZADEH, Morteza RAHROVAN

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 4,   Pages 787-799 doi: 10.1007/s11709-019-0516-8

Abstract: the unconfined compressive strength (UCS) of soil-RAP blend stabilized with Portland cement based on multivariateSensitivity analysis of the proposed model showed that the cement, optimum moisture content, and percent

Keywords： full-depth reclamation     soil-reclaimed asphalt pavement blend     Portland cement     unconfined compressive strength     multivariate    

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Uncertainty Quantification for Multivariate Eco-Hydrological Risk in the Xiangxi River within the Three Article

Yurui Fan,Guohe Huang,Yin Zhang,Yongping Li

Engineering 2018, Volume 4, Issue 5,   Pages 617-626 doi: 10.1016/j.eng.2018.06.006

Abstract: ">This study develops a multivariateeco-hydrological risk-assessment framework based on the multivariate copula method in order to evaluateThe probabilistic features of bivariate and multivariate hydrological risk are also characterized.

Keywords： Flood risk     Copula     Multivariate flood frequency analysis     Distribution     Markov chain Monte Carlo    

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Performance evaluation of circulating fluidized bed incineration of municipal solid waste by multivariate

Hua Tao, Pinjing He, Yi Zhang, Wenjie Sun

Frontiers of Environmental Science & Engineering 2017, Volume 11, Issue 6, doi: 10.1007/s11783-017-0945-3

Abstract: analyzed to assess the overall performance of CFB incineration by applying the Mahalanobis distance as a multivariate

Keywords： Municipal solid waste     Incineration     Circulating fluidized bed     Load change     Multivariate outlier detection    

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Image-based fall detection and classification of a user with a walking support system

Sajjad TAGHVAEI, Kazuhiro KOSUGE

Frontiers of Mechanical Engineering 2018, Volume 13, Issue 3,   Pages 427-441 doi: 10.1007/s11465-017-0465-7

Abstract:

The classification of visual human action is important in the development of systems that interact with humans. This study investigates an image-based classification of the human state while using a walking support system to improve the safety and dependability of these systems. We categorize the possible human behavior while utilizing a walker robot into eight states (i.e., sitting, standing, walking, and five falling types), and propose two different methods, namely, normal distribution and hidden Markov models (HMMs), to detect and recognize these states. The visual feature for the state classification is the centroid position of the upper body, which is extracted from the user’s depth images. The first method shows that the centroid position follows a normal distribution while walking, which can be adopted to detect any non-walking state. The second method implements HMMs to detect and recognize these states. We then measure and compare the performance of both methods. The classification results are employed to control the motion of a passive-type walker (called “RT Walker”) by activating its brakes in non-walking states. Thus, the system can be used for sit/stand support and fall prevention. The experiments are performed with four subjects, including an experienced physiotherapist. Results show that the algorithm can be adapted to the new user’s motion pattern within 40 s, with a fall detection rate of 96.25% and state classification rate of 81.0%. The proposed method can be implemented to other abnormality detection/classification applications that employ depth image-sensing devices.

Keywords： fall detection     walking support     hidden Markov model     multivariate analysis    

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Spatio-temporal variations of water quality in Yuqiao Reservoir Basin, North China

Yuan XU,Ruqin XIE,Yuqiu WANG,Jian SHA

Frontiers of Environmental Science & Engineering 2015, Volume 9, Issue 4,   Pages 649-664 doi: 10.1007/s11783-014-0702-9

Abstract: Fuzzy comprehensive assessment and multivariate statistical techniques including cluster analysis, discriminantanalysis, principal component analysis, and factor analysis were applied to analyze the water qualityBesides, hierarchical cluster analysis divided 7 monitoring sites into two groups (Group A and B), andpH and NO -N were identified as significant variables affecting temporal variations by discriminant analysisFactor analysis identified four latent pollution sources for water quality variations: nutrient pollution

Keywords： Fuzzy comprehensive assessment     multivariate statistical analysis     water quality    

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Field investigation of intelligent compaction for hot mix asphalt resurfacing

Wei HU,Xiang SHU,Baoshan HUANG,Mark WOODS

Frontiers of Structural and Civil Engineering 2017, Volume 11, Issue 1,   Pages 47-55 doi: 10.1007/s11709-016-0362-x

Abstract: In the second project, a multivariate analysis was performed between in situ tests and IC data.

Keywords： intelligent compaction     compaction meter value (CMV)     semivariogram     multivariate analysis    

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Reasonable Scale of Megacity Central Area Based on Multivariate Data and a Traffic Perspective

Lu Huapu, Bai Zhuotong,Wu Zhouhao, Fu Zhihuan

Strategic Study of CAE 2022, Volume 24, Issue 6,   Pages 146-153 doi: 10.15302/J-SSCAE-2022.06.013

Abstract: division, we identified the current central urban areas of ten cities in China using big data analysisFinally, demonstration results were presented through quantitative analysis.

Keywords： reasonable scale     multivariate data     central urban area     megacity     happiness    

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An intuitive general rank-based correlation coefficient Research Articles

Divya PANDOVE, Shivani GOEL, Rinkle RANI

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 6,   Pages 699-711 doi: 10.1631/FITEE.1601549

Abstract: Correlation analysis is an effective mechanism for studying patterns in data and making predictions.

Keywords： General rank-based correlation coefficient     Multivariate analysis     Predictive metric     Spearman’s rank correlation    

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The Lesson From Hurricane Katrina 2005——Risk Analysis for Coastal, Offshore, and Hydraulic Engineering

Liu Defu,Pang Liang,Xie Botao,Shi Hongda,Lu Yijun

Strategic Study of CAE 2007, Volume 9, Issue 10,   Pages 24-29

Abstract:  Based on the lesson from Hurricane Katrina,  this paper involved the uncertainty analysisand multivariate joint probability theory to the risk assessment for coastal,  offshore and hydraulic

Keywords： Hurricane Katrina     compound extreme value distribution     multivariate compound extreme value distribution     uncertainty analysis     coastal     offshore     hydraulic and disaster prevention engineering     risk analysis    

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Expanding the Scope of Multivariate Regression Approaches in Cross-Omics Research Article

Xiaoxi Hu, Yue Ma, Yakun Xu, Peiyao Zhao, Jun Wang

Engineering 2021, Volume 7, Issue 12,   Pages 1725-1731 doi: 10.1016/j.eng.2020.05.028

Abstract: in the amount of high-dimensional data and thus have increased the demand for proper and efficient multivariateNumerous traditional multivariate approaches such as principal component analysis have been used broadlyin various research areas, including investment analysis, image identification, and population geneticstructure analysis.method extensions provide valuable guidelines for future omics research, especially with respect to multivariate

Keywords： Multivariate regression methods     Reduced rank regression     Sparsity     Dimensionality reduction     Variable    

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Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning and unary classification

Frontiers in Energy 2023, Volume 17, Issue 4,   Pages 527-544 doi: 10.1007/s11708-023-0880-x

Abstract: Intelligent power systems can improve operational efficiency by installing a large number of sensors. Data-based methods of supervised learning have gained popularity because of available Big Data and computing resources. However, the common paradigm of the loss function in supervised learning requires large amounts of labeled data and cannot process unlabeled data. The scarcity of fault data and a large amount of normal data in practical use pose great challenges to fault detection algorithms. Moreover, sensor data faults in power systems are dynamically changing and pose another challenge. Therefore, a fault detection method based on self-supervised feature learning was proposed to address the above two challenges. First, self-supervised learning was employed to extract features under various working conditions only using large amounts of normal data. The self-supervised representation learning uses a sequence-based Triplet Loss. The extracted features of large amounts of normal data are then fed into a unary classifier. The proposed method is validated on exhaust gas temperatures (EGTs) of a real-world 9F gas turbine with sudden, progressive, and hybrid faults. A comprehensive comparison study was also conducted with various feature extractors and unary classifiers. The results show that the proposed method can achieve a relatively high recall for all kinds of typical faults. The model can detect progressive faults very quickly and achieve improved results for comparison without feature extractors in terms of F1 score.

Keywords： fault detection     unary classification     self-supervised representation learning     multivariate nonlinear    

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Interactive image segmentation with a regression based ensemble learning paradigm Article

Jin ZHANG, Zhao-hui TANG, Wei-hua GUI, Qing CHEN, Jin-ping LIU

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 7,   Pages 1002-1020 doi: 10.1631/FITEE.1601401

Abstract: First, two spline regressors with a complementary nature are constructed based on multivariate adaptive

Keywords： Interactive image segmentation     Multivariate adaptive regression splines (MARS)     Ensemble learning     Thin-plate    

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15th International Congress for Stereology and Image Analysis 第十五届国际体视学与图像分析学术会议

Conference Date: 27 May 2019

Conference Place: 丹麦/奥胡斯

Administered by: 国际体视学与图像分析学会(ISSIA)

Title Author Date Type Operation

Assessment of temporal and spatial variations in water quality using multivariate statistical methods

Xue LI,Pengjing LI,Dong WANG,Yuqiu WANG

Journal Article

Modeling of unconfined compressive strength of soil-RAP blend stabilized with Portland cement using multivariate

Ali Reza GHANIZADEH, Morteza RAHROVAN

Journal Article

Uncertainty Quantification for Multivariate Eco-Hydrological Risk in the Xiangxi River within the Three

Yurui Fan,Guohe Huang,Yin Zhang,Yongping Li

Journal Article

Performance evaluation of circulating fluidized bed incineration of municipal solid waste by multivariate

Hua Tao, Pinjing He, Yi Zhang, Wenjie Sun

Journal Article

Image-based fall detection and classification of a user with a walking support system

Sajjad TAGHVAEI, Kazuhiro KOSUGE

Journal Article

Spatio-temporal variations of water quality in Yuqiao Reservoir Basin, North China

Yuan XU,Ruqin XIE,Yuqiu WANG,Jian SHA

Journal Article

Field investigation of intelligent compaction for hot mix asphalt resurfacing

Wei HU,Xiang SHU,Baoshan HUANG,Mark WOODS

Journal Article

Reasonable Scale of Megacity Central Area Based on Multivariate Data and a Traffic Perspective

Lu Huapu, Bai Zhuotong,Wu Zhouhao, Fu Zhihuan

Journal Article

An intuitive general rank-based correlation coefficient

Divya PANDOVE, Shivani GOEL, Rinkle RANI

Journal Article

The Lesson From Hurricane Katrina 2005——Risk Analysis for Coastal, Offshore, and Hydraulic Engineering

Liu Defu,Pang Liang,Xie Botao,Shi Hongda,Lu Yijun

Journal Article

Expanding the Scope of Multivariate Regression Approaches in Cross-Omics Research

Xiaoxi Hu, Yue Ma, Yakun Xu, Peiyao Zhao, Jun Wang

Journal Article

Unknown fault detection for EGT multi-temperature signals based on self-supervised feature learning and unary classification

Journal Article

Interactive image segmentation with a regression based ensemble learning paradigm

Jin ZHANG, Zhao-hui TANG, Wei-hua GUI, Qing CHEN, Jin-ping LIU

Journal Article

15th International Congress for Stereology and Image Analysis 第十五届国际体视学与图像分析学术会议

27 May 2019

Conference Information

黄幼麟: Dynamic Consumer Preferences for Electric Vehicles — A Longitudinal Analysis (2020-7-12)

10 Jun 2022

Conference Videos