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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: Combining with point of interest data of multi-type land use and the geographic information systemdata for street administrative division, we identified the current central urban areas of ten citiesin China using big data analysis and the clustering method; their current traffic efficiencieswere then evaluated based on path navigation data via web maps and mobile phone signaling data verification

Keywords： reasonable scale     multivariate data     central urban area     megacity     happiness    

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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 multivariateFor training and testing of MARS model, total of 64 experimental UCS data were employed.

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

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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: The data for monthly average flue gas emission of particles, CO, NO , SO and HCl were collected overThe data were analyzed to assess the overall performance of CFB incineration by applying the Mahalanobisdistance as a multivariate outlier detection method.

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

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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: This study evaluated the temporal and spatial variations of water quality data sets for the Xin'anjiangRiver through the use of multivariate statistical techniques, including cluster analysis (CA), discriminant

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

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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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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: technological advancements and developments have led to a dramatic increase in the amount of high-dimensional dataand thus have increased the demand for proper and efficient multivariate regression methods.Numerous traditional multivariate approaches such as principal component analysis have been used broadlythe field of microbiome research, we applied our chosen method to real population-level microbiome datamethod 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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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, discriminantIn this paper, we considered data for 14 water quality parameters collected during 1990–2004 at 7 water

Keywords： Fuzzy comprehensive assessment     multivariate statistical analysis     water quality    

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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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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: derived from it were compared with univariate statistical parameters for the Compaction Meter Value (CMV) dataIn the second project, a multivariate analysis was performed between in situ tests and IC data.The possibility of combining various IC data to predict the asphalt layer density and improve the current

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

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A review of systematic evaluation and improvement in the big data environment

Feng YANG, Manman WANG

Frontiers of Engineering Management 2020, Volume 7, Issue 1,   Pages 27-46 doi: 10.1007/s42524-020-0092-6

Abstract: The era of big data brings unprecedented opportunities and challenges to management research.Exploring the applicable evaluation methods in the big data environment has become an important subjectpaper is to provide an overview and discussion of systematic evaluation and improvement in the big dataWe first review the evaluation methods based on the main analytic techniques of big data such as dataFocused on the characteristics of big data (association feature, data loss, data noise, and visualization

Keywords： big data     evaluation methods     systematic improvement     big data analytic techniques     data mining    

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Data quality assessment for studies investigating microplastics and nanoplastics in food products: Arecurrent data reliable?

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 8, doi: 10.1007/s11783-023-1694-0

Abstract:

● Data quality assessment criteria for MP/NPs in food products were

Keywords： Microplastic     Nanoplastic     Food products     Data quality     Human health risk    

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Blockchain application in healthcare service mode based on Health Data Bank

Jianxia GONG, Lindu ZHAO

Frontiers of Engineering Management 2020, Volume 7, Issue 4,   Pages 605-614 doi: 10.1007/s42524-020-0138-9

Abstract: To guarantee data privacy and data security as well as to harness the value of health data, the conceptof Health Data Bank (HDB) is proposed.In this study, HDB is defined as an integrated health data service institution, which bears no “ownership” of health data and operates health data under the principal–agent model.; (2) data rights; (3) health data supervision; (4) and willingness to share health data.

Keywords： Health Data Bank     blockchain     data assets     smart contract     incentive mechanism    

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Challenges to Engineering Management in the Big Data Era

Yong Shi

Frontiers of Engineering Management 2015, Volume 2, Issue 3,   Pages 293-303 doi: 10.15302/J-FEM-2015042

Abstract: as the Big Data applications.First, it outlines the definitions of big data, data science and intelligent knowledge and the historyof big data.Second, the paper reviews the academic activities about big data in China.and non-structured data into “structured format” and explores the relationship of data heterogeneity

Keywords： big data     data science     intelligent knowledge     engineering management     real-life applications    

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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: Data-based methods of supervised learning have gained popularity because of available Big Data and computingand cannot process unlabeled data.The scarcity of fault data and a large amount of normal data in practical use pose great challenges toMoreover, sensor data faults in power systems are dynamically changing and pose another challenge.The extracted features of large amounts of normal data are then fed into a unary classifier.

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

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Intelligent data analytics is here to change engineering management

Jonathan Jingsheng SHI, Saixing ZENG, Xiaohua MENG

Frontiers of Engineering Management 2017, Volume 4, Issue 1,   Pages 41-48 doi: 10.15302/J-FEM-2017003

Abstract: Data enabling technology plays an important role in modern scientific discovery and technologic advancementFactual data enables managers to measure, to understand their businesses, and to directly translate thatareas: 1) by making relevant historical data available to the manager at the time when it’s needed;2) by filtering out actionable intelligence from the ocean of data; and 3) by integrating useful dataacquisition and data analytics.

Keywords： engineering management     project management     big data     data analytics     planning     execution    

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Title Author Date Type Operation

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

Lu Huapu, Bai Zhuotong,Wu Zhouhao, Fu Zhihuan

Journal Article

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

Ali Reza GHANIZADEH, Morteza RAHROVAN

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

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

Xue LI,Pengjing LI,Dong WANG,Yuqiu WANG

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

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

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

Journal Article

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

Yuan XU,Ruqin XIE,Yuqiu WANG,Jian SHA

Journal Article

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

Sajjad TAGHVAEI, Kazuhiro KOSUGE

Journal Article

Field investigation of intelligent compaction for hot mix asphalt resurfacing

Wei HU,Xiang SHU,Baoshan HUANG,Mark WOODS

Journal Article

A review of systematic evaluation and improvement in the big data environment

Feng YANG, Manman WANG

Journal Article

Data quality assessment for studies investigating microplastics and nanoplastics in food products: Arecurrent data reliable?

Journal Article

Blockchain application in healthcare service mode based on Health Data Bank

Jianxia GONG, Lindu ZHAO

Journal Article

Challenges to Engineering Management in the Big Data Era

Yong Shi

Journal Article

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

Journal Article

Intelligent data analytics is here to change engineering management

Jonathan Jingsheng SHI, Saixing ZENG, Xiaohua MENG

Journal Article