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Rapid transaction to load variations of active filter supplied by PV system

M. BENADJA,S. SAAD,A. BELHAMRA

Frontiers in Energy 2014, Volume 8, Issue 3,   Pages 335-344 doi: 10.1007/s11708-014-0325-7

Abstract: This paper deals with the analysis and control of a photovoltaic (PV) system connected to the main supply through a Boost converter and shunt active filter supplied by a PV system providing continuous supply of nonlinear load in variation. A robust control of a PV system connected to the grid while feeding a variable nonlinear load is developed and highlighted. This development is based on the control of the Boost converter to extract the maximum power from the PV system using the Perturb and Observe (P and O) algorithm in the presence of temperature and illumination. The proposed modeling and control strategy provide power to the variable nonlinear load and facilitates the transfer of power from solar panel to the grid while improving the quality of energy (harmonic currents compensation, power factor compensation and dc bus voltage regulation). Validation of the developed model and control strategy is conducted using power system simulator Sim-Power System Blockset Matlab/Simulink. To demonstrate the effectiveness of the shunt active filter to load changes, the method of instantaneous power ( theory) is used to identify harmonic currents. The obtained results show an accurate extraction of harmonic currents and perfect compensation of both reactive power and harmonic currents with a lower THD and in accordance with the IEEE-519 standard.

Keywords： solar panels     maximum power point tracking (MPPT)     DC/DC converter (Boost)     shunt active filter     instantaneous power control     power quality     harmonics     imbalances     reactive energy    

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SuPoolVisor: a visual analytics system for mining pool surveillance Research

Jia-zhi XIA, Yu-hong ZHANG, Hui YE, Ying WANG, Guang JIANG, Ying ZHAO, Cong XIE, Xiao-yan KUI, Sheng-hui LIAO, Wei-ping WANG

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 4,   Pages 507-523 doi: 10.1631/FITEE.1900532

Abstract: is also a challenge to achieve intuitive and comprehensive monitoring of multi-source heterogeneous data

Keywords： Bitcoin mining pool     Visual analytics     Transaction data     Visual reasoning     FinTech    

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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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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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Special issue: Innovative applications of big data and artificial intelligence

Frontiers of Engineering Management 2022, Volume 9, Issue 4,   Pages 517-519 doi: 10.1007/s42524-022-0234-0

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Anensemble method for data stream classification in the presence of concept drift

Omid ABBASZADEH,Ali AMIRI,Ali Reza KHANTEYMOORI

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 12,   Pages 1059-1068 doi: 10.1631/FITEE.1400398

Abstract: One recent area of interest in computer science is data stream management and processing.By ‘data stream’, we refer to continuous and rapidly generated packages of data.Specific features of data streams are immense volume, high production rate, limited data processing time, and data concept drift; these features differentiate the data stream from standard types of data.An issue for the data stream is classification of input data.

Keywords： Data stream     Classificaion     Ensemble classifiers     Concept drift    

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Methodological considerations for redesigning sustainable cropping systems: the value of data-mininglarge and detailed farm data sets at the cropping system level

Nicolas MUNIER-JOLAIN, Martin LECHENET

Frontiers of Agricultural Science and Engineering 2020, Volume 7, Issue 1,   Pages 21-27 doi: 10.15302/J-FASE-2019292

Abstract: Large data sets collected from real farms allow for the development of innovative methods to produceData mining methods allow for the diversity of systems to be considered holistically and can take intouse and their effect on farm performance, we advocate further investment in the development of large data

Keywords： data mining     holistic     Integrated Pest Management     economics     DEPHY network.    

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Multi-timescale optimization scheduling of interconnected data centers based on model predictive control

Frontiers in Energy doi: 10.1007/s11708-023-0912-6

Abstract: With the promotion of “dual carbon” strategy, data center (DC) access to high-penetration renewable energyIn this paper, a multi-timescale optimal scheduling model is established for interconnected data centers

Keywords： model predictive control     interconnected data center     multi-timescale     optimized scheduling     distributed    

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Big data and machine learning: A roadmap towards smart plants

Frontiers of Engineering Management   Pages 623-639 doi: 10.1007/s42524-022-0218-0

Abstract: components are smart sensing, mobile communication, Internet of Things, modelling and simulation, advanced dataessential element to this transformation is the exploitation of large amounts of historical process dataand large volumes of data generated in real-time by smart sensors widely used in industry.Exploitation of the information contained in these data requires the use of advanced machine learning

Keywords： big data     machine learning     artificial intelligence     smart sensor     cyber–physical system     Industry 4.0    

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Clinical research of traditional Chinese medicine in big data era

Junhua Zhang,Boli Zhang

Frontiers of Medicine 2014, Volume 8, Issue 3,   Pages 321-327 doi: 10.1007/s11684-014-0370-y

Abstract:

With the advent of big data era, our thinking, technology and methodology are being transformed.Data-intensive scientific discovery based on big data, named “The Fourth Paradigm,” has becomeof diagnosis and treatment, and genomic data have been accumulated dramatically, which generates bigdata in medical field for clinical research and assessment.creation, data analysis technology and big-data professionals fostering and training.

Keywords： big data     traditional Chinese medicine     clinical evaluation     evidence based medicine    

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Appreciating the role of big data in the modernization of environmental governance

Frontiers of Engineering Management 2022, Volume 9, Issue 1,   Pages 163-169 doi: 10.1007/s42524-021-0185-x

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A building-based data capture and data mining technique for air quality assessment

Ni SHENG, U Wa TANG

Frontiers of Environmental Science & Engineering 2011, Volume 5, Issue 4,   Pages 543-551 doi: 10.1007/s11783-011-0369-4

Abstract: Macau Peninsula as a case study, this paper shows the advantages of building-based model system in datacapture and data mining.resolutions of 1–2 km, the building-based approach can extract the street configuration and traffic dataThe study shows that the building-based approach may open an innovative methodology in data mining ofurban spatial data for environmental assessment.

Keywords： traffic air pollution     spatial distribution     high resolution     geographic information system    

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Title Author Date Type Operation

Rapid transaction to load variations of active filter supplied by PV system

M. BENADJA,S. SAAD,A. BELHAMRA

Journal Article

SuPoolVisor: a visual analytics system for mining pool surveillance

Jia-zhi XIA, Yu-hong ZHANG, Hui YE, Ying WANG, Guang JIANG, Ying ZHAO, Cong XIE, Xiao-yan KUI, Sheng-hui LIAO, Wei-ping WANG

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

Intelligent data analytics is here to change engineering management

Jonathan Jingsheng SHI, Saixing ZENG, Xiaohua MENG

Journal Article

Special issue: Innovative applications of big data and artificial intelligence

Journal Article

Anensemble method for data stream classification in the presence of concept drift

Omid ABBASZADEH,Ali AMIRI,Ali Reza KHANTEYMOORI

Journal Article

Methodological considerations for redesigning sustainable cropping systems: the value of data-mininglarge and detailed farm data sets at the cropping system level

Nicolas MUNIER-JOLAIN, Martin LECHENET

Journal Article

Multi-timescale optimization scheduling of interconnected data centers based on model predictive control

Journal Article

Big data and machine learning: A roadmap towards smart plants

Journal Article

Clinical research of traditional Chinese medicine in big data era

Junhua Zhang,Boli Zhang

Journal Article

Appreciating the role of big data in the modernization of environmental governance

Journal Article

A building-based data capture and data mining technique for air quality assessment

Ni SHENG, U Wa TANG

Journal Article