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Technology and Equipment of Big Data on Crop Phenomics

Wen Weiliang , Guo Xinyu, Zhang Ying , Gu Shenghao, Zhao Chunjiang

Strategic Study of CAE 2023, Volume 25, Issue 4, Pages 227-238 doi: 10.15302/J-SSCAE-2023.04.015

Abstract: of crops under different growth conditions, forming big data on crop phenomics.In this paper, the demand for and industrial development of technology and equipment of big dataAt last, the following suggestions are proposed: achieving breakthroughs regarding key crop phenotypingsensor technologies from the underlying chip level, forming an autonomous phenotyping extractiondata on crop phenomics, creating a new model of genotype‒phenotype‒environment big data-driven

Keywords： crop phenomics phenotyping big data technology and equipment for phenotyping multi-omics

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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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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 subjectdata environment.We 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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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: This paper presents a review of the challenges to engineering management in the Big Data Era as wellas 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.

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

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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 bigTo conduct clinical studies involved in big data in TCM domain, top level design is needed and shouldcreation, 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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Scientific computation of big data in real-world clinical research

Guozheng Li,Xuewen Zuo,Baoyan Liu

Frontiers of Medicine 2014, Volume 8, Issue 3, Pages 310-315 doi: 10.1007/s11684-014-0358-7

Abstract:

The advent of the big data era creates both opportunities and challenges for traditional Chinese medicinefeature subset optimizing, multi-label learning, and complex networks based on complexity, intelligence, data

Keywords： big data real world clinical research Chinese medicine medical computing

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A study on specialist or special disease clinics based on big data

Zhuyuan Fang,Xiaowei Fan,Gong Chen

Frontiers of Medicine 2014, Volume 8, Issue 3, Pages 376-381 doi: 10.1007/s11684-014-0356-9

Abstract:

Correlation analysis and processing of massive medical information can be implemented through bigdata technology to find the relevance of different factors in the life cycle of a disease and to provideThis paper explores the concept of constructing a big medical data platform and introduces the clinicalMedical data can be collected and consolidated by distributed computing technology.Big data analysis, such as Hadoop, can be used to construct early prediction and intervention models

Keywords： big data correlation analysis medical information integration data analysis clinical model

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Study on Big Data-based Behavior Modification in Metro Construction

Lie-yun Ding,Sheng-yu Guo

Frontiers of Engineering Management 2015, Volume 2, Issue 2, Pages 131-136 doi: 10.15302/J-FEM-2015037

Abstract: This paper introduces the study on big data-based metro construction behavior modification, aiming to

Keywords： big data unsafe behavior behavior modification behavior-based safety (BBS) unsafe behavior rate

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Slope stability analysis based on big data and convolutional neural network

Yangpan FU; Mansheng LIN; You ZHANG; Gongfa CHEN; Yongjian LIU

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 7, Pages 882-895 doi: 10.1007/s11709-022-0859-4

Abstract: A CNN model can process data quickly and complete a large amount of data analysis in a specific situationIt is difficult to get enough slope data samples in practical engineering.In particular, the combination of typical actual slopes and generated slope data provides enough training

Keywords： slope stability limit equilibrium method convolutional neural network database for slopes big data

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Utilizing big data to build personalized technology and system of diagnosis and treatment in traditional

Baoyan Liu

Frontiers of Medicine 2014, Volume 8, Issue 3, Pages 272-278 doi: 10.1007/s11684-014-0364-9

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Big Data to support sustainable urban energy planning: The EvoEnergy project

Moulay Larbi CHALAL, Benachir MEDJDOUB, Nacer BEZAI, Raid SHRAHILY

Frontiers of Engineering Management 2020, Volume 7, Issue 2, Pages 287-300 doi: 10.1007/s42524-019-0081-9

Abstract: consumption where we developed a 3D urban energy prediction system (EvoEnergy) using the old UK panel datasurvey, namely, the British household panel data survey (BHPS).aim, the household transition and energy prediction modules of EvoEnergy have been tested under both dataand had a good prediction accuracy (MAPE  5%) when compared to actual energy performance certificate data, to consider merging the BHPS and UKHLS data sets.

Keywords： urban energy planning sustainable planning Big Data household transition energy prediction

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IN2CLOUD: A novel concept for collaborative management of big railway data

Jing LIN, Uday KUMAR

Frontiers of Engineering Management 2017, Volume 4, Issue 4, Pages 428-436 doi: 10.15302/J-FEM-2017048

Abstract: Shift2Rail Multi-Annual Action Plan, the challenge of railway maintenance is generating knowledge from dataan intelligent cloud with hybrid cloud learning, and 3) collaborative management using asset-related datalearn from each other (including domain knowledge and experience) but do not want to share their raw data

Keywords： railway intelligent asset management collaborative learning big data hybrid cloud Bayesian

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Imaging technologies for plant high-throughput phenotyping: a review

Yong ZHANG, Naiqian ZHANG

Frontiers of Agricultural Science and Engineering 2018, Volume 5, Issue 4, Pages 406-419 doi: 10.15302/J-FASE-2018242

Abstract: With the rapid development of genomics, many plant phenotyping platforms have been developed to study, and adaptation to biotic or abiotic stress, but the ability to acquire high-throughput phenotypic dataaround the world have conducted extensive experiments and research on high-throughput, image-based phenotypingThis paper considers imaging technologies developed in recent years for high-throughput phenotyping,

Keywords： high-throughput phenotyping imaging technology morphological traits pathological traits physiological

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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