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  • MDPI AG  (3)
  • Zhang, Xiaoming  (3)
  • 2015-2019  (3)
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  • MDPI AG  (3)
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  • 2015-2019  (3)
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  • 1
    In: Polymers, MDPI AG, Vol. 11, No. 12 ( 2019-11-22), p. 1926-
    Abstract: A new strategy for nanocrystal encapsulation, release and application based on pH-sensitive covalent dynamic hyperbranched polymers is described. The covalent dynamic hyperbranched polymers, with multi-arm hydrophobic chains and a hydrophilic hyperbranched poly(amidoamine) (HPAMAM) core connected with pH-sensitive imine bonds (HPAMAM–DA), could encapsulate CdTe quantum dots (QDs) and Au nanoparticles (NPs). Benefiting from its pH response property, CdTe QDs and Au NPs encapsulated by HPAMAM–DA could be released to aqueous phase after imine hydrolysis. The released CdTe/HPAMAM and Au/HPAMAM nanocomposites exhibited excellent biological imaging behavior and high catalytic activities on p-nitrophenol hydrogenation, respectively.
    Type of Medium: Online Resource
    ISSN: 2073-4360
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2527146-5
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  • 2
    Online Resource
    Online Resource
    MDPI AG ; 2019
    In:  Symmetry Vol. 11, No. 12 ( 2019-12-11), p. 1503-
    In: Symmetry, MDPI AG, Vol. 11, No. 12 ( 2019-12-11), p. 1503-
    Abstract: Cross-efficiency evaluation approaches and common set of weights (CSW) approaches have long been suggested as two of the more important and effective methods for the ranking of decision making units (DMUs) in data envelopment analysis (DEA). The former emphasizes the flexibility of evaluation and its weights are asymmetric, while the latter focuses on the standardization of evaluation and its weights are symmetrical. As a compromise between these two approaches, this paper proposes a cross-efficiency evaluation method that is based on two types of flexible evaluation criteria balanced on interval weights. The evaluation criteria can be regarded as macro policy—or means of regulation—according to the industry’s current situation. Unlike current cross-efficiency evaluation methods, which tend to choose the set of weights for peer evaluation based on certain preferences, the cross-efficiency evaluation method based on evaluation criterion determines one set of input and output weights for each DMU. This is done by minimizing the difference between the weights of the DMU and the evaluation criteria, thus ensuring that the cross-evaluation of all DMUs for evaluating peers is as consistent as possible. This method also eliminates prejudice and arbitrariness from peer evaluations. As a result, the proposed cross-efficiency evaluation method not only looks for non-zero weights, but also ranks efficient DMUs completely. The proposed DEA model can be further extended to seek a common set of weights for all DMUs. Numerical examples are provided to illustrate the applications of the cross-efficiency evaluation method based on evaluation criterion in DEA ranking.
    Type of Medium: Online Resource
    ISSN: 2073-8994
    Language: English
    Publisher: MDPI AG
    Publication Date: 2019
    detail.hit.zdb_id: 2518382-5
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  • 3
    In: Information, MDPI AG, Vol. 9, No. 11 ( 2018-11-19), p. 291-
    Abstract: Precision orchard management is an important avenue of investigation in agricultural technology and is an urgently needed part of information development in the fruit industry. Precision management based on a precision agricultural technology system involves many factors and results in users being unable to make accurate judgments. To improve user decision-making accuracy and the level of precision management, we used user preferences to achieve the recommendation function. In this paper, a ranking method based on fuzzy preference relations for user recommendation is proposed. We selected the Nature Reserve of Dangshan Pear Germplasm Resources as the research location and invited experts and representatives of different roles (government, farmers, and tourists) to give the fuzzy preference relation coefficients. Then, an optimization model was proposed based on the fuzzy preference relation. We solved the proposed model by constructing a Lagrangian function, and obtained the ranking values of the user preference recommendation function. Finally, we ranked the order of the given roles and implemented the fuzzy preference recommendation. The experimental results show that the proposed method is effective and can be conveniently applied to other problems related to user preference relations.
    Type of Medium: Online Resource
    ISSN: 2078-2489
    Language: English
    Publisher: MDPI AG
    Publication Date: 2018
    detail.hit.zdb_id: 2599790-7
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