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关键词： 审计结果公开   媒体反腐报道   反腐报道效能   反腐报道风险   腐败治理  

摘要： 党的十九大以来,依法依规公告审计结果已经成为完善审计结果运用机制的重要内容。加大审计结果公开力度已成为各界共识。审计法修订草案(征求意见稿)关于审计结果公开的规定正发生变化,审计结果公开实务得到了更大的发展。媒体反腐报道是社会反腐的组成部分,本文以认知心理学理论为基础,从受众角度研究了媒体对审计结果公开的行为反应以及审计结果公开对媒体反腐报道意愿的影响。理论分析表明,审计结果公开会通过提高媒体反腐效能感、降低媒体反腐风险感而提高媒体反腐报道意愿。实证结果表明,审计结果公开力度越大、媒体反腐报道意愿越高。本文揭示了审计结果公开对媒体反腐的作用,拓展了政府审计结果公开作用的研究领域、丰富了媒体反腐影响理论,为各级审计机关进一步强化审计结果公开提供了新的依据。

关键词： 高校   快递包装   回收箱   绿色物流  

摘要： 本文针对目前快递包装回收率低的社会现状,设计一种供高校师生群体分类回收快递包装的室内外晴雨两用的回收箱.设计的目的在于将拆除的快递包装分类处理,减少资源消耗,降低环境污染.与此同时,将师生群体的环保思想化为有效的实际行动,以此提升快递包装回收率.

关键词： 风险投资   高铁开通   成功退出   专利研发  

摘要： 中国风险投资市场日趋成熟,风险投资在我国资本市场到底起到了什么作用还值得探讨。本文基于2006-2016年所有风险投资和私募股权投资事件,选取了具有中国特色的高铁开通这一外生冲击,从成功退出的概率和专利研发两方面检验了10年间我国风险投资的增值作用。研究表明:高铁开通证实风险投资存在增值作用,而且节约旅行时间和增加出行便利有助于增强风险投资的增值作用;领投比跟投的增强作用更大;此效应在高铁开通的"大照顾"中更大。

关键词： 静电纺丝   抗菌包装   活性包封   聚合物   研究进展  

摘要： 随着现代食品工业对产品抗菌包装的要求不断提高,纳米技术和材料的改进与应用逐渐成为研究热点。其中静电纺丝技术是一种新兴的活性物质包埋技术,同时对活性物质也有较好的缓释效果,利用该技术制备的纳米纤维在食品工业中具有潜在的应用价值。该文从天然聚合物(蛋白质、多糖)和合成聚合物(聚乙烯醇、聚氧化乙烯、聚乳酸、聚丙烯)两方面分别综述了静电纺丝技术在食品封装抗菌物质中的应用现状,并展望了静电纺丝在食品科学领域中的应用前景。静电纺丝技术与食品抗菌包装的结合,在未来将得到更加广泛的应用,抗菌包装也将朝着更加多元化的方向发展。

关键词： 网络平台   精品资源共享   临床微生物学检验  

摘要： 《临床微生物学检验技术》是一门应用性及实践性极强的医学检验技术专业的主干课程,与临床工作的关系密切,在医学检验与临床中发挥着非常重要的衔接作用。有效利用网络平台加强精品资源共享课建设,对学生合理、高效利用现代教育技术,发挥资源共享作用,培养学习力及掌握临床微生物学检验的基本理论、基本知识、基本技能有很好的促进作用。

关键词： Classifier network   Computational complexity   Dataset size reduction   Euclidean distance   Nuclear power plant   EXTREME LEARNING-MACHINE   INDEPENDENT COMPONENT ANALYSIS   PARTIAL LEAST-SQUARES   DATA SELECTION   PERFORMANCE   REGRESSION   SVM  

摘要： The computational complexity rate augments on training a classifier for a dataset with training samples as large as that of a nuclear power plant (NPP). Hence, there has been a constant focus to have classifiers with low training time. One of the methods to tackle such issue is using training dataset size reduction (TDR) techniques. TDR method leads to lowering memory requirements as well as training time. This paper delineates on the implementation of TDR method using Euclidean distance (TDR-ED) with the intention of crafting a hypothetical boundary which selects the necessary samples from the training data set and dumps the rest. This approach is considered to be effective only if the accuracy of the classifier is not compromised even after reduction in the volume of the dataset. This is tested in this paper using some of the real world datasets to investigate the feasibility and efficiency of the TDR-ED approach using the combined effect of the classification accuracy and percentage reduction in the training dataset. Eventually, the feasibility of TDR-ED techniques for classification of some of the transients in a NPP is also inspected in this paper. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Distance-weighted linear regression   hyperspectral image (HSI) classification (HIC)   small samples size problem   spectral-spatial analysis   superpixel (SP) segmentation   training sample enlargement   COLLABORATIVE REPRESENTATION  

摘要： Hyperspectral image (HSI) classification (HIC) has attracted much attention in the last decade. Spectral-spatial HIC methods have been the state-of-the-art methods in recent years. Small labeled training sample size (SLTSS) problem is still an important issue in HIC. This paper presents a spectral-spatial HIC method that is based on superpixel (SP) segmentation and distance-weighted linear regression classifier to tackle the SLTSS problem. First, SP segmentation is applied to the original HSI. Then, those SPs that contain training samples belonging to only one class are first searched out, and all the pixels of each of these SPs are assigned to the class of the training samples it contains. Next, with the identified labels, all these classified pixels are added to the initial training sample set for training sample set enlargement. Later, using this enlarged training sample set, the distance-weighted linear regression classifier is applied to classify each mean vector of each SP. Finally, the last classification map is obtained by assigning each SP with the same label as its mean vector. Experimental results on three HSI data sets demonstrate that the proposed approach can solve SLTSS problem very well and outperforms several state-of-theart algorithms in classification accuracy under different training samples sizes.

关键词： Discriminant analysis   Forensic Science   FTIR   Milk   Principal component analysis   NEAR-INFRARED SPECTROSCOPY   RAPID DETECTION   DAIRY-PRODUCTS   COWS MILK   DIFFERENTIATION   MELAMINE   IDENTIFICATION   CHEMOMETRICS   BIOSENSOR   SYSTEM  

摘要： In the present study, we have utilized attenuated total reflectance Fourier transform infrared spectroscopy for the examination of raw, pasteurized and adulterated milk samples. Principal component analysis and discriminant analysis have been applied for discrimination and classification purposes. According to the observations and the model of "goodness of fit", the obtained results explain 100% of the original classification of the dataset and leave one out cross-validation provides 93.74% of accurate classification.