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关键词： Deep learning   Hyperspectral images   Limited labeled samples   Locality preserving convolutional network  

摘要： One major challenge of designing deep learning systems for hyperspectral data classification is the lack of labeled training samples. Inspired by recent manifold learning researches, this paper presents a novel Locality Preserving Convolutional Network to address this challenge. The proposed method invents a semi-supervised locality-preserving regularization operation, and inserts a new layer in the three-dimensional convolutional neural network for end-to-end spatial-spectral classification. The benefits are three-fold. First, by using unlabeled training samples which are more easily available, the proposed method reduces the number of labeled samples required for training a deep learning model;Second, the proposed method incorporates the intrinsic geographical correlation among nearby samples into the extracted features, which prevents it from losing accuracy when only limited labeled samples are available;Third, with a three-dimensional architecture, the proposed method can extract the spatial and spectral features simultaneously from the hyperspectral data for classification. A gradient-decent based approach is deployed to train the whole network in a unified way. Experiments over different benchmarks show that, the proposed method relieves the Hughes phenomenon for deep learning, and achieves competitively high classification accuracy compared to other state-of-the-art approaches. (C) 2018 Elsevier B.V. All rights reserved.

关键词： 足迹检验技术   刑侦破案   应用探究  

摘要： 我国的科技不断发展社会经济整体水平提升,近年来的侦查案件之中,发现犯罪分子的手段呈多样化发展趋势。其中足迹检验技术应用范围拓展,也是公安机关侦查案件常见的 技术应用依据。所以本文 将结合足迹检验技术的应用实际,将其在侦查破案环节的应用途径探析,将足迹技术的科学性体现,全面分析足迹检验技术还存在的一些问题,希望能给广大同仁带来借鉴参考。

关键词： Stroke   Classification   Aetiology  

摘要： BackgroundInter-observer variability in stroke aetiological classification may have an effect on trial power and estimation of treatment effect. We modelled the effect of misclassification on required sample size in a hypothetical cardioembolic (CE) stroke *** performed a systematic review to quantify the reliability (inter-observer variability) of various stroke aetiological classification systems. We then modelled the effect of this misclassification in a hypothetical trial of anticoagulant in CE stroke contaminated by patients with non-cardioembolic (non-CE) stroke aetiology. Rates of misclassification were based on the summary reliability estimates from our systematic review. We randomly sampled data from previous acute trials in CE and non-CE participants, using the Virtual International Stroke Trials Archive. We used bootstrapping to model the effect of varying misclassification rates on sample size required to detect a between-group treatment effect across 5000 permutations. We described outcomes in terms of survival and stroke recurrence censored at *** 4655 titles, we found 14 articles describing three stroke classification systems. The inter-observer reliability of the classification systems varied from fair' to very good' and suggested misclassification rates of 5% and 20% for our modelling. The hypothetical trial, with 80% power and alpha 0.05, was able to show a difference in survival between anticoagulant and antiplatelet in CE with a sample size of 198 in both trial arms. Contamination of both arms with 5% misclassified participants inflated the required sample size to 237 and with 20% misclassification inflated the required sample size to 352, for equivalent trial power. For an outcome of stroke recurrence using the same data, base-case estimated sample size for 80% power and alpha 0.05 was n=502 in each arm, increasing to 605 at 5% contamination and 973 at 20% *** aetiological classification sys

关键词： Small-sample image classification   Few-shot   Ensemble learning   Deep convolutional neural network  

摘要： Small-sample classification is a challenging problem in computer vision. In this work, we show how to efficiently and effectively utilize semantic information of the annotations to improve the performance of small-sample classification. First, we propose an image-text dual neural network to improve the classification performance on small-sample datasets. The proposed model consists of two sub-models, an image classification model and a text classification model. After training the sub-models separately, we design a novel method to fuse the two sub-models rather than simply combine their results. Our image-text dual neural network aims to utilize the text information to overcome the training problem of deep models on small-sample datasets. Then, we propose to incorporate a decision strategy into the image-text dual neural network to further improve the performance of our original model on few-shot datasets. To demonstrate the effectiveness of the proposed models, we conduct experiments on the LabelMe and UIUC-Sports datasets. Experimental results show that our method is superior to other models. (C) 2018 Elsevier B.V. All rights reserved.

关键词： 公司债券   债券违约   处理方法  

摘要： 截止2017年10月末,中国资本市场上共有将近130只债券违约事件发生,累计违约资金达700多亿元。在这些违约债券中,私募债券违约数量最多,定向工具违约规模最大。在建筑、工程、钢铁、贸易公司、建材等周期性较强的行业违约比重较大。华东、华北、东北地区为债券违约的高发区域。对于债券违约,人们习惯政府来处理,政府的"兜底"政策甚至被视为我国处理债券违约问题的"常规"做法。党的"十三届三中全会"提出的"发展并规范债券市场,提高直接融资比重",充分表明未来债券市场必须打破以往依赖政府来处理的惯例,研究并思考如何应对债券偿付危机办法,减少损失。

关键词： 妊娠   高血压   D-二聚体   凝血指标   临床检验  

摘要： 目的探讨妊娠期高血压患者D-二聚体与凝血指标临床检验的作用。方法选2017年3月至2018年4月在我院进行就诊的妊娠期高血压患者30例作为实验组,选同期体检正常孕妇30例作为对照组,对两组人员均进行D-二聚体与凝血指标检测,对两组检验指标情况进行观察。结果 D-二聚体指标水平会随着孕妇孕周的增加而升高,和对照组检测数据比较,数据差异明显(P <0.05)。实验组孕妇凝血酶时间、部分凝血活酶时间、凝血酶时间、纤维蛋白原指标情况与对照组孕妇比较,数据差异有统计意义(P <0.05)。结论 D-二聚体联合凝血指标检验能够有效提高妊娠期高血压患者病症的检出率,与正常孕妇比较,妊娠期高血压孕妇具备较高的凝血状态,并且有血栓形成的倾向,并且会随着病情的加重而加重。

关键词： 微生物   原始   涂片  

摘要： 目的:探析检验原始涂片的作用。方法:随机抽取1023例住院患者或门诊患者的检验标本研究导航作用,标本抽取时间段为2015年9月～2017年11月,比较涂片检验与培养检验的阳性率。结果:培养检验、涂片检验阳性率无显著差异。结论:检验标本涂片可有效导航微生物检验过程。

关键词： 人防工程   防护设备   质量检测  

摘要： 人防工程是一种特殊的地下建筑,其防护设备是重要的组成部分,对人防工程发挥防护作用起着关键的作用。本文探讨了门式人防工程防护设备的现状、存在的问题和防护设备质量检测,从而加强防护设备的质量检测,全面提高人防工程防护设备的防护能力。

关键词： 血型实验室   输血质量   输血安全   输血检验   交叉配血   质量控制  

摘要： 目的探究在临床输血质量控制及输血安全中应用血型实验室检验的作用。方法此次选择2014年2月—2018年4月本院进行输血的336例患者作为研究对象。根据输血时间先后顺序,将其分为实验组(n=168)和常规组(n=168)。常规组进行普通输血检验,实验组则进行输血检验质量控制,将两种方式输血液后出现的情况进行对比分析。结果在输血安全事故总发生率上,实验组低于对照组(4.76%vs. 23.81%);在交叉配血合格率上,实验组高于对照组(96.43%vs.80.95%),差异具有统计学意义(P <0.05)。影响交叉配血不合格的因素包括输血史、妊娠史等。结论质量控制应用于血型实验室检验,能够确保输血的安全性和质量,减少输血不良事件的发生率。

关键词： 痕迹检验   刑事案件   案发现场   作案工具  

摘要： 目前,我国公安机关和相关部门在处理刑事案件的过程中,已将痕迹检验技术作为侦查人员侦破案件最重要的手段之一。正确利用痕迹检验技术的结果,一方面可以更多了解犯罪分子的行为,另一方面还可以把现场证物和案件紧密联系起来。本文主要针对痕迹检验技术的概念进行阐释以及对该技术所包含的内容进行分析,同时,在此基础上讲述了痕迹检验技术的作用以及其局限性,为痕迹检验技术在刑事侦查案件中科学应用提供了依据。