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关键词： Hyperspectral remote sensing (HSRS) image classification   limited training data   synthetic data  

摘要： The amount of training data that is required to train a classifier scales with the dimensionality of the feature data. In hyperspectral remote sensing (HSRS), feature data can potentially become very high dimensional. However, the amount of training data is oftentimes limited. Thus, one of the core challenges in HSRS is how to perform multiclass classification using only relatively few training data points. In this letter, we address this issue by enriching the feature matrix with synthetically generated sample points. These synthetic data are sampled from a Gaussian mixture model (GMM) fitted to each class of the limited training data. Although the true distribution of features may not be perfectly modeled by the fitted GMM, we demonstrate that a moderate augmentation by these synthetic samples can effectively replace a part of the missing training samples. Doing so, the median gain in classification performance is 5% on two datasets. This performance gain is stable for variations in the number of added samples, which makes it easy to apply this method to real-world applications.

关键词： 16S sequencing   Factor models   Microbiome   Zero-inflated models  

摘要： Distance-based ordination methods, such as principal coordinates analysis (PCoA), are widely used in the analysis of microbiome data. However, these methods are prone to pose a potential risk of misinterpretation about the compositional difference in samples across different populations if there is a difference in dispersion effects. Accounting for high sparsity and overdispersion of microbiome data, we propose a amples (GOMMS) in this article. This method uses a zero-inflated quasi-Poisson (ZIQP) latent factor model. An EM algorithm based on the quasi-likelihood is developed to estimate parameters. It performs comparatively to the distance-based approach when dispersion effects are negligible and consistently better when dispersion effects are strong, where the distance-based approach sometimes yields undesirable results. The estimated latent factors from GOMMS can be used to associate the microbiome community with covariates or outcomes using the standard multivariate tests, which can be investigated in future confirmatory experiments. We illustrate the method in simulations and an analysis of microbiome samples from nasopharynx and oropharynx.

关键词： Speaker recognition   Speaker verification   Logistic regression   Classifier fusion  

摘要： Due to the mismatch between training and test conditions, speaker verification in real environments, continues to be a challenging problem. An effective way of improving such a system is taking advantage of multiple speaker verification systems. In this paper, we propose a novel sample specific speaker verification system. Using this system, the best classifiers are selected as the ensemble set and the optimal weights are obtained for each test sample. In this process, more reliable scores are forced to have higher weights, while less reliable scores are forced to have lower weights. We achieved an improvement of 0.81% in equal error rate (EER), 0.76% in minimum decision cost function (minDCF) and 3.62% in minimum log-likelihood ratio cost (minCLLR) on the NIST 2004 Speaker Recognition Evaluation dataset.

关键词： 检验检测   内审员   审核   监督  

摘要： 实验室的内审员,除肩负内审任务外,往往还是本实验室管理体系建设的骨干。不仅要对管理体系的运行进行检查、判定,还要对本实验室管理体系的建立和实施起着重要的支持和推动作用。

关键词： Transfer learning   SAE   CNN   Deep network   Classification methods  

摘要： The effective classification methods of the small target objects in the no-fly zone are of great significance to ensure safety in the no-fly zone. But, due to the differences of the color and texture for the small target objects in the sky, this may be unobvious, such as the birds, unmanned aerial vehicles (UAVs), and kites. In this paper, we introduced the higher layer visualizing feature extraction method based on the hybrid deep network model to obtain the higher layer feature through combining the Sparse Autoencoder (SAE) model, the Convolutional Neural Network (CNN) model, and the regression classifier model to classify the different types of the target object images. In addition, because the sample numbers of the small sample target objects in the sky may be not sufficient, we cannot obtain much more local features directly to realize the classification of the target objects based on the higher layer visualizing feature extraction;we introduced the transfer learning in the SAE model to gain the cross-domain higher layer local visualizing features and sent the cross-domain higher layer local visualizing features and the images of the target-domain small sample object images into the CNN model, to acquire the global visualizing features of the target objects. Experimental results have shown that the higher layer visualizing feature extraction and the transfer learning deep networks are effective for the classification of small sample target objects in the sky.

关键词： 胶体金法   蛋白芯片法   结核病  

摘要： 目的：研究结核菌蛋白LAM、16KD、ESAT－6、38KD、CFP10蛋白芯片法及胶体金法对结核菌感染诊断的应用价值。方法：研究选取我院2015年8月－2017年8月期间确诊的50例肺结核病患者，50例非结核病患者为研究对象，所有受检人员均实行蛋白芯片法、胶体金法检验，比较两种方法的敏感度、特异性等诊断指标的差异。结果：胶体金诊断肺结核患者的敏感度为92．00％，特异度为94．00％，准确性为93．00％，误诊率为6％，漏诊率为8％。阳性预测值为93．88％，阴性预测值为92．16％；蛋白芯片诊断肺结核患者的敏感度为96．00%，特异度为98．00％，准确性为97．00％，误诊率为2％，漏诊率为4％，阳性预测值为97．96％，阴性预测值为96．08％，两方法对比无明显差异．P〉0．05。结论：在临床诊断结核疾病中应用胶体金法进行辅助检查与蛋白芯片均具有操作简单、灵敏度高等优势，且在早期诊断与治疗结核疾病中实用性强，属于理想程度比较高的免疫学检验技术，可根据实际情况合理选择。

关键词： 医学检验技术   技能竞赛   实践教学  

摘要： 医学检验技术是通过运用各种实验方法,为疾病诊断提供诊断依据的一个临床辅助诊断专业。该专业课程实践操作内容繁杂,手工操作多,为了更好地推进医学检验技术专业课程的实践教学,提高学生对实践学习的积极性,增强学生的实践操作能力,在学院的帮助下,举办高职学生的职业技能竞赛,并对技能竞赛做经验总结,同时就此竞赛对医学检验技术专业课程实践教学的作用进行探讨。

关键词： 产业结构   经济增长   金融集聚   城镇化  

摘要： 文章运用中介效应模型对金融集聚与城镇化在产业结构对经济发展作用过程中的传导和作用效应进行检验。结果表明：金融集聚和城镇化均在产业结构至经济增长间表现为正向部分中介效应;金融集聚、城镇化的并行总体中介效应不显著;存在产业结构→金融集聚→城镇化→经济增长以及产业结构→城镇化→金融集聚→经济增长的传导路径。

关键词： 尿常规检验   干化学法   尿沉渣法   临床作用  

摘要： 目的探析尿常规检验中联合应用干化学法与尿沉渣法的临床作用。方法选择陕西省安康职业技术医学院2016年7月—2018年1月期间接受尿常规检验的240例患者为研究对象,依照随机抽签法分为3组,即甲组、乙组、丙组,各组患者80例。甲组患者给予干化学法进行尿常规检验,乙组患者给予尿沉渣法进行尿常规检验,丙组患者给予干化学法与尿沉渣法联合检验尿常规,统计比较3组患者定量白细胞阳性率、定量红细胞阳性率、误诊率、漏诊率及总错误率。结果甲组患者定量白细胞阳性率、定量红细胞阳性率分别为8.75%、13.75%,乙组患者定量白细胞阳性率、定量红细胞阳性率分别为21.25%、3.75%,丙组患者定量白细胞阳性率、定量红细胞阳性率分别为36.25%、26.25%,甲组定量白细胞阳性率显著低于乙组、丙组(χ~2=4.901 9、17.347 6,P=0.026 8、0.000 0),定量红细胞阳性率显著高于乙组(χ~2=5.009 7,P=0.025 2),低于丙组(χ~2=3.906 2,P=0.048 1),丙组定量白细胞阳性率、定量红细胞阳性率均显著高于甲组、乙组(χ~2=4.393 5、15.882 3,P=0.036 0、0.000 0)。甲组患者误诊率、漏诊率、总错误率分别为10.00%、5.00%、15.00%,乙组患者误诊率、漏诊率、总错误率分别为8.75%、5.00%、13.75%,丙组患者误诊率、漏诊率、总错误率分别为1.25%、0.00%、1.25%,甲组、乙组比较差异无统计学意义(χ~2=0.073 5、0.000 0、0.050 7,P=0.786 2、1.000 0、0.821 7);丙组显著低于甲组(χ~2=5.768 9、4.102 5、10.130 8,P=0.016 3、0.042 8、0.001 4)、乙组(χ~2=4.736 8、4.102 5、9.009 0,P=0.029 5、0.042 8、0.002 6)。结论在尿常规检验中,干化学法与尿沉渣法各具优势,但为了进一步提高检验结果准确率,应联合应用干化学法与尿沉渣法,以此为临床诊治提供更加可靠的参考。

关键词： 检验医师   读书报告   PDCA持续改进  

摘要： 检验医师规范化培训对提高我国临床医师队伍的整体质量和水平有重要作用。本文将计划-实施-检查-纠正(PDCA)持续改进循环方法引入检验医师规范化培训的读书报告中,在读书报告的内容、形式、考核等方面进行持续不断的改进,优化读书报告学习的质量,完善培训的方式方法,提高检验医师的学习效果,拓宽检验医师的知识面,使其不断学习新知识,提高自主学习和终身学习的能力。通过PDCA对读书报告持续改进,培训方法不断完善,读书报告可实现高效学习模式,不断提高检验医师的学习能力和科研水准。