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关键词： laser-induced breakdown spectroscopy   plasma   original rock identification   principal component analysis method   noise reduction  

摘要： Rock classification plays a very important role in geological research. In order to simulate rock classification under unmanned conditions, we selected 13 kinds of rock samples and obtained their classification from spectral information, without any pretreatment, by using laser-induced breakdown spectroscopy (LIBS). Firstly, we collected all the characteristic regions of each rock and used principal component analysis to reduce the dimension of each LIBS spectral signal, to improve the accuracy and speed of the classification algorithm. Secondly, three classification algorithms were used to classify dimension-reduced spectral data, namely linear discriminant analysis, random forest classification and support vector machine (SVM). At the same time, the classification results were evaluated by confusion matrix. The final average classification accuracy was 27%, 91% and 100%, respectively, showing that the SVM algorithm can be applied to the LIBS classification of rocks.

关键词： Random Forest   Samples cleansing   Training sample   Agricultural mapping   Food security  

摘要： Crop type mapping is relevant to a wide range of food security applications. Supervised classification methods commonly generate these data from satellite image time-series. Yet, their successful implementation is hindered by the lack of training samples. Solutions like transfer learning, development of temporal-spectral signatures of the target classes, re-utilization of existing inventories, or crowdsourcing initiatives are commonly applied to generate samples for thematically coarser classifications. These methods are rarely used for generating crop types samples. In this study, we leverage the phenology information of existing data inventories using Time-Weighted Dynamic Time Warping (TWDTW) to address the problem of automatic crop sample generation in two target areas. Resulting labeled samples are refined using proximity measures obtained from Random Forests (RF). Sentinel-2 time-series are used to obtain phenology information from two study areas. The proposed methodology achieved promising results for classes with a reduced inter-classes similarity such as sugar beets (user's accuracy, UA, of 98% and producer's accuracy, PA, of 100%) or grains (UA of 98% and PA of 90%). The crops with a high inter-classes similarity yielded less satisfactory results. Potatoes, for example, obtained a high PA of 95%, but a UA of only 36% because of the spectral-temporal similarity with maize. The methodology works well for areas with balanced crop samples. Yet, it favors prevalent classes in areas with imbalanced crops at the expense of a low accuracy for the minority crops. Despite these shortcomings, the proposed methodology offers a viable option to generate crop samples in regions with few ground labels.

关键词： Training   Feature extraction   Iron   Hyperspectral imaging   Convolutional neural networks   Deep learning   Convolutional neural network (CNN)   deep learning   hyperspectral image (HSI) classification   limited training samples   siamese network  

摘要： In recent years, deep convolutional neural networks (CNNs) have been widely used for hyperspectral image (HSI) classification. The powerful feature extraction capability and high classification performance of CNN highly depend on sufficient training samples. Unfortunately, it is not a common situation because collecting training samples is time-consuming and expensive. In this letter, in order to make the most of deep CNN with limited training samples, dual-path siamese CNN (Dual-SCNN) is proposed for HSI classification. Specifically, the proposed classification framework is a combination of extended morphological profiles, CNN, siamese network, and spectral-spatial feature fusion. In order to solve the problem of insufficiency in hard negative pairs during the training of a siamese network, adversarial training is combined with Dual-SCNN (Dual-SCNN-AT) for HSI classification. Moreover, a data augmentation method titled mixup is combined with Dual-SCNN and Dual-SCNN-AT to further improve the classification performance of HSI. The obtained results on widely used hyperspectral data sets reveal that the proposed methods provide the competitive results in terms of classification accuracy, especially with limited training samples.

关键词： dialogic interaction   epistemic climate   generative learning environments   knowledge generation   Rasch modeling  

摘要： This study investigates two latent constructs (Engagement and Value) of dialogic interaction to examine the epistemic climate. Since the new reform movement emphasizes creating generative learning environments, it is important to examine whether a classroom promotes students' knowledge generation or limit students' epistemic growth through rote memorization. At this point, it is inevitable to focus on dialogic interaction (one of the epistemic practices), because how students engage with and view dialogic interaction provides meaningful information about the epistemic climate. By employing Rasch modeling, this study tested a statistical validity of two latent constructs of dialogic interaction. The findings in this study highlight that the two latent constructs are theoretically and statistically valid and can be used to gauge the epistemic climate through students' engagement with and value of dialogic interaction. While understanding the epistemic climate cannot solely occur through a single perspective, this study plays a significant role in adding a valid instrument. Such instruments help researchers comprehend the epistemic features of learning environments and provide a practical way to reflect students' lived experiences to learn about the overall atmosphere of the learning environment.

关键词： 检验科   实习带教   ISO15189   质量要求  

摘要： 探讨医学检验实习带教中融入ISO15189认可体系质量要求的作用价值。方法:选取我院2017年6月-2020年5月期间检验科实习生66例纳为研究对象,通过随机数字表法均分两组,各33例。对照组行常规带教,研究组将ISO15189认可体系质量要求融入带教中,观察两组考核成绩、实习生对带教的评价。结果:对比两组考核成绩,研究组理论知识、实操水平均明显高于对照组,差异显著(P<0.05);两组报告书写成绩相差不大,无统计学意义(P>0.05);研究组综合成绩明显比对照组高,差异显著(P<0.05),研究组实习生对带教的评价得分明显高于对照组,差异显著(P<0.05)。结论:在医学检验实习带教中融入ISO15189认可体系质量要求,有利于提升实习生对检验医学、ISO15189认可体系质量要求的认识,在实操能力培养和理论知识掌握方面效果突出,能提升实习生综合素质,认可程度较高,具有推广价值。

关键词： 血常规检验   贫血   临床诊断  

摘要： 研究血常规检验,用到贫血患者诊断中的效果。方法:笔者所在基层医院贫血患者共48例(2019.1~2020.1),其中24例为缺血性贫血(甲组)、24例为地中海贫血(乙组),并将同期做健康体检的24例健康人群纳入至丙组,全部入选者均进行血常规检验,观察三组血常规指标。结果:MCH、MCV、Hb:丙组>甲组、乙组,(P<0.05);RDW:丙组<甲组、乙组,(P<0.05);RDW、MCV、MCH乙组<甲组,(P<0.05);Hb:乙组>甲组,(P<0.05)。结论:血常规检验能够为诊断鉴别贫血提供科学依据。

关键词： 微生物检验   临床合理用药   医院感染发生率   医院感染程度  

摘要： 目的 探讨微生物检验对医院感染发生率降低以及临床合理用药产生的影响.方法 将我院2017年6月至2020年8月收治的130例住院患者依据微生物检验工作开展情况完成分组;干预组(65例):合理开展微生物检验工作;参照组(65例):未开展微生物检验工作;就组间医院感染(泌尿道感染、下呼吸道感染、手术切口感染以及胃肠道感染)总发生率、临床合理用药(预防用药、治疗用药)情况以及医院感染程度展开对比.结果 干预组住院患者医院感染总发生率(6.15％)低于参照组(27.69％)明显(P<0.05);干预组住院患者总合理用药率(96.92％)高于参照组(60.00％)明显(P<0.05);干预组住院患者轻度感染发生率(6.15％)高于参照组轻度感染发生率(0.00％)明显(P<0.05),中度感染发生率(0.00％)以及重度感染发生率(0.00％)均低于参照组中度感染发生率(15.38％)以及重度感染发生率(12.31％)明显(P<0.05).结论 微生物检验工作合理开展,能够将医院泌尿道感染、下呼吸道感染、手术切口感染以及胃肠道感染等发生率显著降低,并且可将预防用药、治疗用药合理性显著提升,将医院感染程度显著减轻,期间要求医院需要就院内感染问题以及微生物检验工作开展给予充分重视,将控制力度有效加大,确保微生物检验工作获得合理应用,最终实现住院患者有效治疗、预后.

关键词： 美元债   违约   后续处理及建议   恒鼎实业国际  

摘要： 由于国内融资监管严格、审批复杂等原因导致国内融资环境变化,企业在国内融资难度加大。而国外资本环境较为开放,这也就催生了众多企业在海外发行美元债以达到融资目的。随着世界经济竞争越发激烈,国内企业发行美元债后的违约情况逐年递增。由于美元债发行在境外,美元债违约后的处理方式与国内债券违约后的处理方式大相径庭。本文拟以恒鼎实业国际发行美元债违约后的处理方式为例,试图找到相应美元债违约后的处理及建议,给到相应企业以参考。