A hybrid knowledge and ensemble classification approach for prediction of venous thromboembolism

Clinical narratives such as progress summaries, lab reports, surgical reports, and other narrative texts contain key biomarkers about a patient's health. Evidence-based preventive medicine needs accurate semantic and sentiment analysis to extract and classify medical features as the input to appropriate machine learning classifiers. However, the traditional approach of using single classifiers is limited by the need for dimensionality reduction techniques, statistical feature correlation, a faster learning rate, and the lack of consideration of the semantic relations among features. Hence, extracting semantic and sentiment-based features from clinical text and combining multiple classifiers to create an ensemble intelligent system overcomes many limitations and provides a more robust prediction outcome. The selection of an appropriate approach and its interparameter dependency becomes key for the success of the ensemble method. This paper proposes a hybrid knowledge and ensemble learning framework for prediction of venous thromboembolism (VTE) diagnosis consisting of the following components: a VTE ontology, semantic extraction and sentiment assessment of risk factor framework, and an ensemble classifier. Therefore, a component-based analysis approach was adopted for evaluation using a data set of 250 clinical narratives where knowledge and ensemble achieved the following results with and without semantic extraction and sentiment assessment of risk factor, respectively: a precision of 81.8% and 62.9%, a recall of 81.8% and 57.6%, an F measure of 81.8% and 53.8%, and a receiving operating characteristic of 80.1% and 58.5% in identifying cases of VTE.     

A knowledge construction methodology to automate case-based learning using clinical documents

The case-based learning (CBL) approach has gained attention in medical education as an alternative to traditional learning methodology. However, current CBL systems do not facilitate and provide computer-based domain knowledge to medical students for solving real-world clinical cases during CBL practice. To automate CBL, clinical documents are beneficial for constructing domain knowledge. In the literature, most systems and methodologies require a knowledge engineer to construct machine-readable knowledge. Keeping in view these facts, we present a knowledge construction methodology (KCM-CD) to construct domain knowledge ontology (i.e., structured declarative knowledge) from unstructured text in a systematic way using artificial intelligence techniques, with minimum intervention from a knowledge engineer. To utilize the strength of humans and computers, and to realize the KCM-CD methodology, an interactive case-based learning system(iCBLS) was developed. Finally, the developed ontological model was evaluated to evaluate the quality of domain knowledge in terms of coherence measure. The results showed that the overall domain model has positive coherence values, indicating that all words in each branch of the domain ontology are correlated with each other and the quality of the developed model is acceptable.     

万家寨引黄工程北干线1号隧洞施工方案比选

文中针对引黄北干1号隧洞工程的施工方案，提出了常规钻爆法和TBM施工，并对这两种施工方案进行了比选，最终确定采用TBM施工方案。     

万家寨引黄工程北干1号隧洞Ⅳ标155-274型TBM主轴承总成组装概要

文中对万家寨引黄工程北干线1号隧洞Ⅳ标使用的155—274型TBM主轴承总成各部件组装过程及其相应的技术要求进行了概要的描述，目的是进一步熟悉155—274型TBM主轴承总成的各个部件并加深对主轴承工作原理的理解。     

TBM掘进隧洞回填固结灌浆施工的探讨

豆砾石回填灌浆和固结灌浆在引黄工程南干线长达90kmTBM施工中得到成功的应用。文中介绍了引黄工程南干线4^#-7^#隧洞豆砾石回填灌浆、特殊地质洞段的固结灌浆的灌浆设备、材料、浆液配比、压力、工艺等诸方面的现场施工情况。     

战术弹道导弹落点预报的一种方法

根据椭圆弹道理论，提出了一种可以用于反战术弹道导弹作战的预测弹道及预报落点的方法，给出了算例，并分析了产生误差的原因和对预测结果的影响程度。     

Employing optimized combinations of one-class classifiers for automated currency validation

Automated currency validation requires a decision to be made regarding the authenticity of a banknote presented to the validation system. This decision often has to be made with little or no information regarding the characteristics of possible counterfeits as is the case for issues of new currency. A method for automated currency validation is presented which segments the whole banknote into different regions, builds individual classifiers on each region and then combines a small subset of the region specific classifiers to provide an overall decision. The segmentation and combination of region specific classifiers to provide optimized false positive and false negative rates is achieved by employing a genetic algorithm. Experiments based on high value notes of Sterling currency were carried out to assess the effectiveness of the proposed solution.     

国产掘进机在龙门滩引水隧洞施工中的应用

在长隧洞的施工中，采用掘进机施工的工程越来越多，特别是国外掘进机的引进，加快了长隧洞工程的开发。而国产掘进机由于其性能和材质方面的原因，存在着一定的技术缺陷．通过国产SJ-45型掘进机在龙门滩工程的施工应用，分析和总结了SJ-45型掘进机的机械性能和存在的技术问题及处理结果，以利于国产掘进机的科研、生产和施工。     

Successive pattern classification based on test feature classifier and its application to defect image classification

A novel successive learning algorithm based on a Test Feature Classifier is proposed for efficient handling of sequentially provided training data. The fundamental characteristics of the successive learning are considered. In the learning, after recognition of a set of unknown data by a classifier, they are fed into the classifier in order to obtain a modified performance. An efficient algorithm is proposed for the incremental definition of prime tests which are irreducible combinations of features and capable of classifying training patterns into correct classes. Four strategies for addition of training patterns are investigated with respect to their precision and performance using real pattern data. A real-world problem of classification of defects on wafer images has been dealt with by the proposed classifier, obtaining excellent performance even through efficient addition strategies.     

大伙房水库输水工程TBM维修保养管理模式设计

1 TBM维修管理模式1·1 TBM维修管理模式的源起和思路通过发达国家设备管理模式和我国施工现场设备管理实际情况的比较,国内设备管理工作的成效很大程度上取决于企业的决策者对该项工作的认识,管理水平的高低相差甚远,换一个领导班子就换一种思路,换一批工人就换一种做法,随意性和盲目性比较突出。要改变此状况,可行的做法就是:学习先进的管理经验,设备管理变“人治”为“法治”,制定出科学合理、切实可行的维修保养的模式,形成规范化、标准化、操作性强的文件,作为今后现场设备维修保养的依据。基于此,设备部门在设备安装阶段,利用引进…