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关键词： 业主   合同解除   费用   处理   合同管理  

摘要： 某公路工程由于业主违约并提出解除合同,经过协商承包人同意有条件解除。本文重点介绍在合同解除时,监理工程师对承包人提出的主要合同问题的处理。

关键词： Feature selection   Support vector machine (SVM)   Diseases classification   Recursive feature elimination (RFE)  

摘要： There are growing numbers of studies using machine learning approaches to characterize patterns of anatomical difference discernible from neuroimaging data. The high-dimensionality of image data often raises a concern that feature selection is needed to obtain optimal accuracy. Among previous studies, mostly using fixed sample sizes, some show greater predictive accuracies with feature selection, whereas others do not. In this study, we compared four common feature selection methods. 1) Pre-selected region of interests (ROIs) that are based on prior knowledge. 2) Univariate t-test filtering. 3) Recursive feature elimination (RFE), and 4) t-test filtering constrained by ROIs. The predictive accuracies achieved from different sample sizes, with and without feature selection, were compared statistically. To demonstrate the effect, we used grey matter segmented from the T1-weighted anatomical scans collected by the Alzheimer's disease Neuroimaging Initiative (ADNI) as the input features to a linear support vector machine classifier. The objective was to characterize the patterns of difference between Alzheimer's disease (AD) patients and cognitively normal subjects, and also to characterize the difference between mild cognitive impairment (MCI) patients and normal subjects. In addition, we also compared the classification accuracies between MCI patients who converted to AD and MCI patients who did not convert within the period of 12 months. Predictive accuracies from two data-driven feature selection methods (t-test filtering and RFE) were no better than those achieved using whole brain data. We showed that we could achieve the most accurate characterizations by using prior knowledge of where to expect neurodegeneration (hippocampus and parahippocampal gyrus). Therefore, feature selection does improve the classification accuracies, but it depends on the method adopted. In general, larger sample sizes yielded higher accuracies with less advantage obtained by using knowle

关键词： Contracts   Contract negotiations   Adhesives   Fine print   Readership   Educational attainment   Internet   Reading   Experiment design  

摘要： Recent empirical research has established what many assumed -few people read form contracts. This research employs an online experimental design to fill gaps in the literature by asking two important questions: (1) To what extent does information about the exchange beyond the contract substitute for information in the contract, so that more external information reduces contract reading? (2) Is there a relationship between form-contract readership and contract performance? Results suggest that individuals spend almost three times more time reviewing form contracts when less information is provided outside the contract, and that greater time spent reviewing form contracts is associated with increased contract performance.

关键词： Root Mean Square Error   Learning Curve   Active Learning   Mean Absolute Error   Annotate Data  

摘要： Background: Supervised learning methods need annotated data in order to generate efficient models. Annotated data, however, is a relatively scarce resource and can be expensive to obtain. For both passive and active learning methods, there is a need to estimate the size of the annotated sample required to reach a performance target. Methods: We designed and implemented a method that fits an inverse power law model to points of a given learning curve created using a small annotated training set. Fitting is carried out using nonlinear weighted least squares optimization. The fitted model is then used to predict the classifier's performance and confidence interval for larger sample sizes. For evaluation, the nonlinear weighted curve fitting method was applied to a set of learning curves generated using clinical text and waveform classification tasks with active and passive sampling methods, and predictions were validated using standard goodness of fit measures. As control we used an un-weighted fitting method. Results: A total of 568 models were fitted and the model predictions were compared with the observed performances. Depending on the data set and sampling method, it took between 80 to 560 annotated samples to achieve mean average and root mean squared error below 0.01. Results also show that our weighted fitting method outperformed the baseline un-weighted method (p < 0.05). Conclusions: This paper describes a simple and effective sample size prediction algorithm that conducts weighted fitting of learning curves. The algorithm outperformed an un-weighted algorithm described in previous literature. It can help researchers determine annotation sample size for supervised machine learning.

关键词： Alzheimer"s disease   mild cognitive impairment   support vector machines   shape analysis   feature selection  

摘要： It is well known that hippocampal atrophy is a marker of the onset of Alzheimer"s disease (AD) and as a result hippocampal volumetry has been used in a number of studies to provide early diagnosis of AD and predict conversion of mild cognitive impairment patients to AD. However, rates of atrophy are not uniform across the hippocampus making shape analysis a potentially more accurate biomarker. This study studies the hippocampi from 226 healthy controls, 148 AD patients and 330 MCI patients obtained from T1 weighted structural MRI images from the ADNI database. The hippocampi are anatomically segmented using the MAPS multi-atlas segmentation method, and the resulting binary images are then processed with SPHARM software to decompose their shapes as a weighted sum of spherical harmonic basis functions. The resulting parameterizations are then used as feature vectors in Support Vector Machine (SVM) classification. A wrapper based feature selection method was used as this considers the utility of features in discriminating classes in combination, fully exploiting the multivariate nature of the data and optimizing the selected set of features for the type of classifier that is used. The leave-one-out cross validated accuracy obtained on training data is 88.6% for classifying AD vs controls and 74% for classifying MCI-converters vs MCI-stable with very compact feature sets, showing that this is a highly promising method. There is currently a considerable fall in accuracy on unseen data indicating that the feature selection is sensitive to the data used, however feature ensemble methods may overcome this.

关键词： 交叉感染   综合预防   组织和管理   学生保健服务  

摘要： 高校是人口居住密集、有特定功能的自然社区。高校医疗机构长期为广大师生提供基本医疗、预防保健、计划免疫、健康教育等社区卫生服务工作[1]。但随着社会医疗保险制度的实施和高校后勤社会化改革的推行,为了适应社会发展的客观需要,高校医院可以对外开放以满足附近居民的健康服务需求。近年来,到高校医院就诊的人群逐渐发生变化,除教职工、大学生、离退休教师之外,还包括众多教职工家属、外来培训人员、学校周边居民、外来务工人员以及留学生和专家等。

关键词： 质量安全   行业发展   招商选资   名牌战略  

摘要： 本文简要阐述了国家皮革制品质量监督检验中心（广州）的技术能力，及为政府履职、产业升级、地方经济、企业提升等提供强有力的技术保障和促进作用。

关键词： 包装设计   趣味性   材料   形式  

摘要： 随着科技的发展,包装设计者拥有了更多的选择和更大的可能性。但相当多的包装设计一味地以高成本和新技术取胜,而存在创新不足的问题。对包装趣味性的研究和分析成了丰富包装形式、拓展设计思维的一个有效手段。笔者试对趣味性包装设计的类别和形式进行梳理和归类,并探讨了多种趣味包装的设计手法,以期对包装设计的多样化有所贡献。

关键词： 微生物检验   医院感染   感染控制  

摘要： 目的：探讨微生物检验在控制医院内感染的作用，为加强对医院感染的控制提供参考思路。方法：总结分析微生物检验在在指导临床合理应用抗生素的资料以及在控制医院感染中扮演的发挥的作用。结果：传染源、传播途径以及易感人群都与微生物检验有着极为密切的联系，微生物检验在监测发生医院感染的各个环节发挥重要作用。结论：微生物检验在控制医院感染中能发挥积极的作用，医院应充分利用微生物检验具有的这一优势，以有效控制日益严重的医院感染。

关键词： 医院感染监测   微生物实验室   检验科   医院感染管理   医院感染控制   控制医院感染   抗菌药物使用   平均发病率  

摘要： 根据WHO的调查，在欧洲、东南亚等地医院感染的平均发病率人8，7％。在美国每年发生的医院感染超过两百万例，每例感染增加的直接医疗支出5834886美金，因为医院感染致死者达数万例。医院感染己严重影响到患者的医疗安全，为此国内外也颁布了多条法律法规，再三强调了控制医院感染的重要性：2006年卫生部颁布了《医院感染管理办法》以代替2000年颁布的《医院感染管理规范》，并成立了卫生部医院感染控制标准委员会：建立全国和省市的抗菌药物使用和耐药性监测网，出台临床用药管理规定。新一轮的医院感染控制热潮正在中国兴起。