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关键词： Element   Lung cancer   Diagnosis   Chemometrics   PARTIAL LEAST-SQUARES   TRACE-ELEMENTS   DIAGNOSIS   SELENIUM   BLOOD   SERUM   CARCINOGENESIS   SPECTROSCOPY   DEFICIENCY   TISSUE  

摘要： The detection of lung cancer has a special value in the diagnosis of cancer diseases. Based on nine elemental concentrations (i.e., chromium, iron, manganese, aluminum, cadmium, copper, zinc, nickel, and selenium) in urine samples and an ensemble linear discriminant analysis (ELDA), a detection method for lung cancer has been developed. A dataset containing 30 healthy samples and 27 lung cancer samples is used for experiment. The whole dataset was first split into a training set with 29 samples and a test set with 28 samples. The prediction results from the ELDA classifier were compared with those from single Fisher's discriminate analysis (FDA). On the test set, the ELDA classifier achieved better performance, that is, a sensitivity of 100%, a specificity of 86.7%, and an overall accuracy of 92.9%, while the FDA classifier had a sensitivity of 92.3%, a specificity of 93.3%, and an overall accuracy of 92.9%. The superiority of ELDA to FDA is ascribed to the fact that ELDA can model more nonlinear relationships through the cooperation of several single models, suggesting that ensemble modeling is more advisable in such a task.

关键词： Water sample authentication   Electronic tongue   Machine learning   PLS   Pulse voltametry   PCA   PARTIAL LEAST-SQUARES   POTENTIOMETRIC ELECTRONIC TONGUE   SIMULTANEOUS QUANTIFICATION   QUANTITATIVE-ANALYSIS   SENSORS   RECOGNITION   ARRAY   IONS   MILK   VOLTAMMETRY  

摘要： This paper proposes the development of water sample classification and authentication, in real life which is based on machine learning algorithms. The proposed techniques used experimental measurements from a pulse voltametry method which is based on an electronic tongue (E-tongue) instrumentation system with silver and platinum electrodes. E-tongue include arrays of solid state ion sensors, transducers even of different types, data collectors and data analysis tools, all oriented to the classification of liquid samples and authentication of unknown liquid samples. The time series signal and the corresponding raw data represent the measurement from a multi-sensor system. The E-tongue system, implemented in a laboratory environment for 6 numbers of different ISI (Bureau of Indian standard) certified water samples (Aquafina, Bisleri, Kingfisher, Oasis, Dolphin, and McDowell) was the data source for developing two types of machine learning algorithms like classification and regression. A water data set consisting of 6 numbers of sample classes containing 4402 numbers of features were considered. A PCA (principal component analysis) based classification and authentication tool was developed in this study as the machine learning component of the E-tongue system. A proposed partial least squares (PLS) based classifier, which was dedicated as well; to authenticate a specific category of water sample evolved out as an integral part of the E-tongue instrumentation system. The developed PCA and PLS based E-tongue system emancipated an overall encouraging authentication percentage accuracy with their excellent performances for the aforesaid categories of water samples. (C) 2011 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： VLE data prediction   Binary interaction parameters   Cubic equations of state   PENG-ROBINSON EQUATION   VAPOR-LIQUID-EQUILIBRIUM   PPR78 MODEL   PREDICTIVE 1978   PHASE-EQUILIBRIA   OF-STATE   MIXING RULES   K(IJ)   EOS   SYSTEMS  

摘要： Vapor-liquid equilibrium (VLE) data are important in the optimization of thermodynamic cycles. As energy concerns continue to grow, improving the efficiencies of power and refrigeration cycles is increasingly important. Numerical simulations using empirical equations of state provide an excellent alternative to time consuming experimental measurement of VLE data. However, it is important to understand the limitations of using correlative equations for data prediction. In this study, a water-ethanol mixture is simulated with various VLE models. Non-optimal binary interaction parameters are considered and model accuracy is evaluated in terms of average absolute percent deviation (%AAD) between simulated and experimental bubble and dew point pressures. For this system, it is found that as the correlative accuracy of a model increases, the predictive ability decreases. Specifically, the temperature dependence of the binary interaction parameters is shown to be an important consideration for the water-ethanol system when more complex combining rules are implemented. (C) 2011 Elsevier B.V. All rights reserved.

关键词： 安全分析   动火   进塔入罐   奥氏仪  

摘要： 本文通过对化工生产中的安全分析的论述,讨论了如何通过检验分析加强化工安全生产的安全稳定运行,真正使检验分析成为化工生产不可缺少的一个环节.

关键词： 危急值   准确性   医疗质量管理   医疗安全  

摘要： 本文阐述了危急值的概念,探讨了如何建立危急值和保证危急值的准确性,总结了危急值报告制度应用于医疗质量管理和医疗安全中的重要意义,并指出我院检验科目前危急值管理中存在的局限性和不足。

关键词： 劳动合同   立法模式   理由  

摘要： 一般来讲,劳动合同形式的立法模式决定着劳动合同条款的性质。文章结合我国劳动合同立法的实际,就劳动合同采用书面形式的理由、事实劳动关系概念及其表现形式、劳动关系建立或劳动合同订立与劳动合同必备条款的关系等进行了分析,并提出了自己的看法。

关键词： 再生利用   包装物   联盟   教育活动   垃圾分类   行业   凝聚   生活  

摘要： 2011年5月31日,由中国包装联合会、利乐公司和多家乳品饮料企业联合发起的包装物再生利用联盟在北京正式成立。来自全国人大、环境保护部、国家发改委、环保宣教中心和中国包装联合会的领导以及联盟发起成员企业的代表出席了成立仪式。

关键词： 修船企业   案件处理   船舶修理合同   违约   成功   法律关系   合同主体   自身权益  

摘要： 在船舶修理合同的履行过程中，由于合同主体之间法律关系的复杂性和修船业务的特殊性，合同双方经常会产生纠纷。纠纷发生时承修方如何有效保护自身权益，是国内修船企业普遍关注的问题。

关键词： 外汇干预   资产组合渠道   有效性  

摘要： 2005年7月人民币汇率制度改革以来,人民币升值的压力不断加大。因此,我国中央银行进行了频繁、大规模的外汇干预,同时通过多种公开市场操作手段对由于外汇占款引发的基础货币增加进行冲销。文章对我国外汇干预能否通过资产组合渠道发挥效力进行了实证检验。检验结果表明我国外汇干预能够影响风险溢价,因此外汇干预行为可以通过资产组合渠道发挥效力。

关键词： 淀粉包装   粉尘爆炸   场所分类  

摘要： 淀粉粉尘属于可燃性非导电爆炸性粉尘，淀粉包装工段有很高的粉尘爆炸危险性，在设计和生产中应采取相应措施预防粉尘爆炸。