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关键词： High dimension   Small sample size   Meta-classification   Ensemble classifier   Microarray data   OPTIMAL ENSEMBLE CLASSIFIERS   FEATURE-SELECTION   DNA   FEATURES   ALGORITHM   PROFILES   LYMPHOMA   PATTERNS   TUMOR  

摘要： Classification using small sample size (limited number of samples) with high dimension is a challenging problem in both machine learning and medicine as there are a wide variety of possible modeling approaches. Furthermore, it is not always clear which method is optimal for a prediction task. Different modeling choices include feature selection (dimensionality reduction), classification algorithms, and ensemble selection. There are several possible combinations of these methods, and it is not always clear which is the best. In the previous works, researchers show that evolutionary computation is useful to build an ensemble from the pairs of feature selection and classification algorithms. However, there are several parameters to be determined for the evolutionary computation and it requires computational time for the optimization. In this paper, we attempt to improve the approach by adopting meta-classification with the farthest-first clustering algorithm. The effectiveness and accuracy of our method are validated by experiments on four real micro-array datasets (colon, breast, prostate and lymphoma cancers) publicly available. The results confirm that the proposed method outperforms single individual classifiers and other alternatives (standard genetic algorithm, and methods from literature).

关键词： Airline merger   Mergers & acquisitions   Synergies   Cost synergies   Revenue synergies   PERFORMANCE   ALLIANCES   ACQUISITIONS  

摘要： Deregulation, privatization and shifting demand patterns in the airline industry, combined with the emergence of low-cost airlines and rising fuel prices have increased the competitive pressure on legacy airlines. Since alliances do not deliver sufficient benefits to counterbalance these trends, many airlines have engaged in mergers to seek for additional cost and revenue synergies. An extent body of literature investigates the synergy potential in mergers and alliances, but there is no study on how synergies differ among mergers and what potential influence factors cause these differences. This paper aims at explaining differences in synergy estimates and realized synergies in recent airline mergers and places a special focus on geographical influence factors. The research methodology uses a comparative case study comprising six large airline mergers between 2003 and 2012 from Europe, North America and Latin America. After analyzing the cases individually, the pre-merger situation of the merging airlines, the synergy estimates and the realized synergies of the cases were compared. The results show considerable geographical differences in pre-merger cost structures, synergy estimates, and synergy realization. The European mergers present lower synergy estimates but also lower integration costs than mergers in the Americas. Whereas European airlines estimate cost synergies higher than revenue synergies, both North and Latin American airlines expect more revenue synergies than cost synergies from airline mergers. Only one merger showed superior post-merger profitability which indicates that the achieved synergies in the broad majority of the cases are insignificant. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Directed acyclic graph support vector machines   Benthic macroinvertebrates   Machine learning   Classification   IDENTIFICATION  

摘要： Freshwater areas are an evanescent resource in the globe and, hence, the water quality assessment and examination of human induced changes on aquatic ecosystems are important. Benthic macroinvertebrates are excellent indicators of the state of freshwater area due to their intermediate life cycle and their ability to react changes in an aquatic ecosystem. However, identifying the benthic macroinvertebrates is a slow and expensive task when the process is human-made. Thus, we have an excellent opportunity to save resources by using sophisticated machine learning and pattern recognition methods. In this research we applied Directed Acyclic Graph Support Vector Machine (DAGSVM) and six other baseline methods in automated benthic macroinvertebrate classification. We performed wide experimental tests with six different feature sets where one was chosen by Scatter method. Furthermore, in the case of DAGSVM we tested every feature set with seven kernel functions. Experimental results showed that Scatter method is a good feature selection algorithm and we obtained above 80 % accuracy in classifications which is a very good result for such a challenging classification task. From all tested classification methods DAGSVM showed to be the best alternative for this classification task.

关键词： binary data   double sampling   identifiability   misclassification   contingency table   FALSE-POSITIVE MISCLASSIFICATION   CONFIDENCE-INTERVALS   BAYESIAN-APPROACH   SUBJECT   SCHEME  

摘要： In this article, we construct two likelihood-based confidence intervals (CIs) for a binomial proportion parameter using a double-sampling scheme with misclassified binary data. We utilize an easy-to-implement closed-form algorithm to obtain maximum likelihood estimators of the model parameters by maximizing the full-likelihood function. The two CIs are a naive Wald interval and a modified Wald interval. Using simulations, we assess and compare the coverage probabilities and average widths of our two CIs. Finally, we conclude that the modified Wald interval, unlike the naive Wald interval, produces close-to-nominal CIs under various simulations and, thus, is preferred in practice. Utilizing the expressions derived, we also illustrate our two CIs for a binomial proportion parameter using real-data example.

关键词： MODIS TIME-SERIES   SPATIAL-RESOLUTION   IMAGE CLASSIFICATION   CONTINUOUS FIELD   LATIN-AMERICA   MAP   DATABASE   GENERATION   REGRESSION   SELECTION  

摘要： Land cover mapping for large regions often employs satellite images of medium to coarse spatial resolution, which complicates mapping of discrete classes. Class memberships, which estimate the proportion of each class for every pixel, have been suggested as an alternative. This paper compares different strategies of training data allocation for discrete and continuous land cover mapping using classification and regression tree algorithms. In addition to measures of discrete and continuous map accuracy the correct estimation of the area is another important criteria. A subset of the 30 m national land cover dataset of 2006 (NLCD2006) of the United States was used as reference set to classify NADIR BRDF-adjusted surface reflectance time series of MODIS at 900 m spatial resolution. Results show that sampling of heterogeneous pixels and sample allocation according to the expected area of each class is best for classification trees. Regression trees for continuous land cover mapping should be trained with random allocation, and predictions should be normalized with a linear scaling function to correctly estimate the total area. From the tested algorithms random forest classification yields lower errors than boosted trees of C5.0, and Cubist shows higher accuracies than random forest regression.

关键词： Logistic regression   Classification   Oil analysis   Mining trucks   Machine health   Neural networks   Support vector machine   Receiver operating characteristic curve   ARTIFICIAL NEURAL-NETWORKS   SUPPORT VECTOR MACHINES   FAULT-DIAGNOSIS   DEGRADATION ASSESSMENT   FEATURE-EXTRACTION   ELEMENT BEARING   CLASSIFICATION   MAINTENANCE   DECOMPOSITION   TRANSFORM  

摘要： The era of big data has resulted in an explosion of condition monitoring information. The result is an increasing motivation to automate the costly and time consuming human elements involved in the classification of machine health. When working with industry it is important to build an understanding and hence some trust in the classification scheme for those who use the analysis to initiate maintenance tasks. Typically "black box" approaches such as artificial neural networks (ANN) and support vector machines (SVM) can be difficult to provide ease of interpretability. In contrast, this paper argues that logistic regression offers easy interpretability to industry experts, providing insight to the drivers of the human classification process and to the ramifications of potential misclassification. Of course, accuracy is of foremost importance in any automated classification scheme, so we also provide a comparative study based on predictive performance of logistic regression, ANN and SVM. A real world oil analysis data set from engines on mining trucks is presented and using cross-validation we demonstrate that logistic regression out-performs the ANN and SVM approaches in terms of prediction for healthy/not healthy engines. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： 内部控制   投资者保护   知情权   决策权   收益权  

摘要： 内部控制可通过直接机制对投资者知情权、决策权、收益权起到保护作用,通过间接机制提高会计信息质量,实现对投资者知情权的保障。本文构建了投资者基本权利保护程度指标体系以及过程指标与结果指标相结合的内部控制质量评价体系,能实现投资者基本权利和企业内部控制质量的定量化评价。通过实证检验发现:基于我国特殊的制度环境,投资者决策权保护效果最好,其次为知情权,最后为收益权;高质量的内部控制质量有助于投资者知情权、收益权、决策权的实现,但作用力却依次递减。

关键词： BLOCK-COPOLYMERS   BILAYERS   DRUG   HYDROPHOBICITY   TRANSLOCATION   BIOMEMBRANES   ADSORPTION   STABILITY   LIPOSOMES   POLYMERS  

摘要： We investigate interactions of linear amphiphilic ABA triblock copolymers with lipid bilayer membranes by means of Monte Carlo simulations in a generic coarse-grained model. The polymers have hydrophilic A-blocks and B-blocks of varying hydrophobicity. The effect of different conformational states of the polymer on the induced permeability for solvent molecules is examined. We demonstrate that the local permeability of the membrane can be strongly increased in the transmembrane state, in particular for a mismatch in the hydrophobicity between the middle block and the membrane core, while the hairpin state has almost no effect on this property, especially for growing hydrophobic mismatch. We have investigated the relative stability of the two states using thermodynamic integration and have shown that only in a range of intermediate hydrophobic block lengths NB and hydrophobicities H-B the transmembrane state is stable. Increasing mismatch of the B-block in terms of relative hydrophobicity and block length not only causes stronger perturbations in the membrane if the polymer is in the transmembane state but also renders this state metastable. Our studies support in particular previous experimental studies suggesting a two-state model of PEO-PPO-PEO copolymers.

关键词： 新生儿   溶血   生化检验   作用  

摘要： 目的:分析新生儿溶血样本对生化检验结果的作用及优化措施。方法:选取我院2011年3月-2015年2月期间接受生化检验的138例新生儿作为研究对象,所有患儿均按照常规方式采集两管血液标本,并分别作为溶血标本和未溶血标本,对两组试管进行血常规检测,检测指标包括谷丙转氨酶、总胆红素、直接胆红素、尿酸、谷氨酰转肽酶、谷草转氨酶水平并进行对比。结果:检测结果显示,溶血组新生儿谷丙转氨酶、总胆红素、直接胆红素、尿酸、谷草转氨酶水平均显著低于未溶血组(P<0.05),谷氨酰转肽酶水平均显著高于未溶血组(P<0.05)。结论:新生儿溶血样本会对生化检验结果造成很大的影响,尤其是谷丙转氨酶、总胆红素、直接胆红素、尿酸、谷氨酰转肽酶、谷草转氨酶水平,需引起临床人员重视,在开展溶血检验过程中积极通过合理选择采血点、采血方式等优化措施,避免或减少溶血发生。

关键词： 糖尿病   生化检验指标   临床作用  

摘要： 目的：探讨生化检验指标在糖尿病诊断中的临床作用。方法：选取2012年3月～2015年3月进行生化检验的120例体检者作为研究对象，60例正常健康体检者为对照组，60例糖尿病患者为观察组。结果：观察组糖尿病患者的空腹血糖（FPG）、餐后2h 血糖、糖化血红蛋白（HbAlc）、血清甘油三酯（TG）、总胆固醇（TC）均明显高于对照组（P ＜0.05）。结论：生化检验指标可以有效反应糖尿病患者各项指标变化，有利于糖尿病诊断及治疗结果判断。