Learning Multi Labels from Single Label——An Extreme Weak Label Learning Algorithm

This paper presents a novel algorithm for an extreme form of weak label learning, in which only one of all relevant labels is given for each training sample. Using genetic algorithm, all of the labels in the training set are optimally divided into several non-overlapping groups to maximize the label distinguishability in every group. Multiple classifiers are trained separately and ensembled for label predictions. Experimental results show significant improvement over previous weak label learning algorithms.     

浅析基于电子商务网络安全PKI技术的角色访问控制模型

文本提出了一种区别于传统自主访问控制策略和强制访问控制策略的RBAC网络安全策略,并提出了RBAC的面向对象模型,实现用户身份认证与访问权限的逻辑分离,且易于控制,既能有效的改进系统安全性能,又极大地减少了权限管理的负担。     

Finding finer functions for partially characterized proteins by protein-protein interaction networks

Based on high-throughput data, numerous algorithms have been designed to find functions of novel proteins. However, the effectiveness of such algorithms is currently limited by some fundamental factors, including (1) the low a-priori probability of novel proteins participating in a detailed function; (2) the huge false data present in high-throughput datasets; (3) the incomplete data coverage of functional classes; (4) the abundant but heterogeneous negative samples for training the algorithms; and (5) the lack of detailed functional knowledge for training algorithms. Here, for partially characterized proteins, we suggest an approach to finding their finer functions based on protein interaction sub-networks or gene expression patterns, defined in function-specific subspaces. The proposed approach can lessen the above-mentioned problems by properly defining the prediction range and functionally filtering the noisy data, and thus can efficiently find proteins’ novel functions. For thousands of yeast and human proteins partially characterized, it is able to reliably find their finer functions (e.g., the translational functions) with more than 90% precision. The predicted finer functions are highly valuable both for guiding the follow-up wet-lab validation and for providing the necessary data for training algorithms to learn other proteins.     

现浇框架结构梁、柱、板协同工作体系的有限元方法及其内力特征

应用多种单元集成总刚的有限元法，分析现浇梁、柱、板结构体系在不同工况下的内力分布及组合设计内力，从理论分析角度揭示一些设计计算及构造上值得重视的特征。     

走出科学教育的现代迷茫

科学与人文之争已历经上百年，在以知识为主导的新时代，科学教育倍爱世人的青睐。科学教育既是科学人才的产床，也是人性异化等扼杀人类文明、威胁人类生存的制造之所。科学教育必须走上与人文教育相结合的道路才能走出现代迷惘，并最终使科学真正带给人类以福祉而不是灾难。     

三维动画技术在原子轨道图形表示MCAI中的应用

采用3DSMAX三维动画技术构造原子轨道的角度函数图，通过动画演示，形象，直观地表达了原子轨道的形状特点，极值的方向和节面的位置。     

(E)-3-(3,4-二甲氧基苯基)-2-氰基丙烯酸乙酯的合成和晶体结构

标题化合物C14 H15O4N(3)是由 3,4 二甲氧基苯甲醛 (1) 与氰乙酸乙酯 (2 ) 在KF/蒙脱土催化下以N ,N 二甲基甲酰胺 (DMF)作溶剂反应而得 .结构通过单晶X射线衍射分析确定 ,其晶体属于单斜晶系 ,空间群P2 1/n ,a =1.310 1(3) ,b =0 .80 32 (2 ) ,c =1.385 4 (2 )nm ,β =114 .2 1(1)° ,Mr=2 6 1.2 7,V =1.32 96 (5 )nm3 ,Dc=1.30 5 g/cm3 ,Z =4 ,μ(MoKα) =0 .0 96mm-1,F(0 0 0 ) =5 5 2 .晶体结构用直接法解出 ,使用全矩阵最小二乘法对原子参数进行修正 ,最后的偏离因子R =0 .0 398,RW =0 .0 816 .单晶X衍射分析表明标题化合物为 (E)式异构体产物 ,说明该反应具有立体选择性 .     

反思的现代性与技术理性的解构--海德格尔和福柯论现代技术问题

海德格尔和福柯对于现代技术问题的思考属于某种反思的现代性立场：无论前者对机械技术的本质的追问，还是后者对自我技术的谱系学分析，都没有简单地否定现代技术，而是揭示了现代技术的解蔽和遮蔽双重性。这样的立场告诉我们：面对现代技术的极度张扬，哲学应该坚持一种保守主义姿态，应该在更新的意义上恢复经验的地位。     

Finesse 全瓷冠适合性的体外实验研究

目的 :测量Finesse全瓷冠的边缘浮出量及粘固剂的厚度 ,并与金属全冠及金瓷全冠相比较 ,为Finesse全瓷冠的临床应用提供适合性方面的理论依据。方法 :用片切法测量 3组全冠粘固前、后边缘浮出量及粘固剂的厚度。结果 :Finesse全瓷冠粘固前、后的边缘浮出量分别为 (37 6 1± 9 13) μm、(6 5 85± 15 11) μm ,粘固剂厚度为 (40 84± 9 73) μm ,与金属全冠及金瓷全冠相比较 ,均无显著性差异 ;3组全冠粘固前和粘固后的边缘浮出量有显著性差异。结论 :Finesse全瓷冠适合性良好 ,完全可为临床应用 ;粘接对全冠修复体的边缘浮出量有影响。     

"拾花工"流动现象初探

棉花是新疆生产建设兵团的支柱产业之一.丰收的棉花需要保质保量的完全收回,于是拾棉花的季节工象"候鸟"一样往返于内地与兵团之间,产生了拾花经济产业."拾花工"的流动现象、存在的现状和问题及今后的发展前途亟待理论性指导.