序列模式挖掘的两种典型算法及比较

序列模式挖掘是数据挖掘的重要分支,GSP算法与PSP算法是序列模式挖掘中的两种典型算法。本文介绍了这两种算法并对其进行了分析与比较。     

多维函数全局寻优的团队进步算法

通过模仿团队进步需要的学习、探索行为和成员更新规则,提出了一种新颖的双群体演化算法,称为团队进步算法(TPA).算法将一个团队的成员分为精英和普通组,建立了两组的学习样板,定义了学习和探索运算,并合理设定了成员更新规则.两组成员在搜索过程中出现了明显分工,使算法兼备了全局搜索、局部搜索和定向搜索的能力.数值试验结果验证了新算法具有实现简单、全局寻优成功率高、收敛快、计算量少、坚韧性强和参数选择相对容易等特性,对解决优化应用问题具有较大的价值.     

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.     

基于手机的无线搜索技术

无线搜索已成为一个新的研究、开发领域.并且它主要用到信息检索、人工智能、数据挖掘、自然语言处理、排序算法等多领域的理论和技术.此外,它拥有大量的用户,有很好的经济价值,所以引起了世界各国计算机科学界和信息产业界的高度关注,目前的研究、开发十分活跃,并出现了很多值得注意的动向.     

并行算法软件库PASL

本文介绍了并行算法软件库ＰＡＳＬ。ＰＡＳＬ库运行在具有共享存储的多处理机上，它可以用于科学工程计算和仿真。     

多幅图像显示时色彩压缩的聚类统计算法

在计算机上，同屏显示多幅彩色图像会出现明显的失真（即色彩损失）．特别是两幅图像色调差别较大时（如一幅暖色调，一幅冷色调），失真现象更为严重．为了克服这一缺陷．本文在参考Ｋ均值聚类算法的基础上，优化了初始聚类中心，提出了色彩压缩的聚类统计算法．本算法简单实现较为方便，克服了Ｋ均值算法对色彩压缩不均衡及彩色失真度大的缺点．且不需经过多次迭代即可得到令人满意的效果，压缩时间短．     

关于非平凡的黎斯算子

讨论一般巴拿赫空间上非紧的黎斯算子存在问题,说明各经典巴拿赫空间上确有这种非平凡的黎斯算子,给出一类空间,其上的根算子理想与严格奇异算子理想是不重合的。     

The estimation-valued property of B-valued asymptotic martingale

In this paper, with the Doob decomposition of B-valued asymptotic martingale, we study the estimation-valued property of B-valued asymptotic martingale in Banach space B,which has the Radon-Nikodym Property and is dual-separable, and give a series of result and proof.     

蒙山脆枣与枣及酸枣亲缘关系的研究

以蒙山脆枣及山东省内的9个枣品种和32个酸枣类型(株系)为试材,采用形态学分析和RAPD分析,对蒙山脆枣与枣及酸枣的亲缘关系进行研究,并初步探讨了蒙山脆枣的起源及枣的演化过程。形态学性状数据主成分分析结果表明,蒙山脆枣第1主成分值为5.42,第2主成分值为0.64,介于枣品种和酸枣类型之间,地位较为特殊。对形态学性状数据聚类,结果表明,蒙山脆枣先与酸枣1号在6.40阈值处聚为一类,再与大枣品种的聚类群在11.75阈值处聚为1类之后,才与其它酸枣类型的聚类群聚为一类,显示出蒙山脆枣的分类地位介于枣和酸枣之间。进一步的RAPD分析结果表明,蒙山脆枣与酸枣亲缘关系较近。蒙山脆枣果实长2cm左右,外果皮较薄,中果皮较厚,平均单果重为3.64g,叶片纵横径为6.93cm×3.08cm,形态学性状与枣接近,推测蒙山脆枣可能为供试酸枣类型与枣品种的中间类型。