Status Set Sequential Pattern Mining Considering Time Windows and Periodic Analysis of Patterns

The traditional sequential pattern mining method is carried out considering the whole time period and often ignores the sequential patterns that only occur in local time windows, as well as possible periodicity. Therefore, in order to overcome the limitations of traditional methods, this paper proposes status set sequential pattern mining with time windows (SSPMTW). In contrast to traditional methods, the item status is considered, and time windows, minimum confidence, minimum coverage, minimum factor set ratios and other constraints are added to mine more valuable rules in local time windows. The periodicity of these rules is also analyzed. According to the proposed method, this paper improves the Apriori algorithm, proposes the TW-Apriori algorithm, and explains the basic idea of the algorithm. Then, the feasibility, validity and efficiency of the proposed method and algorithm are verified by small-scale and large-scale examples. In a large-scale numerical example solution, the influence of various constraints on the mining results is analyzed. Finally, the solution results of SSPM and SSPMTW are compared and analyzed, and it is suggested that SSPMTW can excavate the laws existing in local time windows and analyze the periodicity of the laws, which solves the problem of SSPM ignoring the laws existing in local time windows and overcomes the limitations of traditional sequential pattern mining algorithms. In addition, the rules mined by SSPMTW reduce the entropy of the system.     

表面喷砂对有机玻璃沿面闪络性能影响

绝缘子表面粗糙处理是提升其沿面闪络性能的重要途径,表面粗糙化处理方式不当,极易带来表面结构不均匀,难以获得稳定耐压性能的绝缘材料。为提升绝缘子表面粗糙处理的均匀性,本文利用表面喷砂技术对圆柱形有机玻璃（PMMA）绝缘子进行了粗糙化处理研究,以球形二氧化硅（SiO₂）颗粒为工作介质,研究了不同喷砂粒径、氢氟酸后处理等因素对绝缘材料表面形貌和组分的影响,并利用短脉冲高压测试平台对喷砂处理前后有机玻璃绝缘子样品进行了真空沿面闪络性能测试。研究结果表明,喷砂处理在有机玻璃表面形成了较为均匀的凹坑,HF酸能够有效去除表面残留的SiO₂颗粒,具有表面喷砂粗糙结构的绝缘子沿面闪络电压得到了稳定提升,相较于未处理的绝缘子闪络电压提升了约80%。     

Lazy structure-activity relationships (lazar) for the prediction of rodent carcinogenicity and Salmonella mutagenicity

lazar is a new tool for the prediction of toxic properties of chemical structures. It derives predictions for query structures from a database with experimentally determined toxicity data. lazar generates predictions by searching the database for compounds that are similar with respect to a given toxic activity and calculating the prediction from their activities. Apart form the prediction, lazar provides the rationales (structural features and similar compounds) for the prediction and a reliable condence index that indicates, if a query structure falls within the applicability domain of the training database. Leave-one-out (LOO) crossvalidation experiments were carried out for 10 carcinogenicity endpoints ({female|male} {hamster|mouse|rat} carcinogenicity and aggregate endpoints {hamster|mouse|rat} carcinogenicity and rodent carcinogenicity) and Salmonella mutagenicity from the Carcinogenic Potency Database (CPDB). An external validation of Salmonella mutagenicity predictions was performed with a dataset of 3895 structures. Leave-one-out and external validation experiments indicate that Salmonella mutagenicity can be predicted with 85% accuracy for compounds within the applicability domain of the CPDB. The LOO accuracy of lazar predictions of rodent carcinogenicity is 86%, the accuracies for other carcinogenicity endpoints vary between 78 and 95% for structures within the applicability domain.     

典型煤的近红外反射光谱特征的方向性研究

高光谱遥感是煤矿区探测的有效方法,对于煤炭资源调查、矿区环境监测等具有重要意义,其中煤、矸石、植被、水体等被遥测物各个方向的反射光谱特征是煤矿高光谱遥感的基础,为此有必要针对典型煤的方向反射光谱特征进行研究.从我国不同矿区收集了无烟煤、烟煤、褐煤三大类煤中的4种典型煤样,4种煤样按煤阶由高到低顺序包括无烟煤一号、贫煤、...     

Solitary wave solutions of nonlinear financial markets :data-modeling-concept-practicing

This paper seeks to solve the difficult nonlinear problem in financial markets on the complex system theory and the nonlinear dynamics principle, with the data-model-concept-practice issue-oriented reconstruction of the phase space by the high frequency trade data. In theory, we have achieved the differentiable manifold geometry configuration, discovered the Yang-Mills functional in financial markets, obtained a meaningful conserved quantity through corresponding space-time non-Abel localization gauge symmetry transformation, and derived the financial solitons, which shows that there is a strict symmetry between manifold fiber bundle and guage field in financial markets. In practical applications of financial markets, we have repeatedly carried out experimental tests in a fluctuant evolvement, directly simulating and validating the existence of solitons by researching the price fluctuations (society phenomena) using the same methods and criterion as in natural science and in actual trade to test the stock Guangzhou Proprietary and the futures Fuel Oil in China. The results demonstrate that the financial solitons discovered indicates that there is a kind of new substance and form of energy existing in financial trade markets, which likely indicates a new science paradigm in the economy and society domains beyond physics.      

Exploring structure–selectivity relationships of biogenic amine GPCR antagonists using similarity searching and dynamic compound mapping

We design and analyze compound selectivity sets of antagonists with differential selectivity against seven biogenic amine G-protein coupled receptors. The selectivity sets consist of a total of 267 antagonists and contain a spectrum of in part closely related molecular scaffolds. Each set represents a different selectivity profile. Using these com- pound sets, a systematic computational analysis of structure-selectivity relationships is carried out with different 2D similarity methods including fingerprints, recursive partitioning, clustering, and dynamic compound mapping. Screening calculations are performed in a background database containing nearly four million molecules. Fingerprint searching and compound mapping are found to enrich target-selective antagonists over family-selective ones. Dynamic compound mapping effectively discriminates database compounds from GPCR antagonists and consistently retains target-selective antagonists during the final dimension extension levels. Furthermore, the widely used MACCS key fingerprint displays a strong tendency to distinguish between target- and family-selective GPCR antagonists. Taken together, the results indicate that different types of 2D similarity methods are capable of distinguishing closely related molecules having different selectivity. The reported compound benchmark system is made freely available in order to enable selectivity-oriented analyses using other computational approaches.     

基于多支持度的增量式关联规则挖掘算法

传统的基于关联规则的挖掘算法采用的是统一的最小支持度,但是在实际的事务数据库中数据项的重要性是不同的。针对目前多支持度和增量式关联规则更新维护的局限性,提出一种基于多支持度的增量式关联规则挖掘算法。允许用户根据不同项的重要性设置权值,有利于发现更多有趣的规则。采用矩阵的向量内积策略,结合动态剪枝,无需多次扫描事务数据库,不生成庞大候选集。实验结果验证了算法的有效性。更多还原     

应用数据挖掘的束流状态描述建模

聚类分析是描述数据群体特征的有效方法.然而,随着挖掘数据库规模的增大,评分函数极值搜索是计算复杂度很高的问题.文中提出了一种新的算法,并将其运用到束流状态描述建模中.试验结果表明,该算法快速有效.同时,重复性是电子储存环的重要指标,聚类模型可作为机器研究和决策的依据,具有指导意义.     

SDSS-DR10中WDMS光谱的自动搜索研究

SDSS-DR10是美国SLOAN巡天望远镜发布的最新数据,包含了首批APOGEE光谱。这些海量的天文光谱除了可以用来探寻银河系的结构和进行多波段证认外,还蕴藏着包括白矮主序双星在内的特殊天体。白矮主序双星是一类特殊的双星系统,它由两颗主序星演化而来,包含了中低质量恒星演化的终点—白矮星,以及M矮星。白矮主序双星对于密近双星的演化和参数研究有积极的意义。目前针对这类特殊天体的发现主要使用测光筛选结合后期观测证认的方法,不但准确率低,而且需要耗费较多的人工处理时间,无法满足在海量光谱数据中快速发现目标天体的需要。提出一种适用于在海量天文光谱中自动、快速发现白矮主序双星的方法。该方法针对SDSS的DR10数据,使用改进的遗传算法对海量光谱进行自动识别,寻找白矮主序双星候选体。实验共发现了4, 140个白矮主序双星,通过交叉证认,其中24个是未被收录的新的源。验证了遗传算法在天文数据挖掘和自动搜索方面的有效性,为在海量光谱中快速发现特殊天体提供了另一途径。该方法也可用于在其他巡天望远镜的海量光谱中进行特定天体的自动识别。提供了新发现的白矮主序双星的赤经、赤纬等信息,补充了现有的白矮主序双星光谱库。     

铅锌矿区居民头发中Pb，As，Cd等有害元素含量、微区分布及元素形态特征研究

头发是人体元素的排泄器官之一,头发中元素含量能反映出一段时间内矿区毒性元素在人体内的吸收和代谢情况。采用电感耦合等离子体质谱(ICP-MS)和电感耦合等离子体原子发射光谱(ICP-OES)对某铅锌矿区居民头发中Pb,As,Cd,Ca,Mg,Fe,Zn,Cu,Mn和Sr进行了定量分析,应用微区X射线荧光(Micro-XRF)和X射线吸收近边结构谱(XANES)测定了头发中的Pb和As等元素微区分布和Pb形态。研究发现(1)当地部分居民已经受到矿区中Pb,Cd,Cu和Mn等重金属污染的危害。(2)不同性别群体的生理特征和生活习惯是决定其分布特征的主要因素,其中女性头发中Pb,Cd,Ca,Mg,Zn,Cu和Sr的平均含量都显著高于男性,男性头发中的Fe显著高于女性;(3)由于各元素性质、来源和吸收机制等原因,矿区居民头发中Ca-Mg-Sr-Zn,Pb-Cd-Cu-Mn,Fe-Mn具有相关性;(4)矿区典型头发样本中Pb和As主要沿头发中轴分布,从发根至发梢含量有逐渐增多的趋势;(5)头发样品中Pb由4.7%Pb₃(PO₄)₂,36.8%Pb-GSH和8.4%PbS组成;(6)头发中不溶性磷酸铅、铅-半胱氨酸巯基结合态是发铅的主要存在形态,揭示了其为人体铅代谢的主要途径之一。