Possibilistic nested logic programs and strong equivalence

In this paper, the class of possibilistic nested logic programs is introduced. These possibilistic logic programs allow us to use nested expressions in the bodies and heads of their rules. By considering a possibilistic nested logic program as a possibilistic theory, a construction of a possibilistic logic programing semantics based on answer sets for nested logic programs and the proof theory of possibilistic logic is defined. In order to define a general method for computing the possibilistic answer sets of a possibilistic nested program, the idea of equivalence between possibilistic nested programs is explored. By considering properties of equivalence between possibilistic programs, a process of transforming a possibilistic nested logic program into a possibilistic disjunctive logic program is defined. Given that our approach is an extension of answer set programming, we also explore the concept of strong equivalence between possibilistic nested logic programs. To this end, we introduce the concept of poss SE-models. Therefore, we show that two possibilistic nested logic programs are strong equivalents whenever they have the same poss SE-models.The expressiveness of the possibilistic nested logic programs is illustrated by a scenario from the medical domain. In particular, we exemplify how possibilistic nested logic programs are expressive enough for capturing medical guidelines which are pervaded by vagueness and qualitative information.     

Theoretic quantum information entropies for the generalized hyperbolic potential

The Shannon entropy (S) and the Fisher Information (I) entropies are investigated for a generalized hyperbolic potential in position and momentum spaces. First, the Schrodinger equation is solved exactly using the Nikiforov-Uvarov-Functional Analysis method to obtain the energy spectra and the corresponding wave function. By Fourier transforming the position space wave function, the corresponding momentum wave function was obtained for the low-lying states corresponding to the ground and first excited states. The positions and momentum of Shannon entropy and Fisher Information entropies were calculated numerically. Finally, the Bialynicki-Birula and Mycielski and the Stam-Cramer-Rao inequalities for the Shannon entropy and Fisher Information entropies, respectively, were tested and were found to be satisfied for all cases considered.     

Selective Monofunctionalization Enabled by Reaction‐History‐Dependent Communication in Catalytic Rotaxanes

Selective monofunctionalization of substrates with distant, yet equally reactive functional groups is difficult to achieve, as it requires the second functional group to selectively modulate its reactivity once the first functional group has reacted. We now show that mechanically interlocked catalytic rings can effectively regulate the reactivity of stoppering groups in rotaxanes over a distance of about 2 nm. Our mechanism of communication is enabled by a unique interlocked design, which effectively removes the catalytic rings from the substrates by fast dethreading as soon as the first reaction has taken place. Our method not only led to a rare example of selective monofunctionalization, but also to a “molecular if function”. Overall, the study presents a way to get distant functional groups to communicate with each other in a reaction‐history‐dependent manner by creating linkers that can ultimately perform logical operations at the molecular level.     

Side-chain liquid crystalline polyesters for optical information storage

Azobenzene side-chain liquid crystalline polyester structures suitable for permanent optical storage are described. The synthesis and characterization of the polyesters together with differential scanning calorimetry and X-ray investigations are discussed. Optical anisotropic investigations and holographic storage in one particular polyester are described in detail and polarized Fourier transform infrared spectroscopic data complementing the optical data are presented. Optical and atomic force microscope investigations point to a laser-induced aggregation as responsible for permanent optical storage.     

环境监测实验室管理系统的开发与应用

基于2005版《计量认证/审查认可(验收)评审准则》要求,为满足环境监测实验室业务流程而设计开发了信息管理系统。该系统主要用于环境监测实验室的资源管理和日常自动化办公。系统采用B/S架构,实现全球化办公运作,能对监测样品的受理、分发、分析、原始记录、监测报告、数据三级审核、报告签发实现全程自动流转,并运用工作流和智能表单设计实现实验室程序文件中各类程序和日常办公事务流程的执行;原始记录和监测报告全部实现自动归档及智能查询;同时根据2005版准则中的要求,对人员、设备、材料、环境要素、记录、质量控制等所有要素全面实施网络化管理。     

基于视觉辐条图案识别方法的蓝宝石引晶机制研究

工业生产蓝宝石晶体过程中,引晶步骤有着至关重要的地位。引晶必须在温度梯度较小,温度分布趋于稳定的条件下进行。目前,工业生产蓝宝石主要依靠人工经验操控籽晶杆实现引晶操作,但是人工引晶操作的准确性不高会导致成品品质不佳、资源浪费。为此,本文提出一种基于蓝宝石视觉辐条图案识别方法来检测蓝宝石熔体状态自由液面状态,从而实现一种高效率引晶的机制。此方法利用经典骨架化算法细化辐条图案,Harris算子实现特征信息的提取,提取的特征信息放入运动轨迹模型中判断熔体稳定性,分析液面温度分布稳定性从而实现引晶。结果表明,此算法具有有效性,蓝宝石晶体引晶效率大大提高,生产出的成品良率也有提升,可有效指导蓝宝石的工业生产。     

基于二阶段异质随机森林的汽油辛烷值预测

构建了基于二阶段异质随机森林的汽油辛烷值预测模型.首先利用样本-位点信息表知识约简模型,筛选出对汽油辛烷值影响大的位点数据作为第一阶段;然后,利用集成学习思想集成支持向量回归和动态时间序列神经网络,构建异质随机森林预测模型作为第二阶段.利用十折交叉法验证模型精度,结果表明该集成学习算法具有有效性和高精度.     

中高分辨力遥感图像中飞机目标自动识别算法研究

提出了一种中高分辨力的航空航天遥感图像中飞机目标快速自动识别的新算法。在分割和分类过程中充分利用飞机目标的先验知识,提出了一种改进区域分割方法,并应用树分类器对飞机目标进行自动识别。所提出的改进区域分割方法较好地实现了区域分割中阈值的准确自动选取,克服了复杂背景图像中小目标的全局阈值自动分割的失效问题。采用二叉树分类器,通过提取简单的目标几何特征,分层进行种类识别,提高了识别速度,降低了漏检率和虚警率。运用该方法进行了实验。结果表明,识别率达到了100%。