配合煤配比对焦炭综合热性质的影响

以企业生产实践为背景,研究在配合煤中增配肥煤和1/3焦煤对焦炭综合热性质的影响。对不同配比配合煤的性质指标进行检测,采用40 kg焦炉实施炼焦试验,并对炼制焦炭的传统国家标准热性质指标和利用自主研制装置测得的综合热性质指标进行测定。结果表明:增配肥煤和1/3焦煤,均会使配合煤的变质程度降低,挥发分含量升高,胶质体的黏结能力下降,但胶质体的量保持不变。配比变化引起的配合煤性质指标的变化没有显现在焦炭的传统国家标准热性质指标反应性CRI和反应后强度CSR上。以往的研究都是以CRI和CSR指标为目标量判断配合煤的配比是否合适,本研究除此之外还采用了自主提出的焦炭综合热性质指标。配合煤配比变化引起的焦炭的综合热性质指标变化比国家标准热性质CRI和CSR指标变化敏感,这可能与其反映了焦炭某些新的特征有关。基于焦炭综合热性质指标的变化规律,考虑到1/3焦煤具有经济性,生产上增配某些特定的1/3焦煤,可以同时达到提高焦炭质量和降低配煤成本的目的。     

Self-adaptive nonoverlapping sequential pattern mining

Applied Intelligence - Repetitive sequential pattern mining (SPM) with gap constraints is a data analysis task that consists of identifying patterns (subsequences) appearing many times in a...     

多目标定值的一种权系数学习模型

本文先分析了多目标定值的问题环境,然后介绍农业施肥专家系统工具 AFshell 中建立的一个权值学习模型。该模型以二项系数加权和法为基础进行初始权系数的获取,以教导注入式方式进行权向量调整,并能通过实例运行进行权向量的完善.这种学习模型具有推广性,也可用于其它多目标定值的问题领域。     

可见光增强g-C_3N_4/Co_3O_4胶体催化剂的催化产氢性能

通过水热法制备了具有可见光增产氢高性能的g-C_3N_4/Co_3O_4胶体催化剂,采用XRD、TEM、SEM和EDS等分析样品的组成和形貌结构。催化产氢结果表明,光照条件下g-C_3N_4/Co_3O_4胶体催化剂具有极高的催化产氢活性,TOF值高达58.2 min~(-1),通过拟合温度动力学曲线,得到了催化反应的活化能为15.73 kJ·mol~(-1)。对样品进行UV-vis和PL测试发现,g-C_3N_4/Co_3O_4胶体催化剂具有极高的光能利用率和电子-空穴分离率,并进一步阐述了光能促进催化产氢的作用机理。     

高精度可调量程电感式位移传感器测量系统

本文根据电感传感器量程、灵敏度、分辨率和精度之间的关系,以AD598AD芯片为基础设计了电感传感器的后续处理电路。该电路配以数据采集卡和上位机采集程序,搭建了高精度可调量程的电感式位移传感器测量系统。经试验分析验证,测量误差可减小至0.74μm。     

Mining sequential patterns with periodic wildcard gaps

Mining frequent patterns with periodic wildcard gaps is a critical data mining problem to deal with complex real-world problems. This problem can be described as follows: given a subject sequence, a pre-specified threshold, and a variable gap-length with wildcards between each two consecutive letters. The task is to gain all frequent patterns with periodic wildcard gaps. State-of-the-art mining algorithms which use matrices or other linear data structures to solve the problem not only consume a large amount of memory but also run slowly. In this study, we use an Incomplete Nettree structure (the last layer of a Nettree which is an extension of a tree) of a sub-pattern P to efficiently create Incomplete Nettrees of all its super-patterns with prefix pattern P and compute the numbers of their supports in a one-way scan. We propose two new algorithms, MAPB (Mining sequentiAl Pattern using incomplete Nettree with Breadth first search) and MAPD (Mining sequentiAl Pattern using incomplete Nettree with Depth first search), to solve the problem effectively with low memory requirements. Furthermore, we design a heuristic algorithm MAPBOK (MAPB for tOp-K) based on MAPB to deal with the Top-K frequent patterns for each length. Experimental results on real-world biological data demonstrate the superiority of the proposed algorithms in running time and space consumption and also show that the pattern matching approach can be employed to mine special frequent patterns effectively.     

MINING APPROXIMATE REPEATING PATTERNS FROM SEQUENCE DATA WITH GAP CONSTRAINTS

The rapid increase of available DNA, protein, and other biological sequences has made the problem of discovering meaningful patterns from sequences an important task for Bioinformatics research. Among all types of patterns defined in the literature, the most challenging one is to find repeating patterns with gap constraints. In this article, we identify a new research problem for mining approximate repeating patterns (ARPs) with gap constraints, where the appearance of a pattern is subject to an approximate match, which is very common in biological sequences. To solve the problem, we propose an ArpGap (ARP mining with Gap constraints) algorithm with three major components for ARP mining: (1) a data‐driven pattern generation approach to avoid generating unnecessary candidates for validation; (2) a back‐tracking pattern search process to discover approximate occurrences of a pattern under user specified gap constraints; and (3) an Apriori‐like deterministic pruning approach to progressively prune patterns and cease the search process if necessary. Experimental results on synthetic and real‐world protein sequences assert that ArpGap is efficient in terms of memory consumption and computational cost. The results further suggest that the proposed method is practical for discovering approximate patterns for protein sequences where the sequence length is usually several hundreds to one thousand and the pattern length is relatively short.     

A Chinese time ontology for the Semantic Web

Representation of and reasoning with temporal knowledge are fundamental in information systems that involve changes and actions. To build such systems, a time ontology is demanded. The development of a time ontology is also an indispensable part of effort to realize the Semantic Web. Nevertheless, our practice shows that any practical time ontology is closely related with a specific calendar, culture or history. To this end, this paper presents a Chinese time ontology for knowledge systems and web services which involve temporal entities or temporal properties. First, we define a base time ontology. As a core component, it consists of a time system, a timing system, a Gregorian timing system, and a timing ontology. Upon this base ontology, other parts of the Chinese time ontology are finally constructed, including the traditional Chinese timing system, temporal representation in Chinese idiosyncratic ways, and transformation between temporal entities in the Gregorian timing system and temporal entities in the traditional Chinese timing system. We will argue that the base time ontology is not only a basic and integral part of the Chinese time ontology, but also a base for constructing other time ontologies.     

融合术语信息的新能源专利机器翻译研究

传统的神经机器翻译模型是一个黑盒子,并不能有效把术语信息添加进去。而利用用户提供的术语词典来联合训练神经机器翻译模型具有实际意义。据此,该文提出融入术语信息的新能源领域Transformer专利机器翻译模型,使用将源端术语替换为目标端术语以及在源端术语后增添目标端术语两种手段进行术语信息融合,实验表明,在构建的新能源领域专利汉英平行语料库和术语库上,提出的专利翻译模型优于Transformer基准模型。并评测了其在人工构建的数据集、中国专利信息中心的数据集及世界知识产权局的数据集上的翻译效果。     

街接 整合 生长——大连经济技术开发区海滨区域设计研究

以大连经济技术开发区海滨区域设计工程为依托，从大连海滨特有的制约出发，通过对设计发展过程的探讨，归纳出贯穿于设计之中的街接、整合、生长的思想。