高泉背斜地层压力测井多参数综合解释与异常高压成因

目前国内外地层压力测井解释方法较多,但大多数方法基于欠压实沉积理论并局限于单一的地层岩性,尤其是针对盆地边缘山前深层构造,单一测井参数确定地层压力误差较大,且无法解释沉积压实机制以外的异常高压。为此,将多种异常高压机制相关的测井参数进行综合解释,建立适合山前复杂构造的地层压力测井多参数计算模型,评价准噶尔盆地南缘高泉背斜高探1井的地层压力剖面,其计算结果与钻井实测数据吻合,相对误差小于3.00%.同时,基于原始沉积加载—卸载过程力学原理,利用地层压力测井多参数分析判别出高泉背斜深层各层系异常高压的形成机制。     

LinkingPark: An automatic semantic table interpretation system

In this paper, we present LinkingPark, an automatic semantic annotation system for tabular data to knowledge graph matching. LinkingPark is designed as a modular framework which can handle Cell-Entity Annotation (CEA), Column-Type Annotation (CTA), and Columns-Property Annotation (CPA) altogether. It is built upon our previous SemTab 2020 system, which won the 2nd prize among 28 different teams after four rounds of evaluations. Moreover, the system is unsupervised, stand-alone, and flexible for multilingual support. Its backend offers an efficient RESTful API for programmatic access, as well as an Excel Add-in for ease of use. Users can interact with LinkingPark in near real-time, further demonstrating its efficiency.     

消防监督检查中对火灾隐患的认定探析

文章将重点阐述消防监督检查中对火灾隐患的认定,并从实际角度出发,充分的考虑可能存在的问题,具体问题具体分析,制定相应的解决对策,以保证消防监督检查工作能够顺利的开展.     

Skeleton parsing for complex question answering over knowledge bases

Answering complex questions involving multiple relations over knowledge bases is a challenging task. Many previous works rely on dependency parsing. However, errors in dependency parsing would influence their performance, in particular for long complex questions. In this paper, we propose a novel skeleton grammar to represent the high-level structure of a complex question. This lightweight formalism and its BERT-based parsing algorithm help to improve the downstream dependency parsing. To show the effectiveness of skeleton, we develop two question answering approaches: skeleton-based semantic parsing (called SSP) and skeleton-based information retrieval (called SIR). In SSP, skeleton helps to improve structured query generation. In SIR, skeleton helps to improve path ranking. Experimental results show that, thanks to skeletons, our approaches achieve state-of-the-art results on three datasets: LC-QuAD 1.0, GraphQuestions, and ComplexWebQuestions 1.1.     

Structure-sensitive semantic matching for aggregate question answering over knowledge base

Aggregate question answering essentially returns answers for given questions by obtaining query graphs with unique dependencies between values and corresponding objects. Word order dependency, as the key to uniquely identify dependency of the query graph, reflects the dependencies between the words in the question. However, due to the semantic gap caused by the expression difference between questions encoded with word vectors and query graphs represented with logical formal elements, it is not trivial to match the correct query graph for the question. Most existing approaches design more expressive query graphs for complex questions and rank them just by directly calculating their similarities, ignoring the semantic gap between them. In this paper, we propose a novel Structure-sensitive Semantic Matching(SSM) approach that learns aligned representations of dependencies in questions and query graphs to eliminate their gap. First, we propose a cross-structure matching module to bridge the gap between two modalities(i.e., textual question and query graph). Then, we propose an entropy-based gated AQG filter to remove the structural noise caused by the uncertainty of dependencies. Finally, we present a two-channel query graph representation that fuses the semantics of abstract structure and grounding content of the query graph explicitly. Experimental results show that SSM could learn aligned representations of questions and query graphs to eliminate the gaps between their dependencies, and improves up to 12% (F1 score) on aggregation questions of two benchmark datasets.     

InSAR技术在矿区地表变形监测中的应用

以禹州市梁北矿为研究区，利用2018年11月—2020年6月间35景5 m×20 m分辨率Sentinel-1A数据，采用InSAR技术，利用SBAS（短基线集InSAR）雷达干涉测量方法对梁北矿进行地面沉降信息提取解译，并通过实地调查成果认为，采用InSAR技术适合在矿区开展地表变形监测。     

英语修辞问句的构成及其话语和语篇功能简析

英语修辞问句，以主谓倒装的疑问句结构形式出现，句末可以使用问号，句号或感叹号，其本质上不要求读者或听众提供答案，而是起特定的话语或篇章修辞效果。这些效果包括吸引读者或听众的注意力，激发对方的兴趣，获取对方的支持，充当模糊限定语，加强语势，突出重点，强调前述论点，提起新的话轮，回答问题等。对英语修辞问句语篇功能的了解，有助于提高英语学习者的阅读和理解能力。     

致密砂岩气藏多层试井解释方法研究

致密砂岩油气藏储层多套小层叠置发育，为实现产能及经济效益最大化，通常采用一套井网分层压裂多层合采的开发方式，受非均质性影响，开发过程中层间干扰严重，各小层产能贡献比例、能量衰减速度差异大，限制了产能有效发挥。在应用试井分析结果评价生产井储层动态参数、压力水平的过程中，常规试井解释模型只能反映各生产子层数据的平均值，无法准确评价各层段数据，实际指导意义存在局限性。综合运用单层、多层试井解释模型对试井数据开展精细解释，以生产测井的分层产量作为拟合计算的新增约束条件，并以此建立多层渗流试井模型，拟合结果符合率高，在降低单层试井解释模型多解性的同时，实现多层参数定量评价，对于多层合采井在开发过程中技术政策调整以及增产措施制定等工作提供强力支撑。     

工程项目成本管理中存在的问题剖析

对施工企业在工程项目成本管理中存在的问题进行了分析并提出了解决办法。     

遥感技术在土地利用中的应用

本文利用Aster遥感数字图像，建立了彬县煤矸石电厂评价区各土地利用现状类型的遥感影像特征，采用目视解译和人机交互解译相结合的方法，圈定了土地利用现状类型范围，在此基础上，进行土地利用类型面积统计，总结各土地利用现状的空间分布特征，为了科学地评价电厂建设对生态环境的影响提供了基础依据。