“三规合一”数据的注记图层坐标转换处理方法研究

注记图层因为存储了文字的位置信息,且具有相对比例尺,字体大小可以相对变化,越来越多地被应用于GIS数据建库中。 ArcGIS MDB坐标转换中,注记图层的处理不同于普通的点线面图层。本文详细讲述了＂三规合一＂数据坐标转换中注记图层的处理方法和过程,通过本方法进行处理,既省略了重建注记子类型分类的步骤,减少手工录入量,又保留了原有图层各属性字段内容,同时也保留了注记字体、大小、角度等相关显示信息,能最大程度保持原有注记显示效果。     

飞机钣金特征的智能三维标注技术

采用CAA对CATIA进行二次开发,建立了钣金零件的检验规划系统.通过钣金零件的检验规划系统得到特征的检验方法,并将所有特征对应的检验方法通过智能三维标注技术,标注到三维模型上.智能三维标注,即通过人机智能交互的方式,将所有的检验信息全部表示在三维图上,简单,直观,明了.     

云计算中的群体智能与不确定性知识表示

The lasting evolution of computing environment, software engineering and interaction methods leads to cloud computing. Cloud computing changes the configuration mode of resources on the Internet and all kinds of resources are virtualized and provided as services. Mass participation and online interaction with social annotations become usual in human daily life. People who own similar interests on the Internet may cluster naturally into scalable and boundless communities and collective intelligence will emerge. Human is taken as an intelligent computing factor, and uncertainty becomes a basic property in cloud computing. Virtualization, soft computing and granular computing will become essential features of cloud computing. Compared with the engineering technological problems of IaaS (Infrastructure as a service), PaaS (Platform as a Service) and SaaS (Software as a Service), collective intelligence and uncertain knowledge representation will be more important frontiers in cloud computing for researchers within the community of intelligence science.     

基于Matlab的图像自动标注

图像自动标注在检索大量数字图像时起到关键作用,它能将图像的视觉特征转化为图像的标注字信息,为用户的使用及检索带来极大的方便。研究了图像自动语义标注方法,设计并实现了基于Matlab图像自动标注系统,能够提取图像颜色特征和纹理特征,与已标注图像进行相似性度量并标注出图像语义关键词     

从视觉到事件——长沙简牍博物馆文化广场设计

本文通过介绍长沙简牍博物馆文化广场方案,诠释了立足东方传统的流动性、参与性、事件性的空间观念,并以此为线索组织空间道具和空间场景,塑造空间情节,唤起使用者对当地自然特征与文化生活的场所记忆和空间情感。     

An ontology-based approach for formalisation and semantic organisation of conformance requirements in construction

This paper presents an ontology-based method for the formalisation and application of construction conformance requirements for effective code checking. This research continues our work on the development of a generic model automating the conformance checking of construction projects against building codes. We start from the analysis of the related research on the formalisation and organisation of building codes that allows us to formulate our approach for semantic annotation and scheduling of conformance requirements for conformance checking task. Our approach comprises 5 main steps: formalisation, semantic annotation, classification, context-based scheduling and semantic search of conformance requirements. They are implemented as corresponding key components of the C3R (Conformance Checking in Construction — Reasoning) prototype that we have developed to model the conformance checking process in construction. Finally, we discuss the ongoing work and perspectives of our research: the validation of our model by construction practices and the enrichment of our approach by usage-based knowledge.     

Semantic content-based image retrieval: A comprehensive study

The complexity of multimedia contents is significantly increasing in the current digital world. This yields an exigent demand for developing highly effective retrieval systems to satisfy human needs. Recently, extensive research efforts have been presented and conducted in the field of content-based image retrieval (CBIR). The majority of these efforts have been concentrated on reducing the semantic gap that exists between low-level image features represented by digital machines and the profusion of high-level human perception used to perceive images. Based on the growing research in the recent years, this paper provides a comprehensive review on the state-of-the-art in the field of CBIR. Additionally, this study presents a detailed overview of the CBIR framework and improvements achieved; including image preprocessing, feature extraction and indexing, system learning, benchmarking datasets, similarity matching, relevance feedback, performance evaluation, and visualization. Finally, promising research trends, challenges, and our insights are provided to inspire further research efforts.     

基于UG的采煤机防爆盖板三维标注及数控工艺研究

随着三维CAD技术的发展,产品制造信息在三维模型和二维图纸之间的反复传递,严重影响了产品制造信息的正确、快速传递。基于三维产品制造信息技术,以采煤机防爆盖板为例,在UG NX10.0中建立了防爆盖板的三维模型并进行了三维标注,设计了加工工艺路线,规划了数控加工刀具轨迹,进行了加工仿真,验证了数控加工的正确性,在此基础上完成了采煤机防爆盖板的三维工艺式设计。该研究对基于模型定义的数字化设计与制造研究,实现制造业信息化具有重要意义。     

A Novel Auto-Annotation Technique for Aspect Level Sentiment Analysis

In machine learning, sentiment analysis is a technique to find and analyze the sentiments hidden in the text. For sentiment analysis, annotated data is a basic requirement. Generally, this data is manually annotated. Manual annotation is time consuming, costly and laborious process. To overcome these resource constraints this research has proposed a fully automated annotation technique for aspect level sentiment analysis. Dataset is created from the reviews of ten most popular songs on YouTube. Reviews of five aspects—voice, video, music, lyrics and song, are extracted. An N-Gram based technique is proposed. Complete dataset consists of 369436 reviews that took 173.53 s to annotate using the proposed technique while this dataset might have taken approximately 2.07 million seconds (575 h) if it was annotated manually. For the validation of the proposed technique, a sub-dataset—Voice, is annotated manually as well as with the proposed technique. Cohen's Kappa statistics is used to evaluate the degree of agreement between the two annotations. The high Kappa value (i.e., 0.9571%) shows the high level of agreement between the two. This validates that the quality of annotation of the proposed technique is as good as manual annotation even with far less computational cost. This research also contributes in consolidating the guidelines for the manual annotation process.     

Annotation of miRNAs in COVID-19 coronavirus

The COVID-19 coronavirus is a new strain of coronavirus that had not been previously detected in humans. As its severe pathogenicity is concerned, it is important to study it thoroughly to aid in the discovery of a cure. In this study, the microRNAs (miRNAs) of COVID-19 were annotated to provide a powerful tool for the study of this novel coronavirus. We obtained 16 novel coronavirus genome sequences and the mature sequences of all viruses in the microRNA database (miRbase), and then used the miRNA mature sequences of the virus to perform the Basic Local Alignment Search Tool (BLAST) analysis in the coronavirus genome, extending the matched regions of approximately 20 bp to two segments by 200 bp. Six sequences were obtained after deleting redundant sequences. Then, the hairpin structures of the mature miRNAs were determined using RNAfold. The mature sequence on one hairpin arm was selected into a total of 4 sequences, and finally the relevant miRNA precursor prediction tools were used to verify whether the selected sequences are miRNA precursor sequences of the novel coronavirus. The miRNAs of the novel coronavirus were annotated by our newly developed method, which will lay the foundation for further study of this virus.