基于Bert预训练模型的虚假新闻文本检测

虚假新闻剥夺了人们获取真相的权利,也给社会和国家带来了许多危害。文中以虚假新闻文本为例,分析和验证了多种预训练语言模型在虚假新闻文本分类上的分类效果。经实验证明,相较于其他语言模型,Bert预训练语言模型取得了较好的结果,预测准确率为86.97%,召回率为88.12%,F1值为87.54%。     

Nature inspired 21 branches sneezewort/Achillea ptarmica plant growth pattern–shaped antenna for Ku‐band applications

This reported paper presents the design and analysis of wideband nature inspired planar antenna of 46 × 18 × 1.6 mm³ size, designed using FR4 (Flame Retardant) substrate. The antenna patch is delineated from the growth pattern of sneezewort plant with supplementary notion of golden ratio in branching and branch width. The total number of branches in each stage follows the Fibonacci series and the branch width is calculated from the golden ratio concept. Starting from one feed line and two branches, the maximum numbers of branches are increased to 20. There has been significant enhancement in the radiation performance of proposed geometry by increasing the number of branches to 21 and by modifying ground with T‐shaped slot. The antenna covers wide impedance bandwidth of 8.2 to 16.5 GHz by possessing stable radiation characteristics.     

Arabic sign language intelligent translator

ABSTRACT

Arabic sign language (ArSL) is method of communication between deaf communities in Arab countries; therefore, the development of systemsthat can recognize the gestures provides a means for the Deaf to easily integrate into society. In this research we implemented a computational structurefor an intelligent interpreter that automatically recognizes the isolated dynamic gestures. The proposed system recognizes and translates gesturesperformed with one or both hands. It comprises five subsystems, building dataset, video processing, feature extraction, mapping between ArSL and Arabictext, and text generation. To apply the system, 100-signs of ArSL was used, which was applied on 1500 video files. It's were divided into five classes:alphabet, numbers, "prepositions, pronouns and question words", Arabic life expressions, and "nouns and verbs". The evaluation indicated that thesystem automatically recognizes and translates isolated dynamic ArSL gestures by highly accurate manner. The results showed that the system accuracy is 95.8%.     

Paste backfill of high-sulphide mill tailings using alkali-activated blast furnace slag: Effect of activator nature,concentration and slag properties

The effect of activator type, concentration and slag composition on the strength and stability properties of paste backfill (CPB) of high-sulphide tailings using alkali-activated slag (AAS) as binder (7 wt.%) were investigated in this study. Acidic and neutral (AS–NS) slags were activated with liquid sodium silicate (LSS) and sodium hydroxide (SH) at 6–10 wt.% concentrations. Ordinary Portland cement (OPC) results were used for comparison. The strength development was found to remarkably improve with increasing the concentration from 6 to 8 wt.%. Further increase in concentration did not enhance the strength. SH was determined to produce higher early-age strength whilst LSS produced higher long-term strengths as an indication of slag selectivity for activators. More extensive gypsum formation was observed at lower concentrations in SEM/EDS studies. An increase in Na₂O concentration raised the activator consumption. High concentrations also led to poorly crystallized C–S–H gel, loose structure and drying shrinkage cracks especially in NS–SH samples. A reduction in total porosity up to 20% was obtained in AAS samples compared to OPC. Amorphous structure, chemical modulus ratio and/or basicity index (BI) values were seen to control the pozzolanic reactivity, and therefore, the alkali-activation and hardening process.     

A knowledge construction methodology to automate case-based learning using clinical documents

The case-based learning (CBL) approach has gained attention in medical education as an alternative to traditional learning methodology. However, current CBL systems do not facilitate and provide computer-based domain knowledge to medical students for solving real-world clinical cases during CBL practice. To automate CBL, clinical documents are beneficial for constructing domain knowledge. In the literature, most systems and methodologies require a knowledge engineer to construct machine-readable knowledge. Keeping in view these facts, we present a knowledge construction methodology (KCM-CD) to construct domain knowledge ontology (i.e., structured declarative knowledge) from unstructured text in a systematic way using artificial intelligence techniques, with minimum intervention from a knowledge engineer. To utilize the strength of humans and computers, and to realize the KCM-CD methodology, an interactive case-based learning system(iCBLS) was developed. Finally, the developed ontological model was evaluated to evaluate the quality of domain knowledge in terms of coherence measure. The results showed that the overall domain model has positive coherence values, indicating that all words in each branch of the domain ontology are correlated with each other and the quality of the developed model is acceptable.     

基于大数据的C语言程序设计

C语言作为一种程序设计语言,在大数据组成的物联网和云计算中应用广泛,具有强大的适应性和兼容性,是大数据时代下,在IT行业中起到关键作用的程序设计语言。文章分析了基于大数据的C语言程序设计的必然性和应用策略,为C语言在大数据上的应用方向提供了参考依据。以汉字的应用为例,提出了解决C语言应用问题的思路。     

Mímir: An open-source semantic search framework for interactive information seeking and discovery

Semantic search is gradually establishing itself as the next generation search paradigm, which meets better a wider range of information needs, as compared to traditional full-text search. At the same time, however, expanding search towards document structure and external, formal knowledge sources (e.g. LOD resources) remains challenging, especially with respect to efficiency, usability, and scalability.This paper introduces Mímir—an open-source framework for integrated semantic search over text, document structure, linguistic annotations, and formal semantic knowledge. Mímir supports complex structural queries, as well as basic keyword search.Exploratory search and sense-making are supported through information visualisation interfaces, such as co-occurrence matrices and term clouds. There is also an interactive retrieval interface, where users can save, refine, and analyse the results of a semantic search over time. The more well-studied precision-oriented information seeking searches are also well supported.The generic and extensible nature of the Mímir platform is demonstrated through three different, real-world applications, one of which required indexing and search over tens of millions of documents and fifty to hundred times as many semantic annotations. Scaling up to over 150 million documents was also accomplished, via index federation and cloud-based deployment.     

The generic model query language GMQL – Conceptual specification,implementation, and runtime evaluation

The generic model query language GMQL is designed to query collections of conceptual models created in arbitrary graph-based modelling languages. Querying conceptual models means searching for particular model subgraphs that comply with a predefined pattern query. Such a query specifies the structural and semantic properties of the model fragment to be returned. In this paper, we derive requirements for a generic model query language from the literature and formally specify the language’s syntax and semantics. We conduct an analysis of GMQL׳s theoretical and practical runtime performance concluding that it returns query results within satisfactory time. Given its generic nature, GMQL contributes to a broad range of different model analysis scenarios ranging from business process compliance management to model translation and business process weakness detection. As GMQL returns results with acceptable runtime performance, it can be used to query large collections of hundreds or thousands of conceptual models containing not only process models, but also data models or organizational charts. In this paper, we furthermore evaluate GMQL against the backdrop of existing query approaches thereby carving out its advantages and limitations as well as pointing toward future research.