If a child asks friend to play football and the replies, ‘I have cough’, requesting must make ‘relevance inference’ determine communicative intent. Relevance inferencing is key component of pragmatics, that is, ability integrate social context into language interpretation use. We tested which cognitive skills relate relevance inferencing. In addition, we asked whether children’s lab-based pragm...

Intelligent instruments are common components in industrial machinery, and fault diagnosis IoT systems requires the handling of real-time sensor data expert knowledge. sensors cannot collect for all types a specific instrument, long-distance transfer introduces additional uncertainties. However, because equipment has complex causes performances, it is typically difficult or expensive to obtain ...

In this work, we propose a real-time monocular 3D video reconstruction approach named Flora for reconstructing delicate and complete scenes from RGB sequences in an end-to-end manner. Specifically, introduce novel method with two main contributions. Firstly, the proposed feature aggregation module retains both color reliability dual-frequency form. Secondly, loss compensation solves missing str...

In this paper, we describe our effort to build an inference engine for OWL reasoning based on the rule engine paradigm. Rule engines are very practical and effective for their representational simplicity and optimized performance, but their limited expressiveness and web unfriendliness restrict their usability for OWL reasoning. We enumerate and succinctly describe extended features implemented...

We report on the use of medical facts to support the enhancement of natural language processing of biomedical text. Inferencing in semantic interpretation depends on a fact repository as well as an ontology. We used statistical methods to construct a repository of drug-disorder co-occurrences from a large collection of clinical notes, and this resource is used to validate inferences automatical...

The two most important models of inferencing in approximate reasoning with fuzzy sets are Zadeh’s Compositional Rule of Inference (CRI) and Similarity Based Reasoning (SBR). It is known that inferencing in the above models is resource consuming (both memory and time), since these schemes often consist of discretisation of the input and output spaces followed by computations in each point. Also ...

In recent years, deep learning-based approaches have proliferated across a variety of ecological studies. Inspired by learning’s emerging prominence as the preferred tool for analyzing wildlife image datasets, this study employed You Only Look Once (YOLO), single-shot, real-time object detection algorithm, to effectively detect cavity trees Red-cockaded Woodpeckers or RCW (Dryobates borealis). ...