Modular irregular labeling is an edge irregular labeling of a graph in which the edges and vertices are labelled with 1, 2, 3,.. k such that the weight of all vertices are different. The complete bipartite graph is wh...
详细信息
Reducing power consumption in battery-powered medical edge devices is highly required. This study aims to enhancing power efficiency in the Pan-Tompkins algorithm used for electrocardiogram (ECG) feature detection by ...
详细信息
Diabetes, marked by prolonged high blood sugar levels, poses a significant global health challenge. Precise early prediction is vital but faces hurdles due to limited data and complexities like outliers. Uncontrolled ...
详细信息
With the rapid development of digital technology and the continuous updating of various terminal devices, new retail is gradually becoming an important trend in the retail industry. New retail involves the integration...
详细信息
This study presents a revolutionary voice and gesture detection system with applications ranging from augmented reality to presentation control, painting, and sketching. The technology combines voice recognition to co...
详细信息
Electroencephalography (EEG) offers non-invasive, real-time mental workload assessment, which is crucial in high-stakes domains like aviation and medicine and for advancing brain-computer interface (BCI) technologies....
详细信息
In this paper, we study the problem of multi-reward reinforcement learning to jointly optimize for multiple text properties for natural language generation. We focus on the task of counselor reflection generation, whe...
详细信息
Competency Questions (CQs) are essential in ontology engineering;they express an ontology's functional requirements as natural language questions, offer crucial insights into an ontology's scope and are pivota...
详细信息
ISBN:
(纸本)9783031789519;9783031789526
Competency Questions (CQs) are essential in ontology engineering;they express an ontology's functional requirements as natural language questions, offer crucial insights into an ontology's scope and are pivotal for various tasks, e.g. ontology reuse, testing, requirement specification, and pattern definition. Despite their importance, the practice of publishing CQs alongside ontological artefacts is not commonly adopted. We propose an approach based on Generative AI, specifically Large Language Models (LLMs) for retrofitting CQs from existing ontologies and we study how the control parameters in two LLMs (i.e. gpt-3.5-turbo and gpt-4) affect their performance and investigate the interplay between prompts and configuration for retrofitting viable CQs.
The query tuning, which is mostly found in the syntax semantics of fuzzy logic inference algorithms, uses the query syntax of the boolean data type. Fuzzy logic inference is converted using AND and OR operators to con...
详细信息
The addition of antioxidants to the Transformer Oil (TO) is increasingly important due to its benefits during the operation of transformers. Despite its excellent dielectric function, the liquid insulation deteriorate...
详细信息
暂无评论