In this paper, we have designed a machine visionbased method to identify the defected or missed or grounded rail anchors/fasteners that attach each line with the sleepers. Rail line inspection system is executed manually, especially in third world countries, like Bangladesh. This manual inspection is lengthy, laborious and subjective. To detect and classify the damaged or missed or grounded rai...

Thirty years ago, grounded cognition had roots in philosophy, perception, cognitive linguistics, psycholinguistics, cognitive psychology, and cognitive neuropsychology. During the next 20 years, grounded cognition continued developing in these areas, and it also took new forms in robotics, cognitive ecology, cognitive neuroscience, and developmental psychology. In the past 10 years, research on...

In knowledge grounded conversation, domain knowledge plays an important role in a special domain such as Music. The response of knowledge grounded conversation might contain multiple answer entities or no entity at all. Although existing generative question answering (QA) systems can be applied to knowledge grounded conversation, they either have at most one entity in a response or cannot deal ...

Requirements analysis (RA) is a key phase in information systems (IS) development. During this phase, system analysts use different techniques and methods to elicit and structure the system’s requirements. The current paper rationalises the use of grounded theory (GT) as an alternative socio-technical approach to requirement analysis. It will establish theoretically that applying grounded theor...

The promise of theory and model development makes grounded theory an attractive methodology to follow. However, it has been argued that many researchers fall short and provide a detailed description of only the research area or simply a quantitative content analysis rather than an explanatory model. This article illustrates how the researchers used a computer-assisted qualitative data analysis ...

A spoken language generation system has been developed that learns to describe objects in computer-generated visual scenes. The system is trained by a ‘show-and-tell’ procedure in which visual scenes are paired with natural language descriptions. Learning algorithms acquire probabilistic structures which encode the visual semantics of phrase structure, word classes, and individual words. Using ...