Search results

This paper aims to propose a novel model and calibration method to improve the absolute positioning accuracy of a robotic drilling system with secondary encoders and additional axis.

The enhanced rigid-flexible coupling model is developed by considering both kinematic parameters and link flexibility. The kinematic errors of the robot and the additional axis are considered with a model containing 27 parameters. The elastic deformation errors of the robot under self-weight of links and end-effector are estimated with a flexible link model. For calibration, an effective comprehensive calibration method is developed by further considering the coordinate systems parameters of the drilling system and using a two-step process constrained Levenberg–Marquardt identification method.

Experiments are performed on the robotic drilling system that contains a KUKA KR500 R2830 industrial robot and an additional lifting axis with a laser tracker. The results show that the maximum error and mean error are reduced to 0.311 and 0.136 mm, respectively, which verify the effectiveness of the model and the calibration method.

A novel enhanced rigid-flexible coupling model and a practical comprehensive calibration method are proposed and verified. The experiments results indicate that the absolute positioning accuracy of the system in a large workspace is greatly improved, which is conducive to the application of industrial robots in the field of aerospace assembly.

Safety management plays an important part in coal mine construction. Due to complex data, the implementation of the construction safety knowledge scattered in standards poses a challenge. This paper aims to develop a knowledge extraction model to automatically and efficiently extract domain knowledge from unstructured texts.

Bidirectional encoder representations from transformers (BERT)-bidirectional long short-term memory (BiLSTM)-conditional random field (CRF) method based on a pre-training language model was applied to carry out knowledge entity recognition in the field of coal mine construction safety in this paper. Firstly, 80 safety standards for coal mine construction were collected, sorted out and marked as a descriptive corpus. Then, the BERT pre-training language model was used to obtain dynamic word vectors. Finally, the BiLSTM-CRF model concluded the entity’s optimal tag sequence.

Accordingly, 11,933 entities and 2,051 relationships in the standard specifications texts of this paper were identified and a language model suitable for coal mine construction safety management was proposed. The experiments showed that F1 values were all above 60% in nine types of entities such as security management. F1 value of this model was more than 60% for entity extraction. The model identified and extracted entities more accurately than conventional methods.

This work completed the domain knowledge query and built a Q&A platform via entities and relationships identified by the standard specifications suitable for coal mines. This paper proposed a systematic framework for texts in coal mine construction safety to improve efficiency and accuracy of domain-specific entity extraction. In addition, the pretraining language model was also introduced into the coal mine construction safety to realize dynamic entity recognition, which provides technical support and theoretical reference for the optimization of safety management platforms.

The chapter examined the consumer meanings of product placements embedded in social games in different cultural contexts.

The theoretical perspective guiding the study is phenomenology, and the essay assignment and in-depth interviews were used to collect data.

The chapter was based on two qualitative research projects. Findings revealed that consumers in both countries appreciated certain characteristics of product placement in the context of social game, such as subtleness (naturalness) and unobtrusiveness (users’ freedom of choice and proactive choice); consumers’ real-world consumption in both countries seems to be more or less influenced by the product placement in social games; and while the young American consumers didn’t construct specific meanings for Facebook, the Chinese white-collar consumers actively created meanings for the Chinese social-network site.

The chapter offered some thick descriptions and in-depth analyses of product placements in social games in different cultural contexts from consumers’ experiential perspectives to enrich our theoretical understanding of product placement in the new media environment as well as to add valuable insights to the research literature on new advertising formats in general.

No study to date has been conducted to explore the product placement in social games in different cultural contexts. The study fills the research gap by exploring US college-aged consumers’ and Chinese white-collar consumers’ interpretations of product placements in the context of social games.