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Article
Publication date: 1 March 2021

Yiqiang Feng, Leiju Qiu and Baowen Sun

The originality of the crowd cyber system lies in the fact that it possesses the intelligence of multiple groups including intelligence of people, intelligence of objects and…

1407

Abstract

Purpose

The originality of the crowd cyber system lies in the fact that it possesses the intelligence of multiple groups including intelligence of people, intelligence of objects and intelligence of machines. However, quantitative analysis of the level of intelligence is not sufficient, due to many limitations, such as the unclear definition of intelligence and the inconformity of human intelligence quotient (IQ) test and artificial intelligence assessment methods. This paper aims to propose a new crowd intelligence measurement framework from the harmony of adaption and practice to measure intelligence in crowd network.

Design/methodology/approach

The authors draw on the ideas of traditional Confucianism, which sees intelligence from the dimensions of IQ and effectiveness. First, they clarify the related concepts of intelligence and give a new definition of crowd intelligence in the form of a set. Second, they propose four stages of the evolution of intelligence from low to high, and sort out the dilemma of intelligence measurement at the present stage. Third, they propose a framework for measuring crowd intelligence based on two dimensions.

Findings

The generalized IQ operator model is optimized, and a new IQ algorithm is proposed. Individuals with different IQs can have different relationships, such as cooperative, competitive, antagonistic and so on. The authors point out four representative forms of intelligence as well as its evolution stages.

Research limitations/implications

The authors, will use more rigorous mathematical symbols to represent the logical relationships between different individuals, and consider applying the measurement framework to a real-life situation to enrich the research on crowd intelligence in the further study.

Originality/value

Intelligence measurement is one of foundations of crowd science. This research lays the foundation for studying the interaction among human, machine and things from the perspective of crowd intelligence, which owns significant scientific value.

Details

International Journal of Crowd Science, vol. 5 no. 1
Type: Research Article
ISSN: 2398-7294

Keywords

Available. Open Access. Open Access
Article
Publication date: 4 September 2017

Yuqin Wang, Bing Liang, Wen Ji, Shiwei Wang and Yiqiang Chen

In the past few years, millions of people started to acquire knowledge from the Massive Open Online Courses (MOOCs). MOOCs contain massive video courses produced by instructors…

2516

Abstract

Purpose

In the past few years, millions of people started to acquire knowledge from the Massive Open Online Courses (MOOCs). MOOCs contain massive video courses produced by instructors, and learners all over the world can get access to these courses via the internet. However, faced with massive courses, learners often waste much time finding courses they like. This paper aims to explore the problem that how to make accurate personalized recommendations for MOOC users.

Design/methodology/approach

This paper proposes a multi-attribute weight algorithm based on collaborative filtering (CF) to select a recommendation set of courses for target MOOC users.

Findings

The recall of the proposed algorithm in this paper is higher than both the traditional CF and a CF-based algorithm – uncertain neighbors’ collaborative filtering recommendation algorithm. The higher the recall is, the more accurate the recommendation result is.

Originality/value

This paper reflects the target users’ preferences for the first time by calculating separately the weight of the attributes and the weight of attribute values of the courses.

Details

International Journal of Crowd Science, vol. 1 no. 3
Type: Research Article
ISSN: 2398-7294

Keywords

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Article
Publication date: 4 September 2017

Yiqiang Wang, Zhengcai Guo, Botao Liu, Yanfei Zhu and Haibo Luo

The alignment precision of existing methods is limited by the precision of detecting element and worker’s experience, which the parallelism between ball screw and guide way is not…

242

Abstract

Purpose

The alignment precision of existing methods is limited by the precision of detecting element and worker’s experience, which the parallelism between ball screw and guide way is not guaranteed effectively. Thus, this paper aims to propose a method of detecting ball screw’s alignment error (BSAE) via monitoring the average vibration magnitude induced by rotational frequency of ball screw (VMRFBS).

Design/methodology/approach

In this study, the ball screw is simplified as a freely supported beam. A mathematical model of the effect of BSAE on the contact angle of the ball and screw is established. The change of contact angle has effect on the deformation and contact stiffness according to the Hertz contact theory. To improve the accuracy of the experimental results, the VMRFBS are analyzed by using average method, and the average values of the VMRFBS at different BSAEs are calculated by using the least squares method.

Findings

The experimental results show that the average VMRFBS increases with the increasing of BSAE under the BSAE from 0 to 0.2 mm, while the other conditions are unchanged.

Originality/value

This method provides an approach to monitor the BSAE and improve the alignment accuracy of machine tools and automation equipment, which has a certain guide for improving the alignment accuracy of ball screw.

Details

Assembly Automation, vol. 37 no. 4
Type: Research Article
ISSN: 0144-5154

Keywords

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