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Open Access
Article
Publication date: 16 October 2018

Jing Liu, Zhiwen Pan, Jingce Xu, Bing Liang, Yiqiang Chen and Wen Ji

With the development of machine learning techniques, the artificial intelligence systems such as crowd networks are becoming more autonomous and smart. Therefore, there is a…

1241

Abstract

Purpose

With the development of machine learning techniques, the artificial intelligence systems such as crowd networks are becoming more autonomous and smart. Therefore, there is a growing demand for developing a universal intelligence measurement so that the intelligence of artificial intelligence systems can be evaluated. This paper aims to propose a more formalized and accurate machine intelligence measurement method.

Design/methodology/approach

This paper proposes a quality–time–complexity universal intelligence measurement method to measure the intelligence of agents.

Findings

By observing the interaction process between the agent and the environment, we abstract three major factors for intelligence measure as quality, time and complexity of environment.

Originality/value

This paper proposes a calculable universal intelligent measure method through considering more than two factors and the correlations between factors which are involved in an intelligent measurement.

Details

International Journal of Crowd Science, vol. 2 no. 2
Type: Research Article
ISSN: 2398-7294

Keywords

Open Access
Article
Publication date: 9 December 2019

Zhiwen Pan, Jiangtian Li, Yiqiang Chen, Jesus Pacheco, Lianjun Dai and Jun Zhang

The General Society Survey(GSS) is a kind of government-funded survey which aims at examining the Socio-economic status, quality of life, and structure of contemporary society…

Abstract

Purpose

The General Society Survey(GSS) is a kind of government-funded survey which aims at examining the Socio-economic status, quality of life, and structure of contemporary society. GSS data set is regarded as one of the authoritative source for the government and organization practitioners to make data-driven policies. The previous analytic approaches for GSS data set are designed by combining expert knowledges and simple statistics. By utilizing the emerging data mining algorithms, we proposed a comprehensive data management and data mining approach for GSS data sets.

Design/methodology/approach

The approach are designed to be operated in a two-phase manner: a data management phase which can improve the quality of GSS data by performing attribute pre-processing and filter-based attribute selection; a data mining phase which can extract hidden knowledge from the data set by performing data mining analysis including prediction analysis, classification analysis, association analysis and clustering analysis.

Findings

According to experimental evaluation results, the paper have the following findings: Performing attribute selection on GSS data set can increase the performance of both classification analysis and clustering analysis; all the data mining analysis can effectively extract hidden knowledge from the GSS data set; the knowledge generated by different data mining analysis can somehow cross-validate each other.

Originality/value

By leveraging the power of data mining techniques, the proposed approach can explore knowledge in a fine-grained manner with minimum human interference. Experiments on Chinese General Social Survey data set are conducted at the end to evaluate the performance of our approach.

Details

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

Keywords

Open Access
Article
Publication date: 13 November 2018

Zhiwen Pan, Wen Ji, Yiqiang Chen, Lianjun Dai and Jun Zhang

The disability datasets are the datasets that contain the information of disabled populations. By analyzing these datasets, professionals who work with disabled populations can…

1279

Abstract

Purpose

The disability datasets are the datasets that contain the information of disabled populations. By analyzing these datasets, professionals who work with disabled populations can have a better understanding of the inherent characteristics of the disabled populations, so that working plans and policies, which can effectively help the disabled populations, can be made accordingly.

Design/methodology/approach

In this paper, the authors proposed a big data management and analytic approach for disability datasets.

Findings

By using a set of data mining algorithms, the proposed approach can provide the following services. The data management scheme in the approach can improve the quality of disability data by estimating miss attribute values and detecting anomaly and low-quality data instances. The data mining scheme in the approach can explore useful patterns which reflect the correlation, association and interactional between the disability data attributes. Experiments based on real-world dataset are conducted at the end to prove the effectiveness of the approach.

Originality/value

The proposed approach can enable data-driven decision-making for professionals who work with disabled populations.

Details

International Journal of Crowd Science, vol. 2 no. 2
Type: Research Article
ISSN: 2398-7294

Keywords

Open Access
Article
Publication date: 9 December 2019

Xiaoni Wang, Zhiwen Pan, Zhouxia Li, Wen Ji and Feng Yang

This paper aims to optimize and evaluating the performance of the crowd networks through analyzing their information sharing patterns. That is, in a crowd network, the qualities…

Abstract

Purpose

This paper aims to optimize and evaluating the performance of the crowd networks through analyzing their information sharing patterns. That is, in a crowd network, the qualities of accomplishing tasks are highly dependent on the effective information sharing among intelligent subjects within the networks. Hence, proposing an adaptive information-sharing approach can help improve the performance of crowd networks on accomplishing tasks that are assigned to them.

Design/methodology/approach

This paper first introduces the factors that affect effectiveness of information-sharing pattern: the network topology, the resources owned by intelligent subjects and the degree of information demand. By analyzing the correlation between these factors and the performance of crowd networks, an Adaptive Information Sharing Approach for Crowd Networks (AISCN approach) is proposed. By referring to information needed for accomplishing the historical tasks that are assigned to a crowd network, the AISCN approach can explore the optimized information-sharing pattern based on the predefined composite objective function. The authors implement their approach on two crowd networks including bee colony and supply chain, to prove the effectiveness of the approach.

Findings

The shared information among intelligent subjects affects the efficiency of task completion in the crowd network. The factors that can be used to describe the effectiveness of information-sharing patterns include the network topology, the resources owned by intelligent subjects and the degree of information demand. The AISCN approach used heuristic algorithm to solve a composite objective function which takes all these factors into consideration, so that the optimized information-sharing pattern can be obtained.

Originality/value

This paper introduces a set of factors that can be used to describe the correlation between information-sharing pattern and performance of crowd network. By quantifying such correlation based on these factors, this paper proposes an adaptive information-sharing approach which can explore the optimized information-sharing pattern for a variety of crowd networks. As the approach is a data-driven approach that explores the information-sharing pattern based on the network’s performance on historical tasks and network’s characteristics, it is adaptive to the dynamic change (change of incoming tasks, change of network characteristics) of the target crowd network. To ensure the commonality of the information-sharing approach, the proposed approach is not designed for a specific optimization algorithm. In this way, during the implementation of the proposed approach, heuristic algorithms can be chosen according to the complexity of the target crowd network.

Details

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

Keywords

Open Access
Article
Publication date: 14 October 2019

Zhouxia Li, Zhiwen Pan, Xiaoni Wang, Wen Ji and Feng Yang

Intelligence level of a crowd network is defined as the expected reward of the network when completing the latest tasks (e.g. last N tasks). The purpose of this paper is to…

Abstract

Purpose

Intelligence level of a crowd network is defined as the expected reward of the network when completing the latest tasks (e.g. last N tasks). The purpose of this paper is to improve the intelligence level of a crowd network by optimizing the profession distribution of the crowd network.

Design/methodology/approach

Based on the concept of information entropy, this paper introduces the concept of business entropy and puts forward several factors affecting business entropy to analyze the relationship between the intelligence level and the profession distribution of the crowd network. This paper introduced Profession Distribution Deviation and Subject Interaction Pattern as the two factors which affect business entropy. By quantifying and combining the two factors, a Multi-Factor Business Entropy Quantitative (MFBEQ) model is proposed to calculate the business entropy of a crowd network. Finally, the differential evolution model and k-means clustering are applied to crowd intelligence network, and the species distribution of intelligent subjects is found, so as to achieve quantitative analysis of business entropy.

Findings

By establishing the MFBEQ model, this paper found that when the profession distribution of a crowd network is deviate less to the expected distribution, the intelligence level of a crowd network will be higher. Moreover, when subjects within the crowd network interact with each other more actively, the intelligence level of a crowd network becomes higher.

Originality/value

This paper aims to build the MFBEQ model according to factors that are related to business entropy and then uses the model to evaluate the intelligence level of a number of crowd networks.

Details

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

Keywords

Article
Publication date: 5 June 2018

The publishers of International Journal of Crowd Science wish to retract the article “Quality-time-complexity universal intelligence measurement”, by Wen Ji, Jing Liu, Zhiwen Pan

1072

Abstract

The publishers of International Journal of Crowd Science wish to retract the article “Quality-time-complexity universal intelligence measurement”, by Wen Ji, Jing Liu, Zhiwen Pan, Jingce Xu, Bing Liang, and Yiqiang Chen, which appeared in volume 2, issue 1, 2018. It has come to our attention that due to an error in the submission process the above article is an earlier version of the article published in International Journal of Crowd Science, volume 2, issue 2, 2018 (DOI: https://doi.org/10.1108/IJCS-04-2018-0007). The duplicate publication was the result of an inadvertent administrative error by the authors. The authors and publishers of the journal sincerely apologise to the readers.

Details

International Journal of Crowd Science, vol. 2 no. 1
Type: Research Article
ISSN: 2398-7294

Article
Publication date: 18 July 2018

Bing Hua, Zhiwen Zhang, Yunhua Wu and Zhiming Chen

The geomagnetic field vector is a function of the satellite’s position. The position and speed of the satellite can be determined by comparing the geomagnetic field vector…

Abstract

Purpose

The geomagnetic field vector is a function of the satellite’s position. The position and speed of the satellite can be determined by comparing the geomagnetic field vector measured by on board three-axis magnetometer with the standard value of the international geomagnetic field. The geomagnetic model has the disadvantages of uncertainty, low precision and long-term variability. Therefore, accuracy of autonomous navigation using the magnetometer is low. The purpose of this paper is to use the geomagnetic and sunlight information fusion algorithm to improve the orbit accuracy.

Design/methodology/approach

In this paper, an autonomous navigation method for low earth orbit satellite is studied by fusing geomagnetic and solar energy information. The algorithm selects the cosine value of the angle between the solar light vector and the geomagnetic vector, and the geomagnetic field intensity as observation. The Adaptive Unscented Kalman Filter (AUKF) filter is used to estimate the speed and position of the satellite, and the simulation research is carried out. This paper also made the same study using the UKF filter for comparison with the AUKF filter.

Findings

The algorithm of adding the sun direction vector information improves the positioning accuracy compared with the simple geomagnetic navigation, and the convergence and stability of the filter are better. The navigation error does not accumulate with time and has engineering application value. It also can be seen that AUKF filtering accuracy is better than UKF filtering accuracy.

Research limitations/implications

Geomagnetic navigation is greatly affected by the accuracy of magnetometer. This paper does not consider the spacecraft’s environmental interference with magnetic sensors.

Practical implications

Magnetometers and solar sensors are common sensors for micro-satellites. Near-Earth satellite orbit has abundant geomagnetic field resources. Therefore, the algorithm will have higher engineering significance in the practical application of low orbit micro-satellites orbit determination.

Originality/value

This paper introduces a satellite autonomous navigation algorithm. The AUKF geomagnetic filter algorithm using sunlight information can obviously improve the navigation accuracy and meet the basic requirements of low orbit small satellite orbit determination.

Details

International Journal of Intelligent Computing and Cybernetics, vol. 11 no. 4
Type: Research Article
ISSN: 1756-378X

Keywords

Article
Publication date: 9 July 2020

Ting Pan, Jiaqing Yan, Shenyun Zhou, Yingjie Cai and Congda Lu

The purpose of this paper is to propose the situation that the existing parking automated guided vehicle (AGV) has a single walking mode, a spin forward motion mode based on a…

Abstract

Purpose

The purpose of this paper is to propose the situation that the existing parking automated guided vehicle (AGV) has a single walking mode, a spin forward motion mode based on a dual steering wheel driven parking AGV. In this way, the AGV can complete the 180° spin of the AGV in the process of straight forward.

Design/methodology/approach

A spin forward kinematics model of the dual steering wheel AGV is established, and a motion controller of the dual steering wheel AGV is designed based on the principle of model predictive control to complete the path following the spin forward motion mode.

Findings

Computer simulations and laboratory tests were performed on this movement mode, which showed that the operation mode was feasible. It also verified that the mode can improve the handling efficiency, and also solved the problem that the parking space beside the wall could not be set and the site utilization was improved.

Research limitations/implications

The controller should be further improved to make the operation smoother and more accurate.

Practical implications

This mode has the applicability to the indoor logistics AGVs. In addition, it can improve the handling efficiency and also solved the problem that the storage space for goods beside the wall could not be set and the site utilization was improved.

Social implications

This method can solve the problem due to the increasing number of private cars and parking spaces are hard to find. It increases the number of parking spaces and improves the utilization rate of the site. In addition, it also saves people the time to find a parking space and reduces car exhaust emissions in the process. It follows the requirements of sustainable development.

Originality/value

The studies in this paper provide AGV with more ideas on the issue of improving handling efficiency and site utilization and also solves the problem of being unable to set parking spaces when parking against the wall. In addition, this model has applicability to indoor logistics AGV and plays the same role.

Details

Industrial Robot: the international journal of robotics research and application, vol. 47 no. 5
Type: Research Article
ISSN: 0143-991X

Keywords

Article
Publication date: 1 November 2021

Mohmed Y. Mohmed Al-Sabaawi, Ali Abdulfattah Alshaher and M.A. Alsalem

Electronic payment (e-payment) systems literature analysis reveals that they are growing in developing countries; however, they are limited in the Arab countries and, more…

2045

Abstract

Purpose

Electronic payment (e-payment) systems literature analysis reveals that they are growing in developing countries; however, they are limited in the Arab countries and, more importantly, scarce in Iraq in particular. Therefore, this paper aims to investigate the factors influencing the intention of users to use e-payment systems in Iraq. Additionally, this study proposes an e-payment adoption model based on technology usage models to identify user trends toward e-payment systems.

Design/methodology/approach

A quantitative approach is adopted to test the proposed model. The proposed model is based on the Unified Theory of Acceptance and Usage of Technology theory. The proposed model is validated using survey data from 339 e-payment system users. Using Amos software, this study used structural equation modeling (SEM), a statistical technique for analyzing factor relationships.

Findings

The findings of the study indicate that performance expectancy, effort expectancy, social influence, facilitating conditions and price saving orientation influence Intention to accept the e-payment system. Similarly, habit, technology security, trust, innovation resistance, psychological empowerment also affect intention to accept an e-payment system. However, hedonic motivation and perceived risk do not affect e-payment system adoption.

Originality/value

The identified factors play a major role in user intentions toward the adoption of e-payment systems for financial transactions and addressing these factors will make e-payment acceptable in the future. The results of this study contribute to assisting governments or e-payment firms and decision-makers in building strategic decisions or policies that will increase the adoption of e-payment by individuals.

Details

Journal of Science and Technology Policy Management, vol. 14 no. 2
Type: Research Article
ISSN: 2053-4620

Keywords

Article
Publication date: 7 October 2021

Lantian Li and Bahareh Pahlevanzadeh

Cloud eases information processing, but it holds numerous risks, including hacking and confidentiality problems. It puts businesses at risk in terms of data security and…

Abstract

Purpose

Cloud eases information processing, but it holds numerous risks, including hacking and confidentiality problems. It puts businesses at risk in terms of data security and compliance. This paper aims to maximize the covered human resource (HR) vulnerabilities and minimize the security costs in the enterprise cloud using a fuzzy-based method and firefly optimization algorithm.

Design/methodology/approach

Cloud computing provides a platform to improve the quality and availability of IT resources. It changes the way people communicate and conduct their businesses. However, some security concerns continue to derail the expansion of cloud-based systems into all parts of human life. Enterprise cloud security is a vital component in ensuring the long-term stability of cloud technology by instilling trust. In this paper, a fuzzy-based method and firefly optimization algorithm are suggested for optimizing HR vulnerabilities while mitigating security expenses in organizational cloud environments. MATLAB is employed as a simulation tool to assess the efficiency of the suggested recommendation algorithm. The suggested approach is based on the firefly algorithm (FA) since it is swift and reduces randomization throughout the lookup for an optimal solution, resulting in improved performance.

Findings

The fuzzy-based method and FA unveil better performance than existing met heuristic algorithms. Using a simulation, all the results are verified. The study findings showed that this method could simulate complex and dynamic security problems in cloud services.

Practical implications

The findings may be utilized to assist the cloud provider or tenant of the cloud infrastructure system in taking appropriate risk mitigation steps.

Originality/value

Using a fuzzy-based method and FA to maximize the covered HR vulnerabilities and minimize the security costs in the enterprise cloud is the main novelty of this paper.

Details

Kybernetes, vol. 51 no. 6
Type: Research Article
ISSN: 0368-492X

Keywords

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