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1 – 4 of 4This paper aims to investigate the relationship of female participation in labor force with the cybersecurity maturity of nations and the enabling role of e-government development…
Abstract
Purpose
This paper aims to investigate the relationship of female participation in labor force with the cybersecurity maturity of nations and the enabling role of e-government development in moderating the same.
Design/methodology/approach
The authors have conducted fixed-effects regression using archival data for 149 countries taken from secondary sources. Furthermore, the authors have grouped the sample countries into four levels of cybersecurity maturity (unprepared, reactive, anticipatory and innovative) using clustering techniques, and studied the influence of their interest variables for individual groups.
Findings
Results show that female participation in labor force positively influences national cybersecurity maturity, and e-government development positively moderates the said relationship, thereby enabling the empowerment of women.
Practical implications
Encouraging broader participation of women in the labor force and prioritizing investments in e-government development are essential steps that organizations and governments may take to enhance a country’s cybersecurity maturity level.
Originality/value
This study empirically demonstrates the impact of the nuanced interplay between female participation in labor force and the e-government development of a nation on its cybersecurity maturity.
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Fangqi Hong, Pengfei Wei and Michael Beer
Bayesian cubature (BC) has emerged to be one of most competitive approach for estimating the multi-dimensional integral especially when the integrand is expensive to evaluate, and…
Abstract
Purpose
Bayesian cubature (BC) has emerged to be one of most competitive approach for estimating the multi-dimensional integral especially when the integrand is expensive to evaluate, and alternative acquisition functions, such as the Posterior Variance Contribution (PVC) function, have been developed for adaptive experiment design of the integration points. However, those sequential design strategies also prevent BC from being implemented in a parallel scheme. Therefore, this paper aims at developing a parallelized adaptive BC method to further improve the computational efficiency.
Design/methodology/approach
By theoretically examining the multimodal behavior of the PVC function, it is concluded that the multiple local maxima all have important contribution to the integration accuracy as can be selected as design points, providing a practical way for parallelization of the adaptive BC. Inspired by the above finding, four multimodal optimization algorithms, including one newly developed in this work, are then introduced for finding multiple local maxima of the PVC function in one run, and further for parallel implementation of the adaptive BC.
Findings
The superiority of the parallel schemes and the performance of the four multimodal optimization algorithms are then demonstrated and compared with the k-means clustering method by using two numerical benchmarks and two engineering examples.
Originality/value
Multimodal behavior of acquisition function for BC is comprehensively investigated. All the local maxima of the acquisition function contribute to adaptive BC accuracy. Parallelization of adaptive BC is realized with four multimodal optimization methods.
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Han Wang, Quan Zhang, Zhenquan Fan, Gongcheng Wang, Pengchao Ding and Weidong Wang
To solve the obstacle detection problem in robot autonomous obstacle negotiation, this paper aims to propose an obstacle detection system based on elevation maps for three types…
Abstract
Purpose
To solve the obstacle detection problem in robot autonomous obstacle negotiation, this paper aims to propose an obstacle detection system based on elevation maps for three types of obstacles: positive obstacles, negative obstacles and trench obstacles.
Design/methodology/approach
The system framework includes mapping, ground segmentation, obstacle clustering and obstacle recognition. The positive obstacle detection is realized by calculating its minimum rectangle bounding boxes, which includes convex hull calculation, minimum area rectangle calculation and bounding box generation. The detection of negative obstacles and trench obstacles is implemented on the basis of information absence in the map, including obstacles discovery method and type confirmation method.
Findings
The obstacle detection system has been thoroughly tested in various environments. In the outdoor experiment, with an average speed of 22.2 ms, the system successfully detected obstacles with a 95% success rate, indicating the effectiveness of the detection algorithm. Moreover, the system’s error range for obstacle detection falls between 4% and 6.6%, meeting the necessary requirements for obstacle negotiation in the next stage.
Originality/value
This paper studies how to solve the obstacle detection problem when the robot obstacle negotiation.
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Tulsi Pawan Fowdur and Ashven Sanghan
Energy production and distribution is undergoing a revolutionary transition with the advent of disruptive technologies such as the Internet of Energy (IoE), 5G and artificial…
Abstract
Energy production and distribution is undergoing a revolutionary transition with the advent of disruptive technologies such as the Internet of Energy (IoE), 5G and artificial intelligence (AI). IoE essentially involves automating and enhancing the energy infrastructure: the power grid from grid operators to energy generators and distribution utilities. The IoE also relies on powerful connectivity networks such as 5G, big data analytics and AI to optimise its operation. By incorporating the technology that employs ubiquitous devices such as smartphones, tablets or smart electric vehicles, it will be possible to fully exploit the potential of IoE using 5G networks. 5G networks will provide high speed connections between devices such as drones, tractors and cloud networks, to transfer huge amounts of sensor data. Additionally, there are many sources of isolated data across the main energy production units (generation, transmission and distribution), and the data is increasing at phenomenal rates. By applying AI to these data, major improvements can be brought at each stage of the energy production chain. Tying renewable energy to the telecommunications sector and leveraging on the potential of data analytics is something which is gaining major attention among researchers and industry experts. This chapter therefore explores the combination of three of the most promising technologies i.e. IoE, 5G and AI for achieving affordable and clean energy, which is SDG 7 in the UN Sustainable Development Goals (SDGs).
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