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Article
Publication date: 14 February 2019

Lucy Barnard-Brak, David Richman and Zhanxia Yang

Autism spectrum disorder (ASD) is a lifelong disorder that requires intervention and support services for a growing geriatric population. The purpose of this paper is to examine…

Abstract

Purpose

Autism spectrum disorder (ASD) is a lifelong disorder that requires intervention and support services for a growing geriatric population. The purpose of this paper is to examine the mean age at death of individuals with ASD and subsequent comorbidity with Alzheimer’s disease, and any form of dementia, as a whole and according to sex.

Design/methodology/approach

Data consisted of 1,754 individuals who had an ASD listed as one of the causes of deaths from the National Vital Statistics System with data from 1999 to 2015. In the current study, the authors present contradictory results with a mean age at death for individuals with ASD was 68 years by adjusting for changing prevalence rates.

Findings

Females with ASD had a higher mean age at death than males with ASD; consistent with the trend in the sex differences in the general population. The results of the current study also indicate that individuals with ASD were, in fact, less likely than the general population to have Alzheimer’s disease or a form of dementia. However, males with ASD were significantly more likely to have acquired Alzheimer’s disease or a form of dementia as compared to females with ASD.

Originality/value

Guan and Li (2017) reported a mean age at death of 36 years old for individuals with ASD, which was subsequently reported in the mass media, most notably CNN. The authors contend that this study provides a more accurate estimate mean age at death.

Details

Advances in Autism, vol. 5 no. 4
Type: Research Article
ISSN: 2056-3868

Keywords

Article
Publication date: 6 February 2017

Biwei Tang, Zhu Zhanxia and Jianjun Luo

Aiming at obtaining a high-quality global path for a mobile robot which works in complex environments, a modified particle swarm optimization (PSO) algorithm, named…

Abstract

Purpose

Aiming at obtaining a high-quality global path for a mobile robot which works in complex environments, a modified particle swarm optimization (PSO) algorithm, named random-disturbance self-adaptive particle swarm optimization (RDSAPSO), is proposed in this paper.

Design/methodology/approach

A perturbed global updating mechanism is introduced to the global best position to avoid stagnation in RDSAPSO. Moreover, a new self-adaptive strategy is proposed to fine-tune the three control parameters in RDSAPSO to dynamically adjust the exploration and exploitation capabilities of RDSAPSO. Because the convergence of PSO is paramount and influences the quality of the generated path, this paper also analytically investigates the convergence of RDSAPSO and provides a convergence-guaranteed parameter selection principle for RDSAPSO. Finally, a RDSAPSO-based global path planning (GPP) method is developed, in which the feasibility-based rule is applied to handle the constraint of the problem.

Findings

In an attempt to validate the proposed method, it is compared against six state-of-the-art evolutionary methods under three different numerical simulations. The simulation results confirm that the proposed method is highly competitive in terms of the path optimality. Moreover, the computation time of the proposed method is comparable with those of the other compared methods.

Originality/value

Therefore, the proposed method can be considered as a vital alternative in the field of GPP.

Article
Publication date: 6 June 2023

Qianlong Li, Zhanxia Zhu and Junwu Liang

Owing to the complex space environment and limited computing resources, traditional and deep learning-based methods cannot complete the task of satellite component contour…

Abstract

Purpose

Owing to the complex space environment and limited computing resources, traditional and deep learning-based methods cannot complete the task of satellite component contour extraction effectively. To this end, this paper aims to propose a high-quality real-time contour extraction method based on lightweight space mobile platforms.

Design/methodology/approach

A contour extraction method that combines two edge clues is proposed. First, Canny algorithm is improved to extract preliminary contours without inner edges from the depth images. Subsequently, a new type of edge pixel feature is designed based on surface normal. Finally, surface normal edges are extracted to supplement the integrity of the preliminary contours for contour extraction.

Findings

Extensive experiments show that this method can achieve a performance comparable to that of deep learning-based methods and can achieve a 36.5 FPS running rate on mobile processors. In addition, it exhibits better robustness under complex scenes.

Practical implications

The proposed method is expected to promote the deployment process of satellite component contour extraction tasks on lightweight space mobile platforms.

Originality/value

A pixel feature for edge detection is designed and combined with the improved Canny algorithm to achieve satellite component contour extraction. This study provides a new research idea for contour extraction and instance segmentation research.

Details

Aircraft Engineering and Aerospace Technology, vol. 95 no. 8
Type: Research Article
ISSN: 1748-8842

Keywords

Open Access
Article
Publication date: 14 November 2022

Sara Trucco, Maria Chiara Demartini, Kevin McMeeking and Valentina Beretta

This paper aims to investigate the effect of voluntary non-financial reporting on the evaluation of audit risk from the auditors’ viewpoint in a post-crisis period. Furthermore…

1474

Abstract

Purpose

This paper aims to investigate the effect of voluntary non-financial reporting on the evaluation of audit risk from the auditors’ viewpoint in a post-crisis period. Furthermore, this paper analyses whether auditors perceive that voluntary non-financial reporting impacts audit risk differently for old clients as compared with new clients.

Design/methodology/approach

This study is conducted on a sample of Italian audit firms through a paper-based questionnaire. Both Big4 and non-Big4 audit firms have been included in the sample.

Findings

Results show that integrated reporting is perceived to be the most relevant reporting method and intellectual capital statement the least relevant. Surprisingly, empirical findings over the sample period show that auditors do not perceive statistically significant differences between old and new clients.

Practical implications

Auditors can identify opportunities to adapt their assessment model to include voluntary non-financial report information. Moreover, they can use different assessment models regarding the research variables in the case of new and old clients.

Originality/value

Empirical findings highlight the growing role of voluntary non-financial reporting in the auditors’ perception of their client’s audit risk. All the observed voluntary non-financial reporting forms, except for intellectual capital, are considered as relevant by auditors in the evaluation of their client’s audit risk when compared to an indifference point. In addition, findings reveal that female auditors perceive a reduced gap in the relevance between integrated reports and intellectual capital reports compared to their counterparts.

Details

Meditari Accountancy Research, vol. 30 no. 7
Type: Research Article
ISSN: 2049-372X

Keywords

Article
Publication date: 26 September 2019

Asma Ayari and Sadok Bouamama

The multi-robot task allocation (MRTA) problem is a challenging issue in the robotics area with plentiful practical applications. Expanding the number of tasks and robots…

Abstract

Purpose

The multi-robot task allocation (MRTA) problem is a challenging issue in the robotics area with plentiful practical applications. Expanding the number of tasks and robots increases the size of the state space significantly and influences the performance of the MRTA. As this process requires high computational time, this paper aims to describe a technique that minimizes the size of the explored state space, by partitioning the tasks into clusters. In this paper, the authors address the problem of MRTA by putting forward a new automatic clustering algorithm of the robots' tasks based on a dynamic-distributed double-guided particle swarm optimization, namely, ACD3GPSO.

Design/methodology/approach

This approach is made out of two phases: phase I groups the tasks into clusters using the ACD3GPSO algorithm and phase II allocates the robots to the clusters. Four factors are introduced in ACD3GPSO for better results. First, ACD3GPSO uses the k-means algorithm as a means to improve the initial generation of particles. The second factor is the distribution using the multi-agent approach to reduce the run time. The third one is the diversification introduced by two local optimum detectors LODpBest and LODgBest. The last one is based on the concept of templates and guidance probability Pguid.

Findings

Computational experiments were carried out to prove the effectiveness of this approach. It is compared against two state-of-the-art solutions of the MRTA and against two evolutionary methods under five different numerical simulations. The simulation results confirm that the proposed method is highly competitive in terms of the clustering time, clustering cost and MRTA time.

Practical implications

The proposed algorithm is quite useful for real-world applications, especially the scenarios involving a high number of robots and tasks.

Originality/value

In this methodology, owing to the ACD3GPSO algorithm, task allocation's run time has diminished. Therefore, the proposed method can be considered as a vital alternative in the field of MRTA with growing numbers of both robots and tasks. In PSO, stagnation and local optima issues are avoided by adding assorted variety to the population, without losing its fast convergence.

Details

Assembly Automation, vol. 40 no. 2
Type: Research Article
ISSN: 0144-5154

Keywords

Article
Publication date: 18 November 2020

Mahdi Salehi, Samira Ahmadzadeh and Fahimeh Irvani Qale Sorkh

The present study aims to assess the potential effects of intellectual capital (IC) and disclosure of firms' affiliate transactions on contractual costs (CC).

Abstract

Purpose

The present study aims to assess the potential effects of intellectual capital (IC) and disclosure of firms' affiliate transactions on contractual costs (CC).

Design/methodology/approach

The statistical population of the study includes 768 firm-year observations listed on the Tehran Stock Exchange during 2012–2017. According to Pulic's model, the authors divide IC into three components, such as human capital (HC), relational capital and structural capital (SC). CC is also measured by utilising two variables of board cash compensation and unexpected reward of managers.

Findings

The results show that there is a negative and significant relationship between HC and CC. In contrast, the authors find that relational capital and SC have a positive impact on CC. The authors’ further analyses also demonstrate that disclosure of transactions with affiliates has a negative effect on unexpected rewards of managers.

Originality/value

Since there is no conducted study, which discusses the relationship between IC and contractual cost, this paper might be considered the primary studies conducted in this line of literature, specifically in emerging markets. Moreover, to the best of the authors' knowledge, this is the first study investigating the potential impact of disclosure of selling and purchasing transactions, separately, on the director's unexpected reward.

Details

International Journal of Productivity and Performance Management, vol. 71 no. 1
Type: Research Article
ISSN: 1741-0401

Keywords

Article
Publication date: 7 July 2020

Jiehao Li, Junzheng Wang, Shoukun Wang, Hui Peng, Bomeng Wang, Wen Qi, Longbin Zhang and Hang Su

This paper aims on the trajectory tracking of the developed six wheel-legged robot with heavy load conditions under uncertain physical interaction. The accuracy of trajectory…

Abstract

Purpose

This paper aims on the trajectory tracking of the developed six wheel-legged robot with heavy load conditions under uncertain physical interaction. The accuracy of trajectory tracking and stable operation with heavy load are the main challenges of parallel mechanism for wheel-legged robots, especially in complex road conditions. To guarantee the tracking performance in an uncertain environment, the disturbances, including the internal friction, external environment interaction, should be considered in the practical robot system.

Design/methodology/approach

In this paper, a fuzzy approximation-based model predictive tracking scheme (FMPC) for reliable tracking control is developed to the six wheel-legged robot, in which the fuzzy logic approximation is applied to estimate the uncertain physical interaction and external dynamics of the robot system. Meanwhile, the advanced parallel mechanism of the electric six wheel-legged robot (BIT-NAZA) is presented.

Findings

Co-simulation and comparative experimental results using the BIT-NAZA robot derived from the developed hybrid control scheme indicate that the methodology can achieve satisfactory tracking performance in terms of accuracy and stability.

Originality/value

This research can provide theoretical and engineering guidance for lateral stability of intelligent robots under unknown disturbances and uncertain nonlinearities and facilitate the control performance of the mobile robots in a practical system.

Details

Assembly Automation, vol. 40 no. 5
Type: Research Article
ISSN: 0144-5154

Keywords

Article
Publication date: 17 April 2019

Hu Xiao, Rongxin Cui and Demin Xu

This paper aims to present a distributed Bayesian approach with connectivity maintenance to manage a multi-agent network search for a target on a two-dimensional plane.

Abstract

Purpose

This paper aims to present a distributed Bayesian approach with connectivity maintenance to manage a multi-agent network search for a target on a two-dimensional plane.

Design/methodology/approach

The Bayesian framework is used to compute the local probability density functions (PDFs) of the target and obtain the global PDF with the consensus algorithm. An inverse power iteration algorithm is introduced to estimate the algebraic connectivity λ2 of the network. Based on the estimated λ2, the authors design a potential field for the connectivity maintenance. Then, based on the detection probability function, the authors design a potential field for the search target. The authors combine the two potential fields and design a distributed gradient-based control for the agents.

Findings

The inverse power iteration algorithm can distributed estimate the algebraic connectivity by the agents. The agents can efficient search the target with connectivity maintenance with the designed distributed gradient-based search algorithm.

Originality/value

Previous study has paid little attention to the multi-agent search problem with connectivity maintenance. Our algorithm guarantees that the strongly connected graph of the multi-agent communication topology is always established while performing the distributed target search problem.

Details

Assembly Automation, vol. 40 no. 1
Type: Research Article
ISSN: 0144-5154

Keywords

Article
Publication date: 9 February 2024

Ravinder Singh

This paper aims to focus on solving the path optimization problem by modifying the probabilistic roadmap (PRM) technique as it suffers from the selection of the optimal number of…

Abstract

Purpose

This paper aims to focus on solving the path optimization problem by modifying the probabilistic roadmap (PRM) technique as it suffers from the selection of the optimal number of nodes and deploy in free space for reliable trajectory planning.

Design/methodology/approach

Traditional PRM is modified by developing a decision-making strategy for the selection of optimal nodes w.r.t. the complexity of the environment and deploying the optimal number of nodes outside the closed segment. Subsequently, the generated trajectory is made smoother by implementing the modified Bezier curve technique, which selects an optimal number of control points near the sharp turns for the reliable convergence of the trajectory that reduces the sum of the robot’s turning angles.

Findings

The proposed technique is compared with state-of-the-art techniques that show the reduction of computational load by 12.46%, the number of sharp turns by 100%, the number of collisions by 100% and increase the velocity parameter by 19.91%.

Originality/value

The proposed adaptive technique provides a better solution for autonomous navigation of unmanned ground vehicles, transportation, warehouse applications, etc.

Details

Robotic Intelligence and Automation, vol. 44 no. 1
Type: Research Article
ISSN: 2754-6969

Keywords

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