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1 – 10 of 39Qihua Ma, Qilin Li, Wenchao Wang and Meng Zhu
This study aims to achieve superior localization and mapping performance in point cloud degradation scenarios through the effective removal of dynamic obstacles. With the…
Abstract
Purpose
This study aims to achieve superior localization and mapping performance in point cloud degradation scenarios through the effective removal of dynamic obstacles. With the continuous development of various technologies for autonomous vehicles, the LIDAR-based Simultaneous localization and mapping (SLAM) system is becoming increasingly important. However, in SLAM systems, effectively addressing the challenges of point cloud degradation scenarios is essential for accurate localization and mapping, with dynamic obstacle removal being a key component.
Design/methodology/approach
This paper proposes a method that combines adaptive feature extraction and loop closure detection algorithms to address this challenge. In the SLAM system, the ground point cloud and non-ground point cloud are separated to reduce the impact of noise. And based on the cylindrical projection image of the point cloud, the intensity features are adaptively extracted, the degradation direction is determined by the degradation factor and the intensity features are matched with the map to correct the degraded pose. Moreover, through the difference in raster distribution of the point clouds before and after two frames in the loop process, the dynamic point clouds are identified and removed, and the map is updated.
Findings
Experimental results show that the method has good performance. The absolute displacement accuracy of the laser odometer is improved by 27.1%, the relative displacement accuracy is improved by 33.5% and the relative angle accuracy is improved by 23.8% after using the adaptive intensity feature extraction method. The position error is reduced by 30% after removing the dynamic target.
Originality/value
Compared with LiDAR odometry and mapping algorithm, the method has greater robustness and accuracy in mapping and localization.
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Yanmin Zhou, Zheng Yan, Ye Yang, Zhipeng Wang, Ping Lu, Philip F. Yuan and Bin He
Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing…
Abstract
Purpose
Vision, audition, olfactory, tactile and taste are five important senses that human uses to interact with the real world. As facing more and more complex environments, a sensing system is essential for intelligent robots with various types of sensors. To mimic human-like abilities, sensors similar to human perception capabilities are indispensable. However, most research only concentrated on analyzing literature on single-modal sensors and their robotics application.
Design/methodology/approach
This study presents a systematic review of five bioinspired senses, especially considering a brief introduction of multimodal sensing applications and predicting current trends and future directions of this field, which may have continuous enlightenments.
Findings
This review shows that bioinspired sensors can enable robots to better understand the environment, and multiple sensor combinations can support the robot’s ability to behave intelligently.
Originality/value
The review starts with a brief survey of the biological sensing mechanisms of the five senses, which are followed by their bioinspired electronic counterparts. Their applications in the robots are then reviewed as another emphasis, covering the main application scopes of localization and navigation, objection identification, dexterous manipulation, compliant interaction and so on. Finally, the trends, difficulties and challenges of this research were discussed to help guide future research on intelligent robot sensors.
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Chuyu Tang, Hao Wang, Genliang Chen and Shaoqiu Xu
This paper aims to propose a robust method for non-rigid point set registration, using the Gaussian mixture model and accommodating non-rigid transformations. The posterior…
Abstract
Purpose
This paper aims to propose a robust method for non-rigid point set registration, using the Gaussian mixture model and accommodating non-rigid transformations. The posterior probabilities of the mixture model are determined through the proposed integrated feature divergence.
Design/methodology/approach
The method involves an alternating two-step framework, comprising correspondence estimation and subsequent transformation updating. For correspondence estimation, integrated feature divergences including both global and local features, are coupled with deterministic annealing to address the non-convexity problem of registration. For transformation updating, the expectation-maximization iteration scheme is introduced to iteratively refine correspondence and transformation estimation until convergence.
Findings
The experiments confirm that the proposed registration approach exhibits remarkable robustness on deformation, noise, outliers and occlusion for both 2D and 3D point clouds. Furthermore, the proposed method outperforms existing analogous algorithms in terms of time complexity. Application of stabilizing and securing intermodal containers loaded on ships is performed. The results demonstrate that the proposed registration framework exhibits excellent adaptability for real-scan point clouds, and achieves comparatively superior alignments in a shorter time.
Originality/value
The integrated feature divergence, involving both global and local information of points, is proven to be an effective indicator for measuring the reliability of point correspondences. This inclusion prevents premature convergence, resulting in more robust registration results for our proposed method. Simultaneously, the total operating time is reduced due to a lower number of iterations.
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Shiyuan Yin, Mengqi Jiang, Lujie Chen and Fu Jia
Within the current institutional landscape, characterized by increased societal and governmental emphasis on environmental preservation, there is growing interest in the potential…
Abstract
Purpose
Within the current institutional landscape, characterized by increased societal and governmental emphasis on environmental preservation, there is growing interest in the potential of digital transformation (DT) to advance the circular economy (CE). Nonetheless, the empirical substantiation of the connection between DT and CE remains limited. This study seeks to investigate the impact of DT on CE at the organizational level and examine how various institutional factors may shape this relationship within the Chinese context.
Design/methodology/approach
To scrutinize this association, we construct a research framework and formulate hypotheses drawing on institutional theory, obtaining panel data from 238 Chinese-listed high-tech manufacturing firms from 2006 to 2019. A regression analysis approach is adopted for the sample data.
Findings
Our regression analysis reveals a positive influence of DT on CE performance at the organizational level. Furthermore, our findings suggest that the strength of this relationship is bolstered in the presence of heightened regional institutional development and industry competition. Notably, we find no discernible effect of a firm’s political connections on the DT–CE performance nexus.
Originality/value
This study furnishes empirical evidence on the relationship between DT and CE performance. By elucidating the determinants of this relationship within the distinct context of Chinese institutions, our research offers theoretical and practical insights, thus laying the groundwork for subsequent investigations into this burgeoning area of inquiry.
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Muhammad Ashraf Fauzi, Christine Nya-Ling Tan, Puteri Fadzline Muhamad Tamyez, Nurul Ashykin Abd Aziz and Walton Wider
Gender bias and stereotypes are universal issues in today’s society. This study presents a comprehensive review of women’s leadership based on bibliometric analysis. The feminist…
Abstract
Purpose
Gender bias and stereotypes are universal issues in today’s society. This study presents a comprehensive review of women’s leadership based on bibliometric analysis. The feminist approach to leadership is helpful in many ways, and it could be the type of leadership needed in the challenging world of academia. Women present unique characteristics and traits, particularly their motherly approach to leadership.
Design/methodology/approach
A review of the literature based on bibliometric analysis by mapping the knowledge structure of the subject is conferred by uncovering the past, present and future trends based on three bibliometric analyses.
Findings
The finding suggests that gender equality, stereotypes and barriers in women’s leadership are at the forefront of the subject in HEIs. The overall system, mindset and willingness for institutional transformation are needed to change the mindset of accepting women as leaders of HEIs.
Research limitations/implications
This study brought the significant idea of increasing women’s empowerment in HEIs, eventually strengthening institutional leadership’s capability towards advanced education.
Originality/value
This study would present a crucial foundation in women’s empowerment, particularly from the HEIs perspective and from the generic women’s leadership literature.
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Md. Nurul Islam, Guangwei Hu, Murtaza Ashiq and Shakil Ahmad
This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of…
Abstract
Purpose
This bibliometric study aims to analyze the latest trends and patterns of big data applications in librarianship from 2000 to 2022. By conducting a comprehensive examination of the existing literature, this study aims to provide valuable insights into the emerging field of big data in librarianship and its potential impact on the future of libraries.
Design/methodology/approach
This study employed a rigorous four-stage process of identification, screening, eligibility and inclusion to filter and select the most relevant documents for analysis. The Scopus database was utilized to retrieve pertinent data related to big data applications in librarianship. The dataset comprised 430 documents, including journal articles, conference papers, book chapters, reviews and books. Through bibliometric analysis, the study examined the effectiveness of different publication types and identified the main topics and themes within the field.
Findings
The study found that the field of big data in librarianship is growing rapidly, with a significant increase in publications and citations over the past few years. China is the leading country in terms of publication output, followed by the United States of America. The most influential journals in the field are Library Hi Tech and the ACM International Conference Proceeding Series. The top authors in the field are Minami T, Wu J, Fox EA and Giles CL. The most common keywords in the literature are big data, librarianship, data mining, information retrieval, machine learning and webometrics.
Originality/value
This bibliometric study contributes to the existing body of literature by comprehensively analyzing the latest trends and patterns in big data applications within librarianship. It offers a systematic approach to understanding the state of the field and highlights the unique contributions made by various types of publications. The study’s findings and insights contribute to the originality of this research, providing a foundation for further exploration and advancement in the field of big data in librarianship.
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Muhammed Sajid, K.A. Zakkariya and Myriam Ertz
The zero-waste lifestyle (ZWL) is considered a reasonable step towards controlling waste generation and minimizing the consequences of human activities on the environment. The…
Abstract
Purpose
The zero-waste lifestyle (ZWL) is considered a reasonable step towards controlling waste generation and minimizing the consequences of human activities on the environment. The main aim of this study is to examine the behavioral antecedents of ZWL.
Design/methodology/approach
The study draws on the theoretical underpinnings of the theory of planned behavior (TPB) and the norm activation model (NAM) to develop a conceptual framework to understand the antecedents to ZWL. A cross-sectional survey among 349 randomly-selected consumers provided data analyzed with the partial least square-structural equation modeling (PLS-SEM) methodology.
Findings
The results demonstrate that personal norms, attitude, subjective norms and perceived behavioral control positively influenced the intention to adopt ZWL. Additionally, the study showed that the awareness of consequences influenced personal norms, attitudes and subjective norms. However, the study identified an intention–behavior gap in adopting ZWL.
Originality/value
This study serves as a pioneering exploration of the behavioral factors that impact the adoption of ZWL. Additionally, the paper endeavors to elucidate the underlying reasons behind the intention–behavior gap within this particular context. Consequently, the study offers substantial theoretical and practical implications aimed at promoting and fostering greater adoption of ZWL practices.
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Xiaojie Xu and Yun Zhang
Understandings of house prices and their interrelationships have undoubtedly drawn a great amount of attention from various market participants. This study aims to investigate the…
Abstract
Purpose
Understandings of house prices and their interrelationships have undoubtedly drawn a great amount of attention from various market participants. This study aims to investigate the monthly newly-built residential house price indices of seventy Chinese cities during a 10-year period spanning January 2011–December 2020 for understandings of issues related to their interdependence and synchronizations.
Design/methodology/approach
Analysis here is facilitated through network analysis together with topological and hierarchical characterizations of price comovements.
Findings
This study determines eight sectoral groups of cities whose house price indices are directly connected and the price synchronization within each group is higher than that at the national level, although each shows rather idiosyncratic patterns. Degrees of house price comovements are generally lower starting from 2018 at the national level and for the eight sectoral groups. Similarly, this study finds that the synchronization intensity associated with the house price index of each city generally switches to a lower level starting from early 2019.
Originality/value
Results here should be of use to policy design and analysis aiming at housing market evaluations and monitoring.
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Yunis Ali Ahmed, Hafiz Muhammad Faisal Shehzad, Muhammad Mahboob Khurshid, Omayma Husain Abbas Hassan, Samah Abdelsalam Abdalla and Nashat Alrefai
Building information modelling (BIM) has transformed the traditional practices of the Architecture, Engineering and Construction (AEC) industry. BIM creates a collaborative…
Abstract
Purpose
Building information modelling (BIM) has transformed the traditional practices of the Architecture, Engineering and Construction (AEC) industry. BIM creates a collaborative digital representation of built environment data. Competitive advantage can be achieved with collaborative project delivery and rich information modelling. Despite the abundant benefits, BIM’s adoption in the AEC is susceptible to confrontation. A substantial impediment to BIM adoption often cited is data interoperability. Other facets of interoperability got limited attention. Other academic areas, including information systems, discuss the interoperability construct ahead of data interoperability. These interoperability factors have yet to be surveyed in the AEC industry. This study aims to investigate the effect of interoperability factors on BIM adoption and develop a comprehensive BIM adoption model.
Design/methodology/approach
The theoretical foundations of the proposed model are based on the European interoperability framework (EIF) and technology, organization, environment framework (TOE). Quantitative data collection from construction firms is gathered. The model has been thoroughly examined and validated using partial least squares structural equation modelling in SmartPLS software.
Findings
The study’s findings indicate that relative advantage, top management support, government support, organizational readiness and regulation support are determinants of BIM adoption. Financial constraints, complexity, lack of technical interoperability, semantic interoperability, organizational interoperability and uncertainty are barriers to BIM adoption. However, compatibility, competitive pressure and legal interoperability do not affect BIM adoption.
Practical implications
Finally, this study provides recommendations containing the essential technological, organizational, environmental and interoperability factors that AEC stakeholders can address to enhance BIM adoption.
Originality/value
To the best of the authors’ knowledge, this paper is one of the first studies to combine TOE and EIF in a single research model. This research provides empirical evidence for using the proposed model as a guide to promoting BIM adoption. As a result, the highlighted determinants can assist organizations in developing and executing successful policies that support BIM adoption in the AEC industry.
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Mumtaz Ali, Ahmed Samour, Foday Joof and Turgut Tursoy
This study aims to assess how real income, oil prices and gold prices affect housing prices in China from 2010 to 2021.
Abstract
Purpose
This study aims to assess how real income, oil prices and gold prices affect housing prices in China from 2010 to 2021.
Design/methodology/approach
This study uses a novel bootstrap autoregressive distributed lag (ARDL) testing to empirically analyze the short and long links among the tested variables.
Findings
The ARDL estimations demonstrate a positive impact of oil price shocks and real income on housing market prices in both the phrases of the short and long run. Furthermore, the results reveal that gold price shocks negatively affect housing prices both in the short and long run. The result can be attributed to China’s housing market and advanced infrastructure, resulting in a drop in housing prices as gold prices increase. Additionally, the prediction of housing market prices will provide a base and direction for housing market investors to forecast housing prices and avoid losses.
Originality/value
To the best of the authors’ knowledge, this is the first attempt to analyze the effect of gold price shocks on housing market prices in China.
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