Seyyed Mohammadreza Ayazi, Ali Zamani Babgohari and Mohammadreza Taghizadeh-Yazdi
Many European businesses are small and medium enterprises (SMEs), contributing significantly to the well-being of local economies and regions. Even so, SMEs face many challenges…
Abstract
Many European businesses are small and medium enterprises (SMEs), contributing significantly to the well-being of local economies and regions. Even so, SMEs face many challenges in fostering innovation and improving performance. Furthermore, the raw material consumption is increasing globally, necessitating the development of strategies that will reduce the number of raw materials extracted and imported while improving the sustainability of small and medium-sized businesses. Consequently, promoting circular economy (CE) strategies, such as industrial symbiosis (IS) partnerships, whereby waste products from other industries serve as a source of raw materials for companies, is critical. Identifying and analysing enablers or drivers that support IS collaborations among SMEs is necessary to achieve this goal. In this regard, the purpose of this study will explore the enablers of IS among SMEs considering sustainability dimensions (environmental, social and economic). As facing a decision-making (DM) problem, the multiple attribute decision-making (MADM) approach was applied in a hesitant fuzzy (HF) environment in this research to answer the research questions. In this regard, in phase 1, IS enablers were identified and extracted using a literature review and experts’ opinions. In phase 2, the hesitant fuzzy Delphi (HFD) method was implemented to screen and finalise the enablers identified. In phase 3, casual relations among final enablers were determined using the hesitant fuzzy ANP (HF-ANP) method. Finally, in phase 4, the relative importance of enablers was calculated using the hesitant fuzzy best–worst method (HF-BWM). Consequently, this study provided potential strategies for IS that can be implemented quickly and used by local authorities to support SMEs in achieving circular waste management.
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Noel Scott, Brent Moyle, Ana Cláudia Campos, Liubov Skavronskaya and Biqiang Liu
Wenjing Wu, Ning Zhao, Liang Zhang and Yuhang Wu
This paper aims to investigate the problem of adaptive bipartite tracking control in nonlinear networked multi-agent systems (MASs) under the influence of periodic disturbances…
Abstract
Purpose
This paper aims to investigate the problem of adaptive bipartite tracking control in nonlinear networked multi-agent systems (MASs) under the influence of periodic disturbances. It considers both cooperative and competitive relationships among agents within the MASs.
Design/methodology/approach
In response to the inherent limitations of practical systems regarding transmission resources, this paper introduces a novel approach. It addresses both control signal transmission and triggering conditions, presenting a two-bit-triggered control method aimed at conserving system transmission resources. Additionally, a command filter is incorporated to address the problem of complexity explosion. Furthermore, to model the uncertain nonlinear dynamics affected by time-varying periodic disturbances, this paper combines Fourier series expansion and radial basis function neural networks. Finally, the effectiveness of the proposed methodology is demonstrated through simulation results.
Findings
Based on neural networks and command filter control method, an adaptive two-bit-triggered bipartite control strategy for nonlinear networked MASs is proposed.
Originality/value
The proposed control strategy effectively addresses the challenges of limited transmission resources, nonlinear dynamics and periodic disturbances in networked MASs. It guarantees the boundedness of all signals within the closed-loop system while also ensuring effective bipartite tracking performance.
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Zhitian Zhang, Hongdong Zhao, Yazhou Zhao, Dan Chen, Ke Zhang and Yanqi Li
In autonomous driving, the inherent sparsity of point clouds often limits the performance of object detection, while existing multimodal architectures struggle to meet the…
Abstract
Purpose
In autonomous driving, the inherent sparsity of point clouds often limits the performance of object detection, while existing multimodal architectures struggle to meet the real-time requirements for 3D object detection. Therefore, the main purpose of this paper is to significantly enhance the detection performance of objects, especially the recognition capability for small-sized objects and to address the issue of slow inference speed. This will improve the safety of autonomous driving systems and provide feasibility for devices with limited computing power to achieve autonomous driving.
Design/methodology/approach
BRTPillar first adopts an element-based method to fuse image and point cloud features. Secondly, a local-global feature interaction method based on an efficient additive attention mechanism was designed to extract multi-scale contextual information. Finally, an enhanced multi-scale feature fusion method was proposed by introducing adaptive spatial and channel interaction attention mechanisms, thereby improving the learning of fine-grained features.
Findings
Extensive experiments were conducted on the KITTI dataset. The results showed that compared with the benchmark model, the accuracy of cars, pedestrians and cyclists on the 3D object box improved by 3.05, 9.01 and 22.65%, respectively; the accuracy in the bird’s-eye view has increased by 2.98, 10.77 and 21.14%, respectively. Meanwhile, the running speed of BRTPillar can reach 40.27 Hz, meeting the real-time detection needs of autonomous driving.
Originality/value
This paper proposes a boosting multimodal real-time 3D object detection method called BRTPillar, which achieves accurate location in many scenarios, especially for complex scenes with many small objects, while also achieving real-time inference speed.
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Bingjun Li, Shuhua Zhang, Wenyan Li and Yifan Zhang
Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the…
Abstract
Purpose
Grey modeling technique is an important element of grey system theory, and academic articles applied to agricultural science research have been published since 1985, proving the broad applicability and effectiveness of the technique from different aspects and providing a new means to solve agricultural science problems. The analysis of the connotation and trend of the application of grey modeling technique in agricultural science research contributes to the enrichment of grey technique and the development of agricultural science in multiple dimensions.
Design/methodology/approach
Based on the relevant literature selected from China National Knowledge Infrastructure, the Web of Science, SpiScholar and other databases in the past 37 years (1985–2021), this paper firstly applied the bibliometric method to quantitatively visualize and systematically analyze the trend of publication, productive author, productive institution, and highly cited literature. Then, the literature is combed by the application of different grey modeling techniques in agricultural science research, and the literature research progress is systematically analyzed.
Findings
The results show that grey model technology has broad prospects in the field of agricultural science research. Agricultural universities and research institutes are the main research forces in the application of grey model technology in agricultural science research, and have certain inheritance. The application of grey model technology in agricultural science research has wide applicability and precise practicability.
Originality/value
By analyzing and summarizing the application trend of grey model technology in agricultural science research, the research hotspot, research frontier and valuable research directions of grey model technology in agricultural science research can be more clearly grasped.
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Hui Zhao, Yuanyuan Ge and Weihan Wang
This study aims to improve the offshore wind farm (OWF) site selection evaluation index system and establishes a decision-making model for OWF site selection. It is expected to…
Abstract
Purpose
This study aims to improve the offshore wind farm (OWF) site selection evaluation index system and establishes a decision-making model for OWF site selection. It is expected to provide helpful references for the progress of offshore wind power.
Design/methodology/approach
Firstly, this paper establishes an evaluation criteria system for OWF site selection, considering six criteria (wind resource, environment, economic, technical, social and risk) and related subcriteria. Then, the Criteria Importance Though Intercrieria Correlation (CRITIC) method is introduced to figure out the weights of evaluation indexes. In addition, the cumulative prospect theory and technique for order preference by similarity to an ideal solution (CPT-TOPSIS) method are employed to construct the OWF site selection decision-making model. Finally, taking the OWF site selection in China as an example, the effectiveness and robustness of the framework are verified by sensitivity analysis and comparative analysis.
Findings
This study establishes the OWF site selection evaluation system and constructs a decision-making model under the spherical fuzzy environment. A case of China is employed to verify the effectiveness and feasibility of the model.
Originality/value
In this paper, a new decision-making model is proposed for the first time, considering the ambiguity and uncertainty of information and the risk attitudes of decision-makers (DMs) in the decision-making process.
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Zequn Zhao, Peng Li, Xin Li, Yang Chen and Hao Zhang
The purpose of this study is to address the gaps in existing research on the nonlinear characteristics of floating ring bearings, particularly by focusing on second-order…
Abstract
Purpose
The purpose of this study is to address the gaps in existing research on the nonlinear characteristics of floating ring bearings, particularly by focusing on second-order nonlinear stiffness and damping coefficients. Traditional analytical models have limitations in terms of accuracy and computational efficiency. This research aims to develop a more efficient and accurate method for analyzing these nonlinear characteristics, which are crucial for optimizing the design and performance of turbocharger floating ring bearings. The study also seeks to explore how variations in clearance ratio and load influence these coefficients.
Design/methodology/approach
This study develops a novel approach for analyzing the nonlinear characteristics of floating ring bearings by utilizing second-order nonlinear stiffness and damping coefficients. The proposed method replaces traditional analytical solution models with a nonlinear stiffness and damping coefficient model, enhancing both computational efficiency and accuracy. The model is validated through extensive simulations that account for varying clearance ratios and load conditions. The results are compared with those obtained from conventional methods, demonstrating the effectiveness of the proposed approach in accurately capturing the nonlinear behavior of turbocharger floating ring bearings.
Findings
The study finds that the proposed nonlinear stiffness and damping coefficient model significantly enhances computational efficiency while accurately representing the nonlinear characteristics of floating ring bearings. The model not only reduces computation time but also provides a more precise analysis compared to traditional methods. Moreover, the research reveals that the clearance ratio and load conditions of the floating ring bearings have a substantial impact on the nonlinear stiffness and damping coefficients. These findings suggest that the proposed model and method could be highly beneficial for advancing the design and research of floating ring bearings in turbochargers.
Originality/value
With this statement, the authors hereby certify that the manuscript “Investigation on the nonlinear behaviors of floating ring bearings based on nonlinear stiffness and damping coefficient models” submitted to the journal Industrial Lubrication and Tribology is the results of their own effort and ability. They hereby confirm that this manuscript is their original work and has not been published nor has it been submitted simultaneously elsewhere. They further confirm that they have checked the manuscript and have agreed to the submission.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2024-0324/
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Abstract
Purpose
The finite element method (FEM) is used to calculate the two-dimensional anti-plane dynamic response of structure embedded in D’Alembert viscoelastic multilayered soil on the rigid bedrock. This paper aims to research a time-domain absorbing boundary condition (ABC), which should be imposed on the truncation boundary of the finite domain to represent the dynamic interaction between the truncated infinite domain and the finite domain.
Design/methodology/approach
A high-order ABC for scalar wave propagation in the D’Alembert viscoelastic multilayered media is proposed. A new operator separation method and the mode reduction are adopted to construct the time-domain ABC.
Findings
The derivation of the ABC is accurate for the single layer but less accurate for the multilayer. To achieve high accuracy, therefore, the distance from the truncation boundary to the region of interest can be zero for the single layer but need to be about 0.5 times of the total layer height of the infinite domain for the multilayer. Both single-layered and multilayered numerical examples verify that the accuracy of the ABC is almost the same for both cases of only using the modal number excited by dynamic load and using the full modal number of infinite domain. Using the ABC with reduced modes can not only reduce the computation cost but also be more friendly to the stability. Numerical examples demonstrate the superior properties of the proposed ABC with stability, high accuracy and remarkable coupling with the FEM.
Originality/value
A high-order time-domain ABC for scalar wave propagation in the D’Alembert viscoelastic multilayered media is proposed. The proposed ABC is suitable for both linear elastic and D’Alembert viscoelastic media, and it can be coupled seamlessly with the FEM. A new operator separation method combining mode reduction is presented with better stability than the existing methods.