Huajun Liu, Cailing Wang and Jingyu Yang
– This paper aims to present a novel scheme of multiple vanishing points (VPs) estimation and corresponding lanes identification.
Abstract
Purpose
This paper aims to present a novel scheme of multiple vanishing points (VPs) estimation and corresponding lanes identification.
Design/methodology/approach
The scheme proposed here includes two main stages: VPs estimation and lane identification. VPs estimation based on vanishing direction hypothesis and Bayesian posterior probability estimation in the image Hough space is a foremost contribution, and then VPs are estimated through an optimal objective function. In lane identification stage, the selected linear samples supervised by estimated VPs are clustered based on the gradient direction of linear features to separate lanes, and finally all the lanes are identified through an identification function.
Findings
The scheme and algorithms are tested on real data sets collected from an intelligent vehicle. It is more efficient and more accurate than recent similar methods for structured road, and especially multiple VPs identification and estimation of branch road can be achieved and lanes of branch road can be identified for complex scenarios based on Bayesian posterior probability verification framework. Experimental results demonstrate VPs, and lanes are practical for challenging structured and semi-structured complex road scenarios.
Originality/value
A Bayesian posterior probability verification framework is proposed to estimate multiple VPs and corresponding lanes for road scene understanding of structured or semi-structured road monocular images on intelligent vehicles.
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This study aims to understand the epistemic foundation of the classification applied in the first Chinese library catalogue, the Seven Epitomes (Qilue).
Abstract
Purpose
This study aims to understand the epistemic foundation of the classification applied in the first Chinese library catalogue, the Seven Epitomes (Qilue).
Design/methodology/approach
Originating from a theoretical stance that situates knowledge organization in its social context, the study applies a multifaceted framework pertaining to five categories of textual data: the Seven Epitomes; biographical information about the classificationist Liu Xin; and the relevant intellectual, political, and technological history.
Findings
The study discovers seven principles contributing to the epistemic foundation of the catalogue's classification: the Han imperial library collection imposed as the literary warrant; government functions considered for structuring texts; classicist morality determining the main classificatory structure; knowledge perceived and organized as a unity; objects, rather than subjects, of concern affecting categories at the main class level; correlative thinking connecting all text categories to a supreme knowledge embodied by the Six Classics; and classicist moral values resulting in both vertical and horizontal hierarchies among categories as well as texts.
Research limitations/implications
A major limitation of the study is its focus on the main classes, with limited attention to subclasses. Future research can extend the analysis to examine subclasses of the same scheme. Findings from these studies may lead to a comparison between the epistemic approach in the target classification and the analytic one common in today's bibliographic classification.
Originality/value
The study is the first to examine in depth the epistemic foundation of traditional Chinese bibliographic classification, anchoring the classification in its appropriate social and historical context.
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Senyu Xu, Huajun Tang and Yuxin Huang
The purpose of this research is to investigate how to introduce a financing scheme to tackle the manufacturer's capital constraint problem, discuss the effects of data-driven…
Abstract
Purpose
The purpose of this research is to investigate how to introduce a financing scheme to tackle the manufacturer's capital constraint problem, discuss the effects of data-driven marketing (DDM) quality, cross-channel-return (CCR) rate and financing interest rate on the members' pricing and delivery-lead-time decisions and optimal performances, and analyzes `how to achieve the coordination within a dual-channel supply chain (DSC) by contract coordination.
Design/methodology/approach
This work establishes a DSC model with DDM, and the offline retailer can provide internal financing to the capital-constrained online manufacturer. The demand under the price is determined based on DDM quality, customer channel preference and delivery lead time. Then, combined with the Stackelberg game, the optimal pricing and delivery-lead-time decisions are discussed under the inconsistent and consistent pricing strategies with decentralized and centralized systems. Furthermore, it designs a manufacturer-revenue sharing contract to coordinate the members under the two pricing strategies.
Findings
(1) The increase of DDM quality will reduce the delivery-lead-time under the inconsistent or consistent pricing strategy and will push the selling prices; (2) The growth of the CCR rate will raise selling prices and extend the delivery-lead-time under the decentralized decision; (3) Under price competition, the offline selling price is higher than the online selling price when customers prefer the offline channel and vice versa; (4) The retailer and the manufacturer can achieve a win-win situation through a manufacturer-revenue sharing contract.
Originality/value
This paper contributes to the studies related to DSC by investigating pricing and delivery-lead-time decisions based on DDM, CCR, internal financing and supply chain contract and proposes some managerial implications.
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Ziyuan Ma, Huajun Gong and Xinhua Wang
The purpose of this paper is to construct an event-triggered finite-time fault-tolerant formation tracking controller, which can achieve a time-varying formation control for…
Abstract
Purpose
The purpose of this paper is to construct an event-triggered finite-time fault-tolerant formation tracking controller, which can achieve a time-varying formation control for multiple unmanned aerial vehicles (UAVs) during actuator failures and external perturbations.
Design/methodology/approach
First, this study developed the formation tracking protocol for each follower using UAV formation members, defining the tracking inaccuracy of the UAV followers’ location. Subsequently, this study designed the multilayer event-triggered controller based on the backstepping method framework within finite time. Then, considering the actuator failures, and added self-adaptive thought for fault-tolerant control within finite time, the event-triggered closed-loop system is subsequently shown to be a finite-time stable system. Furthermore, the Zeno behavior is analyzed to prevent infinite triggering instances within a finite time. Finally, simulations are conducted with external disturbances and actuator failure conditions to demonstrate formation tracking controller performance.
Findings
It achieves improved performance in the presence of external disturbances and system failures. Combining limited-time adaptive control and event triggering improves system stability, increase robustness to disturbances and calculation efficiency. In addition, the designed formation tracking controller can effectively control the time-varying formation of the leader and followers to complete the task, and by adding a fixed-time observer, it can effectively compensate for external disturbances and improve formation control accuracy.
Originality/value
A formation-following controller is designed, which can handle both external disturbances and internal actuator failures during formation flight, and the proposed method can be applied to a variety of formation control scenarios and does not rely on a specific type of UAV or communication network.
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Huajun Cao, Yanbin Du and Yongpeng Chen
China has become the low‐cost manufacturing center of the world. The purpose of this paper is to provide an in‐depth analysis of a new manufacturing strategy for China's future…
Abstract
Purpose
China has become the low‐cost manufacturing center of the world. The purpose of this paper is to provide an in‐depth analysis of a new manufacturing strategy for China's future manufacturing sector which is trying to transform into a new low‐carbon development paradigm. It also aims to discuss the empirical implications and policy suggestions.
Design/methodology/approach
The paper is based on the broad reviewing of the relative government documents and press reports in China, the USA, and Japan. The authors also conducted case research of China's remanufacturing practices.
Findings
The high energy consumption and emissions of China's manufacturing sector results from the widespread use of obsolete production equipment, which can produce low‐cost products with a severely negative environmental effect. The remanufacturing strategy can upgrade existing production equipment to improve production efficiency, which will be a more practical paradigm for China's future manufacturing sector.
Originality/value
The previous relative low‐carbon policies in China are mainly associated with the administrative measures, such as direct “command‐control”, which have paid little attention to the practical development paradigm. This paper first provides a framework for understanding and practical evidence for the remanufacturing strategy as a new low‐carbon paradigm for the giant manufacturing sector of the world's largest developing country.
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Ran Gong, Jinxiao Li, Jin Xu, He Zhang and Huajun Che
Leakage serves as a core indicator of sealing performance degradation, particularly under high-speed and heavy-duty operational where increased leakage is common. Within…
Abstract
Purpose
Leakage serves as a core indicator of sealing performance degradation, particularly under high-speed and heavy-duty operational where increased leakage is common. Within heavy-duty vehicle transmissions, the leakage can lead to excessive pressure loss and eventual transmission failure. This study aims to introduce a predictive method for assessing sealing ring leakage in vehicle transmissions based on operating conditions.
Design/methodology/approach
Seal test was carried out using a specialized seal test rig. Various data points were collected during this test, including leakage, friction torque, oil temperature, oil pressure and rotating speed. The collected data underwent noise separation and reconstruction using the complete ensemble empirical mode decomposition with adaptive noise method. Subsequently, a leakage prediction model is developed using the random forest regression with parameter optimization. A quantitative evaluation for influencing factors in leakage prediction process is investigated.
Findings
The results achieve a mean accuracy index exceeding 95%, demonstrating close alignment between predicted and actual leakage values. Feature contribution results highlight that the trends of the oil temperature, friction torque and oil pressure significantly affect the leakage prediction, with the oil temperature trend exerting the most substantial influence.
Originality/value
This work sheds light on the interplay between operating conditions and sealing performance degradation, offering valuable insights for understanding and addressing sealing issues effectively.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2024-0271/