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Article
Publication date: 9 February 2024

Fei Hao, Yueming Guo, Chen Zhang and Kaye Kye Sung Kye-Sung Chon

This study aims to investigate the integration of blockchain technology into the food supply chain within the restaurant industry. It focuses on how blockchain can be applied to…

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Abstract

Purpose

This study aims to investigate the integration of blockchain technology into the food supply chain within the restaurant industry. It focuses on how blockchain can be applied to enhance transparency and trust in tracking food sources, ultimately impacting customer satisfaction.

Design/methodology/approach

A service design workshop (Study 1) and three between-subjects experiments (Studies 2–4) were conducted.

Findings

Results indicate that blockchain adoption significantly improves traceability and trust in the food supply chain. This improvement in turn enhances customer satisfaction through perceived improvements in food safety, quality and naturalness. This study also notes that the effects of blockchain technology vary depending on the type of restaurant (casual or fine dining) and its location (tourist destinations or residential areas).

Practical implications

The findings offer practical insights for restaurant owners, technology developers and policymakers. Emphasizing the benefits of blockchain adoption, this study guides decision-making regarding technology investments for enhancing customer service and satisfaction in the hospitality sector.

Originality/value

This research contributes novel insights to the field of technology innovation in the hospitality industry. It extends the understanding of signaling theory by exploring how blockchain technology can serve as a tool for signal transmission in restaurant food supply chains.

Details

International Journal of Contemporary Hospitality Management, vol. 36 no. 10
Type: Research Article
ISSN: 0959-6119

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Article
Publication date: 18 February 2025

Yueming Zhao, Gaohui Li and Zuying Mo

To explore the influence factors and pathways of users’ willingness to participate in the misinformation purification process on the Weibo platform. The findings of this study are…

0

Abstract

Purpose

To explore the influence factors and pathways of users’ willingness to participate in the misinformation purification process on the Weibo platform. The findings of this study are expected to provide valuable insights that can enhance the self-purification mechanisms for misinformation on Weibo, thereby contributing to the effective misinformation control.

Design/methodology/approach

The theoretical framework of the quantitative study is a conceptual model integrated with the theory of planned behavior (TPB), social exchange theory (SET) and co-dependency theory. This model was developed to elucidate the influence factors of users’ willingness to participate in the purification of misinformation on the Weibo platform, the conceptual model was tested and refined through questionnaire surveys, structural equation modeling (SEM) was used to assess its validity and reliability.

Findings

The findings reveal that the attitude toward misinformation purification on the Weibo platform exerts the most significant positive influence on the willingness to engage in such activities. Within the context of this research, community involvement and reciprocity are identified as the factors that have the most substantial positive impact on users’ attitude toward misinformation purification. Conversely, risk perception does not demonstrate a significant influence on users’ attitude toward misinformation purification.

Originality/value

Taking the Weibo platform as an example, this is a pioneering study on the investigation and mechanism of social media self-purification on misinformation and proposes a new perspective to improve the effectiveness of the social media self-purification mechanism from the perspective of focusing on user intention and motivation.

Details

Aslib Journal of Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2050-3806

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Article
Publication date: 10 May 2024

Yueming Cao, Dongjie Zhou and Yunli Bai

This paper aims to examine the impacts of unstable off-farm employment on the probability and stability of farmland rent-out and explore its mechanisms.

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Abstract

Purpose

This paper aims to examine the impacts of unstable off-farm employment on the probability and stability of farmland rent-out and explore its mechanisms.

Design/methodology/approach

The paper adopts Ordinary Least Squares (OLS), Probit, Tobit, Order probit models with two-way fixed effects to conduct empirical analysis based on the balanced panel data collected in 2016 and 2023 with a national representativeness sample of 1,206 rural households in 100 villages across 5 provinces in China.

Findings

The empirical results showed that unstable off-farm employment had negative effects on the probability of farmland rent-out, but it had no effects on the stability of farmland rent-out. The mechanism analysis showed that unstable off-farm employment affected the probability of farmland rent-out by decreasing the probability of purchasing houses in city and endowment insurance with high pension. Heterogeneity analysis indicated that the negative effect of unstable off-farm employment was much larger for the households with higher share of labor engaging in off-farm employment outside home county, elder members in the households and those located in the villages of mountain areas.

Originality/value

This paper is the first to define the unstable off-farm employment from the perspective of incontiguous off-farm employment for several years, which could capture the normality rather than particular case in a certain year of off-farm employment among rural labors. Using these new measurements of unstable off-farmland, this paper examined the impacts and mechanisms of share of unstable off-farm employment on the probability and stability of farmland rent-out.

Details

China Agricultural Economic Review, vol. 16 no. 3
Type: Research Article
ISSN: 1756-137X

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Article
Publication date: 3 May 2016

Liya Wang, Yang Zhao, Yaoming Zhou and Jingbin Hao

The purpose of this paper is to present a detection method based on computer vision for automatic flexible printed circuit (FPC) defect detection.

497

Abstract

Purpose

The purpose of this paper is to present a detection method based on computer vision for automatic flexible printed circuit (FPC) defect detection.

Design/methodology/approach

This paper proposes a new method of watershed segmentation based on morphology. A dimensional increment matrix calculation method and an image segmentation method combined with a fuzzy clustering algorithm are provided. The visibility of the segmented image and the segmentation accuracy of a defective image are guaranteed.

Findings

Compared with the traditional one, the segmentation result obtained in this study is superior in aspects of noise control and defect segmentation. It completely proves that the segmentation method proposed in this study is better matches the requirements of FPC defect extraction and can more effectively provide the segmentation result. Compared with traditional human operators, this system ensures greater accuracy and more objective detection results.

Research limitations/implications

The extraction of FPC defect characteristics contains some obvious characteristics as well as many implied characteristics. These characteristics can be extracted through specific space conversion and arithmetical operation. Therefore, more images are required for analysis and foresight to establish a more widely used FPC defect detection sorting algorithm.

Originality/value

This paper proposes a new method of watershed segmentation based on morphology. It combines a traditional edge detection algorithm and mathematical morphology. The FPC surface defect detection system can meet the requirements of online detection through constant design and improvement. Therefore, human operators will be replaced by machine vision, which can preferably reduce the production costs and improve the efficiency of FPC production.

Details

Circuit World, vol. 42 no. 2
Type: Research Article
ISSN: 0305-6120

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Article
Publication date: 28 November 2024

Yanwen Sun, Xiaojing Shi, Shixun Zhai, Kaige Zhang, Bo Pan and Yili Fu

This paper aims to investigate the problem of vision based autonomous laparoscope control, which can serve as the primary function for semi-autonomous minimally invasive surgical…

37

Abstract

Purpose

This paper aims to investigate the problem of vision based autonomous laparoscope control, which can serve as the primary function for semi-autonomous minimally invasive surgical robot system. Providing the surgical gesture recognition information is a fundamental key component for enabling intelligent context-aware assistance in autonomous laparoscope control task. While significant advances have been made in recent years, how to effectively carry out the efficient integration of surgical gesture recognition and autonomous laparoscope control algorithms for robotic assisted minimally invasive surgical robot system is still an open and challenging topic.

Design/methodology/approach

The authors demonstrate a novel surgeon in-loop semi-autonomous robotic-assisted minimally invasive surgery framework by integrating the surgical gesture recognition and autonomous laparoscope control tasks. Specifically, they explore using a transformer-based deep convolutional neural network to effectively recognize the current surgical gesture. Next, they propose an autonomous laparoscope control model to provide optimal field of view which is in line with surgeon intra-operation preferences.

Findings

The effectiveness of this surgical gesture recognition methodology is demonstrated on the public JIGSAWS and Cholec80 data sets, outperforming the comparable state-of-the-art methods. Furthermore, the authors have validated the effectiveness of the proposed semi-autonomous framework on the developed HUAQUE surgical robot platforms.

Originality/value

This study demonstrates the feasibility to perform cognitive assistant human–robot shared control for semi-autonomous robotic-assisted minimally invasive surgery, contributing to the reference for further surgical intelligence in computer-assisted intervention systems.

Details

Robotic Intelligence and Automation, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2754-6969

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Article
Publication date: 28 November 2024

Hongkang Liu, Qian Yu, Yongheng Li, Yichao Zhang, Kehui Peng, Zhiqiang Kong and Yatian Zhao

This study aims to get a better understanding of the impact of streamlined high-speed trains (HSTs) with geometric uncertainty on aerodynamic performance, as well as the…

33

Abstract

Purpose

This study aims to get a better understanding of the impact of streamlined high-speed trains (HSTs) with geometric uncertainty on aerodynamic performance, as well as the identification of the key parameters responsible for this impact. To reveal the critical parameters, this study creates a methodology for evaluating the uncertainty and sensitivity of drag coefficient induced by design parameters of HST streamlined shapes.

Design/methodology/approach

Bézier curves are used to parameterize the streamlined shape of HSTs, and there are eight design parameters required to fit the streamlined shape, followed by a series of steady Reynolds-averaged Navier–Stokes simulations. Combining the preparation work with the nonintrusive polynomial chaos method results in a workflow for uncertainty quantification and global sensitivity analysis. Based on this framework, this study quantifies the uncertainty of drag, pressure, surface friction coefficient and wake flow characteristics within the defined ranges of streamline shape parameters, as well as the contribution of each design parameter.

Findings

The results show that the change in drag reaches a maximum deviation of 15.37% from the baseline, and the impact on the tail car is more significant, with a deviation of up to 23.98%. The streamlined shape of the upper surface and the length of the pilot (The device is mounted on the front of a train’s locomotive and primarily serves to remove obstacles from the tracks, thereby preventing potential derailment.) are responsible for the dominant factors of the uncertainty in the drag for HSTs. Linear regression results show a significant quadratic polynomial relationship between the length of the pilot and the drag coefficient. The drag declines as the length of the pilot enlarges. By analyzing the case with the lowest drag, the positive pressure area in the front of pilot is greatly reduced, while the nose tip pressure of the tail is enhanced by altering the vortices in the wake. The counter-rotating vortex pair is significantly attenuated. Accordingly, exerts the impacts caused by geometric uncertainty can be found on the wake flow region, with pressure differences of up to 900 Pa. The parameters associated with the shape of the upper surface contribute significantly to the uncertainty in the core of the wake separation region.

Originality/value

The findings contribute to a better understanding of the impact of streamlined HSTs with geometric uncertainty on aerodynamic performance, as well as the identification of the key parameters responsible for this impact. Based on this study, future research could delve into the detailed design of critical areas in the streamlined shape of HSTs, as well as the direction of shape optimization to more precisely and efficiently reduce train aerodynamic drag under typical conditions.

Details

International Journal of Numerical Methods for Heat & Fluid Flow, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0961-5539

Keywords

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