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1 – 10 of 43
Article
Publication date: 18 April 2017

Baihong Chi, Zhiwei Jiao and Weimin Yang

3D printing based on additive manufacturing has advantages in manufacturing products with high geometrical complexity. However, there are many limitations to print plastic…

Abstract

Purpose

3D printing based on additive manufacturing has advantages in manufacturing products with high geometrical complexity. However, there are many limitations to print plastic products with the existing commercial 3D printers. The polymer materials processing industry needs new devices which can satisfy the trend of processing individual units and small batch sizes of plastic parts.

Design/methodology/approach

In this study, a freeform fabrication system with the method of polymer melt droplet deposition is proposed. The performance of this system under different conditions was studied by changing the operating parameters. Furthermore, the dimensional uniformity of droplets and their deposition process are analyzed, and a plastic sample was fabricated with this system as an example.

Findings

The results show a clear correlation between the processing parameters and the droplet diameter. In the experiment for examining the dimensional uniformity of the droplet, the droplets become spindles, and there appears a melt filament between the droplets. The variation of the droplet’s diameters is within 5 per cent. Furthermore, a successfully processed rectangular plastic sample verified the feasibility of this technology for the printing of plastic products.

Originality/value

A freeform fabrication system with polymer melt droplet deposition is proposed, which can process a wide variety of materials in the form of standard granulates like injection molding or extrusion. Based on the principle of droplet deposition, multi-component or colorful materials can be printed.

Details

Rapid Prototyping Journal, vol. 23 no. 3
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 13 June 2023

Zhiwei Jiao, Zhongyu Zhuang, Li Hu, Ce Sun, Yuan Yu and Weimin Yang

The purpose of this study was to fabricate silicone products that had different hardnesses and moduli, thus partially addressing the limitations of homogeneous materials whose…

Abstract

Purpose

The purpose of this study was to fabricate silicone products that had different hardnesses and moduli, thus partially addressing the limitations of homogeneous materials whose deformation depends on altered structure or dimensions, and to provide new dimensions for the design of silicone soft structures.

Design/methodology/approach

A soft material three-dimensional printing platform with a dual-channel printing capability was designed and built. Using the material extrusion method, material screening was first performed using single-channel printing, followed by dual-channel-regulated printing experiments on products having different hardness and modulus values.

Findings

The proportion of additives has an effect on the accuracy of the printed product. Material screening revealed that Sylgard 527 and SE 1700 could be printed without additives. The hardness and mechanical properties of products are related to the percentage in their composition of hard and soft materials. The hardness of the products could be adjusted from 26A to 42A and the Young’s modulus from 0.875 to 2.378 Mpa.

Originality/value

Existing silicone products molded by casting or printing are mostly composed of a single material, whose uniform hardness and modulus cannot meet the demand for differentiated deformation in the structure. The existing multihardness silicone material printing method has the problems of long material mixing time and slow hardness switching and complicated multi-extrusion head switching. In this study, a simple, low-cost and responsive material extrusion-based hardness programmable preparation method for silicone materials is proposed.

Details

Rapid Prototyping Journal, vol. 29 no. 7
Type: Research Article
ISSN: 1355-2546

Keywords

Article
Publication date: 21 November 2022

Lili Gao, Xiaowei Luo, Weimin Yang, Na Zhang and Xiaopeng Deng

This paper aims to explore the influence of social support and the repatriation intention of expatriates in international constructions in the postpandemic era of COVID-19…

Abstract

Purpose

This paper aims to explore the influence of social support and the repatriation intention of expatriates in international constructions in the postpandemic era of COVID-19. Furthermore, test the mediation effect of team climate and individual resilience in this relationship.

Design/methodology/approach

A survey of 347 expatriates in international construction projects was conducted. A cross-level chain mediation model was employed to test the moderating effect of social support and repatriation intention. Then, statistical analysis with a bootstrap sample was used to test the mediation effect of the model.

Findings

The empirical results support that team climate, individual resilience and the chain mediating effect of team climate to individual resilience is significant among the influences of social support on repatriation intention. Social support can enhance the team climate of construction expatriates, promoting their resilience to reduce the repatriation intention further.

Practical implications

This study provides guidelines for international construction enterprises and managers to decide when and which expatriates should return home and formulate a series of policies to support expatriates and maintain a good team climate.

Originality/value

This study contributes to expatriate management literature by establishing the relationship between social support and repatriation intention. It provides a better understanding of how team-level factors impact individual thought. It takes team climate as one of the protective factors affecting individual psychological resilience. Also it takes social support as the antecedents of team atmosphere in case of emergencies.

Details

Engineering, Construction and Architectural Management, vol. 30 no. 8
Type: Research Article
ISSN: 0969-9988

Keywords

Article
Publication date: 22 October 2021

Na Pang, Li Qian, Weimin Lyu and Jin-Dong Yang

In computational chemistry, the chemical bond energy (pKa) is essential, but most pKa-related data are submerged in scientific papers, with only a few data that have been…

Abstract

Purpose

In computational chemistry, the chemical bond energy (pKa) is essential, but most pKa-related data are submerged in scientific papers, with only a few data that have been extracted by domain experts manually. The loss of scientific data does not contribute to in-depth and innovative scientific data analysis. To address this problem, this study aims to utilize natural language processing methods to extract pKa-related scientific data in chemical papers.

Design/methodology/approach

Based on the previous Bert-CRF model combined with dictionaries and rules to resolve the problem of a large number of unknown words of professional vocabulary, in this paper, the authors proposed an end-to-end Bert-CRF model with inputting constructed domain wordpiece tokens using text mining methods. The authors use standard high-frequency string extraction techniques to construct domain wordpiece tokens for specific domains. And in the subsequent deep learning work, domain features are added to the input.

Findings

The experiments show that the end-to-end Bert-CRF model could have a relatively good result and can be easily transferred to other domains because it reduces the requirements for experts by using automatic high-frequency wordpiece tokens extraction techniques to construct the domain wordpiece tokenization rules and then input domain features to the Bert model.

Originality/value

By decomposing lots of unknown words with domain feature-based wordpiece tokens, the authors manage to resolve the problem of a large amount of professional vocabulary and achieve a relatively ideal extraction result compared to the baseline model. The end-to-end model explores low-cost migration for entity and relation extraction in professional fields, reducing the requirements for experts.

Details

Data Technologies and Applications, vol. 56 no. 2
Type: Research Article
ISSN: 2514-9288

Keywords

Article
Publication date: 28 November 2023

Jiaying Chen, Cheng Li, Liyao Huang and Weimin Zheng

Incorporating dynamic spatial effects exhibits considerable potential in improving the accuracy of forecasting tourism demands. This study aims to propose an innovative deep…

Abstract

Purpose

Incorporating dynamic spatial effects exhibits considerable potential in improving the accuracy of forecasting tourism demands. This study aims to propose an innovative deep learning model for capturing dynamic spatial effects.

Design/methodology/approach

A novel deep learning model founded on the transformer architecture, called the spatiotemporal transformer network, is presented. This model has three components: the temporal transformer, spatial transformer and spatiotemporal fusion modules. The dynamic temporal dependencies of each attraction are extracted efficiently by the temporal transformer module. The dynamic spatial correlations between attractions are extracted efficiently by the spatial transformer module. The extracted dynamic temporal and spatial features are fused in a learnable manner in the spatiotemporal fusion module. Convolutional operations are implemented to generate the final forecasts.

Findings

The results indicate that the proposed model performs better in forecasting accuracy than some popular benchmark models, demonstrating its significant forecasting performance. Incorporating dynamic spatiotemporal features is an effective strategy for improving forecasting. It can provide an important reference to related studies.

Practical implications

The proposed model leverages high-frequency data to achieve accurate predictions at the micro level by incorporating dynamic spatial effects. Destination managers should fully consider the dynamic spatial effects of attractions when planning and marketing to promote tourism resources.

Originality/value

This study incorporates dynamic spatial effects into tourism demand forecasting models by using a transformer neural network. It advances the development of methodologies in related fields.

目的

纳入动态空间效应在提高旅游需求预测的准确性方面具有相当大的潜力。本研究提出了一种捕捉动态空间效应的创新型深度学习模型。

设计/方法/途径

本研究提出了一种基于变压器架构的新型深度学习模型, 称为时空变压器网络。该模型由三个部分组成:时空转换器、空间转换器和时空融合模块。时空转换器模块可有效提取每个景点的动态时间依赖关系。空间转换器模块可有效提取景点之间的动态空间相关性。提取的动态时间和空间特征在时空融合模块中以可学习的方式进行融合。通过卷积运算生成最终预测结果。

研究结果

结果表明, 与一些流行的基准模型相比, 所提出的模型在预测准确性方面表现更好, 证明了其显著的预测性能。纳入动态时空特征是改进预测的有效策略。它可为相关研究提供重要参考。

实践意义

所提出的模型利用高频数据, 通过纳入动态空间效应, 在微观层面上实现了准确预测。旅游目的地管理者在规划和营销推广旅游资源时, 应充分考虑景点的动态空间效应。

原创性/价值

本研究通过使用变压器神经网络, 将动态空间效应纳入旅游需求预测模型。它推动了相关领域方法论的发展。

Objetivo

La incorporación de efectos espaciales dinámicos ofrece un considerable potencial para mejorar la precisión de la previsión de la demanda turística. Este estudio propone un modelo innovador de aprendizaje profundo para capturar los efectos espaciales dinámicos.

Diseño/metodología/enfoque

Se presenta un novedoso modelo de aprendizaje profundo basado en la arquitectura transformadora, denominado red de transformador espaciotemporal. Este modelo tiene tres componentes: el transformador temporal, el transformador espacial y los módulos de fusión espaciotemporal. El módulo transformador temporal extrae de manera eficiente las dependencias temporales dinámicas de cada atracción. El módulo transformador espacial extrae eficientemente las correlaciones espaciales dinámicas entre las atracciones. Las características dinámicas temporales y espaciales extraídas se fusionan de manera que se puede aprender en el módulo de fusión espaciotemporal. Se aplican operaciones convolucionales para generar las previsiones finales.

Conclusiones

Los resultados indican que el modelo propuesto obtiene mejores resultados en la precisión de las previsiones que algunos modelos de referencia conocidos, lo que demuestra su importante capacidad de previsión. La incorporación de características espaciotemporales dinámicas supone una estrategia eficaz para mejorar las previsiones. Esto puede proporcionar una referencia importante para estudios afines.

Implicaciones prácticas

El modelo propuesto aprovecha los datos de alta frecuencia para lograr predicciones precisas a nivel micro incorporando efectos espaciales dinámicos. Los gestores de destinos deberían tener plenamente en cuenta los efectos espaciales dinámicos de las atracciones en la planificación y marketing para la promoción de los recursos turísticos.

Originalidad/valor

Este estudio incorpora efectos espaciales dinámicos a los modelos de previsión de la demanda turística mediante el empleo de una red neuronal transformadora. Supone un avance en el desarrollo de metodologías en campos afines.

Article
Publication date: 9 August 2019

Zhifeng Lin, Likun Xu, Xiangbo Li, Li Wang, Weimin Guo, Chuanjie Wu and Yi Yang

The purpose of this paper is to examine the performance of a fastener composite coating system, sherardized (SD) coating/zinc-aluminum (ZA) coating whether it has good performance…

Abstract

Purpose

The purpose of this paper is to examine the performance of a fastener composite coating system, sherardized (SD) coating/zinc-aluminum (ZA) coating whether it has good performance in marine environment.

Design/methodology/approach

In this paper, SD coating was fabricated on fastener surface by solid-diffusion method. ZA coating was fabricated by thermal sintering method. Corrosion behaviours of the composite coating were investigated with potentiodynamic polarization curves, open circuit potential and electrochemical impedance spectroscopy methods.

Findings

Neutral salt spray (NSS) and deep sea exposure tests revealed that the composite coating had excellent corrosion resistance. Polarization curve tests showed that corrosion current density of the sample with composite coating was significantly decreased, indicating an effective corrosion protection of the composite coating. OCP measurement of the sample in NaCl solution demonstrated that the composite coating had the best cathodic protection effect. The good corrosion resistance of the composite coating was obtained by the synergy of SD and ZA coating.

Practical implications

SD/ZA coating can be used in marine environment to prolong the life of carbon steel fastener.

Social implications

SD/ZA composite coating can reduce the risk and accident caused by failed fastener, avoid huge economic losses.

Originality/value

A new kind of composite coating was explored to protect the carbon steel fastener in marine environment. And the composite coating has the long-term anti-corrosion performance both in simulated and marine environment test.

Details

Anti-Corrosion Methods and Materials, vol. 66 no. 5
Type: Research Article
ISSN: 0003-5599

Keywords

Article
Publication date: 16 August 2022

Liyao Huang, Cheng Li and Weimin Zheng

Given the importance of spatial effects in improving the accuracy of hotel demand forecasting, this study aims to introduce price and online rating, two critical factors…

Abstract

Purpose

Given the importance of spatial effects in improving the accuracy of hotel demand forecasting, this study aims to introduce price and online rating, two critical factors influencing hotel demand, as external variables into the model, and capture the spatial and temporal correlation of hotel demand within the region.

Design/methodology/approach

For high practical implications, the authors conduct the case study in Xiamen, China, where the hotel industry is prosperous. Based on the daily demand data of 118 hotels before and during the COVID-19 period (from January to June 2019 and from January to June 2021), the authors evaluate the prediction performance of the proposed innovative model, that is, a deep learning-based model, incorporating graph convolutional networks (GCN) and gated recurrent units.

Findings

The proposed model simultaneously predicts the daily demand of multiple hotels. It effectively captures the spatial-temporal characteristics of hotel demand. In addition, the features, price and online rating of competing hotels can further improve predictive performance. Meanwhile, the robustness of the model is verified by comparing the forecasting results for different periods (during and before the COVID-19 period).

Practical implications

From a long-term management perspective, long-term observation of market competitors’ rankings and price changes can facilitate timely adjustment of corresponding management measures, especially attention to extremely critical factors affecting forecast demand, such as price. While from a short-term operational perspective, short-term demand forecasting can greatly improve hotel operational efficiency, such as optimizing resource allocation and dynamically adjusting prices. The proposed model not only achieves short-term demand forecasting, but also greatly improves the forecasting accuracy by considering factors related to competitors in the same region.

Originality/value

The originalities of the study are as follows. First, this study represents a pioneering attempt to incorporate demand, price and online rating of other hotels into the forecasting model. Second, integrated deep learning models based on GCN and gated recurrent unit complement existing predictive models using historical data in a methodological sense.

Details

International Journal of Contemporary Hospitality Management, vol. 35 no. 1
Type: Research Article
ISSN: 0959-6119

Keywords

Article
Publication date: 29 November 2022

Liyao Huang and Weimin Zheng

This study aims to provide a comprehensive review of hotel demand forecasting to identify its key fundamentals and evolution and future research directions and trends to advance…

Abstract

Purpose

This study aims to provide a comprehensive review of hotel demand forecasting to identify its key fundamentals and evolution and future research directions and trends to advance the field.

Design/methodology/approach

Articles on hotel demand modeling and forecasting were identified and rigorously selected using transparent inclusion and exclusion criteria. A final sample of 85 empirical studies was obtained for comprehensive analysis through content analysis.

Findings

Synthesis of the literature highlights that hotel forecasting based on historical demand data dominates the research, and reservation/cancellation data and combined data gradually attracted research attention in recent years. In terms of model evolution, time series and AI-based models are the most popular models for hotel demand forecasting. Review results show that numerous studies focused on hybrid models and AI-based models.

Originality/value

To the best of the authors’ knowledge, this study is the first systematic review of the literature on hotel demand forecasting from the perspective of data source and methodological development and indicates future research directions.

目的

本研究旨在对酒店需求预测进行全面回顾, 以确定其关键基础和演变以及未来的研究方向和趋势, 以推动该领域的发展。

设计/方法/方法

使用严格和透明的纳入和排除的标准对酒店需求建模和预测的文章进行识别和选择。通过内容分析, 最终有 85个实证研究作为综合分析的样本。

研究结果

综合文献发现, 基于历史需求数据的酒店预测在研究中占主导地位, 近年来预订/取消数据和组合数据逐渐引起研究关注。在模型演化方面, 时间序列和基于人工智能的模型是最受欢迎的酒店需求预测模型。审查结果表明, 许多研究都集中在混合模型和基于 AI 的模型上。

原创性/价值

本研究是第一次从数据源和方法发展的角度对酒店需求预测文献进行系统回顾, 并指出未来的研究方向。

Propósito

Este estudio tiene como objetivo proporcionar una revisión amplia de la previsión sobre la demanda hotelera a la hora de identificar sus fundamentos clave, la evolución y las direcciones y tendencias de investigación futuras para avanzar en el campo de estudio.

Diseño/metodología/enfoque

Se identificaron y seleccionaron de forma rigurosa artículos sobre modelado y previsión de la demanda hotelera utilizando criterios transparentes de inclusión y exclusión. Se obtuvo una muestra final de 85 estudios empíricos para su análisis integral a través del análisis de contenido.

Hallazgos

La síntesis de la literatura destaca que la previsión hotelera basada en datos históricos de demanda ha dominado la investigación, y los datos de reserva/cancelación, así como los datos combinados han atraído gradualmente en los últimos años la atención de la investigación. En términos de evolución del modelo, las series temporales y los modelos basados en IA son los modelos más populares para la previsión de la demanda hotelera. Los resultados de la revisión muestran que numerosos estudios se han centrado en modelos híbridos y basados en IA.

Originalidad/valor

Este estudio es la primera revisión sistemática de la literatura sobre la previsión de la demanda hotelera desde la perspectiva de la fuente de datos y el desarrollo metodológico e indica futuras líneas de investigación.

Article
Publication date: 31 May 2022

Li Zhang, Haiyan Fang, Weimin Bao, Haifeng Sun, Lirong Shen, Jianyu Su and Liang Zhao

X-ray pulsar navigation (XPNAV) is an autonomous celestial navigation technology for deep space missions. The error in the pulse time of arrival used in pulsar navigation is large…

Abstract

Purpose

X-ray pulsar navigation (XPNAV) is an autonomous celestial navigation technology for deep space missions. The error in the pulse time of arrival used in pulsar navigation is large for various practical reasons and thus greatly reduces the navigation accuracy of spacecraft near the Earth and in deep space. This paper aims to propose a novel method based on ranging information that improves the performance of XPNAV.

Design/methodology/approach

This method replaces one pulsar observation with a satellite observation. The ranging information is the difference between the absolute distance of the satellite relative to the spacecraft and the estimated distance of the satellite relative to the spacecraft. The proposed method improves the accuracy of XPNAV by combining the ranging information with the observation data of two pulsars.

Findings

The simulation results show that the proposed method greatly improves the XPNAV accuracy by 70% compared with the conventional navigation method that combines the observations of three pulsars. This research also shows that a larger angle between the orbital plane of the satellite and that of the spacecraft provides higher navigation accuracy. In addition, a greater orbital altitude difference implies higher navigation accuracy. The position error and ranging error of the satellite have approximately linear relationships with the navigation accuracy.

Originality/value

The novelty of this study is that the satellite ranging information is integrated into the pulsar navigation by using mathematical geometry.

Details

Aircraft Engineering and Aerospace Technology, vol. 94 no. 10
Type: Research Article
ISSN: 1748-8842

Keywords

Article
Publication date: 16 March 2020

Zhenyang Zhu, Yi Liu, Zhe Fan, Sheng Qiang, Zhiqiang Xie, Weimin Chen and Congcong Wu

The buried pipe element method can be used to calculate the temperature of mass concrete through highly efficient computing. However, in this method, temperatures along cooling…

Abstract

Purpose

The buried pipe element method can be used to calculate the temperature of mass concrete through highly efficient computing. However, in this method, temperatures along cooling pipes and the convection coefficient of the cooling pipe boundary should be improved to achieve higher accuracy. Thus, there is a need to propose a method for improvement.

Design/methodology/approach

According to the principle of heat balance and the temperature gradient characteristics of concrete around cooling pipes, a method to calculate the water temperature along cooling pipes using the buried pipe element method is proposed in this study. By comparing the results of a discrete algorithm and the buried pipe element method, it was discovered that the convection coefficient of the cooling pipe boundary for the buried pipe element method is only related to the thermal conductivity of concrete; therefore, it can be calculated by inverse analysis.

Findings

The results show that the buried pipe element method can achieve the same accuracy as the discrete method and simulate the temperature field of mass concrete with cooling pipes efficiently and accurately.

Originality/value

This new method can improve the calculation accuracy of the embedded element method and make the calculation results more reasonable and reliable.

Details

Engineering Computations, vol. 37 no. 8
Type: Research Article
ISSN: 0264-4401

Keywords

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