Search results

This study aims to focus on optimization of process parameters for porosity and strength of polyamide porous bone scaffolds fabricated via selective laser sintering (SLS) process.

Taguchi’s design of experiment approach with L18 orthogonal array (OA) has been used to optimize the process parameters. Five process and four response parameters have been considered for this study. Initially, minimum size of the pores that can be depowdered was identified. Then, porous CAD models of test specimen to measure porosity and strength were designed in Solidworks® software and fabricated using EOSINT P395 m/c. Signal-to-noise ratio and analysis of variance were used to identify the optimal levels of parameters and statistical significance of the parameters.

Among five parameters, powder refresh rate, build chamber temperature and layer thickness were found to have significant influence on all the response parameters, whereas build orientation and build position were found insignificant for all the responses. The Taguchi’s confirmation test validated the results of the study with maximum deviation of 5.8% for compressive strength. Comparison of predicted and experimental values revealed a satisfactory predictability of all the developed linear regression models.

This study reveals optimal set of parameters for SLS of the polyamide porous bone scaffolds. The optimal set of parameters may be used by other researchers to get enhanced combination of strength and porosity while fabricating porous scaffolds.

A transmission tower usually experiences bolt loosening under long-term alternating cyclic load, which may lead to collapse of the tower in extreme operating conditions. The paper aims to propose a data-driven identification method for bolt looseness of complicated tower structures based on reduced-order models and numerical simulations to perceive and evaluate the health state of a tower in operation.

The equivalent stiffnesses of three types of bolt joints under various loosening scenarios are numerically determined by three-dimensional finite element (FE) simulations. The order of the FE model of a tower structure with bolt loosening is reduced by means of the component modal synthesis method, and the dynamic responses of the reducer-order model under calibration loads are simulated and used to create the dataset. An identification model for bolt looseness of the tower structure based on convolutional neural networks driven by the acceleration sensors is constructed.

An identification model for bolt looseness of the tower structure based on convolutional neural networks driven by the acceleration sensors is constructed and the applicability of the model is investigated. It is shown that the proposed method has a high identification accuracy and strong robustness to data noise and data missing. Meanwhile, the method is less dependent on the number and location of sensors and is easier to apply in real transmission lines.

This paper proposes a data-driven identification method for bolt looseness of a complicated tower structure based on reduced-order models and numerical simulations. Non-linear relationships between equivalent stiffness of bolted joints and bolt preload depicting looseness are obtained and reduced-order model of tower structure with bolt looseness is established. Finally, this paper investigates applicability of identification model for bolt looseness.

This study aimed to investigate the effect of working remotely on new professionals’ learning and adjustment. Organizational socialization is the process of learning and adjusting to a new professional role. Among new professionals working on-site, this learning and adjustment is indicated by a development of role clarity, task mastery and social acceptance. Less is known about the process when working remotely. This was recognized as a key organizational challenge following the onset of the COVID-19 pandemic.

In this study, with a longitudinal design with 242 graduates and weekly data collections for the first five weeks following professional entry in 2021, the authors compared the learning and adjustment among individuals working on-site, in hybrid or remotely using longitudinal analyses of mean response profiles.

The group-by-time interaction effects were not statistically significant (i.e. no differences were found in the adjustment of the new professionals of the three groups).

These results indicate that working remotely does not jeopardize the organizational socialization process. Furthermore, a marginally statistically significant result indicated that participants working only remotely experienced a greater development of task mastery over time: This suggests that remote work may even benefit learning and professional adjustment. Theoretical and practical implications of the results are discussed.

How to reduce uncertainty in clothing online purchasing has become a primary concern for consumers. This study aims to investigate the effects of quality perception and multisensory perception on consumer online clothing purchase intention and to explore the mediating effect of trust.

This study was conducted with consumers who have online clothing shopping experiences. A total of 539 valid samples were analyzed by bootstrap and structural equation model.

The result of this research revealed that perceived information quality, perceived service quality, perceived haptic imagery and perceived visual-audio cues have a significant influence on purchase intention. Additionally, consumers’ trust is positively correlated with purchase intention. Trust mediates the relationship between the perceptions (perceived information quality, perceived service quality, perceived haptic imagery and perceived visual-audio cues) and purchase intention, irrespectively.

To investigate the effects of multisensory perception on purchase intention, perceived haptic imagery is adopted as a variable in this study. This study investigates the mediating role of trust between multisensory perception and purchase intention. The findings of this study can enrich Stimulus-Organism-Response (S-O-R) framework and Information System (IS) success model in the field of clothing online shopping.

This study explores the relationship between Tourism Systems and Smart Cities, aiming to identify what prevents public managers from including these systems in Smart City strategies. This separation neglects that increasing tourism attractiveness may also impact city resources, infrastructures and inhabitants.

To this end, we developed a critical literature review consulting three databases: Scopus, Web of Science and EBSCOhost. A total of 73 articles were selected and analyzed through thematic analysis.

Through this critical review, we develop a framework of barriers to integrating a tourism system in Smart City strategies composed of four main barrier themes and 11 barrier factors. Findings show the need for innovative research and public managers to go beyond considerations related to technological challenges and instead focus on other barriers hindering integration, such as the lack of participatory governance and knowledge of tourism systems' current and future impact.

This study offers a critical identification of barriers impeding the inclusion of tourism systems in Smart City strategies, providing a useful guideline for public managers aiming to follow an innovative approach to smart development where tourism can still be a tool to enhance the attractiveness of the territory while considering its current and future impact on the city.

Maritime transportation plays an important role in facilitating both the global and regional merchandise trade, where accurate trend prediction is crucial in assisting decision-making in the industry. This paper aims to conduct a macro-level study to predict world vessel supply and demand.

The automatic autoregressive integrated moving average (ARIMA) is used for the univariate vessel supply and demand time-series forecasting based on the data records from 1980 to 2021.

For the future projection of the demand side, the predicted outcomes for total vessel demand and world dry cargo vessel demand until 2030 indicate upward trends. For the supply side, the predominant upward trends for world total vessel supply, oil tanker vessel supply, container vessel supply and other types of vessel supply are captured. The world bulk carrier vessel supply prediction results indicate an initial upward trend, followed by a slight decline, while the forecasted world general cargo vessel supply values remain relatively stable. By comparing the predicted percentage change rates, there is a gradual convergence between demand and supply change rates in the near future. We also find that the impact of the COVID-19 pandemic on the time-series prediction results is not statistically significant.

The results can provide policy implications in strategic planning and operation to various stakeholders in the shipping industry for vessel building, scrapping and deployment.

The main purpose of the present research is to explore the possible effectiveness of information and communication technology (ICT), infrastructure development, exchange rate and governance on inbound tourism demand using time series data in India.

The stationarity of the variables is checked by using the ADF, PP and KPSS unit root tests. The paper uses the Bayer-Hanck and auto-regressive distributed lag (ARDL) bounds testing approach to cointegration to examine the existence of long-run relationships; the error-correction mechanism for the short-run dynamics and the vector error correction method (VECM) to test the direction of causality.

The findings of the research indicate the presence of cointegration among the variables. Further, long-run results indicate infrastructure development, word-of-mouth and ICT have a positive and significant linkage with international tourist arrivals in India. However, ICT has a positive and significant effect on tourist arrivals in the short run as well. The VECM results indicate long-run unidirectional causality from infrastructure, ICT, governance and exchange rate to tourist arrivals.

This study implies that inbound tourism demand in India can be augmented by improving infrastructure, governance quality and ICT penetration. For an emerging country like India, this may have far-reaching implications for sustaining and improving tourism sector growth.

This paper is the first of its kind to empirically examine the impact of ICT, infrastructure and governance quality in India using modern econometric techniques. Inbound tourism demand research aids government and policymakers in developing effective public policies that would reposition India to gain from a highly competitive global tourism industry.

This paper aims to reduce flight delay propagation, improve flight punctuality rate and ensure aircraft maintenance opportunities by establishing an integrated aircraft scheduling model, aiming at minimizing the total propagated delay and direction operational cost.

In this paper, flight data sets are obtained through automatic dependent detection broadcast. To accurately predict flight delay time, the flight delay prediction eXtreme gradient boosting model adds the data set obtained by random forest advance model learning and predicts the newly generated flight delays. Finally, based on the forecast results, the flight plan can be optimized and adjusted by using the improved column generation algorithm.

It is verified by the actual weekly planned operation data of an airline company, experiments show that the model established in this paper can reduce flight delay propagation by 30% in case tests and each aircraft has the opportunity to be repaired at the base airport.

Optimize the aircraft scheduling plan, cover a wide range of data, not just a single route and airport, supplement the gap in the aircraft scheduling plan based on weather factors to predict flight delays.

As sustainability concerns become increasingly influential in shaping wineries’ strategies at the production and processing stages, this study aims to investigate the anticipated benefits, incentives and constraints associated with a territorial sustainability certification in the wine industry.

Focusing on wine producers from the Romagna Consortium (Italy), the research explores the influence of firm characteristics on sustainability attitudes and explores the Consortium potential role in facilitating the ecological transition. Data are collected through an online survey and analyzed by means of factor and cluster analysis.

Findings reveal the Consortium capacity to expand its scope, incorporating elements of sustainability, resilience and territorial development. In addition, it emerges that the perception of sustainability among local producers extends beyond environmental concerns, encompassing the economic and social domains.

Acting as a cluster constituent, the Consortium can stimulate collaborative behavior and promote knowledge dissemination contributing to a mature collaborative environment. A territorial sustainability certification is thus viewed as multifunctional tool, enhancing economic performance and collective reputation, while addressing the numerous environmental challenges faced by the sector.

The study’s originality lies in its direct engagement with a considerable number of producers in a geographic area boasting a mature wine industry but with limited research focusing on coordinated efforts for improved sustainability performance.

This article attempts to contribute to medical dispute resolution by examining the adoption of medical judicial expertise opinions in determining medical malpractice responsibility and its coordination with the judge’s legal opinions.

This article examines the legal basis and empirical data to demonstrate the decisive effect of medical judicial experts’ opinions in allocating medical malpractice responsibility and corresponding dispute resolution effectiveness.

High reliance on medical judicial expertise in medical dispute litigation not only unifies the judicial standards but also limits judges’ discretion, which brings the risk of contradiction between factual and legal findings, which currently ends in judges’ compromise.

The current medical malpractice provisions neglect the divergence of medical judicial expertise and judges’ opinions in determining medical malpractice responsibility, which produces difficulties in harmonizing awarded compensations and parties’ expectations, leading to problematic medical dispute litigation in Mainland China.