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Images taken from construction site interiors often suffer from low illumination and poor natural colors, which restrict their application for high-level site management purposes. The state-of-the-art low-light image enhancement method provides promising image enhancement results. However, they generally require a longer execution time to complete the enhancement. This study aims to develop a refined image enhancement approach to improve execution efficiency and performance accuracy.

To develop the refined illumination enhancement algorithm named enhanced illumination quality (EIQ), a quadratic expression was first added to the initial illumination map. Subsequently, an adjusted weight matrix was added to improve the smoothness of the illumination map. A coordinated descent optimization algorithm was then applied to minimize the processing time. Gamma correction was also applied to further enhance the illumination map. Finally, a frame comparing and averaging method was used to identify interior site progress.

The proposed refined approach took around 4.36–4.52 s to achieve the expected results while outperforming the current low-light image enhancement method. EIQ demonstrated a lower lightness-order error and provided higher object resolution in enhanced images. EIQ also has a higher structural similarity index and peak-signal-to-noise ratio, which indicated better image reconstruction performance.

The proposed approach provides an alternative to shorten the execution time, improve equalization of the illumination map and provide a better image reconstruction. The approach could be applied to low-light video enhancement tasks and other dark or poor jobsite images for object detection processes.

This research aims to build on the pre-existing corpus of literature through the integration of the technology acceptance model (TAM) and usage habit to more accurately capture the determinants associated with social media addiction among university students. This study seeks to delineate how usage habit and TAM may be used as predictors for addiction potential, as well as provide greater insight into current trends in social media usage across this population demographic.

A cross-sectional research design was employed to investigate the determinants of social media addiction among university students in Malaysia at the onset of their tertiary education. A self-administered survey, adapted from prior studies, was administered to a sample of 217 respondents. The hypotheses on social media addiction were subsequently tested using a partial least squares structural equation modeling (PLS-SEM) approach.

Usage habit was found to be a direct and strong predictor of this type of addiction, as well as all TAM variables considered in the research. Additionally, by integrating TAM with usage habit, the study revealed a comprehensive and multi-faceted understanding of social media addiction, providing an important insight into its complexity in the Malaysian context. Although several other factors have been identified as potential contributors to social media reliance and addictive behavior, it appears that usage habit is paramount in driving these addictive tendencies among university students.

This expanded model holds significant implications for the development of interventions and policies that aim to mitigate the adverse effects of social media addiction on students' educational and psychological well-being. The study illustrates the applicability of the TAM in examining addictive behaviors within emerging contexts such as the Malaysian higher education sector, thus contributing to the extant literature on the subject.

The integrated TAM and habit model is an effective predictor of social media addiction among young adults in developing countries like Malaysia. This highlights the importance of actively monitoring and controlling users' interactions with technology and media platforms, while promoting responsible usage habits. Educators can use these findings to create tailored educational programs to educate students on how to use technology responsibly and reduce their risk of becoming addicted to social media.

This study provides a unique perspective on social media addiction among university students. The combination of TAM and usage habit has the potential to shed significant light on how variables such as perceived usefulness (PU) and perceived ease of use (PEOU) may be associated with addictive behaviors. Additionally, by considering usage habit as an explanatory factor, this research offers a novel approach to understanding how addictions form over time.

Construction professionals are the major contributors to developing a sustainable construction industry, whereas architects, engineers and quantity surveyors are the key construction professionals who must play extraordinary roles in achieving better sustainable construction. Therefore, this study aims to identify the job attributes of key Sri Lankan construction professionals in addressing challenges associated with climate change.

The study adopted a mixed research approach. A literature review and preliminary semi-structured interviews were used to appraise the job roles of architects, engineers and quantity surveyors in addressing challenges associated with climate change. The data collected through the qualitative approach were used in an online questionnaire survey, and the findings were analysed using the relative index method.

The findings highlight that regardless of the knowledge of the professional category on green rating tools, carbon footprint, adaptation of renewable energies for the reduction of energy consumption, building information modelling-related applications and waste management concepts/practices are the foremost job attributes required for the key Sri Lankan construction professionals in addressing challenges associated with climate change.

The results from this study provide a handful of guidance to construction industry professionals, national and international professional institutions, non-governmental organisations and other relevant authorities to address climate change within the built environment by identifying ways for improving the relevant key job attributes of construction industry professionals.

To the best of the authors’ knowledge, this is the first study that explores the job attributes of key Sri Lankan construction professionals in addressing the challenges associated with climate change.

From a psychosocial perspective, this study aims to understand the impact of psychosocial safety climate (PSC) on the intent to stay of construction workers and provides practical recommendations for construction enterprises to retain construction workers.

This study proposes the conceptual framework explained by the conservation of resources (COR) theory and develops a mediation model of “PSC – job satisfaction – intent to stay” within the framework supported by the stimulus–organism–response (SOR) model. Then, a questionnaire survey of 489 construction workers in Guangzhou was conducted and structural equation modeling (SEM) analysis was performed on the data collected.

Results show that PSC has a significant and positive effect on job satisfaction and intent to stay. In addition, job satisfaction partially mediates the effect of PSC on intent to stay. Hence, the theoretical model of “PSC – job satisfaction – intent to stay” has been empirically tested and supported.

This study is the first to investigate the effect of PSC on intent to stay and enriches the research on the retention of construction workers. The COR theory explains well the mechanism of PSC influence on intent to stay, thus expanding its application to the construction field. Moreover, this study provides practical recommendations for construction enterprises to retain workers so as to build a stable and productive workforce.

This study seeks to explicate how institutional disruptions impact multinational corporation (MNC) subsidiary control choices. It uses institutional theory to understand the influence of formal and informal institutions across countries on the type of control system employed in an MNC manufacturing subsidiary.

This study’s sample is based on a unique dataset from five trustworthy sources. We use multi-level models to account for the hierarchical nature of the sample of 1,630 multinational subsidiaries spread across 26 host countries by firms from 21 home countries.

The institutional distance between the host and the home country has a negative relationship with strategic control. In contrast, the home country’s power distance has a positive relationship with strategic control.

Study findings indicate the need to incorporate formal and informal institutional elements in the control system’s conceptual framing and design. This notion complements existing visualizations of optimizing MNC controls through extant articulations of minimizing governance costs through organizational design choices or strategic needs.

The purpose of this study is to adapt the incompressible smoothed particle hydrodynamics (ISPH) method with artificial intelligence to manage the physical problem of double diffusion inside a porous L-shaped cavity including two fins.

The ISPH method solves the nondimensional governing equations of a physical model. The ISPH simulations are attained at different Frank–Kamenetskii number, Darcy number, coupled Soret/Dufour numbers, coupled Cattaneo–Christov heat/mass fluxes, thermal radiation parameter and nanoparticle parameter. An artificial neural network (ANN) is developed using a total of 243 data sets. The data set is optimized as 171 of the data sets were used for training the model, 36 for validation and 36 for the testing phase. The network model was trained using the Levenberg–Marquardt training algorithm.

The resulting simulations show how thermal radiation declines the temperature distribution and changes the contour of a heat capacity ratio. The temperature distribution is improved, and the velocity field is decreased by 36.77% when the coupled heat Cattaneo–Christov heat/mass fluxes are increased from 0 to 0.8. The temperature distribution is supported, and the concentration distribution is declined by an increase in Soret–Dufour numbers. A rise in Soret–Dufour numbers corresponds to a decreasing velocity field. The Frank–Kamenetskii number is useful for enhancing the velocity field and temperature distribution. A reduction in Darcy number causes a high porous struggle, which reduces nanofluid velocity and improves temperature and concentration distribution. An increase in nanoparticle concentration causes a high fluid suspension viscosity, which reduces the suspension’s velocity. With the help of the ANN, the obtained model accurately predicts the values of the Nusselt and Sherwood numbers.

A novel integration between the ISPH method and the ANN is adapted to handle the heat and mass transfer within a new L-shaped geometry with fins in the presence of several physical effects.

This study aims to focus on the supply chain (SC) cost drivers of healthcare industries in the USA, as SC costs have increased 40% over the last decade. The second-most significant expense, the SC, accounts for 38% of total expenses in a typical hospital, while most other industries can operate within 10% of their operating cost. This makes healthcare centers supply-chain-sensitive organizations with limited facilities for high-quality healthcare services. As the cost drivers of healthcare SC are almost unknown to managers, their jobs become more complex.

Guided by pragmatism and positivism paradigms, a cross-sectional study has been designed using quantitative and deductive approaches. Both primary and secondary data were used. Primary data were collected from health centers across the country, and secondary data were from healthcare-related databases. This study examined the attributes that explain the most significant variation in each contributing factor. With multiple regression analysis for predicting cost and Student's t-tests for the significance of contributing factors, the authors of this study examined different theories, including the market-based view and five-forces, network and transaction cost analysis.

This study revealed that supply, materials and services represent the most significant expenses in primary care. Supply-chain cost breakdown results in four critical factors: facility, inventory, information and transportation.

This study examined the data from primary and secondary care institutions. Tertiary and quaternary care systems were not included. Although tertiary and quaternary care systems represent a small portion of the healthcare system, future research should address the supply chain costs of highly specialized organizations.

This study suggests methods that can help to improve supply chain operations in healthcare organizations worldwide.

This study presents an empirically proven methodology for testing the statistical significance of the primary factors contributing to healthcare supply chain costs. The results of this study may lead to positive policy changes to improve healthcare organizations' efficiency and increase access to high-quality healthcare.

Effective post-disaster communication is essential for destination marketing organizations to encourage visitors following natural disasters. This research aimed to analyze the impact of two typical types of post-disaster communication messages – solidarity messages and testimonial messages – on post-disaster visiting intention. This research proposes effective communication strategies for post-disaster destination marketing.

For the case of Jiuzhai Valley, China, which experienced market recovery after two years of rebuilding following a 2017 earthquake, this study designed three contextual experiments based on post-disaster communication scenarios on the Internet and social media to test the causal chain between recovery message types and post-disaster visiting intentions. The data were analyzed using analysis of variance, independent samples t-tests, and the bootstrap method.

The results indicate that both solidarity messages and testimonial messages evoked higher visiting intention than the no-message group. However, solidarity messages (vs testimonial messages) were more effective when shared on the destination management organization's official account than when they were shared on an influencer's account, with their effects being mediated by the symbolic – as opposed to the hedonic – value of tourist behavior.

Destination management organizations should actively carry out marketing communication through the Internet and social media for areas that have experienced disasters. Crisis communicators should consider inviting popular social media influencers to visit the destination and share their experiences to enhance market confidence, while also paying more attention to the operation of official social media accounts.

This study sheds light on the use of the Internet and social media as tools for post-disaster marketing. By expanding on post-disaster communication theory, this study fills a research gap regarding the effectiveness of tourism marketing strategies after a crisis.

The purpose of this paper is to examine how users on social media view brands with a heritage. Consumers commonly post opinions and accounts of their experiences with brands on social media. Such consumer-generated content may or may not overlap with content desired by brand managers. Drawing from “The medium is the message” paradigm, this study text-mines user narratives on Twitter1 to shed light on the role of social media in shaping public images of brands with heritage through the lens of the stereotype content model.

The study uses a data set of almost 80,000 unique tweets on 12 brands across six categories, compares brands high versus low in heritage and combines dictionary-based content analysis with sentiment analysis.

The results indicate that both user-generated content and sentiment are significantly more positive for brands low rather than high in heritage. Regarding warmth, consumers use significantly more positive words on sociability and fewer negative words on morality for brands low rather than high in heritage. Regarding competence, tweets include more positive words on assertiveness and ability for low-heritage brands. Finally, overall sentiment is more positive for brands low rather than high in heritage.

Important from co-creation and integrated marketing communication perspectives, the findings provide brand managers with actionable insights on how to more effectively use social media.

To the best of the authors’ knowledge, this research is among the first to examine user-generated content in a brand heritage context. It demonstrates that heritage brands, with their longevity and strong links to the past, need to be aware of how contemporary social media can detract from their image.

In order to extend the application of the original octagonal Goodman–Smith fatigue limit diagram, which is commonly used for the evaluation of structure fatigue stress in engineering, a modification of it is proposed for the structure made of S355 steel (commonly used in high-speed electric multiple units (EMUs) bogie frame).

The modification is made based on Deutscher Verband für Schweißen und verwandte Verfahren e. V. (DVS) 1612 standard and the γ-P-S-N curve, with consideration of the fatigue evaluation requirements of different survival rates and confidence levels. The verification of the modification is performed for three welded joints and for the comparison with the experimental data.

The results indicate that the design survival rate, the design safety margin and the fatigue stress evaluation of welded joint types are all improved by using the modified diagram.

There are relatively few studies on modifying octagonal Goodman–Smith fatigue limit diagram. In this paper, a modified diagram is proposed and applied in order to ensure the safety and durability of key welded structures of rail vehicles.