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Computer vision and deep learning (DL) methods have been investigated for personal protective equipment (PPE) monitoring and detection for construction workers’ safety. However, it is still challenging to implement automated safety monitoring methods in near real time or in a time-efficient manner in real construction practices. Therefore, this study developed a novel solution to enhance the time efficiency to achieve near-real-time safety glove detection and meanwhile preserve data privacy.

The developed method comprises two primary components: (1) transfer learning methods to detect safety gloves and (2) edge computing to improve time efficiency and data privacy. To compare the developed edge computing-based method with the currently widely used cloud computing-based methods, a comprehensive comparative analysis was conducted from both the implementation and theory perspectives, providing insights into the developed approach’s performance.

Three DL models achieved mean average precision (mAP) scores ranging from 74.92% to 84.31% for safety glove detection. The other two methods by combining object detection and classification achieved mAP as 89.91% for hand detection and 100% for glove classification. From both implementation and theory perspectives, the edge computing-based method detected gloves faster than the cloud computing-based method. The edge computing-based method achieved a detection latency of 36%–68% shorter than the cloud computing-based method in the implementation perspective. The findings highlight edge computing’s potential for near-real-time detection with improved data privacy.

This study implemented and evaluated DL-based safety monitoring methods on different computing infrastructures to investigate their time efficiency. This study contributes to existing knowledge by demonstrating how edge computing can be used with DL models (without sacrificing their performance) to improve PPE-glove monitoring in a time-efficient manner as well as maintain data privacy.

Online learning gained ground during the pandemic and has continued to be used in the post-Covid era. Items related to online learning should be included in service quality assessment. The purpose of this study is to examine the influence of service quality, which includes the online learning dimension, on student satisfaction in higher-education in a blended learning environment.

A total of 452 valid questionnaires were collected from business undergraduate students enrolled in public universities in Greece. A modified version of HEdPERF is used to evaluate service quality. Due to the extensive use of online learning, an additional dimension was added to the HEdPERF scale which focuses on online education, a field that has not yet been widely examined. Structural equation modeling is used to examine the relationships between service quality, and student satisfaction.

The research findings verify the six-structure scale of the HEdPERF instrument (non-academic aspects, academic aspects, reputation, access and programs issues and online learning), providing satisfactory results in terms of reliability and validity tests. Service quality dimensions such as academic aspects, access, program issues and online learning are the influential dimensions of student satisfaction in a blended learning context.

To the best of the authors’ knowledge, no previous study has expanded traditional service quality instruments to include the dimension of service quality of online learning.

The purpose of this study is to perform the preliminary design, flight performance and exhaust emissions calculations of a piston engine powered unmanned aerial vehicle (UAV) during a flight cycle which consists of multiple flight altitudes and airspeeds.

A genuine computer model in Matlab/Simulink was developed to predict the size and weight of UAV and piston engine (using Avgas 100LL fuel) performance together with exhaust emissions in an iterative process.

The amount of emitted exhaust gases including carbon dioxide, carbon monoxide, hydrocarbons and nitrogen oxides were calculated in a typical UAV mission profile as a whole and also divided into mission flight segments.

Emissions were calculated based on fuel flow and engine speed inputs based on ground test data for emission indices. Test data for emission indices was very limited.

As UAV utilization has been increasing around the world, this study presents important and noticeable results on the emissions that need to be considered for environmental purposes.

In literature, emission prediction studies for UAVs are very rare. In fact, UAVs typically have quite different flight speeds and altitudes than regular manned aircraft and emissions change with speed and altitude. Additionally, unlike manned aircraft, UAVs can fly more than 24 h with different operation characteristics. The originality of this study presents the emission predictions of a piston engine UAV which flies with a significantly different mission profile than a manned aircraft.

Currently, lifelong learning and sustainable employability are increasingly fostered in the context of interorganizational networks, which provide workers with access to network activities (e.g., training, career counseling). This study aims to investigate the relationship between workers’ participation in network activities and their sustainable employability by considering workers’ experiences with the network activities. This study also examines the role of relational factors, including network trust and leader-member exchange, as conditions that may influence the link between workers’ participation in network activities and their sustainable employability (i.e. workability, perceived employability and vitality).

This study has a mixed methods design. A quantitative approach (cross-sectional, questionnaire) was used to establish associations between variables. This approach was supplemented with qualitative data (semistructured interviews) to explore whether Self-Determination Theory can provide an explanation for the associations and the role of (relational) factors that workers perceive as hindering or facilitating in that process.

The results suggest that participating in network activities have promising benefits for both workers and organizations by facilitating the work ability and perceived employability components of sustainable employability. For these relationships, workers’ satisfaction of their need for competency and relatedness serves as explanatory mechanisms. Moreover, the actualization of benefits of network activities is influenced by relational factors both within the network (i.e. trust) and within organizations (i.e. leader-member exchange).

This study investigates workers’ experiences with network activities, regarding fostering workers’ sustainable employability, and the role of relational factors. Specifically, it considers Human Resource Management practices from a network-level perspective, which is currently understudied. By doing so, this study adds a unique perspective to the Human Resource Management, sustainable employability and career literature streams.

Using suspended nanoparticles in the base fluid is known as one of the most efficient ways for heat transfer augmentation and improving the thermal efficiency of various heat exchangers. Different types of nanofluids are available and used in different applications. The main purpose of this study is to investigate the effects of using hybrid nanofluid and number of plates on the performance of plate heat exchanger. In this study, TiO₂/water single nanofluid and TiO₂-Al₂O₃/water hybrid nanofluid with 1% particle weight ratio have been used to prepare hybrid nanofluid to use in plate type heat exchangers with three various number of plates including 8, 12 and 16.

The experiments have been conducted with the aim of examining the impact of plates number and used nanofluids on heat transfer enhancement. The performance tests have been done at 40°C, 45°C, 50°C and 55°C set outlet temperatures and in five various Reynolds numbers between 1,600 and 3,800. Also, numerical simulation has been applied to verify the heat and flow behavior inside the heat exchangers.

The results indicated that using both nanofluids raised the thermal performance of all tested exchangers which have a various number of plates. While the major outcomes of this study showed that TiO₂-Al₂O₃/water hybrid nanofluid has priority when compared to TiO₂/water single type nanofluid. Utilization of TiO₂-Al₂O₃/water nanofluid led to obtaining an average improvement of 7.5%, 9.6% and 12.3% in heat transfer of heat exchangers with 8, 12 and 16 plates, respectively.

In the present work, experimental and numerical analyzes have been conducted to investigate the influence of using TiO₂-Al₂O₃/water hybrid nanofluid in various plate heat exchangers. The attained findings showed successful utilization of TiO₂-Al₂O₃/water nanofluid. Based on the obtained results increasing the number of plates in the heat exchanger caused to obtain more increment by using both types of nanofluids.

Knowledge sharing enables a firm’s absorptive capacity to reconfigure its dynamic capabilities to sense, track and recognise embryonic business opportunities. Entrepreneurial opportunity recognition triggers entrepreneurs to invest in and upgrade their knowledge practices to improve entrepreneurial performance. This study aims to examine the relationship between knowledge sharing and absorptive capacity on entrepreneurial orientation as well as the moderating effect of opportunity recognition and the mediating effect of absorptive capacity.

A quantitative cross-sectional research design was applied to data from Algerian small and medium-sized enterprise managers in middle- to top-management positions. The final analysis using smart PLS included 246 respondents.

Knowledge sharing positively influenced entrepreneurial orientation and absorptive capacity. In addition, the findings reveal that entrepreneurial orientation positively influences entrepreneurial performance, and opportunity recognition strengthens the relationship between entrepreneurial orientation and entrepreneurial performance. Entrepreneurial orientation and absorptive capacity have partial mediating effects.

This study focuses on how firms create and share developed knowledge to enable absorptive capacity to fit a level of entrepreneurial orientation. This study validates the vital impact of opportunity recognition as a leading motivation for entrepreneurial orientation. The results highlight an important area of research and suggest that firms should focus on knowledge sharing to boost entrepreneurial outcomes.

The notions of entrepreneurship, absorptive capacity and knowledge sharing are extended by building on dynamic capability theory. Knowledge sharing increases absorptive capacity, which drives superior entrepreneurial orientation outcomes.

This study aims to evaluate the loyalty formation model on e-grocery service incorporating food quality, e-grocery quality and relationship quality as determinants of loyalty.

The quantitative approach was used by using 353 data from young Indonesian customers with purchasing experience of local food through e-grocery service. The hypothesized relationships between variables were tested using partial least squares structural equation modeling.

The results confirm that local food quality, e-grocery service quality and the relationship quality elements of a sense of community and attitudinal attachment, are all loyalty drivers. Next, mediation tests reveal that local food quality and e-grocery service quality influence customer loyalty through customers’ attitudinal attachment and a sense of community.

This study recommends that managers of e-grocery services of local food businesses could benefit from the development of attachment and a sense of community among their young clients. Furthermore, to develop loyalty among young customers, offering high-quality local food as well as e-grocery services is suggested.

To the best of the author’s knowledge, this is the first examination of the e-grocery service loyalty in the context of local food.

The Algarve is a region located in the South of Portugal and is mostly known for its sun and sea product. In order to strengthen the Algarve’s competitiveness, the Allgarve program was launched in 2007. We intend to analyze the importance of events as a differentiation factor of tourist destinations. Questions like loyalty, satisfaction, and perception about the event’s program are the main subjects analyzed. This study uses data from a questionnaire applied to 224 individuals who attended “street artist events” and pop music concerts in the 2011 edition of the Allgarve program. Two main techniques were applied: OVERALS and k-means. Despite its flaws, positive conclusions were reached, and after its five editions, the program was finally able to be linked to the region’s image, distinguishing it in a wide range of cultural events and entertainment.

This study aims to explore individuals’ attitudes and intentions towards mask purchase in Pakistan at an initial outbreak of COVID-19.

The study is quantitatively based on the cross-sectional data. The data are collected through a survey questionnaire. Convenience sampling strategy is used to target the individuals of Pakistan. At the first, 650 questionnaires were distributed. In return, the authors received 321 raw samples with the response rate of 53.5%. Finally, 316 useful samples are proceeded to infer the final results.

The structural equation model’s results demonstrate a positive and significant effect of fear of complication of COVID-19, knowledge about COVID-19 and health consciousness on attitudes towards the mask. Further, attitudes towards mask are found to be the robust analyst of mask purchase intention.

The study used cross-sectional data through a single source of data collection. The findings of the survey are on the sample size of 316.

The study would help policymakers to formulate the strategies to make aware individuals regarding their health and COVID-19 issues. The study would provide the guidelines to the government agents of Pakistan to combat with COVID-19 through the purchase of mask. The shopkeepers would be aware to observe the intentions and attitudes of consumers towards mask.

The outcomes of this study offer a shred of empirical evidence for attitudes and intentions regarding the purchase of mask, particularly for developing country settings.

Heat exchangers (HEXs) are extensively used in many applications such as heating and cooling systems. To increase the thermal performance of HEXs, nano-sized particles could be added to the base working fluid which can improve the thermophysical properties of the fluid. In addition, further improvement in the thermal performance of nanofluids can be obtained by using two or more different nanoparticles which are known as hybrid nanofluids. This paper aims to improve the thermal efficiency of U-type tubular HEX (THEX) by using CuO-Al₂O₃/water hybrid nanofluid.

Numerical simulation has been used to model THEX with various configurations. Also, CuO-Al₂O₃/water hybrid nanofluid has been experimented in THEX in two various modes including parallel (PTHEX) and counter flow (CTHEX) regarding to the numerical findings. Hybrid nanofluids have been prepared in two particle concentrations and compared with CuO/water nanofluid at the same concentrations and also with water.

The numerical simulation results showed that adding fins and also using hybrid nanofluid can increase heat transfer rate in HEX. However, adding fins cannot be a good option in U-type THEX with lower diameter because it increases pressure drop notably. Experimental results of this work illustrated that using Al₂O₃-CuO/water hybrid nanofluid in the THEX improved thermal performance significantly. Maximum enhancement in overall heat transfer coefficient of THEX by using CuO-Al₂O₃/water nanofluid in 0.5% and 1% concentrations achieved as 9.5% and 12%, respectively.

The obtained findings of the study showed the positive effects of using hybrid type nanofluid in comparison with single type nanofluid. In this study, numerical and experimental analysis have been conducted to investigate the effect of using hybrid type nanofluid in U-type HEX. The obtained results exhibited successful utilization of CuO-Al₂O₃/water hybrid type nanofluid in HEX. Moreover, it was observed that thermal performance analysis of the nanofluids without any experiment can be done by using numerical method.