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This era is the time for upskilling and producing workforce that is capable of effectively dealing with the day-by-day increasing demand of the industry. As the world is changing, its needs are changing in the same way and at the same speed. The world has become more digitized now. Moreover, we have a dramatic shift from Education 1.0 to Education 4.0 these days. The world now is practicing the internet of things, cloud storage, cyber-physical system and artificial intelligence. The purpose of this study is to identify the factors that affect the level of motivation toward the integration and implication of Industrial Revolution (IR) 4.0 in the education system of Pakistan by considering the Government policies.

For analyzing these factors, 150 research articles were sought out, out of which 84 were chosen for reviewing purpose based on the authentication of and relevance to this study by considering the Pakistani context. All the research articles have been selected from reputed indexed journals from databases (Scopus and Web of Science).

The findings of this review suggest that many factors affect the motivation toward integration and implementation of IR 4.0. These factors mainly include human factors, intrinsic values and influencing factors. Moreover, there is no such framework that provides the base to Education 4.0 in Pakistan because the things exist but are not systematic. Educators are motivated, but there are no resources; policies are there, but there is no practice or implementation. Pakistan is lacking in the latest trends related to Education 4.0 and even has no experience because people are used to doing things manually, but technology is the need of this era. Furthermore, the findings of this study will be useful for developing a systematic plan or a framework of the integration and implication of IR 4.0 that ultimately gives rise to Education 4.0 in the education system of Pakistan.

To the authors’ knowledge, no other study has been conducted on this topic in Pakistan. Also, there is a very little work done on this topic anywhere else in the world. The world is still exploring the IR 4.0, and our topic is solemnly related to these resolutions. Thus, there is a very little amount of literature related to this study.

The development of communication and artificial intelligence technologies has raised interest in connectivity and increased autonomy of automated earthmoving equipment for earthwork. These changes are motivating work to reduce uncertainties, in terms of improving equipment object detection capability and reducing strikes and accidents on site. The purpose of this study is to illustrate industrial drivers for automated earthwork systems; identify the specific capabilities which make the transformation happen; and finally determine use cases that create value for the system. These three objectives act as components of a technology roadmap for automated and connected earthwork and can guide development of new products and services.

This paper used a text mining approach in which the required data was captured through a structured literature review, and then expert knowledge was used for verification of the results.

Automated and connected earthwork can enhance construction site and its embraced infrastructure, resilience by avoiding human faults during operations. Automating the monitoring process can lead to reliable anticipation of problems and facilitate real-time responses to unexpected situation via connectedness capabilities. Research findings are presented in three sections: industrial perspectives, trends and drivers for automated and connected earthwork; capabilities which are met by technologies; and use cases to demonstrate different capabilities.

This study combines the results of disintegrated and fragmented research in the area of automated and connected earthwork and categorises them under new capability levels. The identified capabilities are classified in three main categories including reliable environmental perception, single equipment decision-making toward safe outcomes and fleet-level safety enhancement. Finally, four different levels of automation are proposed for earthwork technology roadmap.

The safety management of construction machines is of primary importance. Considering that traditional construction machine safety monitoring and evaluation methods cannot adapt to the complex construction environment, and the monitoring methods based on sensor equipment cost too much. This paper aims to introduce computer vision and deep learning technologies to propose the YOLOv5-FastPose (YFP) model to realize the pose estimation of construction machines by improving the AlphaPose human pose model.

This model introduced the object detection module YOLOv5m to improve the recognition accuracy for detecting construction machines. Meanwhile, to better capture the pose characteristics, the FastPose network optimized feature extraction was introduced into the Single-Machine Pose Estimation Module (SMPE) of AlphaPose. This study used Alberta Construction Image Dataset (ACID) and Construction Equipment Poses Dataset (CEPD) to establish the dataset of object detection and pose estimation of construction machines through data augmentation technology and Labelme image annotation software for training and testing the YFP model.

The experimental results show that the improved model YFP achieves an average normalization error (NE) of 12.94 × 10^–3, an average Percentage of Correct Keypoints (PCK) of 98.48% and an average Area Under the PCK Curve (AUC) of 37.50 × 10^–3. Compared with existing methods, this model has higher accuracy in the pose estimation of the construction machine.

This study extends and optimizes the human pose estimation model AlphaPose to make it suitable for construction machines, improving the performance of pose estimation for construction machines.

The unique nature of the construction sector makes it fall behind other sectors in terms of productivity. Monitoring construction productivity is crucial for the construction project's success. Current practices for construction productivity monitoring are time-consuming, manned and error prone. Although previous studies have been implemented toward reducing these limitations, a gap still exists in the automated monitoring of construction productivity.

This study aims to investigate and assess the different techniques used for monitoring productivity in building construction projects. Therefore, a mixed review methodology (bibliometric analysis and systematic review) was adopted. All the related publications were collected from different databases, which were further screened to get the most relevant based on the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) criteria.

A detailed review was performed, and it was found that traditional methods, computer vision-based and photogrammetry are the most adopted data acquisition for productivity monitoring of building projects, respectively. Machine learning algorithms (ANN, SVM) and BIM were integrated with monitoring tools and technologies to enhance the automated monitoring performance in construction productivity. Also, it was observed that current studies did not cover all the complex construction job sites and they were applied based on a small sample of construction workers and machines separately.

This review paper contributes to the literature on construction management by providing insight into different productivity monitoring techniques.

On a global scale, the Muslim-friendly hospitality business has intensified hotel competition. Given the paucity of research on the important service quality characteristics of Muslim-friendly hotels, this study aims to identify the major themes encountered by tourists at Muslim-friendly hotels.

The research used content analyzes (qualitative) to examine 1,250 reviews using Leximancer software. Data were gathered from the online travel website booking.com. The top 10 Islamic hotels according to Crescent ranking were taken into a data set.

Qualitative (narratives) analysis showcased nine key themes, namely, “hotel,” “staff,” “food,” “room,” “location,” “pool,” “facilities,” “cleanliness” and “Wi-Fi.” Furthermore, the findings of this study contribute to filling research voids in the literature by distinguishing themes linked with halal hotel “satisfaction” from those associated with “dissatisfaction.”

The findings of this research offer valuable visions into halal-hotel travelers’ overall experiences based on user-generated content and facilitate the identification of the dominant themes linked with a different value for money ratings.

The purpose of this paper is to identify and assess the factors affecting building services’ coordination during the design development and review stages of building projects.

Literature review and interviews were conducted to identify the factors affecting building services’ coordination. In total, 36 factors were identified under six categories: planning phase of the project; design of mechanical, electrical and plumbing (MEP) systems; construction of MEP systems; operation and maintenance of MEP systems; owner; and design team and tools used. This formed the basis of a questionnaire survey designed utilizing a 5-point Likert scale of importance. The survey was assessed by practitioners in the Eastern province of Saudi Arabia.

The top five factors include the scale and complexity of the project, the level of experience of the design team, the quality of the preliminary/conceptual design of the building project, the clarity of the requirements and objectives provided by the owner, the allotted budget for the project and communication skills of the design team members. A high level of agreement between A/E professionals and contractors, and between contractors and facility managers was noted. The research provides the ranking of the identified factors for prioritization.

The paper provides stakeholders in the building services industry with the ranks of the factors that affect building services’ coordination.

The study provided a significant contribution to research and industry, especially in the regional context, where few studies have been conducted. The findings of the study will help in the reduction of construction wastes, delays and cost over-runs.

The purpose of the study is to analyse the occurrence and distribution of different tree species in Gilgit-Baltistan, Pakistan, as a baseline for further inventories, and estimate the biomass per species and plot. Furthermore, it aims to measure forest biodiversity using established formulae for tree species diversity index, richness, evenness and accumulative curve.

Field data were collected, including stratification of forest sample plots. Statistical analysis of the data was carried out, and locally appropriate allometric equations were applied for biomass estimation.

Representative circular 556 forest sample plots of 1,000 m² contained 13,135 trees belonging to nine tree species with a total aboveground biomass of 12,887 tonnes. Sixty-eight per cent of the trees were found between 2,600 and 3,400 masl; approximately 63 per cent had a diameter at breast height equal to 30 cm, and 45 per cent were less than 12 m in height. The Shannon diversity index was 1.82, and Simpson’s index of diversity was 0.813.

Rough terrain, long distances, harsh weather conditions and location of forest in steep narrow valleys presented challenges for the field crews, and meant that fieldwork took longer than planned.

Estimating biomass in Gilgit-Baltistan’s forests using locally developed allometric equations will provide transparency in estimates of forest reference levels, National Forest Monitoring System in Pakistan and devising Reducing Emissions from Deforestation and Forest Degradation national strategies and for effective implementation.

This paper presents the first detailed forest inventory carried out for the dry temperate and semi-arid cold region of Gilgit-Baltistan, Pakistan.

Winglets play a major role in saving fuel costs because they reduce the lift-induced drag formed at the wingtips. The purpose of this paper is to obtain the best orientation of the winglet for the Office National d’Etudes et de Recherches Aérospatiales (ONERA) M6 wing at Mach number 0.84 in terms of lift to drag ratio.

A computational fluid dynamics analysis of the wing-winglet configuration based on the ONERA M6 airfoil on drag reduction for different attack angles at Mach 0.84 was performed using analysis of systems Fluent. First, the best values of cant and sweep angles in terms of aerodynamic performance were selected by performing simulations. The analysis included cant angle values of 30°, 40°, 45°, 55°, 60°, 70° and 75°, while for the sweep angles 35°, 45°, 55°, 65° and 75° angles were used. The aerodynamic performance was measured in terms of the obtained lift to drag ratios.

The results showed that slight alternations in the winglet configuration can improve aerodynamic performance for various attack angles. The best lift to drag ratio for the winglet was achieved at a cant angle of 30° and a sweep angle of 65°, which caused a 5.33% increase in the lift to drag ratio. The toe-out angle winglets as compared to the toe-in angles caused the lift to drag ratio to increase because of more attached flow at its surface. The maximum value of the lift to drag ratio was obtained with a toe-out angle (−5°) at an angle of attack 3° which was 2.53% greater than the zero-toed angle winglet.

This work is relatively unique because the cant, sweep and toe angles were analyzed altogether and led to a significant reduction in drag as compared to wing without winglet. The wing model was compared with the results provided by National Aeronautics and Space Administration so this validated the simulation for different wing-winglet configurations.

The Islamic financial institutions (IFIs) maintain better control over their transactions than conventional financial institutions (CFIs) through the existence of Shari'a Supervisory Board (SSB) and Shari'a Control Department (SCD). The purpose of this paper is to highlight the superiority of Shari'a supervision over external audit and Shari'a audit over internal audit. The study identifies five independent variables that affect the SSB control: ex‐ante Shari'a audit; ex‐post Shari'a audit; SCD reporting to the SSB; corrective actions of SSB towards the management violations; and the number of SSB members.

The variables are articulated in five hypotheses, which are tested by ordinary least square regression. The data are collected via a questionnaire which was sent to the SSB members of 219 IFIs in the Gulf Cooperation Council (GCC) countries.

The results indicate that ex‐ante Shari'a audit, ex‐post Shari'a audit, and reporting of SCD are significantly related to the SSB control, whereas corrective actions and the number of SSB members have insignificant relation.

The research is focused on internal factors only, without considering other external factors such as stakeholders and regulators. Also, the research covered the GCC region alone.

The research recommends testing the hypotheses in other geographies to generalize the results, and including external factors as well as shareholders and board of directors.

The research provides practical implications for the SCD role and calls for merging the SCD with the traditional internal audit department to reduce the excessive work of controlling.

The paper contributes to the literature gap about the SSB. It is believed to be one of few studies that provide empirical evidence about the SSB control in the IFIs of the GCC region.

The purpose of this research is to examine how consumers interpret and understand sustainable fashion production and how this informs their fashion consumption practice.

The research adopts an interpretivist approach with in-depth interviews with 28 participants. Sampling criterion sought consumers already engaged with sustainable production – professionally working mothers – to explore how their sustainability knowledge was evaluated for sustainable fashion claims. Garment labels that descripted facets of sustainable production were introduced to encourage discourse of sustainable fashion knowledge.

The findings illustrate that sustainable fashion production is not understood and efforts to apply sustainability concepts were often misunderstood which led to scepticism for higher pricing and marketing claims. Despite this, there was concern for the wider implications of sustainability.

Limitations include the small sample from one geographical area (Edinburgh), despite the richness of the data collected.

The research offers practical advice for fashion marketers to educate consumers through effective communication strategies how sustainable fashion concepts improve consumer concerns surrounding fashion production.

The research indicates increased concern for fashion sustainability, something that fashion retailers should be mindful of.

There has been little research examining consumer interpretation of sustainable fashion terminology, and this research adds to understanding how sustainability is evaluated within fashion production.