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In this study, an indoor sensor information fusion positioning system of the quadrotor unmanned aerial vehicle (UAV) was investigated to solve the problem of unstable indoor flight positioning.

The presented system was built on Light Detection and Ranging (LiDAR), Inertial Measurement Unit (IMU) and LiDAR-Lite devices. Based on this, one can obtain the aircraft's current attitude and the position vector relative to the target and control the attitudes and positions of the UAV to reach the specified target positions. While building a UAV positioning model relative to the target for indoor positioning scenarios under limited Global Navigation Satellite Systems (GNSS), the system detects the environment through the NVIDIA Jetson TX2 (Transmit Data) peripheral sensor, obtains the current attitude and the position vector of the UAV, packs the data in the format and delivers it to the flight controller. Then the flight controller controls the UAV by calculating the posture to reach the specified target position.

The authors used two systems in the experiment. The first is the proposed UAV, and the other is the Vicon system, our reference system for comparison purposes. Vicon positioning error can be considered lower than 2 mm from low to high-speed experiments. After comparison, experimental results demonstrated that the system could fully meet the requirements (less than 50 mm) in real-time positioning of the indoor quadrotor UAV flight. It verifies the accuracy and robustness of the proposed method compared with that of Vicon and achieves the aim of a stable indoor flight preliminarily.

Vicon positioning error can be considered lower than 2 mm from low to high-speed experiments. After comparison, experimental results demonstrated that the system could fully meet the requirements (less than 50 mm) in real-time positioning of the indoor quadrotor UAV flight. It verifies the accuracy and robustness of the proposed method compared with that of Vicon and achieves the aim of a stable indoor flight preliminarily.

The crane plays an essential role in modern construction sites as it supports numerous operations and activities on-site. Additionally, the crane produces a big amount of data that, if analyzed, could significantly affect productivity, progress monitoring and decision-making in construction projects. This paper aims to show the usability of crane data in tracking the progress of activities on-site.

This paper presents a pattern-based recognition method to detect concrete pouring activities on any concrete-based construction sites. A case study is presented to assess the methodology with a real-life example.

The analysis of the data helped build a theoretical pattern for concrete pouring activities and detect the different phases and progress of these activities. Accordingly, the data become useable to track progress and identify problems in concrete pouring activities.

The paper presents an example for construction practitioners and researcher about a practical and easy way to analyze the big data that comes from cranes and how it is used in tracking projects' progress. The current study focuses only on concrete pouring activities; future studies can include other types of activities and can utilize the data with other building methods to improve construction productivity.

The proposed approach is supposed to be simultaneously efficient in terms of concrete pouring detection as well as cost-effective. Construction practitioners could track concrete activities using an already-embedded monitoring device.

While several studies in the literature targeted the optimization of crane operations and of mitigating hazards through automation and sensing, the opportunity of using cranes as progress trackers is yet to be fully exploited.

Tactile communication that relies on the human sense of touch replicated using vibration motors is increasingly being explored for seamless communication on construction jobsite. However, the technological efficacy cannot secure the users’ acceptability of the tactile communication devices. This study aims to assess the factors affecting the wearability of such a portable tactile device based on the responses from practicing professionals.

The investigation adapted a three-step phenomenological interviewing approach to seek feedback from construction personnel in Texas, the USA, regarding the viability of wearable tactile communication. The interviewees expressed various opinions about the on-body placement upon exposure to a portable tactile feedback prototype developed for this study, which was used to derive inferences regarding the factors affecting its on-field acceptability.

All the participants of the round-table study (11 out of 11) considered tactile feedback as a viable mode of communication on construction jobsite. Seven professionals supported the integration of a tactile device with the hard hat, whereas the rest preferred tactile eyeglasses. Weatherability, rechargeability, traceability, safety and social receptivity were identified as the major factors affecting the on-body placement of the wearable tactile communication device.

This paper presents a roadmap to gain construction industry opinion on the factors that can affect the on-body placement of a wearable tactile communication device. The five aforementioned factors impacting tactile communication acceptability were used to evaluate 10 potential on-body placements. The findings have implications for research and development of wearable tactile devices and the subsequent acceptability of such a device on the jobsite.

This study aims to investigate how institutional and organisational factors affect case management of patients with mental disorders by GPs in Italy and Spain. The paper highlights the importance of improving the effectiveness of primary care to ensure easy access to mental health services, which is crucial in responding to the increasing incidence of mental disorders and preventing negative outcomes.

This article details a qualitative research study that examines the management of patients with mental disorders by general practitioners (GPs) in Italy and Spain, using cross-national comparison and in-depth interviews with GPs as research methods.

The study revealed that Italian self-employed GPs have more scheduling autonomy than Spanish Health Centre GPs. Both face high work pressure and resource scarcity, highlighting the need for targeted training. The COVID-19 pandemic led to a rise in phone consultations.

This study provides novel insights into mental health management by examining the case management of patients with mental disorders by GPs in Italy and Spain, with a focus on the impact of institutional and organisational factors. The cross-national comparison and in-depth interviews enhance the originality of the study, offering a nuanced understanding of the constraints faced by GPs in their work context. Furthermore, the comparison of the similar primary care frameworks of Italy and Spain may offer insight into their evolution.

Using a real-time road network combined with historical traffic data for Al-Salt city, the paper aims to propose a new federated genetic algorithm (GA)-based optimization technique to solve the dynamic vehicle routing problem. Using a GA solver, the estimated routing time for 300 chromosomes (routes) was the shortest and most efficient over 30 generations.

In transportation systems, the objective of route planning techniques has been revised from focusing on road directors to road users. As a result, the new transportation systems use advanced technologies to support drivers and provide them with the road information they need and the services they require to reduce traffic congestion and improve routing problems. In recent decades, numerous studies have been conducted on how to find an efficient and suitable route for vehicles, known as the vehicle routing problem (VRP). To identify the best route, VRP uses real-time information-acquired geographical information systems (GIS) tools.

This study aims to develop a route planning tool using ArcGIS network analyst to enhance both cost and service quality measures, taking into account several factors to determine the best route based on the users’ preferences.

Furthermore, developing a route planning tool using ArcGIS network analyst to enhance both cost and service quality measures, taking into account several factors to determine the best route based on the users’ preferences. An adaptive genetic algorithm (GA) is used to determine the optimal time route, taking into account factors that affect vehicle arrival times and cause delays. In addition, ArcGIS' Network Analyst tool is used to determine the best route based on the user's preferences using a real-time map.

The purpose of this study is to examine the development of environmental performance (EP) through sustainable practices (SPs), environmental corporate social responsibility (environmental CSR) and behavioural intentions (BIs) among Pakistan’s small and medium enterprises (SMEs).

In this study, the researchers applied a quantitative approach which involved significant cross-sectional data. The authors used an online survey to serve the aim of this study. The survey’s respondents are top managers of Pakistan’s manufacturing firms. The authors received 196 valid cases to obtain suitable outcomes from the data.

By using the structural equation model, the path analysis shows that green practices (GPs) have a positive and significant effect on SPs and environmental CSR. This study’s findings also demonstrate that environmental CSR plays a substantial role in developing the SPs, BIs and EP. The results of this study also show that SP plays a positive and significant role towards BIs and EP. Finally, BI predicts the EP.

This study's findings provide planners and policymakers with guidelines to create EP through environmental CSR, SPs and BIs. This study's findings are valuable results in identifying green practices’ significant role in establishing environmental CSR and SPs. Finally, this study's findings offer a new perception of integrating these factors and their contribution to EP.

This study examined the development of EP in the challenging situation of the COVID-19 pandemic. Therefore, in terms of the empirical findings, this study provides original value.

In most developing countries, indigenous emerging construction contractors (ECCs) face severe problems of not adopting a project management framework (PMF) in their business activities. It has increased their business risk and threatened their sustainability. Studies showed that government policy support (GPS) helps mitigate business risks. Thus, there is a paucity of literature concerning GPS on emerging Nigerian construction contractors' business sustainability. Therefore, the paper aims to investigate the moderating effect of GPS on the relationship between PMF and ECCs in Nigeria.

SmartPLS was used to analyse the collected data from the useable 310 questionnaires retrieved from respondents in Abuja and Lagos, Nigeria. Systems Theory was used to support the developed framework.

Findings show that government policy support significantly moderates the relationships between PMF and ECCs in the Nigerian construction sector. It implies that the study's results offer more understanding regarding issues affecting construction entrepreneurs' sustainable business cycle via applying PMF to mitigate business sustainable associated risks.

The study will stir Nigeria's ECCs and policymakers to promote construction business sustainability for a new entrepreneur, emphasising business risk management via PMF and GPS to enhance the sustainable business cycle.

The research (PMF and GPS) is strategies to enhance ECCs business sustainability in the Nigerian construction sector and other developing countries with similar political and economic attributes. Besides the study guiding old and intending ECCs and policymakers in the developing countries industries, it would contribute to bridge the theoretical gap regarding PMF and ECC, especially ECCs in developing countries with similar business sustainability issues.

With the pressing need for environmental conservation, regulatory authorities are actively looking for measures to prevent global warming. In the proposed inventory model for deteriorating items, demand is dependent on the selling price and green technology investment (or carbon reduction investment) for the green product (GP), as well as an investment in price-based preservation technology to slow down the pace of deterioration. Furthermore, emission reduction measures are put in place to reduce carbon emissions (CEs).

The current study executed a thorough literature review to determine how to improve supply chain management performance. Furthermore, assumptions are made to fill research gaps, and a mathematical model is created to address the problem mentioned above. To collect the data, the available inventory literature was reviewed. Additionally, numerical illustrations and sensitivity analyses are presented to emphasize the model's robustness.

The research indicates that it is more prudent to invest in preservation technology based on its selling price in order to control the rate of deterioration. In addition, the proposed model facilitates the management of deteriorated waste through salvage trading and emission reduction investment. The findings validate sustainable practices with a 20.86% increase in profit and a 21.4% decrease in CEs, thereby signifying environmental and economic benefits.

The proposed model enhances understanding of the impact of investments in price-based preservation technology and carbon reduction efforts on consumer perceptions of their intention to purchase GPs. Moreover, the study provides valuable insights by identifying important recommendations for policymakers regarding areas that require further investigation. This guideline can help identify both current and unexplored gaps, enabling researchers to direct future research efforts toward producing new products.

The unprecedented pandemic of COVID-19 is not a typical crisis. This crisis has irrevocably altered human behavior, most notably consumption behavior. The uncertainty caused due to economic insecurity and fears of death have resulted in a paradigm shift away from consumer materialism and toward consumer spiritualism. The present study examines the effect of various dimensions of “spirituality” on consumers’ conspicuous consumption of fashion. The study employs a descriptive empirical research design to determine the impact of multiple dimensions of spirituality on the conspicuous consumption of Generation Z in India. These dimensions include General spirituality belief, Global personal spirituality and reincarnation spirituality. Additionally, the moderating effect of dispositional positive emotion on the relationships mentioned above has been investigated.

The data were accumulated through purposive sampling from 517 Generation Z consumers and analyzed using structural equation modeling.

Reincarnation, general personal and global personal spirituality had a direct positive impact on conspicuous consumption of fashion. Dispositional positive emotion had a positive moderation effect between the reincarnation, general personal and global personal spirituality and conspicuous consumption.

The study will assist fashion brands and retailers in better understanding consumer behavior and associated opportunities and threats post COVID-19. For merchants and business owners in emerging countries, this study will help them to apply new techniques for keeping customers. It is useful to evaluate a shopper’s views towards spirituality, disposition and conspicuous consumption.

The construction industry remains one of the most hazardous industries worldwide, with a higher number of fatalities and injuries each year. The safety and well-being of workers at a job site are paramount as they face both immediate and long-term risks such as falls and musculoskeletal disorders. To mitigate these dangers, sensor-based technologies have emerged as a crucial tool to promote the safety and well-being of workers on site. The implementation of real-time sensor data-driven monitoring tools can greatly benefit the construction industry by enabling the early identification and prevention of potential construction accidents. This study aims to explore the innovative method of prototype development regarding a safety monitoring system in the form of smart personal protective equipment (PPE) by taking advantage of the recent advances in wearable technology and cloud computing.

The proposed smart construction safety system has been meticulously crafted to seamlessly integrate with conventional safety gear, such as gloves and vests, to continuously monitor construction sites for potential hazards. This state-of-the-art system is primarily geared towards mitigating musculoskeletal disorders and preventing workers from inadvertently entering high-risk zones where falls or exposure to extreme temperatures could occur. The wearables were introduced through the proposed system in a non-intrusive manner where the safety vest and gloves were chosen as the base for the PPE as almost every construction worker would be required to wear them on site. Sensors were integrated into the PPE, and a smartphone application which is called SOTER was developed to view and interact with collected data. This study discusses the method and process of smart PPE system design and development process in software and hardware aspects.

This research study posits a smart system for PPE that utilises real-time sensor data collection to improve worksite safety and promote worker well-being. The study outlines the development process of a prototype that records crucial real-time data such as worker location, altitude, temperature and hand pressure while handling various construction objects. The collected data are automatically uploaded to a cloud service, allowing supervisors to monitor it through a user-friendly smartphone application. The worker tracking ability with the smart PPE can help to alleviate the identified issues by functioning as an active warning system to the construction safety management team. It is steadily evident that the proposed smart PPE system can be utilised by the respective industry practitioners to ensure the workers' safety and well-being at construction sites through monitoring of the workers with real-time sensor data.

The proposed smart PPE system assists in reducing the safety risks posed by hazardous environments as well as preventing a certain degree of musculoskeletal problems for workers. Ultimately, the current study unveils that the construction industry can utilise cloud computing services in conjunction with smart PPE to take advantage of the recent advances in novel technological avenues and bring construction safety management to a new level. The study significantly contributes to the prevailing knowledge of construction safety management in terms of applying sensor-based technologies in upskilling construction workers' safety in terms of real-time safety monitoring and safety knowledge sharing.