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As video-based interventions are continuously utilized as alternatives to physical site visits, directing students' attention to specific learning contents within videos could increase their comprehension and stimulate their interest. Students' knowledge of construction practice can be reinforced, misconceptions and improper inferences can be reduced by calling out significant learning concepts. However, few studies have formalized practice concepts that could be beneficial in preparing students for the workplace. This paper presents an investigation of construction practice concepts, based on site visits that would be beneficial in complimenting classroom teaching to prepare students for the realities of practice.

A mixed methods research approach was employed combining qualitative and quantitative data collection and analysis. An online questionnaire, semi-structured interviews and a focus group were conducted with industry practitioners and instructors to identify the topics and practice concepts significant for supporting classroom teaching with site visits.

The findings suggest that the most relevant topics typically supported with site visits are preconstruction management, excavation and foundation work, construction equipment, construction means and methods, project management, road construction, sustainability, building systems, structures, construction technology, building construction, capstone, site logistics and safety. Practice concepts were identified for each of these topics.

The study will guide researchers in the design of video-based pedagogical tools to be used as an effective complement of or alternative to site visit experiences. The findings will support instructors on how to structure their teaching practices to prepare students for some of the complexities of the workplace.

This study adds value to the existing literature by providing insights into industry perception of practice concepts for complementing classroom teaching.

Carpenters are constantly vulnerable to musculoskeletal disorders. Their work consists of subtasks that promote nonfatal injuries and pains that affect different body segments. The purpose of this study is to examine ergonomic exposures of carpentry subtasks involved in floor framing, how they lead to musculoskeletal injuries, and how preventive and protective interventions around them can be effective.

Using wearable sensors, this study characterizes ergonomic exposures of carpenters by measuring and analyzing body movement data relating to major subtasks in carpentry flooring work. The exposures are assessed using Postural Ergonomic Risk Assessment classification, which is based on tasks involving repetitive subtasks and nonstatic postures.

The findings of this paper suggest severe risk impositions on the trunk, shoulder and elbow as a result of the measuring and marking and cutting out vent locations, as well as in placing and nailing boards into place.

Because of the type and size of wearable sensor used, only results of risk exposures of four body-parts are presented.

This study draws insights on how to benchmark trade-specific measurement of work-related musculoskeletal disorders. Safety efforts can be targeted toward these risk areas and subtasks. Specifically, results from these will assist designers and innovators in designing effective and adaptable protective interventions and safety trainings.

Extant studies have failed to provide adequate evidence regarding the relationships between subtasks and musculoskeletal disorders; they have only mimicked construction tasks through laboratory experimental scenarios. This study adds value to the existing literature, in particular by providing insights into hazards associated with floor carpentry subtasks.

The physically-demanding and repetitive nature of construction work often exposes workers to work-related musculoskeletal injuries. Real-time information about the ergonomic consequences of workers' postures can enhance their ability to control or self-manage their exposures. This study proposes a digital twin framework to improve self-management ergonomic exposures through bi-directional mapping between workers' postures and their corresponding virtual replica.

The viability of the proposed approach was demonstrated by implementing the digital twin framework on a simulated floor-framing task. The proposed framework uses wearable sensors to track the kinematics of workers' body segments and communicates the ergonomic risks via an augmented virtual replica within the worker's field of view. Sequence-to-sequence long short-term memory (LSTM) network is employed to adapt the virtual feedback to workers' performance.

Results show promise for reducing ergonomic risks of the construction workforce through improved awareness. The experimental study demonstrates feasibility of the proposed approach for reducing overexertion of the trunk. Performance of the LSTM network improved when trained with augmented data but at a high computational cost.

Suggested actionable feedback is currently based on actual work postures. The study is experimental and will need to be scaled up prior to field deployment.

This study reveals the potentials of digital twins for personalized posture training and sets precedence for further investigations into opportunities offered by digital twins for improving health and wellbeing of the construction workforce.

Construction action recognition is essential to efficiently manage productivity, health and safety risks. These can be achieved by tracking and monitoring construction work. This study aims to examine the performance of a variant of deep convolutional neural networks (CNNs) for recognizing actions of construction workers from images of signals of time-series data.

This paper adopts Inception v1 to classify actions involved in carpentry and painting activities from images of motion data. Augmented time-series data from wearable sensors attached to worker's lower arms are converted to signal images to train an Inception v1 network. Performance of Inception v1 is compared with the highest performing supervised learning classifier, k-nearest neighbor (KNN).

Results show that the performance of Inception v1 network improved when trained with signal images of the augmented data but at a high computational cost. Inception v1 network and KNN achieved an accuracy of 95.2% and 99.8%, respectively when trained with 50-fold augmented carpentry dataset. The accuracy of Inception v1 and KNN with 10-fold painting augmented dataset is 95.3% and 97.1%, respectively.

Only acceleration data of the lower arm of the two trades were used for action recognition. Each signal image comprises 20 datasets.

Little has been reported on recognizing construction workers' actions from signal images. This study adds value to the existing literature, in particular by providing insights into the extent to which a deep CNN can classify subtasks from patterns in signal images compared to a traditional best performing shallow network.

Work-related musculoskeletal disorders constitute a severe problem in the construction industry. Workers' lower backs are often affected by heavy or repetitive lifting and prolonged awkward postures. Exoskeletal interventions are effective for tasks involving manual lifting and repetitive movements. This study aims to examine the potential of a postural-assist exoskeleton (a passive exoskeleton) for manual material handling tasks.

From an experimental observation of participants, the effects of postural-assist exoskeleton on tasks and workers were measured. Associated benefits of the exoskeleton were assessed through task performance, range of motion and discomfort.

Findings suggest that the exoskeleton influenced discomfort significantly, however range of motion decreased with lifting tasks. The reduced back flexion and increased hip flexion were also indicatives of the participants' responsiveness to the feedback from the exoskeleton. In addition, task completion time increased by 20%, and participants' back pain did not reduce.

The work tasks were performed in a controlled laboratory environment and only wearable inertia measurement units (IMUs) were used to assess the risk exposures of the body parts.

This study opens a practical pathway to human-exoskeleton integration, artificial regeneration or enablement of impaired workforce and a window toward a new order of productivity scaling. Results from this study provide preliminary insights to designers and innovators on the influence of postural assist exoskeleton on construction work. Project stakeholders can be informed of the suitability of the postural assist exoskeletons for manual material handling tasks.

Little has been reported on the benefits and impact of exoskeletons on tasks' physical demands and construction workers' performance. This study adds value to the existing literature, in particular by providing insights into the effectiveness and consequences of the postural-assist exoskeleton for manual material handling tasks.

This study aims to examine the housing outcomes of natives and multiple generations of non-natives using a longitudinal survey data in Britain.

The authors use longitudinal data from Britain, in which they can observe multiple generations of immigrants and their demographic and economic information.

The probability models for housing tenure reveal significant variation in the outcomes which are robust to several econometric specifications.

As migration and its impact on local economy is a highly debated topic across several major regions of the world, the findings bring out important insights with policy implications. The research is limited by the sample size of the longitudinal survey.

The empirical evidence on the topic is quite limited with mixed findings. Especially, the authors’ ability to look through multiple generations is unique in identifying the variation in housing outcomes for the native and non-native citizens.

The purpose of this paper is to evaluate the impact of financial inclusion (FI) on control of corruption in selected African countries.

The study employs secondary data spanning over a period of 2005–2016. These data are sourced from IMF's International Financial Statistics, World Bank Development Indicators, Global Financial Development Database, Transparency International and International Country Risk Guide. The author uses Sarma (2008) approach to construct the FI index for 13 countries in Africa. The author applies random effect, robust least square and instrumental variable (IV) estimations to examine the impact of FI on control of corruption in Africa.

The author finds that financial inclusion improves the control of corruption. The author tests for possible FI threshold to avoid the case of extreme FI in Africa. The results show that there is a threshold level if reached, FI would have negative impacts in the control of corruption. This may likely happen mainly due to weak institutions in Africa. The results are robust to alternative proxy for control of corruption and various alternative estimation techniques.

The finding indicates that FI can serve as part of toolkits for reducing corruption in Africa.

This study stresses the important role of FI in the economic system. It is the first paper that empirically suggests the role of FI in controlling corruption in Africa.

The current era of the fourth industrial revolution has attracted significant research on the use of digital technologies in improving construction project delivery. However, less emphasis has been placed on how these digital tools will influence the management of the construction workforce. To this end, using a review of existing works, this chapter explores the fourth industrial revolution and its associated technologies that can positively impact the management of the construction workforce when implemented. Also, the possible challenges that might truncate the successful deployment of digital technologies for effective workforce management were explored. The chapter submitted that implementing workforce management-specific digital platforms and other digital technologies designed for project delivery can aid effective workforce management within construction organisations. Technologies such as cloud computing, the Internet of Things, big data analytics, robotics and automation, and artificial intelligence, among others, offer significant benefits to the effective workforce management of construction organisations. However, several challenges, such as resistance to change due to fear of job loss, cost of investment in digital tools, organisational structure and culture, must be carefully considered as they might affect the successful use of digital tools and by extension, impact the success of workforce management in the organisations.

This study aims to assess the accessibility of women to health-care facilities in the rural areas with a view to unties possible recommendation of enhancing its service delivery. It provides an insight into the levels of satisfaction of the services provided by conventional health-care providers in the area where the majority in the developing countries concentrated. The study unravels the reasons for the low patronage of regular health-care facilities to boost unscientific ones by rural women.

The study relies on extensive field work conducted in the study area mainly rural nature. data was sourced by questionnaire, mainly administered on the women in the area and field observation. Data collected were analysed using descriptive statistics.

The paper provides information on the low socio-economic attributes of rural women. It is further showed that medical facilities and personnel were not relatively available and performed in health-care centres to the satisfaction of the users. Poor roads, poor human relation, low quality of services, inadequate medical personnel and drug shortage hindrance to women accessing appropriate health-care facilities in the rural areas. Rural women, therefore, opted for self-medication folk medicine, disguising and spiritual remedies. Health-care facilities suffered poor patronage as a result of these obstacles The study recommended proper overhauling of health-care facilities.

The paper builds a relationship on the reasons for health-care facilities neglect in the rural area in developing countries and revealed unscientific means by which health care needs are realised rural women.