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Construction safety is a crucial aspect that has far-reaching impacts on economic development. But safety monitoring is often reliant on labor-based observations, which can be prone to errors and result in numerous fatalities annually. This study aims to address this issue by proposing a cloud-building information modeling (BIM)-based framework to provide real-time safety monitoring on construction sites to enhance safety practices and reduce fatalities.

This system integrates an automated safety tracking mobile app to detect hazardous locations on construction sites, a cloud-based BIM system for visualization of worker tracking on a virtual construction site and a Web interface to visualize and monitor site safety.

The study’s results indicate that implementing a comprehensive automated safety monitoring approach is feasible and suitable for general indoor construction site environments. Furthermore, the assessment of an advanced safety monitoring system has been successfully implemented, indicating its potential effectiveness in enhancing safety practices in construction sites.

By using this system, the construction industry can prevent accidents and fatalities, promote the adoption of new technologies and methods with minimal effort and cost and improve safety outcomes and productivity. This system can reduce workers’ compensation claims, insurance costs and legal penalties, benefiting all stakeholders involved.

To the best of the authors’ knowledge, this study represents the first attempt in Bangladesh to develop a mobile app-based technological solution aimed at reforming construction safety culture by using BIM technology. This has the potential to change the construction sector’s attitude toward accepting new technologies and cultures through its convenient choice of equipment.

The purpose of this study is to systematically examine the existing literature published on the circulation methods used in academic libraries and to discuss a proposed model for the self-check-in and check-out methods using quick response (QR) codes.

A systematic literature review (SLR) provided a complete overview of circulation systems used in academic libraries for the last more than 140 years. Preferred reporting items for systematic reviews and meta-analyses (PRISMA) method for SLR was used. Several databases such as ProQuest, Emerald, Library and Information Science Abstracts, EBSCO and Google Scholar were searched. Out of 277 papers retrieved in the search, 43 most relevant papers were taken up for the SLR. These were classified into four themes based on the systems of circulation used, namely, manual (5), mechanized (13), automated (5) and networked system (20). Based on the findings of the SLR, a model of circulation system in which QR code technology has been used.

The result of SLR identified 33 systems used in above mentioned four groups. Among this, a large number 48.48% of mechanized systems were found. Each system has limitations either because of devices used or of technology. The present study proposes a QR code-based model at the circulation desk, for which a prototype of Android app has been designed. This would help to initiate the new “self-services” facility to users at the circulation desk.

The proposed model, after its successful implementation, can be adopted by academic libraries. Guidelines and a graphical representation of this study can be used by any researcher for further experimentation.

To the best of the authors’ knowledge, this is the first kind of study in which a QR code-based Android app model has been proposed for library circulation records.

This research paper aims to provide information about certified learning apps for biological education and gave an ordered list of all learning apps currently used by Austrian biology teachers in the classroom, which should serve as an overview for all biology teachers. In addition, the (currently little known) certification process of learning apps (seal of quality for educational applications) is described.

Online questionnaire for all biology teachers throughout Austria, on the one hand to find out the apps, and on the other hand to research how Austrian teachers find suitable apps. The data were evaluated using descriptive statistics.

A total of84 different learning apps are currently used by biology teachers in Austria. There are two certified lernapps in Austria, both are used. The most common app in biology lessons is “Anton”. The teachers find the information about apps throughout their own research or through colleagues. There are regional and school-specific differences in regards of usage and knowledge about seal of quality. It needs its own teacher training (TT) via suitable learning apps, because problems (data protection, advertising) are sometimes not taken into account during use.

Limitations of this paper are that some of the teachers indicated the apps from other subjects (mathematics) to use this learning app, although this is not possible for biology lessons. Data protection was stated to the best of the authors’ knowledge by the authors, if the authors were not sure it says “unsure”. The participants are mainly women, but this corresponds to the gender ratio, which is typical of the Austrian teaching profession.

The overview of the apps, compiled by this Austria-wide research, can be taken over into the biology lessons of all teachers. In addition, on the basis of this study, a TT at the University of Education 2023 in Linz was created. In addition, the (currently little known) certification process of learning apps is described.

The TT and the overview of the learning apps used serve as guidelines for teachers as to which apps they can use in biology lessons without hesitation. Above all, the aspect of the follow-up of digital media/apps will be emphasized. Data backup, inappropriate advertising must be processed in class or completely omitted. Biology teachers need the right training (TT) and appropriate materials and tools (apps) to reduce problems (cybercrimes).

Currently, there is no prepared list of suitable (certified and uncertified) learning apps for biology lessons. There are isolated recommendations and individual apps, but the selection criteria and backgrounds of the authors are not clear. This list shows which apps (how often) are used by which teachers. In addition, the (currently little known) certification process of learning apps is described.

The purpose of this paper is geared towards the capture and analysis of network traffic using an array ofmachine learning (ML) and deep learning (DL) techniques to classify network traffic into different classes and predict network traffic parameters.

The classifier models include k-nearest neighbour (KNN), multilayer perceptron (MLP) and support vector machine (SVM), while the regression models studied are multiple linear regression (MLR) as well as MLP. The analytics were performed on both a local server and a servlet hosted on the international business machines cloud. Moreover, the local server could aggregate data from multiple devices on the network and perform collaborative ML to predict network parameters. With optimised hyperparameters, analytical models were incorporated in the cloud hosted Java servlets that operate on a client–server basis where the back-end communicates with Cloudant databases.

Regarding classification, it was found that KNN performs significantly better than MLP and SVM with a comparative precision gain of approximately 7%, when classifying both Wi-Fi and long term evolution (LTE) traffic.

Collaborative regression models using traffic collected from two devices were experimented and resulted in an increased average accuracy of 0.50% for all variables, with a multivariate MLP model.

This study investigates human behavior, specifically attitude and anxiety, toward humanoid service robots in a hotel business environment.

The researcher adopted direct observations and interviews to complete the study. Visitors of Henn-na Hotel were observed and their spatial distance from the robots, along with verbal and non-verbal behavior, was recorded. The researcher then invited the observed hotel guests to participate in a short interview.

Most visitors showed a positive attitude towards the robot. More than half of the visitors offered compliments when they first saw the robot receptionists although they hesitated and maintained a distance from them. Hotel guests were also disappointed with the low human–robot interaction (HRI). As the role of robots in hotels currently remains at the presentation level, a comprehensive assessment of their interactive ability is lacking.

This study contributes to the HRI theory by confirming that people may treat robots as human strangers when they first see them. When a robot's face is more realistic, people expect it to behave like an actual human being. However, as the sample size of this study was small and all visitors were Asian, the researcher cannot generalize the results to the wider population.

Current robot receptionist has limited interaction ability. Hotel practitioners could learn about hotel guests' behavior and expectation towards android robots to enhance satisfaction and reduce disappointment.

Prior robot research has used questionnaires to investigate perceptions and usage intention, but this study collected on-site data and directly observed people's attitude toward robot staff in an actual business environment.

The purpose of this paper is to perform a comparative analysis of the delay associated in running two real-time machine learning-based applications, namely, a video quality assessment (VQA) and a phishing detection application by using the edge, fog and cloud computing paradigms.

The VQA algorithm was developed using Android Studio and run on a mobile phone for the edge paradigm. For the fog paradigm, it was hosted on a Java server and for the cloud paradigm on the IBM and Firebase clouds. The phishing detection algorithm was embedded into a browser extension for the edge paradigm. For the fog paradigm, it was hosted on a Node.js server and for the cloud paradigm on Firebase.

For the VQA algorithm, the edge paradigm had the highest response time while the cloud paradigm had the lowest, as the algorithm was computationally intensive. For the phishing detection algorithm, the edge paradigm had the lowest response time, and the cloud paradigm had the highest, as the algorithm had a low computational complexity. Since the determining factor for the response time was the latency, the edge paradigm provided the smallest delay as all processing were local.

The main limitation of this work is that the experiments were performed on a small scale due to time and budget constraints.

A detailed analysis with real applications has been provided to show how the complexity of an application can determine the best computing paradigm on which it can be deployed.

In a technological era driven by coding, programming and artificial intelligence (AI), there is more need than ever to develop computing skills and knowledge for non-specialist students. Nonetheless, the literature on computer science teaching methods of non-scientific majors is not as comprehensive as that of scientific ones.

Pedagogically, the authors designed and implemented prototyping from John Dewey's pragmatic epistemological lens. Using a mixed methods approach, the authors tested the effectiveness and efficiency of this approach within the same course over four semesters across four academic years.

As an epistemological pedagogic device, prototyping facilitated learning by doing and experimenting and stimulated graduate students' self-directed learning, engagement and their overall ownership of the learning and teaching process, changing their role from being merely passive recipients of “strange, awkward and unfamiliar” knowledge to active constructors of “relevant and exciting” content knowledge. Such a change was reflected in the significant progress students made, driven by their commitment, motivation and enthusiasm, irrespective of their prior knowledge and age (Generations X, Y and Z). Prototyping also served as an avenue for a “Deweyian Reflection”, where graduate students, after internalizing the acquired computing skills and knowledge, started transferring such skills and knowledge to their professions (journalism and public relations (PR)) and daily practices.

Findings from this study will add to the literature review on this subject matter and will inform future case studies in computer science education for graduate students from non-scientific backgrounds.

This paper reveals that learning by doing/experimenting needs to be accompanied by in-depth reflection to enable students to transfer the acquired knowledge and skills to other settings and contexts beyond that of the lesson, task, or project in hand.

There is little research published on introductory programming courses offered to non-specialized students (i.e. students from non-scientific backgrounds). This study contributes to the body of research on how to effectively engage these students in programming courses informed by John Dewey's pragmatic lens/epistemological lens.

Mobile travel apps (MTA) smart features were identified based on recent travel application (app) trends and a literature review of MTA smart features. Subsequently, the MTA features that could be prioritised to increase user interest in MTA were determined. The MTA smart feature development challenges that should be mitigated were also identified.

The app identification and selection were based on the one-stop solution characteristics containing the common function of travel apps and eight MTA smart features. A total of 193 Apple apps and 250 Google apps were identified, where 36 apps that met the inclusion and exclusion criteria based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart were selected for evaluation.

The high user ratings for apps from both app stores revealed the acceptance of smart technology in the tourism industry. Geolocation tracking services, travel itinerary generators, and real-time personalisation and recommendation were the three major features available in the included MTA. The challenges of MTA with smart features were highlighted from the tourism organisation, app developer and user perspectives.

The findings can guide tourism organisations and app developers on the smart features that MTA should offer for user engagement. Technological organisations could optimise their technology stack by considering the identified smart features. The findings are valuable for scholars in terms of MTA aesthetics and usability to gain acceptability. The development challenges included significant investment in technology, location accuracy and privacy concerns when implementing MTA smart features.

The previous literature mainly focused on evaluating app quality, assessing app functionality, and user ratings using the Mobile Application Rating Scale, and scoping reviews of MTA articles. Contrastingly, this study is among the first in which MTA smart features were examined from a developer-centric perspective. Moreover, it is suggested that MTA includes integrated smart features for better tourism services and market penetration in the tourism industry.

Our prior work has identified a trade-off that new entrants face in obtaining favorable market reception, whereby initial entrants suffer from a deficit of legitimacy whereas later entrants suffer from a deficit of authenticity. This research has also proposed that a single mechanism is responsible for this trade-off: the tendency for customers and other stakeholders to assess the entrant's claim to originality based on the visible work that it has done to legitimate the new product or organizational form. This chapter extends and deepens our understanding of such “legitimation work” by showing how it can illuminate cases that seem in the first instance to defy this trade-off. In particular, we focus on two “off-diagonal” cases: (a) when, as in the case of “patent trolls” and fraudulent innovators, early entrants are viewed as inauthentic despite having a credible claim to originality; (b) when late entrants, as in the case of Dell Computers, mechanical watches and baseball ballparks, are viewed as authentic despite obviously not being the originators. We clarify how each off-diagonal case represents an ‘exception that proves the rule’ whereby audiences attribute authenticity on the basis of legitimation work rather than on the order of entry per se. The last case also leads to an opportunity to clarify why “cultural appropriation” can sometimes project authenticity and sometimes inauthenticity, why audiences bother to make inferences about a producer's authenticity on the basis of visible legitimation work, and why legitimacy is a universal goal of early movers whereas authenticity varies in its importance.

In the last few decades, the growth in management institutions in India has become significant. The Open and Distance Learning (ODL) institutions also have started offering management programmes at various levels. In the ODL scenario, the learning path has been shifting from the traditional Self-Learning Material (SLM) -based model to technology-mediated platform. The digital divide in India is also a widely discussed area. In this context, a need has been felt to understand the implications for educators, more specifically, for the programmes offered through technology-enabled ODL mode.

This study uses triangulation method covering literature review, personal interview and survey. Primary data have been collected through structured questionnaire in the Google Form administered on the learners of UG and PG progammes of management in Krishna Kanta Handiqui State Open University (KKHSOU), India. The sample size is 101, and the sampling frame is within Assam, a province of India. Select interviews (15 nos.) were also conducted with a cross section of learners to capture the emerging shift in the learning path and the limiting factors of digital divide.

Learners possess multiple digital devices for e-learning (41.8% uses laptop and 88.8% uses android phone). Interaction in WhatsApp and Telegram groups are mostly related with evaluation and course administration, rather than content and academic discussion. eSLMs are widely used. Though promoted, video lectures are not widely used. Some of the problems faced by the learners are low bandwidth, high cost of data subscription etc. Learners are not constrained by digital device, and they are engaged in positive communication with stake holders in digital platform.

This study will help in understanding the technology-enabled learning for management education in ODL mode in India. As a wide majority of the learners (88%) are dependent on small screen; print SLM and eSLM on a larger screen can provide augmented learning in case of complex topics like analysis of financial statements, project scheduling etc. Though the COVID-19 pandemic forced a shift in learning path, the transition is not full. The digitally constrained learners still look for solutions to complex learning problems mainly through print SLM and counselling. The talent of the students cannot be facilitated in WhatsApp and Telegram e-mentoring groups, like the way it could be done in learning management system (LMS)-mediated platforms.