Evaluation of Hand Washing Procedure Using Vision-Based Frame Level and Spatio-Temporal Level Data Models

Hand hygiene is obligatory for all healthcare workers and vital for patient care. During COVID-19, adequate hand washing was among recommended measures for preventing virus transmission. A general hand-washing procedure consisting several steps is recommended by World Health Organization for ensuring hand hygiene. This process can vary from person to person and human supervision for inspection would be impractical. In this study, we propose computer vision-based new methods using 12 different neural network models and 4 different data models (RGB, Point Cloud, Point Gesture Map, Projection) for the classification of 8 universally accepted hand-washing steps. These methods can also perform well under situations where the order of steps is not observed or the duration of steps are varied. Using a custom dataset, we achieved 100% accuracy with one of the models, and 94.23% average accuracy for all models. We also developed a real-time robust data acquisition technique where RGB and depth streams from Kinect 2.0 camera were utilized. Results showed that with the proposed methods and data models, efficient hand hygiene control is possible.

Problems of Regulation and Prospective Development of E-commerce Systems in the Post-coronavirus Era

The article examines the application of e-commerce systems and technologies that have a positive impact on the development of the economy of the post-coronavirus period and the formation of appropriate technical and technological infrastructure for it, as well as promising features and directions of e-commerce. The physical and virtual opportunities created by e-commerce technologies for buyers and sellers are explained. The advantages of e-commerce in the international economic space have been identified. The functions of e-business models in accordance with the commercial stages of enterprises are explained. It was noted that the development of ICT has accelerated the process of transition from traditional commerce to e-commerce, led to the emergence of new global trends in e-commerce. These innovations have raised the issue of the application of modern ICT in the development of e-commerce on the platform of the 4.0 Industrial Revolution. Taking into account these factors, the presented article discusses the application of modern technologies in e-commerce systems, such as 3D modeling, the Internet of Things, artificial intelligence, big data. Features of application and regulation mechanisms of E-commerce systems in real economic sectors, which have a direct stimulating effect on economic growth in Azerbaijan, have been studied. Recommendations were given for the modernization and use of e-commerce systems with the application of the latest ICT technologies.The purpose of the research. The main goal of the scientific research carried out in the article was to develop the scientific-methodological basis for the regulation of the application of e-commerce systems and the study of perspective development problems in the so-called post-coronavirus period after 2020. In the article, attention was paid to the problems of regulation of the application of e-commerce systems and the development of recommendations on increasing the efficiency of prospective development directions.Taking into account the characteristics of the relevant electronic business models, applying them in accordance with the commercial stages of the enterprises' activities and obtaining effective results were among the main goals. Attempts have been made to implement e-commerce systems based on the developing technologies of the Industry 4.0 platform. An attempt was made to solve the issue of using modern ICT in the development of trade processes, which corresponds to the 4.0 Industrial revolution platform. The main stages of application of modern technologies such as 3D modeling, the Internet of Things, artificial intelligence, and Big Data in electronic commerce systems are described.The following are included among the goals of the conducted scientific research: investigation of the application features and regulation mechanisms of e-commerce systems that have a stimulating effect on the economic development of Azerbaijan in real economic sectors, development of recommendations on increasing the efficiency of electronic commerce systems using modern ICT technologies, etc.Research methods used. In the post-coronavirus period, the following research methods were used in the study of the problems of regulation of the application of e-commerce systems and prospective development directions and in the development of their scientific and methodological bases: a systematic analysis, correlation, and regression analysis, mathematical and econometric modeling methods, expert evaluation method, measurement theory, algorithmization, ICT tools, and technologies, etc.Achievements of the author. Achievements of the author. In the so-called post-coronavirus period after 2020, a special approach was taken to the application of e-commerce systems and technologies, which have a positive impact on the development of the economy as an innovative element, and to the study of its prospective development features and directions. By providing scientific support to ensure the effective formation of the digital economy and its sustainability, the researcher offered relev nt recommendations to achieve the solution to some of the goals set before the country. It should be noted that the development of e-commerce systems based on technologies relevant to the Industry 4.0 platform can give a serious impetus to the development of the sustainability of the digital economy.Due to the fact that e-commerce technologies create new additional physical and virtual opportunities for buyers and sellers, the scientific-methodological approaches proposed by the author develop them as a special tool for ensuring the stability of both e-commerce systems and the digital economy in general. The proposals presented will lead to more effective results for the economy to be more cyber resilient through the application of e-commerce systems in the so-called post-coronavirus era. The researcher showed that the effective application of electronic business models in the activities of enterprises can help to achieve effective results. In the development of e-commerce, solutions to the issues of application of 4.0 Industrial technologies such as 3D modeling, Internet of Things, artificial intelligence, and Big Data can be considered as a contribution to the investigation of solutions to existing problems in economic development. For this reason, the means and mechanisms proposed by the author for solving the problems of regulation of the application of e-commerce systems in the post-coronavirus era can be considered one of the main ways to ensure the stability and development of the digital economy.

Thoracic Pedicle Screw Placement Utilizing Hands-On Training Session on Three-Dimensional Models.

The utilization of three-dimensional (3D) models has been an important element of medical education. We demonstrate a three-dimensionally-printed (3DP) thoracic spine model for use in the teaching of freehand pedicle screw placement. Neurosurgical residents with varying years of experience practiced screw placement on these models. Residents were timed, and models were evaluated for medial and lateral breaches. Overall, this technical report describes the utility of 3D spine models in the training of thoracic pedicle screw placement. The tactile feedback from the 3D models was designed to represent both cortical and cancellous bones.

Application of Deep Learning in the Deployment of an Industrial SCARA Machine for Real-Time Object Detection

In the spirit of innovation, the development of an intelligent robot system incorporating the basic principles of Industry 4.0 was one of the objectives of this study. With this aim, an experimental application of an industrial robot unit in its own isolated environment was carried out using neural networks. In this paper, we describe one possible application of deep learning in an Industry 4.0 environment for robotic units. The image datasets required for learning were generated using data synthesis. There are significant benefits to the incorporation of this technology, as old machines can be smartened and made more efficient without additional costs. As an area of application, we present the preparation of a robot unit which at the time it was originally produced and commissioned was not capable of using machine learning technology for object-detection purposes. The results for different scenarios are presented and an overview of similar research topics on neural networks is provided. A method for synthetizing datasets of any size is described in detail. Specifically, the working domain of a given robot unit, a possible solution to compatibility issues and the learning of neural networks from 3D CAD models with rendered images will be discussed.

Energy Consumption Prediction for Fused Deposition Modelling 3D Printing Using Machine Learning

Additive manufacturing (AM) technologies are growing more and more in the manufacturing industry;the increase in world energy consumption encourages the quantification and optimization of energy use in additive manufacturing processes. Orientation of the part to be printed is very important for reducing energy consumption. Our work focuses on defining the most appropriate direction for minimizing energy consumption. In this paper, twelve machine learning (ML) algorithms are applied to model energy consumption in the fused deposition modelling (FDM) process using a database of the FDM 3D printing of isovolumetric mechanical components. The adequate predicted model was selected using four performance criteria: mean absolute error (MAE), root mean squared error (RMSE), R-squared (R2), and explained variance score (EVS). It was clearly seen that the Gaussian process regressor (GPR) model estimates the energy consumption in FDM process with high accuracy: R2 > 99%, EVS > 99%, MAE < 3.89, and RMSE < 5.8.

DESIGN AND NUMERICAL ANALYSIS OF FACE MASK POLYMER SHIELD AGAINST INFECTIOUS DISEASES

Viruses that cause infections spread very quickly and has a fatal risk to people with chronic diseases. Since the virus vaccine and the drugs to be used in treatment are not fully developed, alternative ways to protect from the virus are being investigated. The Covid-19 virus has been recognized by the World Health Organization (WHO) as a pandemic. In this study, the effect of face mask shield against Covid-19 and other infections were investigated using finite element analysis (FEA). Three-dimensional model of the conventional face mask, equipment and shield was performed with the SolidWorks software. Computer-aided simulations were performed using AnsysWorkbench explicit dynamics module. The loading, boundary conditions and material properties were defined in the AnsysWorkbench. The effects of droplets formed because of cough or sneezing on the human model with mask and shield were analyzed. It has been confirmed from the analyzes that both the mask and the shield are effective against the virus.

Design and Implementation of OPC UA-Based VR/AR Collaboration Model Using CPS Server for VR Engineering Process

In order to cope with the changing era of the innovative management paradigm of the manufacturing industry, it is necessary to advance the construction of smart factories in the domestic manufacturing industry, and in particular, the 3D design and manufacturing content sector is highly growthable. In particular, the core technologies that enable digital transformation VR (Virtual Reality)/AR (Augmented Reality) technologies have developed rapidly in recent years, but have not yet achieved any particular results in industrial engineering. In the manufacturing industry, digital threads and collaboration systems are needed to reduce design costs that change over and over again due to the inability to respond to various problems and demands that should be considered when designing products. To this end, we propose a VR/AR collaboration model that increases efficiency of manufacturing environments such as inspection and maintenance as well as design simultaneously with participants through 3D rendering virtualization of facilities or robot 3D designs in VR/AR. We implemented converting programs and middleware CPS (Cyber Physical System) servers that convert to BOM (Bill of Material)-based 3D graphics models and CPS models to test the accuracy of data and optimization of 3D modeling and study their performance through robotic arms in real factories.

Virtual field trips utilizing virtual outcrop: construction, delivery and implications for the future

The advent of photorealistic, 3D computer models of cliff sections (virtual outcrops) has improved the immersive nature of virtual geological field trips. As the COVID-19 pandemic led to widespread national and international travel restrictions, virtual field trips (VFTs) became practical and essential substitutes for traditional field trips and accelerated the development of VFTs based on virtual outcrop data. This contribution explores two such VFTs delivered to a masters level Integrated Petroleum Geoscience course at the University of Aberdeen. These VFTs are based on traditional field trips that are normally run to the Spanish Pyrenees and Utah (USA). The paper summarizes the delivery mechanism for VFTs based on virtual outcrops and examines student perception, gauged primarily through questionnaires and learning outcomes. The VFTs were run in LIME, a software specifically designed for the interpretation of 3D models and the delivery of VFTs. Overall, the student perception was very positive and comparable to satisfaction with the conventional trips. Staff feedback and student assessments suggest that the learning outcomes were satisfied and highlight the value of this method of teaching for students who are unable to attend the field trip and as an addition for those who can.

Discretization Fractional-Order Biological Model with Optimal Harvesting

In this paper, a discretization of a three-dimensional fractional-order prey-predator model has been investigated with Holling type III functional response. All its fixed points are determined;also, their local stability is investigated. We extend the discretized system to an optimal control problem to get the optimal harvesting amount. For this, the discrete-time Pontryagin’s maximum principle is used. Finally, numerical simulation results are given to confirm the theoretical outputs as well as to solve the optimality problem.

Ventilation‐induced epithelial injury drives biological onset of lung trauma in vitro and is mitigated with prophylactic anti‐inflammatory therapeutics

Mortality rates among patients suffering from acute respiratory failure remain perplexingly high despite the maintenance of blood oxygen homeostasis during ventilatory support. The biotrauma hypothesis advocates that mechanical forces from invasive ventilation trigger immunological mediators that spread systemically. Yet, how these forces elicit an immune response remains unclear. Here, a biomimetic in vitro three‐dimensional (3D) upper airways model allows to recapitulate lung injury and immune responses induced during invasive mechanical ventilation in neonates. Under such ventilatory support, flow‐induced stresses injure the bronchial epithelium of the intubated airways model and directly modulate epithelial cell inflammatory cytokine secretion associated with pulmonary injury. Fluorescence microscopy and biochemical analyses reveal site‐specific susceptibility to epithelial erosion in airways from jet‐flow impaction and are linked to increases in cell apoptosis and modulated secretions of cytokines IL‐6, ‐8, and ‐10. In an effort to mitigate the onset of biotrauma, prophylactic pharmacological treatment with Montelukast, a leukotriene receptor antagonist, reduces apoptosis and pro‐inflammatory signaling during invasive ventilation of the in vitro model. This 3D airway platform points to a previously overlooked origin of lung injury and showcases translational opportunities in preclinical pulmonary research toward protective therapies and improved protocols for patient care.

Construction Management Supported by BIM and a Business Intelligence Tool

The construction sector generates large amounts of heterogeneous and dynamic data characterized by their fragmentation throughout the life cycle of a project. Immediate and accurate access to that data is fundamental to the management, decision-making and analysis by construction owners, supervisors, managers, and technicians involved in the different phases of the project life cycle. However, since construction project data are diverse, dispersed, uncorrelated, and difficult to visualize, a reliable basis for decision-making can rarely be established by the management team. Aiming to bridge this gap, a methodology for data management during building construction by means of Data with BIM and Business Intelligence (BI) analysis tools was developed in this study. This methodology works by extracting data from 3D parametric model and integrating it with a BI tool, through which data are visualized and interrelated with the same database, the BIM model. To demonstrate the applicability of the methodology, a study case was carried out. It was shown that this methodology provides a collaborative platform for accurate data analysis to the construction management and supervision teams, allowing project stakeholders to access and update data in real-time, in permanent linkage with the BIM model. Additionally, improving the reliability of the decision-making process and ensuring project deliverability, the developed methodology contributes to a more sustainable management process by decreasing errors and resource consumption, including energy. Therefore, the main goal of this study is to present a methodology for data analysis with BIM models integrated with BI for sustainable construction management.

Novel Drone Design Using an Optimization Software with 3D Model, Simulation, and Fabrication in Drone Systems Research

This paper presents the design of a small size Unmanned Aerial Vehicle (UAV) using the 3DEXPERIENCE software. The process of designing the frame parts involves many methods to ensure the parts can meet the requirements while conforming to safety and industry standards. The design steps start with the selection of materials that can be used for the drone, which are polylactic acid (PLA), acrylonitrile styrene acrylate (ASA), and acrylonitrile butadiene styrene (ABS). The drone frame consists of four main parts, which are the center top cover (50 g), the side top cover (10 g), the middle cover (30 g), and the drone’s arm (80 g). A simulation was carried out to determine the stress, displacement, and weight of the drone’s parts. Additionally, a trade-off study was conducted to finalize the shapes of the parts and the various inputs based on their priorities. The outcome of this new design can be represented in design concepts, which involve the use of the snap hook function to assemble two body parts together, namely the middle cover and the center top cover, without the need of an additional fastener.

SARS-CoV-2 Dynamics in the Mucus Layer of the Human Upper Respiratory Tract Based on Host–Cell Dynamics

A thorough understanding of the inhalation dynamics of infectious aerosols indoors and infection dynamics within the host by inhaled viruses such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) plays an important role in the assessment and control of infection risks indoors. Here, by combining computational fluid–particle dynamics (CFPD) and host–cell dynamics (HCD), SARS-CoV-2 infection dynamics in the mucus layer of the human upper airway were studied. To reproduce the diffusive and convective transport of the virus in the nasal cavity–nasopharynx by mucociliary motion, a three-dimensional (3D)-shell model with a mucus layer was developed. The initial virus concentrations for HCD calculation were estimated based on the deposition distribution of droplets with representative sizes analyzed by CFPD. To develop a new HCD model, the target-cell-limited model was integrated with the convection–diffusion equation. Additionally, the sensitivity of the infection rate β to the infection dynamics was systematically investigated. The results showed that the time series of SARS-CoV-2 concentration in the mucus layer strongly depended on diffusion, convection, and β. Although the SARS-CoV-2 dynamics obtained here have not been verified by corresponding clinical data, they can preliminarily reveal its transmission mode in the upper airway, which will contribute to the prevention and treatment of coronavirus disease 2019.

A remote field course implementing high-resolution topography acquisition with geomorphic applications

Here we describe the curriculum and outcomes from a data-intensive geomorphic analysis course, “Geoscience Field Issues Using High-Resolution Topography to Understand Earth Surface Processes”, which pivoted to virtual in 2020 due to the COVID-19 pandemic. The curriculum covers technologies for manual and remotely sensed topographic data methods, including (1) Global Positioning Systems and Global Navigation Satellite System (GPS/GNSS) surveys, (2) Structure from Motion (SfM) photogrammetry, and (3) ground-based (terrestrial laser scanning, TLS) and airborne lidar. Course content focuses on Earth-surface process applications but could be adapted for other geoscience disciplines. Many other field courses were canceled in summer 2020, so this course served a broad range of undergraduate and graduate students in need of a field course as part of degree or research requirements. Resulting curricular materials are available freely within the National Association of Geoscience Teachers' (NAGT's) “Teaching with Online Field Experiences” collection. The authors pre-collected GNSS data, uncrewed-aerial-system-derived (UAS-derived) photographs, and ground-based lidar, which students then used in course assignments. The course was run over a 2-week period and had synchronous and asynchronous components. Students created SfM models that incorporated post-processed GNSS ground control points and created derivative SfM and TLS products, including classified point clouds and digital elevation models (DEMs). Students were successfully able to (1) evaluate the appropriateness of a given survey/data approach given site conditions, (2) assess pros and cons of different data collection and post-processing methods in light of field and time constraints and limitations of each, (3) conduct error and geomorphic change analysis, and (4) propose or implement a protocol to answer a geomorphic question. Overall, our analysis indicates the course had a successful implementation that met student needs as well as course-specific and NAGT learning outcomes, with 91 % of students receiving an A, B, or C grade. Unexpected outcomes of the course included student self-reflection and redirection and classmate support through a daily reflection and discussion post. Challenges included long hours in front of a computer, computing limitations, and burnout because of the condensed nature of the course. Recommended implementation improvements include spreading the course out over a longer period of time or adopting only part of the course and providing appropriate computers and technical assistance. This paper and published curricular materials should serve as an implementation and assessment guide for the geoscience community to use in virtual or in-person high-resolution topographic data courses that can be adapted for individual labs or for an entire field or data course.

Field Work’s Optimization for the Digital Capture of Large University Campuses, Combining Various Techniques of Massive Point Capture

The aim of the study is to obtain fast digitalization of large urban settings. The data of two university campuses in two cities in northern Spain was captured. Challenges were imposed by the lockdown situation caused by the COVID-19 pandemic, which limited mobility and affected the field work for data readings. The idea was to significantly reduce time spent in the field, using a number of resources, and increasing efficiency as economically as possible. The research design is based on the Design Science Research (DSR) concept as a methodological approach to design the solutions generated by means of 3D models. The digitalization of the campuses is based on the analysis, evolution and optimization of LiDAR ALS points clouds captured by government bodies, which are open access and free. Additional TLS capture techniques were used to complement the clouds, with the study of support of UAV-assisted automated photogrammetric techniques. The results show that with points clouds overlapped with 360 images, produced with a combination of resources and techniques, it was possible to reduce the on-site working time by more than two thirds.

Drivers and barriers of virtual reality adoption in UK AEC industry

Purpose>Virtual reality (VR) offers unique features of a three-dimensional (3D) model during early design stages in the virtual environment with immersive functions. Although the potential of VR is to increase the effectiveness and productivity of the project phases from initial concept design to detailed design preparation. VR adoption in the United Kingdom (UK) Architectural Engineering and Construction (AEC) sector is slow compared to other sectors. This research focuses on ascertaining the drivers and barriers of VR in construction projects in the UK.Design/methodology/approach>The study adopts an online survey design. It uses Bristol Online Survey (BOS) to create a structured questionnaire that is used to assess UK construction professionals using a convenience sampling technique. Therefore, researcher uses descriptive and inferential technique for data analysis and presentation based on Statistical Package for Social Sciences (SPSS) to analyze the questionnaire.Findings>The research findings revealed the most significant barriers to VR adoption in UK construction industry were lack of skills/expertise and cultural change. Hence, the main drivers of VR adoption as rated by the professionals in the UK construction industry are improved safety, improved quality and improved productivity.Practical implications>The identification and assessment of the drivers and barriers to VR adoption could advance VR adoption among construction professionals and other stakeholders of the UK AEC sector. This could also be extended to developing countries, given the status of VR as being in the developing stage.Originality/value>This study provides valuable insights to construction professionals and stakeholders to plan actions that could enhance the drivers and mitigate the barriers of VR. This study's main contribution is to group and classify various drivers and barriers into easily understood categories, in order to potentiate the drivers and reduce the barriers effectively. The groupings could be used as benchmarks in similar studies in developing countries.

V3Geo: a cloud-based repository for virtual 3D models in geoscience

V3Geo is a cloud-based repository for publishing virtual 3D models in geoscience. The system allows storage, search and visualisation of mesh models typically acquired using techniques such as photogrammetry and laser scanning. The platform has been developed to handle models at the range of scales typically used by geoscientists from microscopic, hand samples and fossils through to outcrop sections or terrain covering metres to tens of kilometres. The cloud storage system serves the models to a purpose-built 3D web viewer. Models are tiled to ensure efficient streaming over the Internet. The web viewer allows 3D models to be interactively explored without the need for specialist software to be installed. A measurement tool enables users to gauge simple dimensions, such as widths, thicknesses, and fault throws. V3Geo allows very large models comprising multiple sections and is designed to include additional interpretation layers. The specific focus on geoscience data is supported by defined metadata and a classification schema. Public and private storage is available, and public models are assigned Creative Commons licenses to govern content usage. This paper presents V3Geo as a sustainable resource for the geoscience community, including the motivation and main characteristics and features. Example usage scenarios are highlighted: from undergraduate geology teaching, supporting virtual geoscience education and preparing virtual field trips based on V3Geo models. Finally, best practice guidelines for preparing 3D model contributions for publication on V3Geo are included as the Appendix.

Digital 3D Technologies for Humanities Research and Education: An Overview

Digital 3D modelling and visualization technologies have been widely applied to support research in the humanities since the 1980s. Since technological backgrounds, project opportunities, and methodological considerations for application are widely discussed in the literature, one of the next tasks is to validate these techniques within a wider scientific community and establish them in the culture of academic disciplines. This article resulted from a postdoctoral thesis and is intended to provide a comprehensive overview on the use of digital 3D technologies in the humanities with regards to (1) scenarios, user communities, and epistemic challenges;(2) technologies, UX design, and workflows;and (3) framework conditions as legislation, infrastructures, and teaching programs. Although the results are of relevance for 3D modelling in all humanities disciplines, the focus of our studies is on modelling of past architectural and cultural landscape objects via interpretative 3D reconstruction methods.

Guest editorial

“Sustainable and resilient extractive and circular economies under uncertainty” Increased uncertainty in the global economy and business environment characterised by rapid demand fluctuations and technological breakthroughs, digitization and global disruptions, creates the need for systemic transformation of extractive and construction industries. Recent global supply disruptions, which will possibly become a norm in the future, calls for novel managerial approaches, policy and regulatory frameworks, decision-support tools and technological innovations that collectively enable a critical step towards sustainable and resilient extractive and construction industries and enhance value creation for all industry stakeholders. Zhao et al. describe the development of the 3D model for ROM stockpiles, that helps to improve product quality control, which ultimately helps to meet sustainability goals and ensure more resilient operations of the mining enterprise.

Advanced Technologies Used in Digitizing the Cultural Heritage of Northwestern Colchis: The Experience of the Markul Expedition

The article presents the experience of the Institute of Archeology of the Russian Academy of Science’s Markul Expedition, which utilized digital technologies for the study, preservation, and popularization of cultural heritage. The objective of the Markul Expedition was to obtain a complete picture of the historical and cultural landscape of Northwestern Colchis in antiquity by applying two key digital technologies: geographic information systems (GIS) and photogrammetry. The results obtained from the latter were used both independently and were integrated into GIS as separate layers (orthophotomaps, digital terrain models) or as hyperlinks to objects (3D models, videos, plans, sections, etc.). The objects investigated by the expedition are very diverse both in size and in terms of shooting conditions. Accordingly, each category of archaeological site required an individual approach, and a separate methodology and equipment. The final visualization angles differ to a fair extent from the original samples even though photogrammetry provides more accurate results than manual measurements. There are several reasons for this, including the vegetation, which is a dominant factor in the Caucasus subtropical area and led to partial visual distortions of the photographed objects. For this reason, the final projections of architectural forms required corrections and some hand drawing. In this process, new aspects appeared in the final result, resulting from the archaeologist and artist’s differing views of the objects. Our experience of using modern remote sensing technologies is also presented in the article.