Physical Counterpart Research Articles

Events-within-events and the online reproduction of their emotional dimensions: a case study of the Dubai 2020 expo

ABSTRACT Large-scale events are typically described as single, monolithic entities. In this paper, we argue that large-scale events actually comprise multiple sub-events or events-within-events and their online representations. We explore the theoretical implications of this shift in perspective for the study of audiences and event engagement through the lens of communication power theory. We also discuss the practical implications for event management. The paper uses the Expo 2020 Dubai as its case study to illustrate the richness of sub-events within large-scale events and to consider the role of digital communications. The discussion highlights the ways in which physical events' digital twins aim to solicit similar emotional responses by audiences as their physical counterparts. By adding complexity to our understanding of these sorts of events, we argue that large-scale events comprise multiple sub-events, taking place both face-to-face and online, that make large-scale events richer and more multifaceted than they are typically seen to be. Our research shows that event organisers will need to go beyond the creation of virtual event replicas if they want to take full advantage of the affordances of digital communication. The paper concludes by calling for more critical and interdisciplinary research on large-scale events and their online representations.

A Cyber–Physical System Based on Digital Twin and 3D SCADA for Real-Time Monitoring of Olive Oil Mills

Cyber–physical systems involve the creation, continuous updating, and monitoring of virtual replicas that closely mirror their physical counterparts. These virtual representations are fed by real-time data from sensors, Internet of Things (IoT) devices, and other sources, enabling a dynamic and accurate reflection of the state of the physical system. This emphasizes the importance of data synchronization, visualization, and interaction within virtual environments as a means to improve decision-making, training, maintenance, and overall operational efficiency. This paper presents a novel approach to a cyber–physical system that integrates virtual reality (VR)-based digital twins and 3D SCADA in the context of Industry 4.0 for the monitoring and optimization of an olive mill. The methodology leverages virtual reality to create a digital twin that enables immersive data-driven simulations for olive mill monitoring. The proposed CPS takes data from the physical environment through the existing sensors and measurement elements in the olive mill, concentrates them, and exposes them to the virtual environment through the Open Platform Communication United Architecture (OPC-UA) protocol, thus establishing bidirectional and real-time communication. Furthermore, in the proposed virtual environment, the digital twin is interfaced with the 3D SCADA system, allowing it to create virtual models of the process. This innovative approach has the potential to revolutionize the olive oil industry by improving operational efficiency, product quality, and sustainability while optimizing maintenance practices.

Exploring the Potential of a Novel Iodine-Based Material as an Alternative Contrast Agent in X-ray Imaging Studies.

Contrast-enhanced mammography is one of the new emerging imaging techniques used for detecting breast tissue lesions. Optimization of imaging protocols and reconstruction techniques for this modality, however, requires the involvement of physical phantoms. Their development is related to the use of radiocontrast agents. This study assesses the X-ray properties of a novel contrast material in clinical settings. This material is intended for experimental use with physical phantoms, offering an alternative to commonly available radiocontrast agents. The water-soluble sodium salt of the newly synthesized diiodine-substituted natural eudesmic acid, Sodium 2,6-DiIodo-3,4,5-TriMethoxyBenzoate [NaDITMB], has been investigated with respect to one of the most commonly applied radiocontrast medium in medical practice-Omnipaque®. For this purpose, simulation and experimental studies were carried out with a computational phantom and a physical counterpart, respectively. Synthetic and experimental X-ray images were subsequently produced under varying beam kilovoltage peaks (kVps), and the proposed contrast material was evaluated. Simulation results revealed equivalent absorptions between the two simulated radiocontrast agents. Experimental findings supported these simulations, showing a maximum deviation of 3.7% between the image gray values of contrast materials for NaDITMB and Omnipaque solutions for a 46 kVp X-ray beam. Higher kVp X-ray beams show even smaller deviations in the mean grey values of the imaged contrast agents, with the NaDITMB solution demonstrating less than a 2% deviation compared to Omnipaque. The proposed contrast agent is a suitable candidate for use in experimental work related to contrast-enhanced imaging by utilizing phantoms. It boasts the advantages of easy synthesis and is recognized for its safety, ensuring a secure environment for both the experimenter and the environment.

Digital Twin Meets Knowledge Graph for Intelligent Manufacturing Processes.

In the highly competitive field of material manufacturing, stakeholders strive for the increased quality of the end products, reduced cost of operation, and the timely completion of their business processes. Digital twin (DT) technologies are considered major enablers that can be deployed to assist the development and effective provision of manufacturing processes. Additionally, knowledge graphs (KG) have emerged as efficient tools in the industrial domain and are able to efficiently represent data from various disciplines in a structured manner while also supporting advanced analytics. This paper proposes a solution that integrates a KG and DTs. Through this synergy, we aimed to develop highly autonomous and flexible DTs that utilize the semantic knowledge stored in the KG to better support advanced functionalities. The developed KG stores information about materials and their properties and details about the processes in which they are involved, following a flexible schema that is not domain specific. The DT comprises smaller Virtual Objects (VOs), each one acting as an abstraction of a single step of the Industrial Business Process (IBP), providing the necessary functionalities that simulate the corresponding real-world process. By executing appropriate queries to the KG, the DT can orchestrate the operation of the VOs and their physical counterparts and configure their parameters accordingly, in this way increasing its self-awareness. In this article, the architecture of such a solution is presented and its application in a real laser glass bending process is showcased.

Nomina loci с наставка -ниц(а) в българския език (продуктивна в миналото и днес)

Place names (nomina loci) in Bulgarian represent a very interesting research subject both in a diachronic and synchronic perspective. The word-formation type of the nouns derived by attaching the ending -ниц(а) or the extended suffixes -арниц(а), -ачниц(а), -илниц(а), -джийниц(а)/-чийниц(а) to designate the places where the activity or occupation denoted by the motivating verb is performed or exercised (or the places/homes where the entities denoted by the motivating noun are stored), is represented by a significant number of substantives. This group of derivatives clearly reflects the dynamics of the language as observed in the transition of words from the active to the passive lexical layer, the revival of lexical items belonging to the passive lexis, the emergence of neologisms following the established derivational patterns, the development of neosemantics, the proprialisation resulting in the formation of firmonyms. A recent phenomenon attested in the language has been the incorporation of nomina loci into the internet space: without actually existing, these places perform similar functions to their physical counterparts. The suffixes under discussion are used in the derivation of both simple and compound substantives. The empirical material confirms the productivity of the ending -ниц(а) in contemporary Bulgarian.

State Observer-Based Conditioned Reverse-Path Method for Nonlinear System Identification

In light of the complex behavior of vibrating structures, their reliable modeling plays a crucial role in the analysis and system design for vibration control. In this paper, the reverse-path (RP) method is revisited, further developed, and applied to modeling a nonlinear system, particularly with respect to the identification of the frequency response function for a nominal underlying linear system and the determination of the structural nonlinearities. The present approach aims to overcome the requirement for measuring all nonlinear system states all the time during operation. Especially in large-scale systems, this might be a tedious task and often practically infeasible since it would require having individual sensors assigned for each state involved in the design process. In addition, the proper placement and simultaneous operation of a large number of transducers would represent further difficulty. To overcome those issues, we have proposed state estimation in light of the observability criteria, which significantly reduces the number of required sensor elements. To this end, relying on the optimal sensor placement problem, the state estimation process reduces to the solution of Kalman filtering. On this ground, the problem of nonlinear system identification for large-scale systems can be addressed using the observer-based conditioned RP method (OBCRP) proposed in this paper. In contrast to the classical RP method, the current one can potentially handle local and distributed nonlinearities. Moreover, in addition to the state estimation and in comparison to the orthogonal RP method, a new frequency-dependent weighting is introduced in this paper, which results in superior nonlinear system identification performances. Implementation of the method is demonstrated on a multi-degree-of-freedom discretized lumped mass system, representing a substitute model of a physical counterpart used for the identification of the model parameters.

Cost-effective Robotic Arm Simulation and System Verification

In recent years, the utilization of virtual environments in industry 4.0 has witnessed significant growth, particularly in the design, implementation, and management of robotic systems. This paper addresses the need for enhanced control in robotic arms by presenting the design and implementation of a 5DoF robotic arm transformed into a digital platform through specialized software. The methods employed involve detailed direct and inverse kinematic modeling to replicate the physical arm in a digital environment. Our measurements indicate an impressive accuracy ranging from 97% to 100% in the movements of the digital model, closely mirroring its physical counterpart. This research not only contributes to the development of simulation systems but also holds promise for the broader adoption of digital twins. The paper discusses the background, outlines the methodology, highlights key findings, and concludes with the potential future impact of this work on the advancement of robotic systems and simulation technologies.

Backlash Against Women and Support for Men? On the Perception of Men and Women Researchers in Gender Stereotype-Inconsistent Domains

Even in academic fields dominated by women students (e.g., educational research), academic careers are characterized by vertical gender segregation in favor of men. This clashes with the public understanding of educational research as a women's domain that is more strongly associated with warmth (a stereotypically feminine trait) than competence (a stereotypically masculine trait), as revealed in our first study. We thus conducted an experimental vignette study of 189 adults from the general public to explore how women versus men researchers working in educational research versus physics (as a contrasting domain clearly dominated by men) were perceived on several dimensions of competence and warmth. Whereas the female researcher in physics was rated as more competent than the female researcher in educational research, the woman in physics was penalized for her gender stereotype-incongruent domain choice by being perceived as less warm. However, the male researcher in educational research was perceived as both warmer and more competent than his man counterpart in physics, and as smarter than the female researcher in educational research. These findings suggest rewards instead of penalties for men pursuing academic careers in initially women-dominated domains, likely contributing to the increasing gender gap in academic careers in these domains.

The Data Product-service Composition Frontier: A Hybrid Learning Approach

The service dominant logic is a base concept behind modern economies and software products, with service composition being a well-known practice for companies to gain a competitive edge over others by joining differentiated services together, typically assembled according to a number of features. At the other end of the spectrum, product compositions are a marketing device to sell products together in bundles that often augment the value for the customer, e.g., with suggested product interactions, sharing, and so on. Unfortunately, currently each of these two streams—namely, product and service composition—are carried out and delivered individually in splendid isolation: anything is being offered as a product and as a service, disjointly. We argue that the next wave of services computing features more and more service fusion with physical counterparts as well as data around them. Therefore a need emerges to investigate the interactive engagement of both (data) products and services. This manuscript offers a real-life implementation in support of this argument, using (1) genetic algorithms (GA) to shape product-service clusters, (2) end-user feedback to make the GAs interactive with a data-driven fashion, and (3) a hybridized approach which factors into our solution an ensemble machine-learning method considering additional features. All this research was conducted in an industrial environment. With such a cross-fertilized, data-driven, and multi-disciplinary approach, practitioners from both fields may benefit from their mutual state of the art as well as learn new strategies for product, service, and data product-service placement for increased value to the customer as well as the service provider. Results show promise but also highlight plenty of avenues for further research.

XR and digital twins, and their role in human factor studies

Digital twins (DT) are synchronized clones that mirror their physical counterparts at all times, enabling real-time monitoring, analysis, decision-making, and planning for optimized operations. Digital twins can transcend traditional two-dimensional interfaces by incorporating VR/AR/MR (XR) technology, providing immersive, intuitive, and interactive representations of systems, assets, and processes. Furthermore, real-time data from sensors, simulations, and other sources can be integrated into the XR-enabled digital twins, leading to better and more intuitive understanding and to more efficiently monitor, analyze, and maintain complex systems such as nuclear assets. Immersive, interactive, multi-player XR capabilities embedded in DTs will allow spatially accurate and more realistic representation, leading to improved risk assessment, optimized and predictive maintenance scheduling, enhanced situational awareness, and more effective communication among interdisciplinary teams. By combining the strengths of XR and digital twins, nuclear facilities can achieve heightened safety, operational efficiency, and decision-making accuracy. Marrying XR technology with digital twins is also likely to extend the utilization of digital twins to optimize those aspects of the design and operation of nuclear assets that involve human beings–specifically in human factors engineering. Training can also be significantly enhanced if DTs are linked with XR technology. These systems may also be used to assess human performance through human factors engineering for the safety analysis of nuclear assets. A specific example is assessing human performance in semi-autonomous nuclear assets or operating multiple nuclear assets. After briefly reviewing digital twins of nuclear systems from the perspective of XR technology, this paper summarises our work in the nuclear energy space on VR/AR/MR and how these can be integrated into the newly evolving DTs of nuclear assets. The paper also describes the potential use of such systems in optimizing the design and operations of nuclear systems. As XR technology advances, its symbiotic relationship with digital twins can significantly reshape the landscape of nuclear operations and asset management.

Metaverse Servicescape: Emotional Response to Virtual Retail Design

The highly anticipated global Metaverse market presents a burgeoning arena, particularly in shopping and retail. While physical retail environments have long emphasized the details of exterior and interior servicescape design, the shift to online shopping raises questions about applying these traditional retail principles to the Metaverse setting. This research adopts conjoint analysis to delve into the potential of localized Metaverse retail design by merging consumer emotions, market segmentation, and innovative retail technologies. Using the Pleasure, Arousal, Dominance (PAD) model, we examine Metaverse servicescape attributes, based on real-world counterparts, application in segmenting store design based on consumer preferences. Like in physical retailing cases, music, crowding, and noise are the most influential Metaverse attributes affecting consumer emotion. However, three different clusters emerged according to their emotional responses. Our experiment reveals that Metaverse servicescape attributes may evoke emotional responses akin to their physical counterparts while offering a valuable opportunity for customization that better satisfies market segments. Insights are offered for retailers navigating the dynamic Metaverse landscape, where personalization and localization are now more affordable and where multiple store designs can coexist in digital form—reaching larger markets.

Enhancing Wireless Security and Privacy: A 2-Way Identity Authentication Method for 5G Networks

The communication network would have potential uses dependent on the infrastructure once the fifth generation (5G) network is fully commercialized. Subscriber Identification Module (SIM) authentication is a well-known mechanism for safeguarding the confidentiality of wireless device users. Fifth-generation computer technologies are very advanced in certification based on geolocation, regular confirmation, and authentication mechanisms. The clonable authentication feature solves the issue of authentication using duplicate modules. In highly dynamic environments, the problem poses a risk to privacy protection, adaptiveness, self-organization, information leakage, and the reliability of services. The article introduces a 2-way identity authentication method (2WIAM) using a Physical Unclonable Function (PUF) to address the issue above. The suggested technique for detecting module clones depends on user-provided authentication and geolocation data. The 2-way mutual authentication used in the suggested technique is a clever way to combine the many wireless technologies accessible to a given network node and enable the creation of wireless on-demand service providers and networks. The initial stage involves immediate passcode authentication, and the second is verifying the identity of the mobile equipment and any shifts or copies in its physical position. A new-cross authentication is then carried out to determine the identity of the clone's physical counterpart. In prior authentication situations, the choice to provide authorization or ban the clone was made fairly and objectively. The experiment results show that the users' privacy is protected, enhanced adaptiveness and the amount of data lost is limited.

IoTwins: Implementing Distributed and Hybrid Digital Twins in Industrial Manufacturing and Facility Management Settings

A Digital Twin (DT) refers to a virtual representation or digital replica of a physical object, system, process, or entity. This concept involves creating a detailed, real-time digital counterpart that mimics the behavior, characteristics, and attributes of its physical counterpart. DTs have the potential to improve efficiency, reduce costs, and enhance decision-making by providing a detailed, real-time understanding of the physical systems they represent. While this technology is finding application in numerous fields, such as energy, healthcare, and transportation, it appears to be a key component of the digital transformation of industries fostered by the fourth Industrial revolution (Industry 4.0). In this paper, we present the research results achieved by IoTwins, a European research project aimed at investigating opportunities and issues of adopting DTs in the fields of industrial manufacturing and facility management. Particularly, we discuss a DT model and a reference architecture for use by the research community to implement a platform for the development and deployment of industrial DTs in the cloud continuum. Guided by the devised architectures’ principles, we implemented an open platform and a development methodology to help companies build DT-based industrial applications and deploy them in the so-called Edge/Cloud continuum. To prove the research value and the usability of the implemented platform, we discuss a simple yet practical development use case.

Digital Twin Prototypes for Supporting Automated Integration Testing of Smart Farming Applications

Industry 4.0 marks a major technological shift, revolutionizing manufacturing with increased efficiency, productivity, and sustainability. This transformation is paralleled in agriculture through smart farming, employing similar advanced technologies to enhance agricultural practices. Both fields demonstrate a symmetry in their technological approaches. Recent advancements in software engineering and the digital twin paradigm are addressing the challenge of creating embedded software systems for these technologies. Digital twins allow full development of software systems before physical prototypes are made, exemplifying a cost-effective method for Industry 4.0 software development. Our digital twin prototype approach mirrors software operations within a virtual environment, integrating all sensor interfaces to ensure accuracy between emulated and real hardware. In essence, the digital twin prototype acts as a prototype of its physical counterpart, effectively substituting it for automated testing of physical twin software. This paper discusses a case study applying this approach to smart farming, specifically enhancing silage production. We also provide a lab study for independent replication of this approach. The source code for a digital twin prototype of a PiCar-X by SunFounder is available open-source on GitHub, illustrating how digital twins can bridge the gap between virtual simulations and physical operations, highlighting the symmetry between physical and digital twins.

Acoustical feature analysis and optimization for aesthetic recognition of Chinese traditional music

Chinese traditional music, a vital expression of Chinese cultural heritage, possesses both a profound emotional resonance and artistic allure. This study sets forth to refine and analyze the acoustical features essential for the aesthetic recognition of Chinese traditional music, utilizing a dataset spanning five aesthetic genres. Through recursive feature elimination, we distilled an initial set of 447 low-level physical features to a more manageable 44, establishing their feature-importance coefficients. This reduction allowed us to estimate the quantified influence of higher-level musical components on aesthetic recognition, following the establishment of a correlation between these components and their physical counterparts. We conducted a comprehensive examination of the impact of various musical elements on aesthetic genres. Our findings indicate that the selected 44-dimensional feature set could enhance aesthetic recognition. Among the high-level musical factors, timbre emerges as the most influential, followed by rhythm, pitch, and tonality. Timbre proved pivotal in distinguishing between the JiYang and BeiShang genres, while rhythm and tonality were key in differentiating LingDong from JiYang, as well as LingDong from BeiShang.

The Performance of Flexible Fluid-Structure Interaction Module for Saltmarsh Vegetation Under Flow and Wave Action

This paper evaluates the performance of a new flexible fluid-structure interaction (FSI) module in an open-source computational fluid dynamics (CFD) software - REEF3D - for use in modelling saltmarsh vegetation. Unlike previous studies, which focussed on hydrodynamic response to plants (for example, wave attenuation) to check the accuracy of their numerical modelling efforts, this work attempts to replicate the plants’ drag force and motion behavior, based on results from several physical modelling studies. The flexible FSI module was found to consistently overestimate both the drag and motion of the numerical plants when compared to their physical counterparts. It is hypothesized that this is due to the module’s use of linearly elastic material theory for the flexible structures. This is arguably inadequate for the relatively flexible materials of saltmarsh vegetation.

Computational Fluid Dynamics-Aided Simulation of Twisted Wind Flows in Boundary Layer Wind Tunnel

The twisted wind flow (TWF), referring to the phenomenon of wind direction varying with height, is a common feature of atmospheric boundary layer (ABL) winds, noticeably affecting the wind-resistant structural design and the wind environment assessment. The TWF can be effectively simulated by a guide vane system in wind tunnel tests, but the proper design and configuration of the guide vanes pose a major challenge as practical experience in using such devices is still limited in the literature. To address this issue, this study aims to propose an approach to determining the optimal wind tunnel setup for TWF simulations using a numerical wind tunnel, which is a replica of its physical counterpart, using computational fluid dynamics (CFD) techniques. By analyzing the mechanisms behind guide vanes for generating TWF based on CFD results, it was found that the design must take into account three key parameters, namely, (1) the distance from the vane system to the side wall, (2) the distance from the vane system to the model test region, and (3) the separation between the vanes. Following the optimal setup obtained from the numerical wind tunnel, TWF profiles matching both the power-law and Ekman spiral models, which, respectively, reflect the ABL and wind twist characteristics, were successfully generated in the actual wind tunnel. The findings of this study provide useful information for wind tunnel tests as well as for wind-resistant structural designs and wind environment assessment.

Cooperative Game-Based Digital Twin Drives Decision Making: Overall Framework, Basic Formalization and Application Case

The emerging progress brought about by Industry 4.0 generates great opportunities for better decision making to cope with increasingly uncertain and complex industrial production. From the perspective of game theory, methods based on computational simulations and methods based on physical entities have their intrinsic drawbacks, such as partially accessible information, uncontrollable uncertainty and limitations of sample data. However, an insight that inspired us was that the digital twin modeling method induced interactive environments to allow decision makers to cooperatively learn from the immediate feedback from both cyberspace and physical spaces. To this end, a new decision-making method was put forward using game theory to autonomously ally the digital twin models in cyberspace with their physical counterparts in the real world. Firstly, the overall framework and basic formalization of the cooperative game-based decision making are presented, which used the negotiation objectives, alliance rules and negotiation strategy to ally the planning agents from the physical entities with the planning agents from the virtual simulations. Secondly, taking the assembly planning of large-scale composite skins as a proof of concept, a cooperative game prototype system was developed to marry the physical assembly-commissioning system with the virtual assembly-commissioning system. Finally, the experimental work clearly indicated that the coalitional game-based twinning method could make the decision making of composite assembly not only predictable but reliable and help to avoid stress concentration and secondary damage and achieve high-precision assembly. Obviously, this decision-making methodology that integrates the physical players and their digital twins into the game space can help them take full advantage of each other and make up for their intrinsic drawbacks, and it preliminarily demonstrates great potential to revolutionize the traditional decision-making methodology.

Model‐based digital twins of medicine dispensers for healthcare IoT applications

SummaryHealthcare applications with the Internet of Things (IoT) are often safety‐critical, thus, require extensive testing. Such applications are often connected to smart medical devices from various vendors. System‐level testing of such applications requires test infrastructures physically integrating medical devices, which is time and monetary‐wise expensive. Moreover, applications continuously evolve, for example, introducing new devices and users and updating software. Nevertheless, a test infrastructure enabling testing with a few devices is insufficient for testing healthcare IoT systems, hence compromising their dependability. In this paper, we propose a model‐based approach for the creation and operation of digital twins (DTs) of medicine dispensers as a replacement for physical devices to support the automated testing of IoT applications at scale. We evaluate our approach with an industrial IoT system with medicine dispensers in the context of Oslo City and its industrial partners, providing healthcare services to its residents. We study the fidelity of DTs in terms of their functional similarities with their physical counterparts: medicine dispensers. Results show that the DTs behave more than 92% similar to the physical medicine dispensers, providing a faithful replacement for the dispenser.

Virtual measurements for exterior vibro-acoustic problems using experimental modal models

This paper presents a virtual sensor scheme for vibroacoustic radiation applications based on experimental modal state-space models and sparse measurements. A Kalman filter is used for the estimation combining data from the acoustical and the structural domain together with the numerical modal process model. It is proposed to use Gramians, as an energy-related measure of a system’s observability which enables assessing the observability of the coupled vibroacoustic system in the modal state-space domain and the physical state domain counterpart. This Gramian-based observability metric reveals modes or states of high observability, which ensure good estimation results in the subsequent estimation. The proposed method is validated using an industrial test setup for which, due to its high complexity, modelling with first-principle techniques is not feasible. The estimation results demonstrate improved performance compared to a pure forward use of the identified model, indicating the effectiveness of the virtual sensor approach. Additionally, the newly proposed Gramian-based observability criterion outperforms state-of-the-art metrics for sensor placement in terms of estimation accuracy for particular states of interest, as demonstrated in a sensor placement task. Overall, this paper provides a promising approach for virtual sensing for vibroacoustic applications, enabling accurate and efficient system monitoring and control.