Digital Representation Research Articles

A legal status for Avatars in the Metaverse from a Private Law perspective

Avatars, or digital representations of ourselves in the Metaverse are often seen as a fun and unique aspect of virtual worlds, but the legal implications of their use — and potential misuse— remain largely unexplored. In this paper, I address various issues relating to the utilization of avatars in online virtual platforms by individuals, highlighting both their potential benefits advantages and potential problems. In that context, I provide a very much needed clarification of what the Metaverse entails, and I propose a Private Law-oriented framework for thinking and regulating certain aspects of digital avatars in a legally feasible manner.

Personalization above anonymization? A role for considering the humanity and spirituality of the dead in anatomical education.

Clinical anatomy education is meant to prepare students for caring for the living, often by working with the dead. By their nature many clinical anatomy education programs privilege topographical form over the donor's humanity. This inbalance between the living and the dead generates tensions between the tangible and the spiritual insofar as semblances of the humanity of donors endure even in depictions and derivatives. This article argues that considering the relevance of spirituality, and what endures of a donor's humanity after death, would enhance contemporary anatomy education and the ethical treatment of human body donors (and derivatives). In developing this argument, we (the authors) address the historical connection between spirituality and anatomy, including the anatomical locations of the soul. This serves as a basis for examining the role of the mimetic-or imitative-potential of deceased human donors as representations of the living. We deliberate on the ways in which the depersonalization and anonymization of those donating challenge themimetic purpose of human body donorsand the extent to which such practicesare misaligned with the health care shift from a biomedical to a biopsychosocial model. Weighing up the risks and opportunities of anonymization versus personalization of human body donors, we propose curricula that could serve to enhance the personalization of human donors to support students learning topographical form. In doing so, we argue that the personalization of human donors and depictions could prevent the ill effects of digital representations going "viral," and enhance opportunities for donors to help the general public learn more about the human form.

Shaping the future of industry: Understanding the dynamics of industrial digital twins

A digital twin (DT) is a representation of anything in the real-world that gets updates from both its physical and environmental equivalents. As a result, it is seen as the cornerstone of Industry 4.0 and the wave of innovation to come since it connects virtual cyberspace with actual physical entities. Virtualization of machinery control, use of data analysis in decision-making, and information flow through the Internet are some trends in Industrial Digital Twins (IDTs). IDT is one of the possible digital technologies that are currently being developed to facilitate digital transformation and decision-making in many industrial sectors. Even after more than two decades, the concept of digital twin is continuously developing, taking new forms like IDT as it permeates industries and applications. This has led to an ever-growing diversity of definitions, which poses a danger to the concept’s clarity and might result in the technology’s use ineffectively. To define what qualifies an IDT and what does not, there is a requirement for a comprehensive description with well-defined criteria. A digital representation of a physical process enables safe management, remote control, and simulations of the process. This paper offers recommendations for creating a Digital Twin architecture that incorporates the Industrial Internet of Things (IIoT) and modern technology, integrating aforementioned features in an experimental application. Additionally, the article concentrates on the IDT characteristics, major technological practices behind IDT, related sustainable solutions, and major use-cases. Furthermore, the existing challenges are explored with a specific focus on the open issues and related future opportunities.

Enhancing Resilience in Biometric Research: Generation of 3D Synthetic Face Data Using Advanced 3D Character Creation Techniques from High-Fidelity Video Games and Animation.

Biometric authentication plays a vital role in various everyday applications with increasing demands for reliability and security. However, the use of real biometric data for research raises privacy concerns and data scarcity issues. A promising approach using synthetic biometric data to address the resulting unbalanced representation and bias, as well as the limited availability of diverse datasets for the development and evaluation of biometric systems, has emerged. Methods for a parameterized generation of highly realistic synthetic data are emerging and the necessary quality metrics to prove that synthetic data can compare to real data are open research tasks. The generation of 3D synthetic face data using game engines' capabilities of generating varied realistic virtual characters is explored as a possible alternative for generating synthetic face data while maintaining reproducibility and ground truth, as opposed to other creation methods. While synthetic data offer several benefits, including improved resilience against data privacy concerns, the limitations and challenges associated with their usage are addressed. Our work shows concurrent behavior in comparing semi-synthetic data as a digital representation of a real identity with their real datasets. Despite slight asymmetrical performance in comparison with a larger database of real samples, a promising performance in face data authentication is shown, which lays the foundation for further investigations with digital avatars and the creation and analysis of fully synthetic data. Future directions for improving synthetic biometric data generation and their impact on advancing biometrics research are discussed.

REVERSE ENGINEERING AND PROTOTYPING OF DISC BRAKE CALIPER

Disc brake calipers are the components which plays a vital role in automotive braking systems, which are responsible for slowing down or stopping the vehicle. This project aims to understand the design and functionality of a disc brake caliper through Reverse engineering and create a new, improved prototype. We will disassemble an existing disc brake caliper, analyse its components, and understand its working principles. Using techniques such as 3D scanning and CAD modelling we will create a digital representation of the caliper. This digital model will serve as the basis for our prototyping phase, where we will leverage rapid prototyping technologies to create a physical model of the disc brake caliper. The goal of this project is not only to replicate the existing design but also to identify potential areas for improvement and innovation. By integrating reverse engineering and prototyping, we aim to enhance the performance and efficiency of disc brake calipers. Keywords: Disc Brake Caliper, Rapid Prototyping, Reverse Engineering, 3D Scanning, Calibry Nest Software.

The digital euro: a materialization of (in)security

The European Central Bank (ECB) has entered the preparation phase for the potential issuance of a digital euro. The digital euro under consideration represents a retail central bank digital currency (CBDC), a digital representation of central bank money that is intended for use by the general public. This article foregrounds the digital euro as an infrastructure that furthers European security ambitions. It argues that the development of the digital euro is a materialization of European (in)security rationales that aim to secure pan-European financial transactions amid growing geopolitical tensions. It focuses on the development of the technology and analyses how central bankers’ scenarios of the future manifest in the anticipated design and prototypes. While the provision of a financial infrastructure is the most decisive security-related implication of the digital euro, the introduction of a new form of public money is the decisive financial feature with potentially wide-ranging implications for banks. Although the ECB seeks to balance the interests of banks and other financial actors in the development of the digital euro, its plans are still met with criticism. Finally, the article argues that the ECB exerts itself more explicitly than before as a geopolitical actor in its own regard.

A novel spectrogram based lightweight deep learning for IoT spectrum monitoring

The integration of cognitive radio network (CRNet) with internet of things (IoT) holds tremendous potential for creating more intelligent and advanced technological ecosystems. By allowing IoT devices to dynamically access and utilize the available radio spectrum, CRNet-based IoT systems can enable transparent connectivity, faster data transmission, and efficient resource utilization. The successful deployment of CRNet-based IoT systems highly depends on spectrum sensing implementation, which makes selecting the appropriate spectrum sensing technique extremely critical. However, several challenges are associated with the current spectrum sensing techniques, including limited representation of signal features, susceptibility to noise, inadequate hardware compatibility, and significant performance degradation using deep learning models. To deal with these issues, a novel approach is proposed integrating spectrogram representation and lightweight convolutional neural network models. Unlike raw digital representation, spectrograms allow efficient and consistent feature extraction using time–frequency representation of the received signals. Lightweight convolutional neural network models leverage advanced deep learning techniques to achieve fast and accurate predictions from spectrograms. They require few parameters to process while reduce the computational burden. The proposed approach is a promising solution for performing spectrum sensing in resource-constrained environments paving the way for efficient use of radio spectrum in IoT networks. The performance of the proposed approach is evaluated and compared to the existing techniques. Spectrogram based lightweight deep learning achieved high efficiency while required less computational resources.

ExTern: Boosting RISC-V core performance using ternary encoding

This paper presents an effective μ-architectural design method, called ExTern, to enhance the performance of a RISC-V processor experiencing computation bottlenecks. ExTern involves integrating Canonical Signed Digit (CSD) representation, a ternary number system enabling carry/borrow-free addition/subtraction in constant time O(1), into the RISC-V processor, particularly into the execution stage. Furthermore, it adopts an extended six-stage pipeline architecture to maximize employed encoding benefits, leading to more improvement in overall execution time and throughput. Despite the presence of optimized circuits, such as fast carry chain (CARRY4) modules for binary encoding on FPGA, the customized processor applying ExTern, RISC-VT, showcases remarkable improvement in computation performance. Experimental results demonstrate a 34.3% (12.2%) improvement in working frequency leading to a lower 31% (11.5%) execution time and a 32% (12%) increase in throughput compared to a State-of-the-Art open-source five(six)-stage RISC-V processor.

Towards a Digital Representation of Building Systems Controls

Energy monitoring and performance optimization processes play a significant role in ensuring energy-efficient building operation. However, the current implementation of these processes requires substantial time and effort due to the fragmented and non-digital nature of technical building equipment information. To address these challenges, we demonstrate the application of the PLCont methodology within an ongoing monitoring process in a real building. PLCont utilizes Semantic Web Technologies and established RDF ontologies to describe the control topology. The digital representation of control functions aligns closely with the IEC standard 61131-3, and the PLCont ontology establishes a connection between the topology and the control functions. We compare the conventional approach and the PLCont methodol-ogy using the supply air temperature control of an Air Handling Unit (AHU) as a use case. A graphical user interface built upon the PLCont backend provides a comprehensive represen-tation of the system's functionality. It displays the system topology as a digital HVAC schema, the function code exported from the PLC, time-series data plots, and textual descriptions of implemented functions. We demonstrate how this approach enhances transparency and facil-itates the identification and elimination of faulty system behavior, ultimately contributing to the optimization and energy efficiency of building systems.

The Hyperreality of Virtual Influencer Lentari Pagi on Instagram

Rapid developments in the 4.0 era of industry have created technology with capabilities similar to humans, namely artificial intelligence. One example is virtual influencers, which result from progress made by real human influencers supported by technological development. The presence of virtual influencers has become an interesting phenomenon in the contemporary social media ecosystem. Lentari Pagi is a digital representation designed to imitate human behavior and interact with its followers through visual and narrative content shared online. This research aims to understand hyperreality in the appearance and interactions of virtual influencer Lentari Pagi on Instagram and analyze the impact of artificial intelligence technology on the perception and participation of social media users. The qualitative research method was used, with interviews and observation as data collection techniques. The results of this research show that Lentari Pagi succeeded in creating an emotional connection with its followers, conveying promotional messages, and forming a unique self-image in the minds of its audience. In conclusion, this hyperreality phenomenon reflects the complex dynamics between technology, culture, and identity in the current digital era.

3D Model of a Famous Landmark

The production of three-dimensional models of well-known sites is an example of how technology and cultural legacy can coexist in the rapidly developing field of digital representation. This study investigates the complex procedure involved in creating, constructing, and deploying 3D models of well-known international monuments. An intensive data collecting phase is when historical, architectural, and geographical information is acquired to start the process. The successive phases of 3D modeling are built upon this knowledge. Keywords—Three-dimensional models, Digital representation, Creating, Constructing

Performance evaluation of electro-mechanical railway interlocking system for digital twin application

The industries engaged healthcare, manufacturing, and construction automated with exquisite creativity and innovation at the doorstep of Industry 4.0. In this process, digital twins are diligently used to supplement industrial processes, reduce costs, monitor assets, streamline maintenance, reduce downtime, and enable the creation of connected goods. The research is aimed at finding the digital representation of electro-mechanical railway interlocking elements are simulated and its functionality is verified accordingly. With respect to carry out this research, the Indian Railways Mangalagiri Railway Station blueprints were collected to represent the physical Model which consists of signals, points, a crank handle, an LC gate, and many more elements. In this paper, three interlocking elements such as points, crank handle, and LC gate, are analysed, modelled, and simulated by using Model Sim ME of Libero SoC software. Representation of these digital elements were developed using a smart design canvas. Therefore, the proposed methodology will enhance the safety measures and security levels of the train movements and reduces the time required to replace the faulty relay. Similarly, in future, the proposed model could be dumped into the FPGA kit to verify the real-time data for finding the faulty relay in the relay-based interlocking system.

Enhanced Inclusion through Advanced Immersion in Cultural Heritage: A Holistic Framework in Virtual Museology

In recent years, the digitization of cultural heritage has been favored by significant advancements in specific technologies, such as photogrammetry and three-dimensional scanning. The digital representations of artifacts, paintings, books, and collections, as well as buildings or archaeological sites, has led to the transfer of cultural organizations to the digital space. On the other hand, the rapid development of immersive technologies and the Internet of Things is expected to decisively shape virtual cultural heritage in the coming years. However, this digital transition should expand its impact on most of the population. This article aims to cover the lack of structured methodology in the design and development of inclusive virtual spaces in cultural heritage. This research introduces a holistic framework that is mainly based on the disciplines of virtual museology. The proposed methodology takes into account the advancements in extended reality and the creative industry of computer games. The multisensory approach would lead to advanced immersive experiences, while the multilayered approach of cultural heritage content would enhance accessibility in inclusive virtual spaces. Moreover, this holistic framework could provide evidence from the virtual worlds that could be applied to real cultural heritage organizations.

Practical aspects of the application of the remote physical rehabilitation support system under audiovisual self-control

The problem of developing a system for monitoring the health state of people with chronic non-communicable disease (CNCD) is considered. To improve the effectiveness of medical care for such patients, it is proposed to use long-term remote monitoring of their health outside the medical institution and, based on the analysis of personalized patterns of dynamics of diagnostically significant indicators for the state of remission and exacerbation of the disease, to ensure the possibility of detecting its exacerbation at an early stage of development. Diseases of the musculoskeletal system remain a serious problem for modern man. A long-term physical rehabilitation is required for the treatment of such condition. At the outpatient stage, it is carried out by the patient himself. The patient doesn’t have the possibility of qualified control over the correctness of performing rehabilitation exercises at home. The remote monitoring system will allow to assess the patient's condition during the outpatient period objectively. However, existing technical solutions are difficult to use for an ordinary user. Therefore, a convenient system is needed that could increase the availability of medical services without the use of additional equipment. The presence of a motion sensor system in a smartphone increases the possibility of using this technical tool to monitor motor activity in everyday life. Purpose of the present paper: to assess the effectiveness of a remote physical rehabilitation sup-port system through its implementation in a medical institution involving patients who have under-gone a rehabilitation course during their inpatient period, including the performance of a specific set of rehabilitation exercises, and to explore the participants' experiences using a mobile application and remote physical rehabilitation support system. During the development on the NEFITNESS project, the team developed and successfully implemented in clinical practice a system for remote physical rehabilitation support under audio-visual self-control. The support system, based on an inertial sensor, a mobile application, and an online platform, led to a 11% increase in muscle endurance over six months of regular sessions compared to standard rehabilitation techniques. The following objectives were achieved: a) experience with the mobile application and physical rehabilitation support system was studied; b) quantitative characteristics of rehabilitation trajectory success were obtained through exercise performance feedback; c) participant engagement in the topic of remote rehabilitation support increased; d) accessibility of rehabilitation technologies for a wide range of users improved. The practical possibility of using a remote rehabilitation and motor activity recovery system under audiovisual self- control is presented, where a smartphone served as a feed-back tool based on an integrated motion sensor to ensure the correct execution of rehabilitation exercises. Within the framework of joint scientific research carried out at the Research Institute of Emergency Pediatric Surgery and Traumatology under the project "Development of a complex of remote physical rehabilitation of children", the remote physical rehabilitation system and mobile application "NEFITNESS" were tested. The developed system resulted in increased muscle endurance over six months of regular sessions can be scaled and applied to address various tasks related to the digital representation of restorative exercises for other segments of the musculoskeletal system.

Simulation of national-scale groundwater dynamics in geologically complex aquifer systems: an example from Great Britain

ABSTRACT The national-scale British Groundwater Model (BGWM) is implemented to simulate groundwater dynamics and budgets in Great Britain. Notwithstanding the challenges of integrating a very large amount of data, finding a trade-off between computational efficiency and realism, performing automatic calibration, and addressing multiple sources of structural and parameter uncertainty, a quantitative–qualitive evaluation approach showed that the BGWM provides a reasonably accurate digital representation of groundwater systems and processes at a national scale. In this work, the model was applied to understand the variability of budget components across multiple spatial and temporal scales. Comparisons showed regional differences linked to lithological and climatic factors, which in turn can be associated with more or less groundwater resilience to extreme climatic events. There is confidence that the current and future versions of the BGWM can become valuable tools for effective water resources management and adaptation strategies under future climatic and population changes.

Navigating the Landscape of Precision Education: Insights From On-the-Ground Initiatives.

A central goal of precision education (PE) is efficiently delivering the right educational intervention to the right learner at the right time. This can be achieved through a PE cycle that involves gathering inputs, using analytics to generate insights, planning and implementing interventions, learning and assessing outcomes, and then using lessons learned to inform modifications to the cycle. In this paper, the authors describe 3 PE initiatives utilizing this cycle. The Graduate Medical Education Laboratory (GEL) uses longitudinal data on graduate trainee behavior, clinical skills, and wellness to improve clinical performance and professional fulfillment. The Transition to Residency Advantage (TRA) program uses learner data from medical school coupled with individualized coaching to improve the transition to residency. The Anesthesia Research Group for Educational Technology (TARGET) is developing an automated tool to deliver individualized education to anesthesia residents based on a longitudinal digital representation of the learner. The authors discuss strengths of the PE cycle and transferrable learnings for future PE innovations. Common challenges are identified, including related to data (e.g., volume, variety, sharing across institutions, using the electronic health record), analytics (e.g., validating augmented intelligence models), and interventions (e.g., scaling up learner assessments with limited resources). PE developers need to share their experiences in order to overcome these challenges, develop best practices, and ensure ethical development of future systems. Adapting a common framework to develop and assess PE initiatives will lead to a clearer understanding of their impact, help to mitigate potential risks, and allow deployment of successful practices on a larger scale.

Accuracy of Three-dimensional Scan Technology and Its Possible Function in the Field of Hand Surgery.

Three-dimensional (3D) technology has become a standard manufacturing element in many industries and has gained significant interest in plastic surgery. The 3D scans are widely used for patient communication, virtual surgery planning, and intraoperative tool manufacturing, providing a more comprehensive view of procedures and their outcomes compared with 2D visualization. We evaluated the performance of six commercially available 3D scanners by acquiring 3D models of a human hand and a 3D-printed replica of a human hand. We performed objective comparisons between the 3D models of the replica using color mapping techniques. Moreover, we compared the results of the human hand 3D scans. We achieved the highest precision with the Artec Space Spider 3D scanner (Artec 3D) when scanning the 3D-printed replica. The SD was ±0.05 mm, and the scan did not have major defects that needed manual correction. On the human hand scan, we achieved the best results using the Artec Eva (Artec 3D), the resulting scan was an accurate digital representation of the scanned human hand. In our study, the Artec Space Spider 3D scanner demonstrated superior precision when scanning a 3D-printed replica, deviating only slightly from the original data, making it an optimal choice for nonmoving objects such as casts or medical instruments. For scanning human hands, the Artec Eva 3D scanner exhibited the highest performance, offering accuracy comparable to the Artec Space Spider, but with the added benefit of being able to scan larger objects.

MODELING OF ANALOG-TO-DIGITAL SIGNAL CONVERTERS FOR SENSOR MICROSYSTEMS IN THE MICROWIND SOFTWARE

For the results of simulating the operation of analog-digital converters, we chose such a converter as the serial approximation ADC (SAR ADC). A sequential approximation ADC is a type of analog-to-digital converter that converts a continuous analog waveform to a discrete digital representation by binary search through all possible quantization levels before finally converging on a digital output for each conversion. There are three important blocks in the SAR ADC architecture: the sample and hold circuit (Sample and Hold, S/H), the comparator, and the SAR block. The topology and principle of operation of which was modeled in the Micro Wind software environment.

Predictive dynamic modeling and analysis of blisks through digital representations constructed upon precise geometry measurements

Blade geometric variations generally have a significant impact on the structural dynamics of integrally bladed disks widely used in the advanced aero-engines. This paper presents a holistic research in regard to the predictive dynamic modeling, analysis and experimental verification for a blisk by taking advantage of the advanced 3D optical geometry measurement technology. Geometrically mistuned models (GMMs) are semi-automatically constructed upon the precisely measured blisk geometry by an efficient FE mesh updating strategy. They provide explicit, high-fidelity digital representations of the geometric variations within the integrally manufactured blisk. A ‘Sector Mode Assembling Reduction Technique’ is developed and specifically tailored for efficient dynamic analysis of the large-sized GMMs at a relatively low computational cost and memory requirement. Intensive test campaigns, including forced response tests in the stationary/spinning rig under well-controlled laboratory conditions, are carried out for a full assessment of the GMMs’ dynamic prediction capability. Experimental verification results show that the GMM is able to capture the modal dynamics and resonant vibration of the stationary/rotating blisk with satisfactory accuracy. The physical-reality-based GMM converted directly from the precise geometry measurement data can be considered as a viable and valuable tool for predictive vibration evaluation of blisks. However, its model accuracy exhibits a mode-related dependence on the mesh density. The tradeoff between model accuracy and prohibitive computational cost proved to be the bottleneck of this promising blisk modeling approach.

Pheno-data: using tomatoes to rethink data and data practice for ecological worlds

ABSTRACT Notions of data increasingly revolve around digital representations prioritizing the efficiency and productivity of global economic-systems, often side-lining tangible and local information that is crucial for ‘more-than-human’ worlds. To challenge this, we propose the concept of, “Pheno-data,” which aims to embody the livingness of the lifeworld through the evolving characteristics and responses of organisms. We also introduce, “Pheno-fication”, as a means to access Pheno-data, and use tomatoes to exemplify the process. Through a fabulation workshop, we integrate these concepts into design practice in order to tangibly explore their potential for shifting perspectives from an anthropocentric to an ecological viewpoint.