Digital Data Acquisition Research Articles

Accuracy of different digital data acquisition work flows for full arch maxillary implant prostheses (an invitro study)

Accuracy of different digital data acquisition work flows for full arch maxillary implant prostheses (an invitro study)

Systematic analysis of the digital technologies used in the documentation of historical buildings

Cultural heritage buildings have values that provide a connection from past to present. The first stage of ensuring that these values are preserved and transferred to future generations is the documentation and diagnosis studies. The digital acquisition of the documentation data of historical buildings by digitizing, the creation of 2D drawings and 3D models with numerical data, provides an accurate analysis of the current situation of cultural heritage buildings and allows the evaluation of damage status of the building in the process after the documentation works. Although current studies in the literature mostly focus on the use of a certain method, device or software, it has been determined that there is no study that examines digital documentation methods in detail and systematically addresses the current technologies, programs and tools used in this process. Based on this gap in the literature, in this study, firstly, the documentation of cultural heritage and its importance are mentioned, the components of documentation are explained, and the methods, tools, applications and software programs that could be used in the documentation, recording and data processing of cultural heritage structures were systematically brought together. By comparing the data obtained as a result of this research study, in which the qualitative research method was used, with the documentation methods, it points out that digital documentation of cultural heritage structures allows for a more precise assessment by increasing the accuracy of data collection and analysis studies. The study also highlights the importance of the use of digital technologies, which makes it easier to store, share and manage the data at hand.

Convolutional Neural Networks and Regression Algorithms Supporting Buildings Facility Management

Facility Management is a multi-disciplinary task in which coordination is key to attaining success during the building life cycle and for which technology assumes an increasing role. This sector is demanding more available and accurate tools to optimize the management process, decrease the probability of failure, and reduce the time spent on anomaly analysis. So, the present paper presents work developed to improve access to building anomaly recognition and to predict the building degradation state in an automatized way. The methodology applied to achieve this goal started with a survey and digital data acquisition from a case study, followed by the automatized detection of building anomalies using supervised classification in Deep Learning; then, the early diagnosis of threatening conditions for building degradation took place using degradation curves based on data records and regression algorithms. The results drive this study a step forward toward obtaining advanced tools for Facility Management based in Artificial Intelligence, able to provide the most appropriate moment at which to intervene according to the cost-benefit. The present work provided better results on the harmonic mean of precision and recall when compared with previous studies of image classification for the construction sector. Moreover, the mathematical functions for the prediction of future degradation based on the data field for each construction system were presented and can be applied to the typologies of other buildings. In the end, future developments and limitations are highlighted.

Test-retest reliability of pain extent and pain location using a novel pain drawing analysis software application, on patients with shoulder pain

ABSTRACT Objectives A method of pain assessment is the drawing of pain on a specially designed manikin where the patients color the area representing their pain distribution. In recent years, software applications have been developed for the purpose of digital pain drawing data acquisition and processing. Although such specific software applications have already been released, they have been built with obsolete programming tools. The purpose of the study was to investigate the test – retest reliability of a new pain drawing analysis software, in a sample of patients with shoulder pain. Methods Data collected from 31 subjects with shoulder pain. Participants were asked twice to color their pain distribution in the painting environment of a tablet software application called ‘Pain Distribution.’ Results The reliability of pain extent was found to be good (ICC = 0.80). The Jaccard index for the reliability of pain location was found to be moderate, equal to 42.02 ± 19.13%. Conclusion The results demonstrated good reliability of pain extent and moderate reliability of pain location using the new pain distribution analysis application ’Pain Distribution.’ This pain drawing software application could be a reliable, inexpensive, and clinically usable solution for assessing the distribution of pain in patients with shoulder pain.

A Review of the Digital Skills Needed in the Construction Industry: Towards a Taxonomy of Skills

The construction industry is slowly embracing digitalisation in line with the Industry 4.0 revolution and the aftermath of the COVID-19 pandemic. However, progress has been sluggish due to stakeholders’ limited awareness of digital skills. This study addresses this issue by developing a comprehensive taxonomy of digital skills required to successfully implement the Industry 4.0 principles of digitalisation in the construction industry. A systematic literature review was conducted by mining the Scopus and Web of Science databases to identify relevant literature and map the skills currently used or needed for digitalisation. The study also examined publication trends and outlets to gain insight into developments. Additionally, VOSviewer was used to conduct a scientometric analysis of the shortlisted articles to identify important keywords and authorship collaboration networks within this research domain. A total of thirty-five digital skills were identified from the literature. These skills were organised into a taxonomy with categories named automation and robotics, coding and programming, design, drafting and engineering, digital data acquisition and integration, digital literacy, digitisation and virtualisation, modelling and simulation, and planning and estimation. The developed taxonomy will help stakeholders plan strategically to provide digital skills to the new graduates joining the workforce, enabling a more comprehensive approach to the digitalisation of the construction industry.

Evaluation of the use of different intraoral scanners for auricular prosthetic reconstruction

The use of intraoral optical scanners has been introduced for direct digital data acquisition in maxillofacial prosthetics, but their clinical accuracy has not been evaluated sufficiently. The purpose of this observational study was to evaluate the use of different intraoral scanners for extraoral maxillofacial digitization of an ear and to assess visually the clinical outcome of the generated 3-dimensional ear casts. A selected intact ear was scanned by using 3 different intraoral optical scanners: CEREC Primescan (Dentsply Sirona), Medit i700 (Medit Corp) and Panda P2 (Pengtum Technologies). Three-dimensional printed auricular casts were fabricated from the obtained scans, and a questionnaire administered to assess visually the clinical outcome of the generated casts. Comparisons between scanners were done by using the Kruskal-Wallis test followed by the post hoc test with Bonferroni correction when results were significant. The Wilcoxon Sign Rank test was used to compare the responses of both the prosthodontists and the lay personnel. All tests were 2-tailed (α=.05). The 3-dimensional printed auricular casts fabricated from the data acquired by using Primescan and Medit i700 scanners showed a statistically significant difference in matching scores when compared with the Panda P2 scanner (P<.001). Digital ear scanning with the Primescan and Medit i700 intraoral scanners should produce auricular prostheses that more closely match the normal ear when compared with those scanned by the Panda P2 scanner.

Authoritarian Alliances and the Politicking of Data in Africa

This research note explores the need for further research into increasing accounts of the unregulated acquisition, use, and control of personal data by foreign states in collaboration with certain African states. Limited local research on the acquisition of large-scale digital data by African authoritarian governments, with the backing of certain foreign actors, has meant that African civil society has insufficiently confronted the human rights implications. Yet these practices are not new and are a continuation of authoritarian influence into the digital era.

Digital Strategies to Enhance Cultural Heritage Routes: From Integrated Survey to Digital Twins of Different European Architectural Scenarios

This paper focuses on a research project for the acquisition and post-production of digital data to create informative virtual representations and digital twins of different European Cultural Heritage sites. The goal was to establish a reliable database for a multi-scalar web platform, also accessible through extended reality (XR) tools. This initiative aims to support the promotion and management of cultural and historical monuments within the context of European Cultural Routes supported by the Council of Europe. The project involves different case studies spanning European geographic regions, such as the Upper Kama in Russia, the Valencian Routes of Jaime I in Spain, and the Gdańsk fortresses in Poland. The methodology employed in this effort primarily relies on integrated rapid survey techniques. Unmanned aerial vehicles (UAVs) and simultaneous localization and mapping (SLAM) technologies were used for data collection. These methods contribute to the creation of accurate 3D databases and models that transform the cultural routes into a digital format accessible via an informative platform. The actions presented in this paper are part of the European project “PROMETHEUS”, which is funded by the Horizon 2020 program of the European Union. The project involves collaboration between universities and enterprises, fostering inter-sectoral cooperation. Various techniques such as photographic archives, census analysis, and scan-to-BIM (building information modeling) processes are employed to develop this method further. In fact, the ultimate goal of the project is to establish a framework that can be replicated in other cultural contexts, enhancing the digital documentation and valorization of heritage sites.

Precise mass measurement of the 32S member of the (A=32, T=2) quintet of analogue states

This contribution presents a precise measurement of the excitation energy of the lowest (0+, T=2) state in 32S. Combined with the mass excesses of the 32S ground state and of the four other members of the (A=32,T=2) quintet of analogue states, it allows to test the validity of the Isobaric Multiplet Mass Equation to the third order in Tz, which renders it highly sensitive to the mechanisms inducing isospin mixing in the involved sd-shell nuclei. The (0+, T=2) isobaric analogue state in 32S was resonantly populated in the 31P(p, γ) reaction at ~3.3 MeV incident energy. The measurement procedure, involving high-purity germanium detectors, is described and the preliminary result obtained with a digital data acquisition system is presented.

Towards standardized guidelines in digital data acquisition for monitoring and maintenance of European transport infrastructures

AbstractThe digital transformation of the architecture, engineering, and construction sector is associated with an enormous production of data. The appearance of new technologies is leading the way for more sustainable and interconnected infrastructures. Therefore, data analytics is crucial to know the current state of infrastructure and will help towards the efficient management of assets. The main issue is how to collect and exploit meaningful data throughout the lifecycle of infrastructure assets to further allow human experts and computers to make accurate diagnostics, predictions, and decisions. This contribution presents the insights gained in the course of IM‐SAFE project, showing the strategy followed to create guidelines for data collection to monitor and maintain critical assets in the infrastructure network (bridges and tunnels). It tackled a variety of surveying technologies, from destructive and non‐destructive, to chemical methods, among others. The results obtained will support the European Committee for Standardization (CEN) in the standards for monitoring and maintenance of bridges and tunnels, accelerating the adoption of new standards by public authorities and stakeholders in transport infrastructure.

Bioreceptor-inspired soft sensor arrays: recent progress towards advancing digital healthcare

Recent advances in soft sensor technology have pushed digital healthcare toward life-changing solutions. Data reliability and robustness can be realised by building sensor arrays that collect comprehensive biological parameter data from several points on the underlying organs simultaneously, a principle that is inspired by bioreceptors. The rapid growth of soft lithography and printing, three-dimensional (3D) printing, and weaving/knitting technologies has facilitated the low-cost development of soft sensors in the array format. Advances in data acquisition, processing, and visualisation techniques have helped with the collection of meaningful data using arrays and their presentation to users on personal devices through wireless communication interfaces. Local- or cloud-based data storage helps with the collection of adequate data from sensor arrays over time to facilitate reliable prognoses based on historical data. Emerging energy harvesting technologies have led to the development of techniques to power sensor arrays sustainably. This review presents developmental building blocks in wearable and artificial organ-based soft sensor arrays, including bioreceptor-inspired sensing mechanisms, fabrication methods, digital data-acquisition techniques, methods to present the results to users, power systems, and target diseases/conditions for treatment or monitoring. Finally, we summarise the challenges associated with the development of single and multimodal array sensors for advanced digital healthcare and suggest possible solutions to overcome them.

A setup for high-energy [formula omitted]-ray spectroscopy with the ELI-NP large-volume LaBr3:Ce and CeBr3 detectors at the 9 MV Tandem accelerator at IFIN-HH

We have performed the first experimental campaign using large-volume LaBr3:Ce and CeBr3 detectors from several of the Extreme Light Infrastructure-Nuclear physics (ELI-NP) instrumental setups together with detectors and infrastructure from the ROSPHERE array at the 9 MV Tandem facility at the Horia Hulubei National Institute for Physics and Nuclear Engineering (IFIN-HH). The performance of the detectors and the digital data acquisition system is shown to give a good energy resolution at high energies, and an excellent time resolution. We, furthermore, present the possibilities to integrate the detector system and the digital electronics with various ancillary detectors for, for example, charged particles.

Design of a high performance Digital data AcquIsition SYstem (DAISY) for innovative nuclear experiments

A dedicated digital data acquisition (DAQ) system has been developed for innovative nuclear data measurements, from time-of-flight to irradiation experiments as well as other basic nuclear physics experiments. The DAQ system is based on fast digitizers with 14 bits resolution and 1 GS/s sampling rate for reliable pulse shape discrimination, energy and timing resolution measurements. Thanks to the high throughput provided by the PCIe bus, data can be processed at CPU or co-processor level, thus allowing great flexibility and reliability. The use of an external clock system and a dedicated triggering system guarantee a very precise synchronization with other possible subsystems in any experimental setup. Finally, its modularity allows to build a flexible and scalable system.

Managing Healthcare Infodemic by deep learning in providing healthcare services

Digital Health care data acquisition and processing is performed by Artificial Intelligence and Internet of Things technologies and digitization of data and information affects the patients’ behavior. News about COVID-19, a global pandemic, is circulating on social media worldwide providing a collection of big data. Awareness about the pandemic is spreading drastically in the form of messages, social media posts, tweets, and videos. It is, therefore, significant to assess the early flow of information on social media during the pandemic to prevent alarmism. This study aims to perform sentiment analysis of social media big data about COVID-19 by deep learning on a dataset provided by IEEE Data Port. The goal is to assist healthcare professionals in developing social media policies that can be used to change public opinion. The Dataset used consists of 11,858 COVID-19-related tweets collected on May 30, 2020. Data are labeled as positive or negative in the first step using TextBlob and VADER. In step II, various machine learning models are compared using three feature extraction techniques in combination with VADER and TextBlob. The results show that Extra Tree Classifier using TF-IDF features outperforms with an accuracy of 0.9474.

SIMPLE PHYSICAL PRINCIPLES AND MEDICAL USES OF COMPUTED TOMOGRAPHY (CT) SCAN A NEW ASSESSMENT

The development of X-ray computed tomography (CT) has been founded on the discovery of X-rays, the inception of the Radon transform, and the growth of X-ray digital data acquisition systems and computer knowledge. Dissimilar conventional X-ray imaging (general radiography), CT reconstructs cross-sectional anatomical images of the internal structures according to X-ray attenuation co-efficients (approximate tissue density) for almost every region in the body. This articleappraisals the essential physical principles and practical aspects of the CT scanner, including numerous notable evolutions in CT technology that resulted in the appearance of helical, multidetector, cone beam, portable, dual-energy, and phase-contrast CT, in integrated imaging modalities, such as positronemission- tomography一CT and single-photon-emission-computed-tomography-CT, and in clinical applications, including image acquisition parameters, CT angiography, image adjustment, versatile image visualizations, volumetric/surface rendering on a computer workstation, radiation treatment planning, and target localization in radiotherapy. The understanding of CT characteristics will provide more effective and accurate patient care in the fields of diagnostics and radiotherapy, and can lead to the improvement of image quality and the optimization of exposure doses.

A web scrapping and AI approach for archeologists to analyze the ancient cities

Studies on machine learning have started to reach a level where we can save a great amount of time and labor by producing structures that can think as a human and have decisions. Deep learning, one of the methods of machine learning, is an artificial intelligence-training technique that can predict the outputs from the given dataset In this study, the use of web scraping technique was investigated to determine the potential of identifying ancient columns, which are one of the most important architectural elements of cultural heritage, by artificial intelligence. In this study, web scraping approach is presented as a digital data acquisition method for archaeology field to collect imagery datasets from web to analyze the ancient cities. For analysis, a free online, and easy-to-use tool ‘Amazon Rekognation’ is used for comparing the number of columns found in the scrapped images. For summarizing the research, simply, we have tried to get the answer the question from PC that ‘which site has the columns most, Perge, Xanthos or Phaselis?’. With this proposed approach, the archeologists can have a primarily knowledge about the sites they will study with use of operational tools for their further comprehensive research.

Going beyond general competencies in teachers' technological knowledge: describing and assessing pre-service physics teachers' competencies regarding the use of digital data acquisition systems and their relation to general technological knowledge

The use of digital technologies and media in physics classrooms has pedagogical potential. In addition to everyday common technologies (e. g., presenters or computers), highly subject-specific media and technologies (e. g., simulation and digital data acquisition systems) are now available for these purposes. As the diversity of these technologies/media increases, so do the required competencies on the part of the (pre-service) physics teachers who must be able to exploit the given potential. Corresponding competency frameworks and related evaluation instruments exist to describe and assess the corresponding competencies. These frameworks and scales are characterized by their generality and do not reflect the use of highly subject-specific technologies. Thus, it is not clear how relevant they are for describing competencies in highly subject-specific technological situations, such as working with digital data acquisition systems in educational lab work settings. Against this background, two studies are presented. Study 1 identifies empirically 15 subject-specific competencies for handling digital data acquisition systems in lab work settings based on a literary review of lab manuals and thinking aloud. In Study 2, based on the 15 identified competencies, an abbreviated content- and construct-validated self-efficacy scale for handling digital data acquisition systems is provided. We show that general technological-specific self-efficacy is only moderately related to the highly subject-specific self-efficacy of handling digital data acquisition systems. The results suggest that specific competency frameworks and measurement scales are needed to design and evaluate specific teaching and learning situations.

Multiple-Dimension Biohealth Data Acquisition System for 5G Telehealthcare Application

A 5G-enabled digital multiple-dimension biohealth data acquisition system prototype integrating an electrochemical dongle, a photochemical dongle and a fluorescence sensor for remote and smart healthcare application is proposed in this paper. The system evolves from the Internet of Medical Things (IoMT) and can automatically collect multiple biochemical indicators including chronic disease markers, renal function indicators, and inflammatory factors from patients' blood samples with rapid speed and high accuracy. Because the system is based on Massive Machine Type Communications (mMTC), it can interact reliably with hospital systems or personal mobile devices with ultra-low latency. To generate a platform for in-time interaction between patients and medical staff, an Application (App) terminal is developed to guarantee real-time medical data sharing and face-to-face remote consultation. This not only promotes the personal proactive health management, but also generates valuable records to hospitals for future prevention of diseases, which is highly practical for tele-health management.

A position-sensitive large-area microchannel plate detector with digital data-acquisition system for studies of exotic nuclei

Development of a position-sensitive large-area microchannel plate (MCP) detector based detection system is reported. Two MCPs with 120 mm active diameter, mounted in chevron configuration, with delay-line anode are read out by a digital data-acquisition system consists of fast-timing amplifier unit and CAEN v1751 waveform digitizer. Details of the digital pulse processing, programmed triggering and calibration setup are described. The obtained position resolution was studied using α-particles, the best resolutions on X and Y axes are 460 ± 1μm and 579 ± 1μm in FWHM, respectively.

SPARTIN: a Bayesian method for the quantification and characterization of cell type interactions in spatial pathology data.

Introduction: The acquisition of high-resolution digital pathology imaging data has sparked the development of methods to extract context-specific features from such complex data. In the context of cancer, this has led to increased exploration of the tumor microenvironment with respect to the presence and spatial composition of immune cells. Spatial statistical modeling of the immune microenvironment may yield insights into the role played by the immune system in the natural development of cancer as well as downstream therapeutic interventions. Methods: In this paper, we present SPatial Analysis of paRtitioned Tumor-Immune imagiNg (SPARTIN), a Bayesian method for the spatial quantification of immune cell infiltration from pathology images. SPARTIN uses Bayesian point processes to characterize a novel measure of local tumor-immune cell interaction, Cell Type Interaction Probability (CTIP). CTIP allows rigorous incorporation of uncertainty and is highly interpretable, both within and across biopsies, and can be used to assess associations with genomic and clinical features. Results: Through simulations, we show SPARTIN can accurately distinguish various patterns of cellular interactions as compared to existing methods. Using SPARTIN, we characterized the local spatial immune cell infiltration within and across 335 melanoma biopsies and evaluated their association with genomic, phenotypic, and clinical outcomes. We found that CTIP was significantly (negatively) associated with deconvolved immune cell prevalence scores including CD8+ T-Cells and Natural Killer cells. Furthermore, average CTIP scores differed significantly across previously established transcriptomic classes and significantly associated with survival outcomes. Discussion: SPARTIN provides a general framework for investigating spatial cellular interactions in high-resolution digital histopathology imaging data and its associations with patient level characteristics. The results of our analysis have potential implications relevant to both treatment and prognosis in the context of Skin Cutaneous Melanoma. The R-package for SPARTIN is available at https://github.com/bayesrx/SPARTIN along with a visualization tool for the images and results at: https://nateosher.github.io/SPARTIN.