Rapid Digitization Research Articles

Treharne, Elaine. Perceptions of Medieval Manuscripts: The Phenomenal Book

This monograph is both a study of medieval books as they were understood around the period of their creation, and an exploration of their meanings over time, culminating in reflections on the rapid digitization of old or rare books and manuscripts today. Treharne’s focus is on British books, and is aimed primarily at an academic readership. She links the medieval period and the internet age by concentrating on their differing approaches to the phenomenology of the book: its status as an object which can be accessed by all of the senses. For Treharne, following Maurice Merleau-Ponty’s phenomenology (to which she returns frequently), understanding a physical manuscript book requires being able to ‘see it in its entirety – immanently and from all angles open to me’ (p. 5). Her focus is on recovering a range of perspectives on manuscripts through time, based on the ways in which they were produced and used. The phenomenology of the medieval book as viewed in a Special Collections reading room lies in the reader’s whole experience of it, from the texture of each page to the marginalia it has accrued over centuries, and from its physical weight to evidence of wear and tear. Where a twenty-first-century reader may tend to concentrate on the words or images contained within a text which is likely to be a copy or reproduction, Treharne seeks to celebrate the sensory pleasures that can be found in each unique and individual book. This leads to her reservations about digitization: what is lost when such a sensory encounter is transformed into a series of images on a screen? While the internet broadens the accessibility of a medieval book, and so in a sense democratizes the experience of it, the uniqueness of the original via its appeal to the non-visual senses is fundamentally diminished. The ‘aura’ of the object, to use Walter Benjamin’s term, is dampened, and the online viewer may ultimately be left longing for the heft and smell of the physical book. This is important for understanding function, as well as aesthetic experience: online resources can make it difficult to determine scale and weight, and it can therefore be unclear, for instance, whether a particular psalter is made to be carried around for private study or kept permanently in one ceremonial location. The tensions between accessibility, preservation and phenomenological experience are the subject of the later stages of this book, but perhaps the most rewarding sections are those in which Treharne uncovers the richness of the medieval book-as-object, from her discussion of the ways in which books were made to her exploration of their spiritual resonances and authority. It is in this context that she also explores ‘libricide’, the physical deconstruction of manuscript books, often for the rare book trade. After so convincingly and evocatively showing how books were once seen as ‘living objects […] extensive artefacts that are irreducible to their component parts’ (p. 168), the notion of their being filleted and resold in lots seems as shocking to this contemporary reader as it surely would have to the monks who first laboured prayerfully over them with quills and ink.

Neural rendering-enabled 3D modeling for rapid digitization of in-service products

Rapid digitization of physical objects enables monitoring, analysis, and maintenance of in-service products, of which an up-to-date CAD model is not available. It provides designers with the products’ actual response to the real-world usage, which provides a reference base for design optimization. This paper presents neural rendering as a novel method for rapid digital model building. It learns a radiance field from RGB images to determine the characteristics of the physical object. Textured mesh can be generated from the learned radiance field for efficient 3D modeling. The effectiveness of the method is demonstrated by an engine component.

FULL ENUMERATION METHODS ON GRAPHS

Requirements for algorithms for specific problems of discrete mathematics are changing. This is dictated by an urgent need to increase calculation accuracy in technology-related problems brought about by rapid digitization and virtualization, which actively permeated various scientific areas and changes the approach to previously studied objects. These objects include n-dimensional structures, known as circular structures, that describe global processes occurring in communication networks, multi-processor systems, in collective communications, stock market structures etc. Given that, both the development of new mathematical methods of solving problems and the solution of related calculation problems are deemed important. The enumeration method, based on various modifications of systematic viewing (traversal) of graph elements and labeling, has been widely used and quite fully developed for a long time. The purpose of the article is to announce graphs presentation and the enumeration methods on graphs presentations: the transposition method and the node-graph method. This publication presents the basic results of the author's work on reducing the severity of the NP-complete problem class.

A typology of adolescents’ technology use before and during the COVID-19 pandemic: A latent profile analysis

The COVID-19 pandemic has made adolescents´ technology use unavoidable for sustaining teaching and learning processes. In the present paper we conducted two studies using a person-centered latent profile analysis to examine adolescents’ technology use before (Study 1, N = 643) and during (Study 2, N = 644) the COVID-19 pandemic in the region of Bavaria, Germany. While adolescents’ technology use before the COVID-19 pandemic was divergent in terms of study-related and social technology use, the results show that during the COVID-19 pandemic, adolescents’ technology use increased in terms of both, study-related and social purposes. Although our results suggest that adolescents’ use of technology for study-related purposes increased during the COVID-19 pandemic, adolescents from educationally disadvantaged families still appear to be at risk of being left behind by the even more rapid digitization of the COVID-19 pandemic, for which we discuss future research and targeted interventions.

Knowledge and perception of primary care healthcare professionals on the use of artificial intelligence as a healthcare tool.

The rapid digitisation of healthcare data and the sheer volume being generated means that artificial intelligence (AI) is becoming a new reality in the practice of medicine. For this reason, describing the perception of primary care (PC) healthcare professionals on the use of AI as a healthcare tool and its impact in radiology is crucial to ensure its successful implementation. Observational cross-sectional study, using the validated Shinners Artificial Intelligence Perception survey, aimed at all PC medical and nursing professionals in the health region of Central Catalonia. The survey was sent to 1068 health professionals, of whom 301 responded. And 85.7% indicated that they understood the concept of AI but there were discrepancies in the use of this tool; 65.8% indicated that they had not received any AI training and 91.4% that they would like to receive training. The mean score for the professional impact of AI was 3.62 points out of 5 (standard deviation (SD) = 0.72), with a higher score among practitioners who had some prior knowledge of and interest in AI. The mean score for preparedness for AI was 2.76 points out of 5 (SD = 0.70), with higher scores for nursing and those who use or do not know if they use AI. The results of this study show that the majority of professionals understood the concept of AI, perceived its impact positively, and felt prepared for its implementation. In addition, despite being limited to a diagnostic aid, the implementation of AI in radiology was a high priority for these professionals.

Rapid tunnel scanning using a 360-degree camera and SfM photogrammetry

Photogrammetric scanning can be employed for the digitization of underground spaces, for example for remote mapping, visualization, or training purposes. However, such a technique requires capturing many photos, which can be laborious and time-consuming. Previous research has demonstrated that the acquisition time can be reduced by capturing the data with multiple lenses or devices at the same time. Therefore, this paper demonstrates a method for rapid scanning of hard rock tunnels using Structure-from-Motion (SfM) photogrammetry and a 360-degree camera. The test was performed in the Underground Research Laboratory of Aalto University (URLA). The tunnel is located in granitic rocks at a depth of 20 m below the Otaniemi campus in Espoo, Finland. A 10 m long and 3.5 m high tunnel section with exposed rock was selected for this study. Photos were captured using the 360-degree camera from 27 locations and 3D models were reconstructed using SfM photogrammetry. The accuracy, speed, and resolution of the 3D models were measured and compared with models scanned with a digital single-lens reflex (DSLR) camera. The results show that the data capture process with a 360-degree camera is 6x faster compared to a conventional camera. In addition, the orientation of discontinuities was measured remotely from the 3D model and the digitally obtained values matched the manual compass measurements. Even though the quality of the 360-degree camerabased 3D model was visually inferior compared to the DSLR model, the point cloud had sufficient accuracy and resolution for semi-automatic discontinuity measurements. The quality of the models can be improved by combining 360-degree and DSLR photos which result in a point cloud with 3x higher resolution and 2x higher accuracy. The results demonstrated that 360-degree cameras can be used for the rapid digitization of underground tunnels.

Цифровые технологии в развитии русской речи и социокультурных компетенций детей-билингвов в России и за рубежом

The research uses the methods of triadic scaffold protocol, case study, survey, interviewing, and observation. The researchers created and tested the first ever model for the development of Russian speaking skills and social and cultural competences in children aged 3 to 8 living in the multilingual regions of Russia and abroad using digital educational tools, as well as the general principles for the integration of digital tools into preschool speech development programs.
 Rapid digitization of education and society in general make this work extremely important. Research findings can be recommended for consideration by methodologists, teachers, and parents interested in the development of competencies related to understanding early bilingual development mechanisms, the peculiarities of the generation of digital natives, the criteria for assessing digital resources for preschool and elementary school children’s speech development, scenarios of digital resource integration into family and formal (mass) education, as well as pedagogical strategies for taking advantage of multimodality, interactivity, and gamification offered by digital teaching tools.

MUHASEBE ALANINA GÜNCEL YAKLAŞIMLAR: METİN MADENCİLİĞİ

Metin madenciliği; bilgi bilimleri, dilbilim, bilgisayar bilimleri ve veri bilimleri gibi farklı alanlardan kavram ve teknikleri içeren çok disiplinli bir bilgi dalıdır. Kuruluşların kâğıt verilerden elektronik belgelere ve dijital kayıtlara geçmesiyle birlikte, iş süreçlerinin hızla dijitalleşmesi metin madenciliğine olan ilgiyi artırmıştır. Muhasebe alanındaki verilerin giderek büyümesinden dolayı metin madenciliği teknolojisi bu alan için önemli bir araştırma konusu olmuştur. Bu çalışmanın amacı; muhasebe alanında, metin madenciliğinin kullanımına yönelik bilgiler verilerek gelecekte bu teknolojinin kuruluşlara ve kişilere etkisini özlü bir şekilde ortaya koymaktır. Sonuç olarak metin madenciliği teknolojisinin muhasebe alanında kullanımı; muhasebe otomasyonu, denetim otomasyonu, vergi otomasyonu ve iş danışmanlığı otomasyonu şeklinde ele alınmış ve açıklamalar yapılmıştır. Ayrıca yapay zekâ ve makine öğrenmesi yaklaşımlarıyla birleştirilen metin madenciliğinin, işlemleri çok daha fazla otomatikleştirmesinden dolayı kuruluşlara ve muhasebe meslek mensuplarına önemli fırsatlar sunacağı ön görülmektedir.

CollembolAI, a macrophotography and computer vision workflow to digitize and characterize samples of soil invertebrate communities preserved in fluid

Abstract Soils are inhabited by communities of tiny invertebrates that participate in the essential functions of soils. Characterizing those communities in terms of species diversity and species abundance is part of investigating soil functions and response to perturbation. Dozens to hundreds of specimens can be extracted from a sample that need to be sorted, counted and identified. It involves an enormous amount of time, straining the workflow of soil zoologists. Deep learning‐based computer vision approaches have become increasingly popular to monitor biodiversity, as they can be applied to detect, count and classify organisms. In this work, we present CollembolAI, an open‐source prototype for a computer vision workflow. It includes a hardware system for acquiring high‐resolution pictures of soil species samples in fluid and a deep learning‐based application (Faster R‐CNN with Slicing Aided Hyper Inference) to train and evaluate models for the detection and classification of animals on those pictures. We evaluated the workflow using a mix of specimens belonging to 12 species of springtail and mite, picked from our taxonomic collection. Specimens were photographed multiple times under various angle of views. The model was trained using 5671 views on specimens on 30 images and tested on 442 views from new specimens on six images. CollembolAI is affordable, simple to build and allows the rapid digitization of mesofauna samples. Our deep learning model achieved a Precision of 0.940, Recall of 0.918 and a mAP@0.5 (Pascal VOC) of 0.868. The model showed a lower Recall for one species, but was performant on all others. Our prototype offers an operational workflow for the creation of soil fauna picture datasets needed to develop efficient deep learning‐based classifiers. The applications are numerous, for example, collection digitization, soil biodiversity analysis and monitoring, or automatic assessment of mesofauna‐based bioindicators. Computer vision is a rapidly emerging tool to handle efficiently the complexity of biodiversity and is already successfully used for plants and vertebrates recognition of pictures. It is on the way to become a major asset for dealing with invertebrate diversity. The code and setup instructions are available on Github.

BRACS: A Dataset for BReAst Carcinoma Subtyping in H&E Histology Images.

Breast cancer is the most commonly diagnosed cancer and registers the highest number of deaths for women. Advances in diagnostic activities combined with large-scale screening policies have significantly lowered the mortality rates for breast cancer patients. However, the manual inspection of tissue slides by pathologists is cumbersome, time-consuming and is subject to significant inter- and intra-observer variability. Recently, the advent of whole-slide scanning systems has empowered the rapid digitization of pathology slides and enabled the development of Artificial Intelligence (AI)-assisted digital workflows. However, AI techniques, especially Deep Learning, require a large amount of high-quality annotated data to learn from. Constructing such task-specific datasets poses several challenges, such as data-acquisition level constraints, time-consuming and expensive annotations and anonymization of patient information. In this paper, we introduce the BReAst Carcinoma Subtyping (BRACS) dataset, a large cohort of annotated Hematoxylin and Eosin (H&E)-stained images to advance AI development in the automatic characterization of breast lesions. BRACS contains 547 Whole-Slide Images (WSIs) and 4539 Regions Of Interest (ROIs) extracted from the WSIs. Each WSI and respective ROIs are annotated by the consensus of three board-certified pathologists into different lesion categories. Specifically, BRACS includes three lesion types, i.e., benign, malignant and atypical, which are further subtyped into seven categories. It is, to the best of our knowledge, the largest annotated dataset for breast cancer subtyping both at WSI and ROI levels. Furthermore, by including the understudied atypical lesions, BRACS offers a unique opportunity for leveraging AI to better understand their characteristics. We encourage AI practitioners to develop and evaluate novel algorithms on the BRACS dataset to further breast cancer diagnosis and patient care. Database URL: https://www.bracs.icar.cnr.it/

Input Digitization of the Manufacturing Industry and Carbon Emission Intensity Based on Testing the World and Developing Countries.

Facing the increasingly deteriorating climate, carbon emission reduction has become a global consensus. In particular, as an industry with very serious pollution emissions, the manufacturing industry is under enormous pressure to reduce environmental consumption. At the same time, against the background of rapid digitization development, the production and organization of the manufacturing industry have greatly changed, which also provides new research ideas for global carbon emission reduction. Based on the panel data of 40 major economies in the world, this paper calculates the degree of input digitization of the manufacturing industry using the input–output method and constructs a triple fixed effect model to analyze the impact of manufacturing’s input digitization on its carbon emission intensity from the perspective of the world and developing countries. The research finds that, first, on the global level, input digitization significantly reduces the carbon emission intensity of manufacturing, and the effect of carbon reduction increases gradually over time, with a noticeable industry spillover effect. Second, the test results from developing countries show that the relationship between digital input from developed countries and manufacturing’s carbon intensity in developing countries presents an inverted U shape. Third, heterogeneity analysis shows that digital input has the most obvious effect on carbon reduction in the pollution-intensive manufacturing sector. Tracking the sources of digital input, it is found that digital input from high-tech economies has the most obvious effect on carbon reduction. The paper takes the lead in clarifying the impact of digitization on carbon emissions from the manufacturing sector, expands the existing research on the digital economy and the environment, and also makes a theoretical contribution to global carbon emission reduction.

Use of Technology for Health-Related Tasks among Older Adults: Trend Analysis of Pre-&-during COVID

The rapid digitization of health care during the Covid-19 pandemic has increased the concern of the ‘digital divide,’ particularly for older adults. This study captures the trend of technology use among older populations before and during the Covid-19 pandemic. The study also measures the impact of the pandemic, healthcare technologies, and health status on older adults’ likelihood of communicating with the doctors, making independent treatment decisions, and achieving health-related goals. According to the study, older adults during the Covid-19 pandemic were less likely to communicate with their doctors or achieve their health-related goals by a factor of 1.158 and 1.130, respectively. Older adults who had depression were more likely to make independent treatment-related decisions by a factor of 0.744. We noted an increased usage of mHealth appli- cations and the internet during the Covid-19 pandemic. However, fewer people had access to smartphones and tablet computers. We also reported a significant increase in the proportion of older adults who did not use or understand online medical records over the years. The study emphasizes that as more older adults adopt technology, it is imperative to consider human factors’ methodologies and considerations. Authorities should consider technology affordance and affordability for patients across various socio-economic gradients and with different physical and cognitive capabilities.

Artificial intelligence in healthcare: Should it be included in the medical curriculum? A students' perspective.

The application of artificial intelligence (AI) in healthcare has increased due to rapid digitization and integration of computer science in all fields. However, the outcome in relation to patient treatment and healthcare delivery is not that visible. The reasons could be non-availability of data, lack of computerization and financial constraints. Besides this, the lack of appropriate teaching at undergraduate level about AI and its medical applications could be an obstacle. Including AI in medical school curriculum and collaboration with faculties of computer science can augment the knowledge of medical students about AI at the graduate level for better application in the real world. This will help the medical profession to prepare their younger fraternity for the future in AI.

MODELING OF THE LOGISTICS SYSTEM OF THE ENTERPRISE IN THE CONDITIONS OF THE DIGITAL ECONOMY

In a globalized world characterized by technological changes, interactions between economic and social actors are crucial to exploit market opportunities and maximize resource efficiency. The digital transformation of the economy creates the prerequisites for the emergence of technological tools with fundamentally new properties, which are driven by the industrial implementation of artificial intelligence technologies, cloud computing and other innovative products. Production and logistics systems that support the life cycle of promising technical systems are also becoming active components of a single network of intelligent machines operating on the basis of Internet technologies. The problems of logistics remain relevant, because the successful functioning of any organization and its competitiveness directly depend on the competent interaction of all subsystems of the enterprise, including the logistics one. Organizations that cannot adapt to today’s information exchange and business process management requirements will find it harder to add value to their products and services. Digital transformation is a leading trend that reflects the development vector of the economy and society as a whole. The implementation of digital technologies in the logistics processes of the enterprise should be considered as an integral part of the development of the logistics system and the enterprise in general in modern conditions. The implementation of modern digital technologies in logistics activities leads to changes in business models and strategic planning; improves interaction between all participants of the logistics process; increases the productivity of activities and, as a result, increases the competitiveness of logistics enterprises in the market. In the conditions of rapid digitization, there is a need to master current delivery channels and formats, analyze big data, automate processes, implement blockchain and robots. The logistics industry is becoming one of the drivers of digitalization.

Сучасний стан та перспективи підвищення функціональності доповненої реальності за допомогою нейронних мереж

The dynamics of the development of modern society and the rapid breakthrough of the technological component led to the need to interact with fast-changing and client-oriented information in real time. This need is met through the use of augmented reality technology, which allows users to interact in real time with both the real physical and virtual digital worlds. The rapid digitization of human existence has provoked an exponential increase in the amount of existing data, thereby posing new challenges to the scientific community. At the same time, the technology of deep learning, which is successfully applied in various fields, has a rather large potential. The purpose of this study is to present the potential of combining technologies of augmented reality and deep learning, their mutual improvement and further application in the development of modern highly intelligent programs. The work briefly provides an understanding of the concepts of augmented and mixed reality and also describes the technology of deep learning. Based on the literature review, relevant studies on the development of augmented reality applications and systems using these technologies are presented and analyzed. After discussing how the integration of deep learning into augmented reality increases the quality and efficiency of applications and facilitates the daily life of their users, conclusions and suggestions for future research are provided.

Beartooth: Nuclear material testbed with MBSE and digital twin

AbstractDigital engineering can fundamentally change the construction and operation of complex projects. Traditional engineering teams operate in siloed tools and disparate teams. Throughout a project lifecycle, data is translated manually or over brittle point‐to‐point connections, which increases the risk of silent errors. These potential errors can cascade across the effort, resulting in significant project delays and cost overruns. Furthermore, traditional engineering projects are not designed for the rapid digitization that allows for advanced analytic tools. Digital engineering can create a cohesive data “source of truth” to ensure a project is designed for the digital future. There is a need for a standard toolset to normalize and integrate project datasets. Idaho National Laboratory (INL) has developed DeepLynx, a crucial tool to mitigate this data management problem. This paper introduces INL's digital engineering approach and provides a concrete example of a digital engineering design effort currently taking place with Beartooth, a new nuclear material processing testbed project. This paper will provide the benefits, challenges, and lessons learned in using digital engineering on this complex system. The digital engineering approach is utilizing model‐based systems engineering, extended reality, and a digital twin. Finally, this paper will discuss the new possibilities provided by using a digital thread and twin during future operation of a nuclear fuel cycle testbed.

Introduction. Confronting the Challenges of the 21st Century

Introduction. Confronting the Challenges of the 21st Century

Art Research Based on Machine Learning and Artificial Intelligence

In this paper, machine learning and artificial intelligence are applied to art research to improve the intelligence of art research. This study concludes that the Gaussian homomorphic filter has the best processing impact in the image homomorphic filtering stage by comparing the processing effects of Gaussian homomorphic filter, Butterworth homomorphic filter, and exponential filter. Moreover, this study uses median filtering to eliminate salt and pepper noise in images and designs and implements a rapid digitization system for art works based on three-dimensional reconstruction. In addition, in order to improve the time efficiency of the system and the digital quality of art works and optimize the SIFT feature matching speed, this study proposes a relative position-based SIFT feature fast matching algorithm. Finally, this study verifies the effectiveness of the method proposed in this study through experimental research. The results show that it has a certain effect on promoting the development of art research and the application of computer technology in the art industry.

Effects of the GIG economy on the workplace

Rapid digitization has disrupted withinside the labour marketplace. The economy is witnessing a paradigm shift in the team of workers, places of work and working systems withinside the age of Tech Next- Gen. Technology performed an essential role in galvanizing the scope of unbiased working systems regardless of the geographical boundaries. Independence & Flexibility became the brand-new mantra that has redefined that means of labour. This so-called GIG economy system has continually been prevailing, however, it grabbed eyeballs short growth during the last couple of years. The new tech worm ioT has caused a transformation in work area arena. This has caused clean demarcation among a conventional and non-conventional quarter of employment. The evolving desires of today’s operating populace, the struggle fare for the expertise and the globalization of the team of workers are only a few motives to kick largely begin the GIG economy system. However developing swiftly in Indian Labour marketplace and higher recognize its structure, operating preparations and advise a coverage alternate to any organizations that the authorities need to act as a facilitator and be a part of Industry and Academia via way of means of permitting numerous new platform in understanding gig economy.

Social Media and SMEs’ Performance in Developing Countries: Effects of Technological-Organizational-Environmental Factors on the Adoption of Social Media

Increasing globalization and rapid digitization across industries have led to greater international competition. Furthermore, the emergence of new innovation has created both challenges and opportunities for small and medium-sized enterprises (SMEs). SMEs have recently been attracted to social media applications to reach a larger audience, improve their relationship with potential customers, and retain existing customers. However, the scant focus has been devoted to comprehensively understanding the adoption of social media in the SME context in developing countries. This study investigates the effects of technological-organizational-environmental (TOE) factors on social media adoption and its effect on SME performance. Data was collected by generating online survey link. SmartPLS 3.3 was used for the path analysis of 381 SMEs. The findings revealed a significant effect of relative advantage, cost-effectiveness, compatibility, interactivity (technological), entrepreneurial orientation (organizational), and customer pressure (environmental) factors, and an insignificant effect of top management support (organizational) and competitive pressure (environmental) determinants on social media adoption. The study found a significant influence of social media on SME performance. This paper offers several implications for decision-makers, policy-makers, and scholars interested in social media and its use. It builds an empirical, integrated framework for SMEs in developing countries.