Digital Form Research Articles

The effectiveness of the formation of new digital services of JSC “Russian Railways” for the registration of transportation documents in the field of freight transportation

In recent years, the sector of freight and commercial work in railway transport has undergone global changes in the field of customer orientation. The purpose of the presented scientific research is to assess the formation of new digital services and services of JSC Russian Railways for the registration of transportation documents, the provision of contactless digital formats, which have become the main tool for interaction between the client, the rolling stock operator and the carrier. The algorithm of acceptance of empty and loaded wagons for transportation in digital format is presented, the relevance of the formation of new digital services of JSC “Russian Railways” for registration of transportation documents in the field of freight transportation is proved. The feasibility study for the reception of empty and loaded wagon traffic to the transportation process in the “Digital transceiver” format with the organization of combining professions is calculated in advance, using the example of the operation of the railway station of the Eastern Polygon of railways and adjustments are allowed in the process of implementing a similar design solution for other facilities.

Cross study analyses of SEND data: toxicity profile classification.

A SEND toxicology data transformation, harmonization, and analysis platform were created to improve the identification of unique findings related to the intended target, species, and duration of dosing using data from multiple studies. The lack of a standardized digital format for data analysis had impeded large-scale analysis of in vivo toxicology studies. The CDISC SEND standard enables the analysis of data from multiple studies performed by different laboratories. This work describes methods to analyze data and automate cross-study analysis of toxicology studies. Cross-study analysis can be used to understand a single compound's toxicity profile across all studies performed and/or to evaluate on-target versus off-target toxicity for multiple compounds intended for the same pharmacological target. This work involved development of data harmonization/transformation strategies to enable cross-study analysis of both numerical and categorical SEND data. Four de-identified SEND datasets from the BioCelerate database were used for the analyses. Toxicity profiles for key organ systems were developed for liver, kidney, male reproductive tract, endocrine system, and hematopoietic system using SEND domains. A cross-study analysis dashboard with a built-in user-defined scoring system was created for custom analyses, including visualizations to evaluate data at the organ system level and drill down into individual animal data. This data analysis provides the tools for scientists to compare toxicity profiles across multiple studies using SEND. A cross-study analysis of 2 different compounds intended for the same pharmacological target is described and the analyses indicate potential on-target effects to liver, kidney, and hematopoietic systems.

Feedback-free starbursts at cosmic dawn. Observable predictions for JWST

We extend the analysis of a physical model within the standard cosmology that robustly predicts a high star-formation efficiency (SFE) in massive galaxies at cosmic dawn due to feedback-free starbursts (FFBs). This model implies an excess of bright galaxies at $z 10$ compared to the standard models based on the low SFE at later epochs, an excess that is indicated by JWST observations. Here we provide observable predictions of galaxy properties based on the analytic FFB scenario. These can be compared with simulations and JWST observations. We use the model to approximate the SFE as a function of redshift and mass, assuming a maximum SFE of $ max 1$ in the FFB regime. From this, we derive the evolution of the galaxy mass and luminosity functions as well as the cosmological evolution of stellar and star-formation densities. We then predict the star-formation history (SFH), galaxy sizes, outflows, gas fractions, metallicities, and dust attenuation, all as functions of mass and redshift in the FFB regime. The major distinguishing feature of the model is the occurrence of FFBs above a mass threshold that declines with redshift. The luminosities and star formation rates in bright galaxies are predicted to be in excess of extrapolations of standard empirical models and standard cosmological simulations, an excess that grows from $z 9$ to higher redshifts. The FFB phase of $ is predicted to show a characteristic SFH that fluctuates on a timescale of $ The stellar systems are compact ($ at $z 10$ and declining with $z$). The galactic gas consists of a steady wind driven by supernovae from earlier generations, with high outflow velocities FWHM low gas fractions ($<\!0.1$), low metallicities ($ and low dust attenuation UV 0.5$ at $z 10$ and declining with $z$). We make tentative comparisons with current JWST observations for initial insights, anticipating more complete and reliable datasets for detailed quantitative comparisons in the future. The FFB predictions are also offered in digital form.

Harmonized Database of Western U.S. Water Rights (HarDWR) v.1

In the arid and semi-arid Western U.S., access to water is regulated through a legal system of water rights. Individuals, companies, organizations, municipalities, and tribal entities have documents that declare their water rights. State water regulatory agencies collate and maintain these records, which can be used in legal disputes over access to water. While these records are publicly available data in all Western U.S. states, the data have not yet been readily available in digital form from all states. Furthermore, there are many differences in data format, terminology, and definitions between state water regulatory agencies. Here, we have collected water rights data from 11 Western U.S. state agencies, harmonized terminology and use definitions, formatted them for consistency, and tied them to a Western U.S.-wide shapefile of water administrative boundaries.

Automated Invoice Data Extraction: Advancements and Challenges in OCR-Based Approaches

The Invoice Recognition System (IRS) is an innovative system that is poised to revolutionize automatic data extraction from invoices. The IRS expertly translates handwritten and printed invoice data into efficient digital formats, utilizing cutting-edge data capture techniques and Optical Character Recognition (OCR) technology. The IRS, built for businesses with huge invoice volumes, aims to significantly enhance financial and administrative productivity by reducing errors and eliminating the need for manual data entry. The system makes advantage of OCR precision to ensure that information is thoroughly interpreted and extracted, enhancing data accuracy and processing speed. The IRS appears to be a useful tool for improving complex financial and administrative procedures, thanks to its adaptability to various invoicing forms. Keywords: invoice recognition system,OCR(optical character recognition),Automation,Invoices.

Implementation of Black Box Testing with the Application of Equivalence Partitioning Techniques in the M-Magazine Android Application at Semen Gresik High School

This research aimed to improve the M-Magazine application at Semen Gresik High School to enhance its usability for students and teachers. The study focused on developing a digital platform called "mading" to improve the dissemination of information within educational institutions. The research addressed security issues and limitations associated with physical media by transitioning from traditional wall-mounted magazines to a digital format. The research followed a three-phase approach consisting of preparation, analysis, and implementation, which involved a literature review, data collection, system design, and testing. The resulting digital Magazine system offers a centralized platform for schools to manage and share information. Students can actively contribute by submitting content through the website. The system provides features to sort, filter, and publish information, ensuring timely and relevant updates. The findings demonstrated that the Digital Magazine effectively improves information dissemination in schools by providing better security, accessibility, and efficiency than traditional methods. This technology-powered platform empowers schools and students to share knowledge and stay informed.

The Digital Fabric of Nationalism: How Social Media Weaves Banal Nationalism into Everyday Life

In the digital era, social media platforms such as Facebook, Twitter, and Weibo have transcended their roles as mere communication tools, emerging as pivotal arenas for the expression and amplification of banal nationalism. This paper explores how these platforms embed subtle nationalistic sentiments within the everyday online interactions of millions, thereby enhancing and reinforcing users sense of national identity. Through qualitative analysis of various social media posts and a comprehensive literature review, this study investigates the mechanisms through which these digital platforms perpetuate nationalistic narratives. Additionally, the paper employs visual data analysis of social media content to demonstrate the prevalence of national symbols and narratives, particularly during significant national events. The findings indicate that social media platforms not only reflect but actively shape societal trends through algorithm-driven content curation that promotes emotionally charged nationalistic posts. This paper underscores the need for a nuanced understanding of how digital environments influence national identity construction and the subtle ways in which they foster a digital form of banal nationalism.

Old Permic Universal Dependencies Treebank

Old Permic, also known as Old Komi, is an extinct variety of Komi that was spoken in the late Middle Ages in the lower Vychegda river basin in Northeastern European Russia, in an area that currently is not Komi-speaking. This language variety is attested in fragmentary records from the 14th to 17th century written both in the Old Permic alphabet and in Cyrillic. These records are of significant importance for research on the history of the Komi language. Here we introduce our attempt towards a new Universal Dependencies treebank that will eventually contain the existing corpus of Old Permic in a structured and CoNLL-U annotated format. This will be the first time this material is being made openly available in digital format, and our contribution describes the current state of the art and remaining challenges.

Preservasi naskah kuno Gandoang melalui kegiatan digitisasi

Introduction. Ancient manuscripts are one of the nation's many cultural heritages with historical significance. As a result, conservation measures must be implemented, one of which is the transfer of digital media. The purpose of this study is to learn about the efforts made to transfer Gandoang ancient manuscripts to Ciamis. Data Collection Methods. This study employs a qualitative case study approach, with data collected through observation techniques and semi-structured interviews with three informants. Data Analysis. Through Miles and Hubberman data analysis techniques; researchers organize, organize, and categorize them. Result and Discussion. The findings of this study indicate that, as part of the management's effort to preserve the Gandoang ancient manuscripts in collaboration with Tapak Karuhun Nusantara Foundation, converting them into a digital form into an e-book can be considered effective and efficient. The ancient manuscripts in this fragile state can now be preserved, allowing their existence to be used for a long time. Conclusion. Because of the internet, which allows everyone to read it wherever and whenever they want, the Gandoang e-book has proven to be more popular in the public. However, many ancient manuscripts in the Ciamis still require the attention of various parties due to their endangered state.

Indexing with Excel, Part 4. Conversions 2

The first two articles in this series explained how Excel can be set up for indexing and how checks can be done using Excel. The third article gave an overview of how to transfer data from a dedicated indexing program (DIP) or an embedded indexing program like Word into Excel data. The current article examines the conversion process further by explaining how to convert an index from a digital format into Excel.

Use of Digital Media in the Public Sector

Abstract In the current context, more and more public services are offered in digital format, the trust of users in these online environments is essential to ensure the adaptation and use of these services efficiently and effectively. The main aim of the paper is to investigate and identify the factors that positively or negatively influence users’ trust in public sector digital environments. The paper will refer to the way users interact with the digital services that the local public administration makes available. Based on the presented case study, it was possible to analyze the degree and mode of interaction of citizens with these online services. It could be concluded that the essentiality of increasing users’ trust in digital environments in the public sector, by improving the accessibility, security and quality of these services, is crucial for promoting their use and for encouraging citizens’ participation in the decision-making and administrative process. The most important factors that affect users’ trust in digital environments in the public sector are the transparency of information, but also the security of personal data, the quality of information and the accessibility of digital platforms for effective use, respectively services and information to be up-to-date, easily accessible and the platform to be easy to navigate to streamline time spent on the platform or work time for public sector employees.

Recursive Filtering Under Probabilistic Encoding-Decoding Schemes: Handling Randomly Occurring Measurement Outliers.

This article focuses on the recursive filtering problem for networked time-varying systems with randomly occurring measurement outliers (ROMOs), where the so-called ROMOs denote a set of large-amplitude perturbations on measurements. A new model is presented to describe the dynamical behaviors of ROMOs by using a set of independent and identically distributed stochastic scalars. A probabilistic encoding-decoding scheme is exploited to convert the measurement signal into the digital format. For the purpose of preserving the filtering process from the performance degradation induced by measurement outliers, a novel recursive filtering algorithm is developed by using the active detection-based method where the "problematic" measurements (i.e., the measurements contaminated by outliers) are removed from the filtering process. A recursive calculation approach is proposed to derive the time-varying filter parameter via minimizing such the upper bound on the filtering error covariance. The uniform boundedness of the resultant time-varying upper bound is analyzed for the filtering error covariance by using the stochastic analysis technique. Two numerical examples are presented to verify the effectiveness and correctness of our developed filter design approach.

The Concept of Electronic Pensioner in Some Countries Versus Romania

We aim to introduce the concept of e-pensioner (EP) with the intention of having this term used as a document within the European Union’s strategy on Artificial Intelligence (AI) for the period 2023-2027 and after implemented into the legislation of member countries. The relationship between older generations and emerging forms of digitalization and artificial intelligence is the focal point, aiming to provide an easily approachable dimension for pensioners. This article presents an analytical framework and approaches for integrating pensioners into the digital era. Following the exposition of theoretical foundations, the article delineates the use of pensioner cards in select countries worldwide. The intersection of pensioners with the digital era proves to be a fertile entry point for examining regulatory ordinances in the digital realm. A novel digital form, the AI-based digital portal, involves a technique of facial authentication for pensioners to send digital life certificates. Two key factors are named across all examined countries. The primary driver of digital transformation is propelled by the desire to enhance the efficiency and efficacy of public administration, which becomes particularly crucial as populations age, leading to increased demand for social services and competition for limited resources in the developed public sector. The innovative application of technology presents opportunities for streamlining processes, enhancing productivity, and reducing costs while concurrently improving service quality. The use of artificial intelligence (AI) in the management and administration of public pension funds stands for a natural progression of technology in the public domain. In an environment characterized by complexity and volatility, AI can provide a level of analysis and prediction that exceeds human ability. Presently, there exists a wide array of AI-powered tools for object detection, natural language processing, understanding and inference, optical character recognition, predictive analytics, anomaly detection, noise elimination, model forecasting, recommendation systems, and monitoring and observability.

IDENTIFICATION OF SIGNIFICANT TEMPORAL FEATURES FROM PHOTO PULSE PLETHYSMOGRAM FOR PREDICTION OF HYPERGLYCEMIA

The increase in diabetic class population is witnessed every year and hence frequent need of checking blood glucose levels is highly required in both diabetic and healthy subjects. This requirement has led many researchers to develop efficient, accurate and easy estimation of blood glucose level without painful blood pricking or extraction. In line with this objective, this study is an effort for waveform analysis of autonomic response of photo pulse plethysmogram (PPG) and to evaluate PPG features that may provide better non-invasive detection of the disease. A total of 300 (150 diabetic and 150 control) subjects aged more than 18 years are considered for this study. Relevant patient details were obtained, and finger PPG recording in digital form was performed for 5 min with the digitization sampling rate of 200 sample points per second. After signal baseline correction, features are calculated from averaged normalized PPG and its first and second derivatives. A total of 41 features were derived from normalized PPG pulse and its derivatives for the assessment of hyperglycemia. But in practice, computation of many features is time-consuming and truly a tedious job for any model design. Further, model performance and accuracy are affected significantly. Applying six different statistical and machine learning methods for the identification of important features, 20 features were identified out of 41 features whose values are highly significantly different for control and study (diabetic) groups. This work was focused on feature extraction stage for a PPG-based diagnostic system. Though our study is aimed to identify significant features that can discriminate between diabetic and control groups non-invasively, these features have the potential for much clinical assessment and other pathological disorders without any doubt.

Смех и нормативно-банальное: вызов цифры

The habitual and normal is not laughable. What is laughable is untenable deviation. Thus, it is either the triumph of the normative or its failure in the face of a new desired norm that is consolidated in laughter. In this regard, laughter expresses the dynamics of comprehension, socialization, and the development of subjectivity; it is the ability to transcend culture inherent in it. Meanwhile, laughter itself appears to be normative in relation to appropriateness: topic, time, place, channel and measure (in relation to art — genre). In the context of digital communication formats, the problem of appropriateness is exacerbated. It does not come down to the issue of recognizing the laughable. There is a possibility of a sharp reduction in the field of the implementation of laughter culture. The work was supported by the Russian Science Foundation, grant No. 22-18-00591 “Pragmasemantics as an interface and operational system of meaning formation”.

Exploring the Impact of Digital Platforms on Publishing: A Bibliometric Analysis

Abstract Platformization is a phenomenon arising from the process of digitalization and affects businesses of all types throughout the world. While platformization closely relates to digital business models, it also influences the traditional models to some extent, concerning the marketing and distribution functions. This paper focuses on the implications of the new media on the generation, dissemination, and reception of content in publishing. Specifically, the study examines the effects and implications of the platformization processes, and the role played by digital ecosystems in the value chain of the publishing business and the structures of the book market. For the current study, the research carries out a network analysis of scholarly literature on the integration of digital platforms in publishing using VOSviewer. It declared to provide an understanding of the field’s conceptual directions, determine key articles, and depict the developmental process of this phenomenon. The paper contributes to the understanding of the primary discourses; the literature review reveals the research gaps and potential development. The contribution of this research shall be useful for both theorists and practitioners in the field. It can help practitioners analyze the current processes in the publishing industry’s transition to digital formats and inform policy decisions. It can also help small and medium companies within creative industries that possess characteristics that are akin to publishing and other businesses clustered within the book market niche category. Given that current trends and potential directions for development and innovation in today’s rapidly developing digital environment are traced and practical recommendations and further research questions are outlined in this study, it helps to get a detailed understanding of how platformization in the context of the publishing industry is addressed in the academic literature.

3D scanning techniques in power engineering

Information about component geometry is a key parameter for assessing residual life and monitoring degradation processes during the life cycle of a technology. High-precision optical measurement systems are complex metrology devices that enable the collection of complex data on the physical properties of components and their rapid evaluation in CAD-based programs. These solutions offer an analysis of changes in component characteristics over time and comparing them with as-built documentation. The quality of production can be evaluated by comparing the condition of the equipment with the product documentation or monitoring the influence of service conditions on the degradation of the equipment and the trend of future development of defects. All this in digital form of data, which enables new progressive approaches to repair and maintenance programs of monitored equipment. The use of advanced metrology and diagnostic systems and the procedures they offer can reduce the time required for measurement by conventional methods and multiply the data yield from metrology, which in conjunction with modern IT technologies can detect new degradation mechanisms and increase safety service and extend projected lifetime. Up-to-date technology data can significantly save on maintenance costs or even eliminate maintenance procedures. It also provides important data for the setup of LTO.

Efficient site selection for clinical trials using simulated annealing.

1558 Background: Identifying sites with eligible patients for multi-site oncology clinical trials is challenging given increasingly complex inclusion/exclusion criteria, limited site resources, and the need to ensure diversity in trials. This is a complex systems problem with many factors that present nonlinear behaviors. Given manifold combinations of sites, research capabilities, and study characteristics, artificial intelligence solutions may help research sites and sponsors optimize site selection to achieve enrollment, speed, and diversity of goals. We report on one of the first deployments of a multi-AI model solution to optimize site selection for an ongoing clinical trial. Methods: The clinical trials were translated into a standardized digital form expressed as rules fully encompassing the inclusion and exclusion criteria. A patient cohort was created from the criteria using the ConcertAI oncology research database, including site affiliations. The sites had numerical features specific to the protocol indication, such as physician count and projected patient count. Each site was scored by its features with the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to create higher alignment to the best matched sites. Feature weights allowed TOPSIS to emphasize desirable attributes in an interpretable way. A simulated annealing algorithm, adept with nonlinear objectives, explored site combinations, yielding a high-scoring, constraint satisfying solution. Independent simulations measured convergence and provided a distribution of solutions. Shapley analysis clarified site contributions to score and constraints. The implementation was compiled and parallelized. Results: Utilizing a Multiple Myeloma clinical trial protocol with 7 criteria, we formed a cohort of 15,881 patients across 1,246 US clinical trial sites. Each site had 12 features. The weights optimized patient diversity while enrolling at least 10 patients per month across all sites to achieve the targeted study accrual timeline. The result was a set of 3 sites enrolling 12 patients per month with 51% diversity, in agreement with the optimal solution obtained through detailed, multi-week, manual analysis. As constraints increased, and exact verification became impractical, convergence was gauged by decreasing variance in independent solutions. Conclusions: Our study introduced a robust, efficient, and interpretable approach to clinical trial site selection. It addressed the challenges posed by increasingly complicated protocols, requirements for study participant diversity, and heterogeneous site features. The multi-AI model scalability underscored its practical utility in streamlining the site selection process for clinical research networks, academic centers, industry sponsored trials, cooperative group studies, and investigator-initiated studies.

MTWSI-Net: Towards Improved Multi-Task Whole Slide Image Classification with Contrastive Learning

Pathology is a digital technology for the capture and analysis of high-resolution Whole Slide Images (WSIs). WSI entails scanning glass pathology slides, typically containing tissue samples, into a digital format. This facilitates comprehensive digital viewing, analysis, and interpretation by pathologists. Despite the undeniable utility of this method, the inherent time-consuming and labor-intensive nature of traditional pathology image analysis, which is heavily reliant on expert pathologists, is well-known. Recent years have seen a surge in research aiming to address these challenges through the development of automated systems using machine learning approaches. While promising, such systems often exhibit bias towards specific datasets and struggle to transition effectively to real-world scenarios. For this reason, there is a need to establish a uniform machine learning training approach for generating more robust and consistent results. In this paper, I introduce a contrastive learning-based multi-task whole slide image classification system. The proposed system excels at extracting consistently reliable features for identical cancer categories, thereby enhancing accuracy in downstream tasks. Through extensive experiments, the results demonstrate that the proposed system outperforms pre-existing state-of-the-art machine learning models. I expect that the proposed system can significantly contribute to pathologists by offering valuable cancer screening capabilities in WSIs.

The well-being benefits of virtual art galleries: Examining the roles of emotion, immersion, and individual differences

A wealth of research suggests that engaging with visual art and visiting art museums is beneficial to flourishing; however, less is known about the potential benefits of digital forms of engagement. An emerging literature provides preliminary evidence of the benefits of digital art engagement, but additional research on mechanisms and potential moderators of the benefits is necessary. The present study examines the impacts of repeated visitation to a virtual art gallery to address three questions: 1) Do well-being, emotion, and immersion differ between those in a digital art gallery versus those reading about art?; 2) Do personality and interest in art influence virtual art gallery visit qualities (i.e., emotion and immersion)?; and 3) Do visit qualities and individual differences predict well-being? A sample of 890 U.S. adults was recruited from Prolific. The findings suggest that: 1) People in a virtual gallery show greater well-being, immersion, and aesthetic emotion than those reading about art; 2) Openness to experience is most strongly linked with visit qualities; and 3) Immersion, positive and aesthetic emotion, extraversion, and neuroticism are associated with well-being. This work suggests that repeated engagement with art in a digital format has benefits and that future research should continue to examine the underlying mechanisms and ways digital art experiences can be best designed to be effective well-being interventions.