Reviewerly/exHarmony huggingface dataset:
Recognition of static or dynamic LIBRAS words in complex background environments

The present article seeks to present a viable methodology for the recognition of static and dynamic expressions of the Brazilian sign language, LIBRAS, in environments whose background is complex. For this, the Keras library, which is part of TensorFlow, was used as a training tool and the OpenCV library, together with MediaPipe for the recognition of incoming frames. Concluding, therefore, with the use of perceptron neural networks for machine learning.
Psychodynamics of work: Bibliometric mapping in 53 years of publications indexed in Scopus and agenda for future studies

The study aimed to map the bibliometric profile of publications on Psychodynamics of Work and propose an agenda for future studies. This was a quantitative research, using bibliometric methods proposed by Zupic and Cater (2015). The 195 publications located in Scopus, from 1970 to 2022, were analyzed using the VOSviewer software. For future studies, it is suggested to relate PDT with technology and precarious work, the future of work, diversity management, sustainable work, remote work, as well as Covid-19 and work.As for the subjects, it is suggested to conduct research with other health professionals, with informal workers, self-employed workers, casual workers, dangerous professions, liberal professionals, volunteers, interns, workers in the economy of the sea, teachers and outsourced workers.
GOP-LeS: Practical Learning Innovation in Managing Office Administration in Groups

This study aims to produce office simulation media in groups for archives, finance, public relations protocol, and correspondence subjects. The design of this study adopts the Borg and Gall model which consists of 10 stages. This research was conducted in Malang City at the Office Management and Business Service Vocational High School. The trial subjects involved 15 students in the small group trial and 50 students in the large group trial. This research activity also involves expert valiators to determine the feasibility and validity of the products being developed. The results of this research and development are learning media called GOP-LeS that are feasible and valid to be applied in the learning process of managing office administration practices. This is based on the results of small group trials which obtained an average of 86% and large group trials obtained an average of 87%. While the results of the expert validator obtained an average score of 88%. So it can be concluded that the GOP-LeS learning media can be used as an alternative media for the practice of managing office administration in the Department of Office Management and Business Services.
Performance and Pleasure: Exploring the Perceived Usefulness and Appeal of Physical Activity Data Visualizations with Older Adults

Wearable activity trackers hold the promise of making older adults aware of their levels of physical activity (PA), encouraging them to remain or become physically active. However, little is known about older adults’ preferences regarding data visualizations of PA, which is of concern as many of the currently implemented visualizations strongly emphasize performance. In our work, we present findings from a study (N = 44) in which we combined semi-structured interviews and an online survey to explore different approaches towards visualizing PA data for older adults. Through thematic analysis and statistical analysis, we highlight that visualizations’ perceived usefulness and appeal is individual and mediated by the lived experiences of late life, and that the potential of performance and pleasure can be leveraged to be complementary. On this basis, we discuss design opportunities for visualizations of PA data specifically addressing the needs of older adults from the perspective of PA in late life.
Cloud cybersecurity will draw tighter scrutiny

The reliance of public and private organisations on cloud infrastructure is rising
Peran Perpustakaan Sekolah Sebagai Sumber Belajar Siswa di SDN Bagus 2 Marabahan

This study aims to describe the implementation and obstacles in the role of the library as a learning resource at SDN Bagus 2 Marabahan.This research is a qualitative descriptive study. The informants of this research are school principals, administrators, teachers and students. Data collection techniques used are observation, interviews, and documentation. Data analysis uses the steps of data collection, data presentation, and drawing conclusions. Data validity testing techniques using triangulation, reference materials, and member checks. The results of the research show that the implementation of library management as a learning resource has not run optimally. Some aspects of library management still have many shortcomings, such as buildings that do not meet the requirements, equipment and supplies that are not yet complete, collections of library materials are still small, services are still not supervised, and there is no clear library code of conduct. Obstacles to the library as a source of learning are inadequate building or room facilities, limited book collections, incomplete tools and equipment, and the limited quota of assistance provided by the government through the education office.
N.A. Rubakin and the Russian Bibliographic Society

The article discusses aspects of cooperation of the outstanding figure of the book N.A. Rubakin (1862–1946) with the Russian Bibliographic Society in the 1910s — 1920s. The author analyzes the history of the publication of the scientist’s articles in the journal «Bibliograficheskiye izvestiya», reading his reports at the meetings of the society. The research was carried out based on the bibliographer’s archive materials kept at the Department of Manuscripts of the Russian State Library.
Bookselling infrastructure in Siberia and the Far East in 2019–2021 (based on the materials of the project «Cultural map of Russia. Literature. Reading»)

The article is based on the materials of the next stages of the project «Cultural map of Russia. Literature. Reading» the state of the bookselling infrastructure of the Siberian-Far Eastern region in 2019– 2021 and has been analyzed. The aggregate infrastructure of book distribution, the availability of bookstores are characterized. The leaders and outsiders among the subjects of the Federation of Siberia and the Far East have been identified. The main characteristics and features of the current state of the book trade in the region are summarized, the peculiarities of the adaptation of the elements of the bookselling infrastructure to the consequences of the pandemic are revealed. The ways of optimizing the development of book distribution in the Siberian and Far Eastern Federal Districts are determined.
General A.N. Kuropatkin’s personal library fund (based on a printed catalog)

The article first presents and analyses the printed catalog of books of the personal library of Lieutenant General A.N. Kuropatkin, published during the period when he was the chief and commander of the troops of the Trans-Caspian Territory, the head of the Trans-Caspian Military Railway (1890–1897). The book collection of A.N. Kuropatkin was not preserved as a single whole, the catalog of his library brought into scientific circulation allows you to reconstruct its fund in the indicated years. The printed works of A.N. Kuropatkin himself and included in his library are listed.
Рublishing of periodicals editions in Russia in the first half of 2022

The authors of the article provide the main statistics of the Russian printed periodicals output in the first half of 2022, analyzing the current state and trends in this sphere in Russia.
Personal chapter in the popular biobibliographic essays

The article deals with the features of the structure of the personal chapter (chapters-personalities) in modern popular bio-bibliographic essays. Prospects for further practical work on the creation of modern heads-personalities are outlined. It is told about the bibliographic manual of the modern sample which is currently being worked on. The research is based on more than half a century of recommendatory bibliographic activity of the Russian State Library. The material used for the study was the bibliographic production of this library, dedicated to fiction and first of all to the domestic literature.
Phishing Email Mitigation Technique Using Back-Propagation Neural Network for Cyber Space

Nowadays email is gaining significant popularity over the past years. Peoples use email as a one of the fastest formal mediums through which they are sending messages and exchanging some files. Due to tremendous use of email between peoples, the new serious threat comes into picture which will be malicious email. The malicious email can be phishing or spam email. Phishing email means financial loss or identity theft to the person who receive phishing email and through which he/she surrenders or gives his confidential information to the phisher, and spam means unsolicited bulk commercial email or advertising emails. The detection of phishing email is one of the crucial parts, and most of detection schemes are not intelligent as has to be. In this paper, we have proposed a new model for detecting phishing email through the use of artificial neural network (ANN). We have used multilayer feed-forward neural networks for phishing email detection, and both legitimate and phish emails are used for training and testing purpose. We have used optimum set of features which are always present in the phishing email, and using these features, we have got 99.79% accuracy in terms of email classification.
Comparative Study of Fraudulent Activities and Various Fraud Detection Techniques

Abstract: This study highlights the critical role that effective fraud detection systems play by examining the rising occurrence of fraud across industries, which is being driven by technological advancements. By examining a number of fraud categories, such as money laundering, cryptocurrency-related schemes, credit card fraud, and mortgage fraud, this study highlights the need for rigorous preventive measures. By carefully examining a wide range of detection techniques, including Support Vector Machines, Fuzzy Logic, Artificial Neural Networks, Hidden Markov Models, K-Nearest Neighbour, and Bayesian Networks, the research reveals the expanding toolset against fraudulent activity. Through a rigorous examination of applicable literature, creative cutting-edge methods, and astute investigations, the research highlights the crucial necessity of fraud detection systems across a variety of industries. The need for more innovation and interdisciplinary collaboration is highlighted by the discovery of knowledge gaps in real-time data analysis, handling unbalanced datasets, and resilient tactics against adversarial attacks. Our research also contributes to the development of strategies for preventing fraud, ensuring the dependability of financial institutions, and fostering confidence in a time of complex technological connections.
Supplemental Material: Formation and evolution of a magmatic system in the Indian passive margin: Insights from the Triassic Yumai Complex from the eastern Tethyan Himalaya

&lt;p&gt;Analytical methods and data: Text S1, Figure S1, and Tables S1 and S2. &lt;/p&gt;
AUTOMATIC TEXT SUMMARIZATION: PROBLEMS AND PERSPECTIVES

The present paper focusses on the automatic text summarization (AS), the analysis of linguistic problems related to it and the ways to overcome them, as well as on the perspectives of using some natural language processing computer programs. The author carries out a comparative analysis of two AS programs, MSWord2003 and Pertinence Summarizer, for literary, journalistic and scientific texts. The chosen methodology of comparative analysis allows not only to single out the peculiarities and limitations of each program, but also to make some general conclusions about the problems existing in the process of automatic summarization. The analysis of source texts and results of AS presented in the paper is focused on the correlation between the text genre and the process/result of AS. The analysis does not take into account such factors influencing the quality of summary as the length of the original text, the original language, the subject, etc. The primary hypothesis of the study was the assertion that the quality of automatic summarization of a text directly depends on the genre of this text. The obtained results made it possible to confirm this hypothesis and highlight the interdependence between the level of formalism in the text, which can be explained by its genre, and the pertinence of the summary. The conducted research showed that both AS programs are based, first of all, on morphological and, to a lesser extent, on morpho-syntaxic analysis of the source text. Furthermore, the issue of processing the implicit information available in the text, at the semantic and pragmatic level in particular, still seems unresolved. One of the possible ways to overcome this problem is the dynamic summarization of the text, which necessitates broader participation and involvement of the program user in the process of automatic summarization.
Framework for Assessing the Usability of Augmented Reality Applications for Construction Work

Visualizing real-world features along with digital textual data and virtual objects has made augmented reality (AR) technology attractive for commercial uses such as sales, manufacturing, and construction. AR application developers are designing new applications for a variety of purposes. New AR applications related to construction are becoming increasingly available to industry practitioners. It can be challenging for them to select a truly useful one from many existing AR applications through a trial-and-error approach that is time-consuming and costly. Therefore, a systematic evaluation procedure is desired to allow users to evaluate AR applications during their trial period without having to commit significant financial resources. This study aims to develop a framework that evaluates the usability of off-the-shelf AR applications. The authors proposed a framework for assessing the usability of construction-focused augmented reality applications based on the International Organization for Standardization 9241-11:2018 standard and other relevant works of literature. Using the proposed criteria, the authors examined the five most popular AR construction apps with the highest number of downloads and at least four-star reviews to validate the proposed framework. To validate the study, participants were recruited to evaluate applications and rank them in predefined categories, including effectiveness, efficiency, and satisfaction, using the proposed framework. Out of five applications tested, two applications, VisualLive and Gamma AR, were ranked as the first and second-best applications. The ranking is consistent with the expert review of the applications. The proposed framework helps in the selection of the most useful applications from a pool of off-the-shelf software. It enables users in the construction industry to make an informed decision about AR application selection before committing time and money to acquisition and implementation.
Dyslexia recognition by handwriting using Convolutional Neural Networks

This project focuses on using technological tools to describe and classify children's handwriting behaviors. This in order to help a proper diagnosis of dyslexia. It was necessary to collect all the necessary information on Developmental Dyslexia. Thus, studying the origin, characteristics, diagnosis, treatments, etc. There are several tests to carry out a diagnosis. These are focused on the study of the phonetic behavior of the voice during a reading. In addition, reader-reader tests, among others. Given this, it has been decided to develop a mobile application, which performs readingwriting tests in participants with and without dyslexia. Thus, finding a large number of patterns that can be studied, mainly related to Dysgraphia, Dysortography and Dyscalculia. After collecting the images from the tests carried out, the second part is to find an artificial intelligence model that allows them to be classified. 2 models were used: convolutional model 1 and the Unet model. These models gave promising results. Finally, the need to continue collecting more images of reading-writing tests in patients with dyslexia was demonstrated.
Victimization study of cybercrime related fraud and scams in the city of Mar del Plata, Argentina.

The digital transformation of organizations, accelerated by the COVID 19 pandemic, forced millions of people to use different technological tools to continue carrying out their daily activities, such as making purchases, banking procedures or maintaining social interactions. This situation generated an increase in cybercrime, specifically cyber scams and cyber fraud, however, in Argentina there are no official statistics in this regard. This paper presents a victimization study carried out during the year 2021 in the city of Mar del Plata, Argentina in order to investigate and collect information on the commission of crimes mediated by technology, in order to contribute to the design of crime policies. public safety, as a first situational diagnosis.
Artificial Intelligence and Blockchain for Copyright Infringement Detection

Copyright infringement suggests the unauthorized use of protected works, which includes literary, artistic, dramatic, musical works, and sound recordings without the consent of the owner of the work. Various Technologies used effectively to achieve the objective of detecting copyright infringement include Artificial Intelligence (AI) and Blockchain technology. This study explores the feasibility of the additive technological intervention in the Intellectual Property (IP) domain for the protection of rights. In earlier studies, the accuracy of Artificial Neural Networks (ANN) in detecting a specific data string in a limited-length document has been recognized and this study analyses the use of ANN in detecting infringement of literary works on the websites. Additionally, the use of Convolutional Neural Networks (CNN) for the detection of infringement in audio and video content using the camera model identification technology, has been evaluated. Moreover, the use of Blockchain technology can provide a mechanism to create a transparent and secure platform to prevent the dissemination of copyright-protected digital musical works has been discussed. Finally, a framework is recommended and future suggestion has been provided to detect copyright infringement.
Clustering Distribution Islands with DERs for Limited System Restoration

When a major outage has occurred in an area with constant disruptive storms, a coordinated decision to safely restore power in the region is critical in the recovery efforts.However, the certainty of grid status can be hard to predict, especially determining if a communication infrastructure is devastated.In this paper, characterizing the potential restoration likelihood is formulated based on a generalization of the restoration process.Such cluster of restorative methodology is proposed as a decision tool for power service restoration.The milestone captures models of transitions, probabilistic estimation, and statuses for generic power system components that are developed to establish the network behavior.Multiple test scenarios have been developed to validate the proposed methodology.Results indicate that after a catastrophic event, the proposed approach can suggest the steps for the switching sequence of the T&D system during the grid recovery process based on the power monitoring devices.This approach can be integrated as a planning tool for grid planning.
Web application proposal using the Scrum methodology to enhance the sales process of companies in Trujillo, Peru

This research was carried out in order to analyze the characteristics of the sales process and the aspects of the SCRUM methodology that should be considered to propose a web application design in the city of Trujillo. The type of study was intentional; calculating 45 service companies as a sample. A questionnaire was used to collect data. In addition, for the design of the proposal, the web application based on information symmetry was used as a theoretical framework. The dimensions of the factual variable were sales and customers, while the propositional axes considered in the propositional variable were security and usability. Likewise, the thematic axes on which the thematic variable was analyzed were roles, events and artifacts.The results show that "Effectiveness in sales made", "Execution of the sales process", "Customer acquisition" and "Customer recurrence" had an average "regularly" score of 49%, 49%, 36% and 29%, respectively.Having said all the above, it can be concluded that there is a deficiency in the sales processes; the indicator with the lowest score is "Customer Recurrence", which is why a web application was developed based on the symmetry of information for service companies in the city of Trujillo.
New Testing Techniques to Evaluate the Quality of Information Visualization Implementations

The use of information visualization has significantly grown thanks to Industry 4.0, and now we can see its usage in more critical sectors. In this context, the implementation of such visualizations must adhere to higher quality standards. To ensure such quality, we present a set of tools developed from a software engineering perspective, particularly from the software verification and validation area. These visualization testing tools go from one to test interactions from the user point of view to another to test their code at run time. Since the toolset is free and open-source, we believe it can be the foundational basis for future developments to expand its functionality and application domains.
Gestures and Behaviors on Multitouch Surfaces for Collaborative Software Design.

In this research work, the authors conducted an analysis of the gestures and behaviors performed by software designers when working in groups on multi-touch interactive surfaces (in this case, simulated). They identified the most common behaviors in collaborative work. Additionally, they investigated the implications in the learning process when learning to design software as a team. Furthermore, the importance of teamwork in different areas and organizational approaches is addressed.
Adaptive Decomposition and Shared Weight Volumetric Transformer Blocks for Efficient Patch-Free 3D Medical Image Segmentation

High resolution (HR) 3D medical image segmentation is vital for an accurate diagnosis. However, in the field of medical imaging, it is still a challenging task to achieve a high segmentation performance with cost-effective and feasible computation resources. Previous methods commonly use patch-sampling to reduce the input size, but this inevitably harms the global context and decreases the model's performance. In recent years, a few patch-free strategies have been presented to deal with this issue, but either they have limited performance due to their over-simplified model structures or they follow a complicated training process. In this study, to effectively address these issues, we present Adaptive Decomposition (A-Decomp) and Shared Weight Volumetric Transformer Blocks (SW-VTB). A-Decomp can adaptively decompose features and reduce their spatial size, which greatly lowers GPU memory consumption. SW-VTB is able to capture long-range dependencies at a low cost with its lightweight design and cross-scale weight-sharing mechanism. Our proposed cross-scale weight-sharing approach enhances the network's ability to capture scale-invariant core semantic information in addition to reducing parameter numbers. By combining these two designs together, we present a novel patch-free segmentation framework named VolumeFormer. Experimental results on two datasets show that VolumeFormer outperforms existing patch-based and patch-free methods with a comparatively fast inference speed and relatively compact design.