Reviewerly/exHarmony huggingface dataset:
Preprocessing Methods to Improve Performance of Imbalanced Data in Healthcare

Background: Machine learning is gaining enormous significance and has developed into an essential technology as the reliability of healthcare information improves rapidly. However, the complex, incomplete, and multifaceted nature of healthcare data makes the timely and precise identification of disease a continuing problem. Processing the data is an important phase whose main objective is to give processed information in order to increase forecast accuracy. Methods: The imbalanced dataset namely WiDS (Women in Data Science) Challenge data is used in our work. Missing values are imputed with advanced multiple imputations by chained equations methods. Dimensionality reduction is accomplished using the wrapper-based forward feature selection method. Various sampling techniques combined with a neural network algorithm are used to address the imbalance problem. Results: Our proposed model got higher accuracy of 92.45% using deep neural network with SMOTH sampling compared to other preprocessing methods. Conclusion: This study compares the model performance with different combination of preprocessing methods and significantly improves the model performance.
Convolutional Neural Network Assessment of Image Quality Based on the TID2013 Database

The problem of automatic neural network assessment of image quality based on the widely used TID2013 image database is considered in the paper. Image quality assessment without the use of basic reference images, as one of the preliminary stages of their processing, is of great importance from the point of view of the information capacity of the images, the necessity and possibilities of enhancement of the image quality when solving the next tasks of segmentation, classification, recognition, etc. A preliminary analysis of the used image quality assessment metrics and, as an alternative, the use of neural networks, primarily deep neural networks, was conducted. The structures of used neural networks and variants of input data for training neural networks in the problem of image quality assessment are presented. The first variant is a regression problem, and the other one is a classification task. Keras software using TensorFlow for tensor operations is used to build and study neural networks.
Remote Voice Control of Computer Based on Convolutional Neural Network

This paper dwells upon the solution of the task of creating the voice assistant to control the personal computer based on Windows in English using third-party language engines and the voice recognition models. The Python programming language, the Speech Recognition and PyTorch library are used to solve this problem. The article analyzes similar programs, tells about the stages of software development, demonstrates the program demo version example and analyzes the prospects for project work. The created model for speech recognition, which was developed during the implementation of this research has the following results as average loss 0.4305, average WER 0.3428 and average CER 0.121629.
Analysis of a Cryptographically Secure Pseudo Random Number Generator

We present an analysis of a cryptographically secure pseudo random number generator (CSPRNG) that involves the permutation of the internal state of the PRNG. This CSPRNG was described in a previous publication. The cryptographic quality of the CSPRNG is examined using the Dieharder test software and comparisons are made against AES. An analysis of these tests results is presented, and a discussion of future work concludes the paper.
MRI Denoising Neural Network Architecture Convolution

Ensemble learning of machine vision (ML) models, particularly deep neural networks, has emerged as a powerful technique for enhancing the quality of medical image processing. In this research endeavor, we investigated the application of the Deep Convolutional Neural Network (DnCNN) to the denoising of medical images. The DnCNN model was trained using a diverse dataset comprising medical images encompassing various noise levels and types. The primary objective was to train the model to restore a clean version of the image from its noisy counterpart. To evaluate the performance of the proposed approach, we employed widely-used quality metrics, namely the Structural Similarity Index (SSIM) and Peak Signal-to-Noise Ratio (PSNR). The experimental results demonstrated the efficacy of the DnCNN model in effectively reducing noise while preserving crucial image details, thus offering a promising solution for denoising medical images.
Agile and Waterfall Approaches Hybridization in the Hyper-Casual Games Projects

One of the largest and most profitable areas of software development is video games. There are many gaming devices and platforms, with games having their own unique genres, features, and characteristics. One of the most popular gaming platforms today is mobile phones and smartphones. Scientific progress has turned small pocket devices into powerful systems capable of processing large amounts of information and storing gigantic amounts of data. Today, almost every person on the planet has a mobile phone, and in developed countries, a smartphone. The mobile gaming industry has been developing rapidly for more than fifteen years. More and more people, when traveling by public transport or standing in queues, prefer to pass the time with a mobile game rather than reading a book. Fast mobile games, whose logic and rules can be easily understood even without gaming experience, have taken over the mobile gaming markets and are becoming increasingly popular. The genre of such fast and simple mobile games is called Hyper-Casual. The development of mobile games is a complex process that requires a team of highly qualified specialists from different specialties and fields of knowledge. In order for the game, as the final product of development, to meet the project criteria that were set at the planning stage, it is necessary to choose the right method of planning and managing the project and its processes.
Non-Fungible Tokens as Alternative Means of User Access to Additional Services in the Blockchain Platform Payment Process

The unprecedented development of blockchain technology has sparked a wave of innovation in payment systems areas. Blockchain offers a decentralized, secure, and transparent platform for conducting transactions. It does not have any additional intermediaries, such as banks. Blockchain provides many advantages and encourages the qualitative transformation of payment systems, offering new opportunities to create efficient and low-cost payment systems. However, blockchain-based payment systems are still in their infancy, and rooms for improvement still exist in their implementation. This paper proposes using the non-fungible token to interest customers and provide them with additional options when paying with a blockchain-based payment system.
Accuracy Improvement of Neural Networks Under Semi-Supervised Learning

This work concerns the problem of improving the accuracy of semi-supervised machine learning in solving a multiclass classification problem by choosing the optimal semi-supervised machine learning algorithm from a set of known ones. As the optimality criteria, we use the metrics proposed by the authors based on the criteria for the purity of clusters and normalized general information, which enables the assessment of cluster assumption for a given dataset. As an example of using the proposed approach, we consider the presence of the cluster assumption in the training sample, and, accordingly, the choice of the optimal semi-supervised learning algorithm in the presence of this assumption.
Cyber Crime Prevention and Techniques: A Comprehensive Survey

The wide spread use of mobile device and computer or any device which enable access of internet increases the incidents of cybercrime. The worldwide web creation revolutionized the communication. In 21 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">st</sup> century more than 5 billion people using the internet. The use of internet contains both advantages and disadvantages. The biggest disadvantages of using internet is cybercrime. In simple words doing illegal activities with computer by using internet or network is called cybercrime. Some people who uses internet to harm other such as gain unauthorized access, stealing personal data and important files etc. Cybercriminals use a range of techniques, which includes hacking, phishing, malware, and social engineering to gain unauthorized access to computer systems, steal sensitive data, and disrupt critical infrastructure. One of the most effective techniques in cybercrime prevention is the use of encryption and fire wall. In this paper we study about the cybercrime, which techniques using in the cybercrime and how to prevent it. This paper also provide the different types of cybercrime. This paper provides an overview of cybercrime techniques and prevention strategies to protect individuals, organizations, and nations from cyber attack.
The Use of BBC micro:Bit in Automatic Irrigation System Through Cross-Curricular Teaching of Biology and Informatics

The BBC micro:bit is used worldwide as a computer hardware tool for teaching Informatics. Slovakia is no exception, and a significant part of lower secondary and high schools teach with micro:bits. In most cases, it starts with simple programs and basic hardware, which are then extended with a variety of additional components. We decided to not only extend the components but also the teaching and to link Informatics with the subject of Biology. The research goal was to find out if it is possible to link Biology and Informatics through a micro:bit project so that students understand that nature and technology can form an interplay. We have made this link in the framework of automatic irrigation with the help of the Smart Home Kit.
Data geopolitics <b>Data Sovereignty: From the Digital Silk Road to the Return of the State</b> <i>Anupam Chander and Haochen Sun, Eds.</i> Oxford University Press, 2023. 408 pp.

A group of scholars explore the implications of how governments control and restrict digital information.
Teacher’s Professional Qualifications in Terms of Competency Model Pedagogical Growth

The paper considers the system of professional qualifications for teachers of subject education and defines the most important criterion for obtaining a higher pedagogical education. As part of the implementation of the structural model of teacher education, bachelor's and master's programs are distinguished. Each level is an independent system, but in unity, they form a model of a complete higher pedagogical education. This study established the pedagogical model of professional growth of a bachelor's graduate at the formal and non-formal levels of education, and the pedagogical trajectory of a graduate of a master's program determined the deepening of qualifications and work in higher education. The results of this study indicate a clear system of qualification levels, however, at the level of its content – professional competence – there is no single description of its constituent competencies. In the context of the competence-based approach to teaching implemented in higher education, pedagogical and methodological competence for a teacher of any qualification, as well as research competence for a master's degree graduate, are defined as a key component of pedagogical qualification. Based on the analysis of previous studies of teacher training under the conditions of a competency-based model, regulations and standards, the previously defined competencies were identified as basic ones. The development of the basic competencies of a teacher is determined by the system of professional growth and, within the framework of the “lifelong learning” model, forms a system of continuous teacher education. The system of professional growth in this study is determined by the qualifications achieved and depends on the education system: for a teacher of secondary education, the model for improving pedagogical skills through obtaining qualification categories is determined as the basis, and for a teacher of higher education, obtaining an academic degree, title and professional growth by position is available. Lifelong education for a teacher in this study also depends on the level: in secondary education – an increase in the level of pedagogical and methodological activities, and in higher education – an increase in the level of scientific and pedagogical activity throughout the entire period of professional activity.
More is less - Adding zoom levels in multi-scale maps to reduce the need for zooming interactions

When you zoom in or out of current multi-scale cartographic applications, it is common to feel lost and disoriented for a few seconds because dimensions and map symbols have changed. To make the exploration of these multi-scale maps more fluid, one option is to design maps where the transformations due to scale change are more progressive. This paper proposes to use cartographic generalization techniques to design these multi-scale maps with additional intermediate scales to improve progressiveness. These more progressive maps are tested in a user study with a task requiring multiple zooms in and out. The users perform better with the progressive maps, and in particular, the total quantity of required zooming is reduced compared to maps without additional intermediate scales. However, the survey is not fully conclusive on task performance due to the complexity of such a survey with real maps. This difficulty in assessing how well progressive map generalisation reduces disorientation is discussed and guidelines are proposed to design further studies.
Research on encoding path distance based on constructing quantum adjacency phase matrix

Quantum computing is a novel computational paradigm that harnesses the fundamental principles of quantum mechanics to perform calculations. In comparison to classical computers, quantum computers can exhibit significant acceleration and storage advantages for specific problems. Inspired by classical adjacency matrices, this paper proposes a quantum adjacency matrix that encodes distances between vertices as phase distances. The quantum adjacency matrix constructs unitary matrices associated with each vertex, which are then decomposed into various phase gates. Leveraging the phase kickback effect, the phase distances are stored in the quantum state's phases. The approach is implemented on a noisy superconducting quantum computer, and distance information is extracted through measurements of the constructed circuit. Due to the complexity of phase rotation operations within the circuit, substantial errors occur on current real quantum computers, preventing the attainment of anticipated results. This paper employs circuit swapping and mapping optimization techniques during the compilation stage. The circuit is compiled multiple times to generate a minimally deep compilation route. In the measurement phase, Qiskit's measurement error mitigation techniques are utilized, involving measurement fitters and filter calibration to mitigate errors in measurement outcomes. These measures facilitate the presentation of expected results on IBM's real superconducting quantum computer.
Research on equipment entity recognition and attribute extraction for knowledge graph construction

Equipment entity recognition and attribute extraction are the basis of constructing equipment knowledge graph. In this paper, we firstly design a model framework for equipment entity recognition and its attribute extraction. Then, combining the advantages of BiLSTM and CRF, an equipment entity recognition method based on Dic+BiLSTM-CRF is proposed by constructing a domain-specific dictionary for equipment. Furthermore, the equipment entity attribute extraction method is designed based on HMM model and Viterbi algorithm. The experiment results show that compared with the traditional methods, the performance of equipment entity recognition based on Dic+BiLSTM-CRF is close to the general domain entity recognition level. The accuracy rate, recall rate and F1 value of equipment entity attribute extraction are higher than 80%.
The Future of Data in Research Publishing: From Nice to Have to Need to Have?

Science policy promotes open access to research data for purposes of transparency and reuse of data in the public interest. We expect demands for open data in scholarly publishing to accelerate, at least partly in response to the opacity of artificial intelligence algorithms. Open data should be findable, accessible, interoperable, and reusable (FAIR), and also trustworthy and verifiable. The current state of open data in scholarly publishing is in transition from ânice to haveâ to âneed to have.â Research data are valuable, interpretable, and verifiable only in context of their origin, and with sufficient infrastructure to facilitate reuse. Making research data useful is expensive; benefits and costs are distributed unevenly. Open data also poses risks for provenance, intellectual property, misuse, and misappropriation in an era of trolls and hallucinating AI algorithms. Scholars and scholarly publishers must make evidentiary data more widely available to promote public trust in research. To make research processes more trustworthy, transparent, and verifiable, stakeholders need to make greater investments in data stewardship and knowledge infrastructures.
CHOOSING METRICS FOR SOFTWARE DEVELOPER’S SCRUM TEAMS

Background. There are many books about software development, slightly fewer books about software development team’s management, and very little about work metrics of software development teams. Existing developers scrum team metrics definition practices were analyzed in this article and common rules were proposed. Application of the rules will allow implementing the Pareto principle in the choosing and using of metrics in developer’s scrum teams.&#x0D; Methods. General scientific methods such as the analysis of Russian-language and foreign thematic literature, comparative analysis, induction and analogy were used.&#x0D; Results. The result of the article is an ordered action plan, using of which makes it possible to most effectively evaluate the work of the developer’s scrum team. The target audience of the article is wide. Managers of different levels (from the team manager or scrum master to the head of the department) can use the described approach to create metrics for their departments. Developers will be able to better understand how managers see their work and take this into account in their work.&#x0D; Conclusion. Software developer typical tasks are divided into technical stages. When allocating metrics to evaluate the effectiveness of each stage, the risk of local optimizations increased. In addition, if the area of responsibility of the manager shifts from the whole to the part, from the efficiency of the company to the efficiency of the business unit, then the risk of choosing the wrong metrics increases many times. Metrics that evaluate a partial result are considered incorrect – they relate to a part of the functionality, a division within the company, etc. As a result, the likelihood of making a management decision in accordance with the interests of the division, rather than the company or the product as a whole, increases. For this reason, the use of private metrics should be avoided.
CLASSIFICATION OF UNIVERSITY PROPERTY

The property of the educational organizations is a material basis of their accomplishment of significant public functions of education and upbringing. The increase in effective management of property of the educational organizations is important as it provides the improvement of education quality as well as the increase in the potential for science development/ It also promotes the increase in the efficiency of the use of the state-owned property as the state-owned property is transferred to the most educational organizations (namely – state and municipal ones) on the right of operational management. At the same time, the structure of the property of the organizations of higher education (OHE) is the most difficult. Some options of classification of the property of educational organizations are widely provided in literature. At the same time, the property is classified according to various bases. However, there is no system approach to the classification of property.&#x0D; Purpose. The purpose of the research is to form the systematized classification of OHE property considering the main factors, which are significant for the determination of features and borders of managerial influences.&#x0D; Method or methodology: the study was conducted based on the method of analyzing documents and synthesizing the information presented in them.&#x0D; Результаты. The formed classification takes into account the organizational and legal forms of OHE, economic, as well as functional aspects.&#x0D; Practical implications. The use of a systematized classification helps to take into account the specifics of the activities of OHE, allows you to optimize the “cost of ownership” of property, increase the efficiency of its use, and involve it in the educational and scientific process.
The Making of 'Commotion'

“Commotion” is a fixed media multichannel composition that revolved around the principles of minimalist music. This exposition aims at understanding these principles while it tries to place the process of composing the piece within the common premises of artistic research. Due to the nature of its context, this approach includes also theories of reception - mostly by exploring themes such as intentionality, interpretation and representation. With this exposition, the author shares technical terminology of sound practices, in order to promote it in contexts predominantly visual-oriented.
MOOCs in Research Methodology for Universities in Ecuador

It is imperative that universities incorporate ICT in their teaching and learning processes because now more than ever it is a fact that we live in the "Age of the information and interaction society", where information and communication technologies play Its determining role The general objective of this work was to create an online MOOC course with an expected learning model for undergraduate and postgraduate students. This work will encourage UNEMI to overcome limits that only apply to the education of professionals through face-to-face training systems and will adopt them in the near future in mixed learning environments that open the way to new paradigms that consider principles epistemological, ontological, ethical, political and educational. The general objective of this research was to propose a massive open online course MOOC for Research Methodology. Said course was born from the investigation of Didactic Strategies to improve the attitude towards research of students of a university in the province of Guayas, Ecuador. This work contributes to massify research at the university by using ICT as a means to change traditional face-to-face learning environments into virtual learning environments. The results obtained allow us to say with all seriousness that they have been positive, managing to educate a large group of students and teachers from an Ecuadorian university.