Reviewerly/exHarmony huggingface dataset:
Mathematical model of the software development process according to the “outsource” scheme

The software development process is complex and multifaceted, influenced by a multitude of factors such as project complexity, collaboration among different teams, interaction with clients, and development methodologies. Efficiently managing this process becomes a crucial task for ensuring quality and meeting deadlines. In the context of the “outsourcing” scheme, where certain stages of software product development can be delegated to external specialists or teams, challenges arise in assessing the probabilistic-temporal characteristics of the development process. Questions arise about the expected time for each stage's completion, the likelihood of meeting set deadlines, and the factors exerting the greatest impact on process effectiveness. The objective of this research is to develop a mathematical model that enables the analysis of probabilistic-temporal characteristics of software development processes within the “outsourcing” scheme. The model takes into account various factors, including participants' expertise level, communication effectiveness, and other parameters influencing stage durations. The proposed mathematical model incorporates probabilistic transitions between stages, with transition probabilities and intensities depending on the involvement of external specialists and communication effectiveness. Relevant probabilistic distributions are used to estimate the duration of each stage, and statistical methods are employed to analyze probabilistic outcomes. By considering the intricacies of the “outsourcing” scheme, this study aims to facilitate informed decision-making in resource allocation, project planning, and risk assessment within the domain of software development. Insights derived from the model's probabilistic-temporal characteristics provide valuable tools for enhancing process management and outcomes in the dynamic realm of software development.
Extended IMECA Technique for Assessing Risks of Successful Cyberattacks

The research focuses on improving the IMECA risk-based method of cyber security analysis by detailing its elements that form “threat-vulnerability-attack-consequences-impact Of other attacks/On other attacks-criticality” and creating dependencies between the impact of attacks on each other, which are used in the risk calculations. The possibility of using quantitative and qualitative indicators to assess the risks of successful attacks is implemented, as well as the implementation of the “questionnaire” methodology for a more reasoned and accurate assessment of criticality and comparison of countermeasures. The proposed version of the extended IMECA reduces the influence of expert opinion in risk analysis.
Search for the Shortest Route Considering Physical Obstacles: Method of Controlled Waterfall, Tool, and Application

The article overviews solutions for organizing LiFi communication in an obstacle-ridden environment using UAVs. The goal of the research is to develop an improved rectangle method approach and a tool to provide reliable P2P communication for a swarm of UAVs in an obstacle environment. Approaches for developing algorithms for circumventing mechanical obstacles considering communication range constraints are described. Methods and algorithms for solving the problem are developed. A tool for constructing a P2P route in obstacle conditions and comparing the rectangle method with the presented improvements for the minimum distance traveled and the minimum number of UAVs deployed are presented.
Relationship between factors influencing the software development process and software defects

Poor software quality can lead to crashes, failures or downtime, the consequences of which may be lost profits, financial costs, leakage or loss of data, accidents, human casualties, material losses or environmental disasters. The total cost of poor software quality for IT companies in the USA is estimated at ${\$}$2.41 trillion per year and tends to increase. Among the identified costs, the cost of unsuccessful projects is estimated at ${\$}$260 billion, and the total cost of operational failures caused by poor quality software is estimated at ${\$}$1.81 trillion. Late finding and fixing of software defects directly affects the success of the project as a whole, since it significantly increases the cost and development time, and affects its quality. This paper discussed the relationship between factors affecting the software development process and various groups of defects. It has been found that the leading groups of defects affecting the software quality are the defects in software requirements and defects in the design of software interfaces for human-computer interaction with the total percentage of influence of 33.3%.
Intelligent extraction of the informative features for UAV motion modelling: principles and techniques

The aim of the article is to develop a methodology for intelligent extraction of informative features of unmanned aerial vehicle (UAV) motion modelling using a Variational Autoencoder. Practical use of the developed methodology will allow to extract the most informative features of UAV motion modelling in the process of intelligent flight path planning. This fact will further reduce the complexity of calculations on their analysis and processing using the selected bases.In order to achieve this goal, a practical set of input data of the Variational Autoencoder is generated and investigations are carried out for examples of UAV velocity variation and manoeuvring. The autoencoder is used to reduce the dimensionality of the data to 3 indices, which will further reduce the complexity of the calculations to analyse and process them using the chosen bases. In the context of UAV motion modelling, this allowed up to 30% reduction in the volume of calculations.
Assessing Ukrainian Territory Suitability for Solar Power Station Placement Using Satellite Data on Climate and Topography

This research aims to assess the suitability of Ukrainian territories for the placement of solar power stations using satellite data on climate and topographic characteristics. The suitability of the territories was determined using a weighted sum method, incorporating input parameters from climate maps sourced from ERA5-Land dataset, which included data on annual global horizontal solar irradiation (GHI), accumulated annual temperature above $25^{\circ} \mathrm{C}$, average annual wind speed, and maps of accumulated annual precipitation. Additionally, topographic maps from the SRTM dataset were utilized, providing information on elevations, slopes, and terrain shading. Furthermore, data from Wikimapia on the locations of existing major solar power stations in Ukraine were used to verify the placement optimization. The results of the study revealed that the largest portion of the country (over 48%) exhibits moderate suitability scores (0.3-0.4). Favorable territories (suitability score above 0.3) outweigh unsuitable ones for solar power stations. The southern regions and the Crimean Peninsula offer the most favorable conditions for the placement of solar farms. Overall, all analyzed major solar power stations in Ukraine were located in optimal territories. Furthermore, it was found that certain regions such as Odessa, Poltava, Kharkiv, Zaporizhia, Dnipropetrovsk, Donetsk, and Luhansk demonstrate good suitability scores (0.3-0.4), yet they are not fully exploited. These regions hold significant potential for the future construction of powerful and productive solar power stations.
A Bresenham-based Global Path Planning Algorithm on Grid Maps

This paper presents a novel global path planning algorithm adapted to grid maps extending the Bug algorithm family. During experiments with Bresenham’s line algorithm, it was found that this algorithm allows natural obstacle avoidance. Based on this observed property, a recursive path planning algorithm was developed that operates on the grid maps represented by a masked array and solves potential looping problems using a state machine-based loop breaking mechanism. BRP was compared with existing methods from the Bug family of algorithms as well as with more classical algorithms such as A*, D*, and Dijkstra. The Piano Movers problem was also touched upon. The time performance of the BLA algorithm for different line thicknesses was compared. Based on these experiments, future optimisation of the BRP algorithm for motion planning tasks is possible. Through experiments, BRP was found to show significant improvement in path planning time for certain map cases compared to existing algorithms while acknowledging a slight increase in route length, approximately 0.43% above the optimal path. The presented work improves the field of global path planning by providing efficient and adaptable solutions that can be applied to specific applications. The algorithm is available at https://github.com/qr34t0r/BRP
Insights for Economic Security: Recovery Strategies from Cyber-Attacks

This article delves into strategies for businesses to bolster cybersecurity and mitigate financial losses post-cyber-attacks. It leverages Lean Six Sigma methodologies and data from past research on significant data breaches in US and EU stock markets. The study investigates the link between cyber-attacks and stock market dynamics, with a focus on reputation management. Gaussian distribution and Six Sigma methodology are used for probability analysis. Key findings underscore the significance of predictability, precision, and reputation management in cyber-risk mitigation. Effective reputation management reduces insurance costs and market share loss, while inadequate management results in higher expenses. The research introduces novel insights into safeguarding a company's value, reducing vulnerabilities, and advocating for Cyber Autonomy and reputation management to lower insurance premiums and enhance protective measures.
Increasing the cryptographic strength of CETencryption by ensuring the transformation quality of the information block

The article is devoted to the study of the cryptographic algorithms’ correctness, symmetry and quality, as well as to the analysis of ways to increase the cryptographic strength of low-resource cryptographic algorithms based on overcoming the contradiction between the quality of the information blocks transformation and the statistical characteristics of the encryption results. Basing on the formalization of the requirements for the cryptographic algorithm’s correctness, the cryptographic algorithms’ classification is detailed through the processes of direct and inverse transformation, as well as the keys for direct and inverse transformation of information. The causes of the contradiction appearance between the quality of the information blocks transformation and the statistical characteristics of the encryption results, as well as the ways to overcome it, are described and discussed. The conclusion is made about the expediency of additional XOR ciphering of the key sequence. The possibility of increasing the key of a low-resource cryptographic algorithm due to additional XOR ciphering in the encryption process is demonstrated and discussed. Alternative ways of increasing the cryptographic algorithms’ cryptographic strength based on key management are considered.
The Principle of Control by Diagnosis – the Fundamental Principle of Computer-based Learning Process Intellectualisation

The paper is aimed at studying new methods of teaching students in the conditions of modern requirements in education. Effective methods of assessing students’ performance are analysed in the article. The authors propose a method of evaluating students. The problem of introducing intelligent computer systems in the process of teaching students to perform calculations is considered. The procedure of diagnosing the correctness of solving systems of equations on the example of solving an equation by the Cramer method is considered. The peculiarity of the approach is illustrated on the example of solving the system of two linear algebraic equations. The result is obtained in the form of a dichotomous tree, which allows to identify student’s errors made when performing algebraic operations. The results of theoretical research on the possibility of applying the principle of control by diagnosis in the process of computer-aided teaching of knowledge and skills of performing calculus operations are presented.
Development of Technological Competence Through Digital Educational Activities

While instructing in information and communication technologies, learners cultivate essential knowledge, hands-on competencies, adeptness in purposeful internet utilization, foundational grasp of office software, thereby equipping themselves to apply their fundamental scholastic grounding congruent with their chosen higher education domains. The extensive and cohesive integration of digital technologies aids educators in attaining objectives, notably in enhancing the depth of theoretical subject understanding and fostering the growth of digital technological skills. The conducted research uncovered that educators in both general education schools and higher learning establishments encounter difficulties in effectively employing information technology, amidst the digital realm, they struggle to fully acquire the computer skills imperative for nurturing, educating and developing the upcoming generation. An ICT instructor at secondary and higher educational levels should possess the capacity to amalgamate professional expertise with digital technologies. Its obligation lies in rendering the educational process efficient, leveraging technologies to consider the interests of the succeeding generation, their individual aptitudes, and the available technological resources.
Combined Lossless/Lossy Compression of Three-channel Images

This paper deals with the compression of three-channel images that offers near-lossless and lossless options. The lossy compression is based on discrete atomic functions. They provide several benefits such as easy control of introduced distortions, privacy protection, and quite efficient compression. Lossless mode is provided due to archiving the differences between the original and lossy compressed images. An increase in a compression ratio of the lossy compression part leads to larger differences and worse lossless compression. Due to this, an optimum has to be found. We look for this optimum using a set of color images of different complexity. It is shown that the maximal compression ratio of lossless compression is achieved for traditional modes of atomic compression when the peak signal-to-noise ratio of the lossy compressed part is about 40-42 dB, i.e. practically near-lossless or visually lossless compression is carried out.
Blood Smear Leukocyte Identification Using an Image Segmentation Approach

The focus of this study is on biomedical image data processing and analysis. The primary objective is to identify leukocytes in blood smear samples and determine their quantities. Since the manual laboratory processing of this data is a laborious task, it is susceptible to subjectivity and time-consuming. Hence, the objective of this study is to examine contemporary processing methodologies and existing technologies that have the potential to speed up and automate this procedure. This study presents a concept that utilizes existing methods to address a problem, including a unique sequence of operations. Finally, it evaluates the accuracy of this approach for future research. This approach has the potential to be used in the diagnosis of a range of disorders, including blood malignancies or infections.
The Impact of Digital Technologies in Education

The rapid and unprecedented development of digital technologies in the contemporary world has influenced all aspects of society, presenting new opportunities and challenges on a daily basis. Technology has become an integral part of our lives, significantly shaping our daily routines and work patterns. In this context, digital technologies play an important role in driving a country’s prosperity and fostering economic development. In the domain of education, these technologies have become a transformative force, revolutionizing the learning process to enhance accessibility, engagement, and efficiency. The article explores the critical intersection of higher education and dependable systems, services, and technologies, delving into its impact on simplifying complex processes and empowering educational institutions and organizations to enhance their competitiveness. The research process involved a comprehensive analysis of legislative acts, sharing advanced experiences, and employing various research methods, leading to valuable insights into the transformative effects of digital technologies on the education. Embracing the potential of digital technologies, education unlocks boundless possibilities for learners of all ages. Innovative tools and methods enable educators to create dynamic, interactive and safe learning environments that cater to diverse learning styles, fostering deeper engagement and understanding. Moreover, digital technologies have facilitated the growth of online learning platforms and virtual classrooms expanding access to education. This inclusive approach ensures that education empowers learners from diverse backgrounds to pursue their educational aspirations.
Mathematical and Software Provision for Optimization of Water Treatment Processes

A mathematical model of the process of regeneration and optimization of the operation of a cationic water softener has been developed. The mathematical model takes into account the distribution of sorbet ions along the filter loading height and the change in the concentration of the solution entering the filter loading. To find the height of the calculated layer, the coefficient of interdiffusion of sodium and calcium ions was determined. Using the layer-by-layer method for calculating the regeneration process, the apparent ion exchange coefficient was determined, which makes it possible to obtain results that closely coincide with the experiments. The software package allows you to obtain output data for any initial parameters, which makes it possible to obtain output curves for filter loading layers and portions of the regeneration solution. The set of programs can be used in the management of water resources.
Cross-Domain Reconfigurable GAN with Fuzzy Components for Anomaly Detection

Anomaly detection remains a critical task in various domains, including cybersecurity and healthcare monitoring. Traditional approaches often rely on low-level machine learning and statistical methods, which may struggle to capture complex, multidimensional data patterns and adapt to evolving anomalies. In recent years, generative adversarial networks (GANs) have demonstrated promising potential for anomaly detection due to their ability to learn the underlying data distribution. This paper presents an anomaly detection system, which leverages a GAN-based model integrated with fuzzy logic components. We explore the integration of the GAN architecture with auxiliary components to enhance the performance and robustness of the anomaly detection system. This approach endeavors to explore the practical potential of GAN-based models in the field of anomaly detection and paves the way for future research in this rapidly evolving domain.
Towards Effective Safety and Cybersecurity Co-engineering in Critical Domains

The primary objective of functional safety and cybersecurity co-engineering is to streamline assessment processes and enhance efficiency by implementing integrated approaches, therefore reducing overall effort and bringing several consequential advantages. Although this concept is not new, and there have already been successful attempts at its utilization in different critical domains such as nuclear, railway, and automotive, no mature approach could be easily adopted and applied during the assessment. Another challenge is that the understanding of co-engineering is essentially different, depending on domain specifics and priorities. Moreover, issues are still related to measuring efficiency achieved by co-engineering utilization. This paper addresses the current state of safety and cybersecurity co-engineering in critical domains. With a focus on nuclear, automotive, and railway domains, it proposes directions toward developing effective co-engineering frameworks for them.
An Accelerated Approach for Public Key Cryptography Implementation on IoT Terminal Platforms

In the paper, a method for accelerating computational implementation of the most massive open-key cryptography operation - modulo squaring of numbers whose length significantly exceeds the processor’s bit rate - is proposed and investigated. The acceleration of the calculations is achieved via the combined use of the Montgomery group reduction based on pre-calculations and dynamic reduction of the length of operands. Theoretically and experimentally, it is shown that the proposed approach reduces the modular multiplication time by 3-4 times and thereby speeds up the implementation of data protection in remote control systems based on IoT technologies.
BPG-based compression of Poisson noisy images

The article is devoted to the lossy compression of noisy images, considering the currently popular trend of green computing. In this paper, we show how this trend can be incorporated into solving an essential task of image data transferring via communication lines and what benefits it can bring to this area of interest. We consider the case of images corrupted with signal-dependent Poisson-distributed noise, which is quite common in real-life situations. Compression of noisy images has several peculiarities, among which there is the existence of optimal operation point (OOP), which is a value of compression control parameter (CCP) where a compressed image is closer to a noise-free image than the original noisy one. We show the possible presence of OOP for various visual quality metrics, both SSIM-based and PSNR-based. The recommendations for compression in OOP and its neighborhood are presented.
A Two Step Chaos-Based 3D Model Encryption

Augmented and virtual reality, game designing, medicine, medical engineering, and many other fields all revolve around 3D models. This is because 3D models have superior visual information than digital images. However, in recent years the advancements in digital image encryption are more rapid than in 3D model encryption. As such, more study on 3D model encryption is deemed necessary. In this paper, a new 3D model chaos-based encryption scheme is suggested based on a shuffling process on the vertices and faces that compose the 3D object and a modulation on the vertex coordinates. The effectiveness of the proposed encryption technique is then verified through the distribution of occupied position analysis, peak signal to noise ratio, structural similarity index and correlation coefficients.
Simple Yet Effective Named Entity Oriented Sentiment Analysis

Sentiment analysis, i.e. the automatic evaluation of the emotional tone of a text, is a common task in natural language processing. Entity-Oriented Sentiment Analysis (EOSA) predicts the sentiment of entities mentioned in a given text. In this paper, we focus on the EOSA task for the Russian news. We propose a text classification pipeline to solve this task and show its potential in such tasks. Moreover, in general, EOSA implies labeling both named entities and their sentiment, which can require a lot of annotator labour and time and, thus, presents a major obstacle to the development of a production-ready EOSA system. To help alleviate this, we analyse the potential of applying an Active learning approach to EOSA tasks. We demonstrate that by actively selecting instances for labeling in EOSA the annotation effort required for training machine learning models can be significantly reduced.