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Abstract Background A variant can be pathogenic or benign with relation to a human disease. Current classification categories from benign to pathogenic reflect a probabilistic summary of the current understanding. A primary metric of clinical utility for multiplexed assays of variant effect (MAVE) is the number of variants that can be reclassified from uncertain significance (VUS). However, a gap in this measure of utility is that it underrepresents the information gained from MAVEs. The aim of this study was to develop an improved quantification metric for MAVE utility. We propose adopting an information content approach that includes data that does not reclassify variants will better reflect true information gain. We adopted an information content approach to evaluate the information gain, in bits, for MAVEs of BRCA1, PTEN, and TP53. Here, one bit represents the amount of information required to completely classify a single variant starting from no information. Results BRCA1 MAVEs produced a total of 831.2 bits of information, 6.58% of the total missense information in BRCA1 and a 22-fold increase over the information that only contributed to VUS reclassification. PTEN MAVEs produced 2059.6 bits of information which represents 32.8% of the total missense information in PTEN and an 85-fold increase over the information that contributed to VUS reclassification. TP53 MAVEs produced 277.8 bits of information which represents 6.22% of the total missense information in TP53 and a 3.5-fold increase over the information that contributed to VUS reclassification. Conclusions An information content approach will more accurately portray information gained through MAVE mapping efforts than by counting the number of variants reclassified. This information content approach may also help define the impact of guideline changes that modify the information definitions used to classify groups of variants.

The purpose of this article is to develop a model for an access control policy and to formulate a method for creating a model of information security threat scenarios in industrial control system (ICS). The results of developing an access control policy model based on role assignment are presented. This model encompasses the information assets derived from the analysis of technological processes ˗ access objects that are vital for the functioning of the industrial network. In addition to that a specific and refined list of personnel access subjects ˗ responsible for maintaining production technological processes within the ICS context is provided. Furthermore, a hierarchy of user roles has been constructed, wherein the role of a super user, possessing all privileges, has been excluded, and an access differentiation matrix has been developed. The model can be utilized in the development of a customized access differentiation policy within the scope of administrative policies of information security. The article formulates a way for EPC-modelling of scenarios depicting the implementation of information security threats. These scenarios outline the stages of complex multi-component attacks targeting the objects of the ICS. It depicts situations where cybercriminals infiltrate the external subnet ˗ the enterprise network ˗ and subsequently penetrate the internal industrial network, violating access management policies. An example illustrating the construction of a threat scenario targeting an OPC-server based on EPC-model is provided. This example delineates the tactics and techniques employed by cybercriminals, leading to the realization of a security incident from the Threats Data Bank. The method for constructing scenarios enables the visual representation of the sequence of actions undertaken by attacker. This sequence involves the exploitation of vulnerabilities and techniques, as well as the resultant events that influence the progression of the attack. SIEM (Security Information and Event Management) can be constructed to detect sequences of events identified using EPC-modeling. Therefore, the developed scenarios will contribute to timely detection and appropriate response during the early stages of cyberattack implementation.

The paper analyzes the features of the experimental evaluation of the single event effects (SEE) cross section dependence on linear energy transfer (LET) for ions with energies above 100 MeV/nucleon. Ion energy degraders use in order to change the values of the LET. The paper presents calculations of LET spectrum at different thicknesses of a polycarbonate degrader for iron ions with energies of 100...450 MeV/nucleon as an example. It is proposed to evaluate the LET values in packaged electronic devices with an unknown physical and chemical composition with help of the modified technique used at the ion accelerator at Brookhaven National Laboratory in the USA. An additional technique with preliminary studies on X-ray of packaged electronic is proposed to estimate the mass thickness of the protective layers in integrated circuit. In order to reduce the influence of infamous factors, it is proposed to thin the package based on the results of the analysis of X-ray images. The proposed approach makes it possible to correctly determine the dependence of the SEE cross sections on the LET of both packaged and decapsulated integrated circuits for SEE under high-energy ions. The obtained results are supposed to be used at the specialized ISKRA station, which is part of the NICA nuclotron complex at JINR, Dubna. The presented results make it possible to assess the upset and failure hardness of electronic information systems to the effects of ions of artificial and natural origin.

This study explores the prevalent issue of non-compliance with information security policies (ISPs) within organizations, offering a way by which organizations can monitor non-compliance of ISPs using a practical suggested approach. By crowdsourcing artificial intelligence (AI) driven algorithms from a well-known and popular public site and applying the Design Science Research (DSR) approach, this work offers a way that organizations can monitor non-compliance in real-time with the proposed AI-driven algorithm prompting behavior that fosters better compliance. The research integrates principles embedded in the Theory of Planned Behavior (TPB) into two algorithms, with results showing that algorithm 2, which applies a binary classification model, generates prompts that are more efficient in eliciting desired compliance than algorithm 1. The study's practical significance lies in the crowdsourcing appeal, where readily available and cost-effective resources may reach ordinary organizations. The study contributes to the field by exploring AI-driven algorithms, crowdsourcing and addressing user attitudes, subjective norms, and perceived behavioral control challenges. The study concludes by acknowledging limitations, proposing future research directions, and highlighting its valuable contribution to understanding and addressing non-compliant behavior.

The article develops a functional model of unauthorized access (UA) protection mechanisms at information infrastructure objects (IIOs). It defines the content of protection measures, techniques used, and stages of their implementation. It substantiates the order of execution of individual functional components of the structural representation of the objective function "Protection of information of IIOs from UA". The sequence of implementation of these components is illustrated as a change in the states of the Markov process for constructing such a model. A table is provided of the correspondence between the list of procedures performed by an intruder in the process of implementing an UA threat to information of an IIOs and the procedures for protecting information, and it demonstrates the possibility of transition from the description of information protection measures from UA at IIOs in terms of functional modeling to the mathematical representation of the time characteristics of the functional components of the objective function of protection. The corresponding analytical expressions are provided for various options for representing the order of the functional components performed.

Problem description. One of the areas of digital transformation of Russian society is the development and implementation of the National Digital Ruble System (DR) in the credit and financial sphere (CFS) of the economy of the Russian Federation. The National DR system should be based on the information technology infrastructure (ITI) for ensuring information security (IS). In fact, the ITI for ensuring IS is a trust infrastructure (ITIT) based on the public key infrastructure (PKI). ITIT should have a number of functional properties, including identification and authenti­cation of objects and subjects of electronic financial transactions, protection of the integrity and confidentiality of data and the electronic financial transactions themselves, implementation of the principle of non-repudiation of the parties to information interaction. At the same time, the absence of ITIT in the National DR System can completely discredit the very idea of digitalization of the CFS, associated with the absence of any guarantees of reliability and trust in the National DR System, based on the implementation of the entire range of methods and means of cryptographic protection of information (electronic financial transactions), including systems for managing cryptographic keys. The absence of comprehensive protection of the National DR System will entail risks and problems in ensuring IS, which can negatively affect individuals, groups, organizations, sectors of the economy and society as a whole. Goals. To propose and analyze a heuristic model of DR and a model of functional and structural ITIT, which solves the main problems of ensuring IS of the National DR System, associated primarily with confirmation of the authenticity and ownership of DR, as well as the protection of electronic payment transactions and the possibility of withdrawing (withdrawing from circulation) DR immediately (on-line) after detection of its compromise. Results. The article presents a heuristic (hypothetical) model of C₽ and describes the DR format (as an information object) that includes cryptographically linked information blocks and public key certificates issued by accredited certification authorities using electronic signatures. A functional and structural model of the ITIT of the National DR System is proposed. The composition, main elements of the ITIT structure, as well as their goals and implemented functions are described. The results of the analysis of trust assurance based on the PKI of the Bank of Russia (BR) are presented. Practical significance. The heuristic (hypothetical) model of DR, the functional and structural model of the ITIT of the National DR System and the results of the analysis of trust assurance based on the PKI of the BR are of great practical significance in the development and implementation of the National DR System in the CFS of the Russian Federation economy. Conclusions. The results obtained will increase the level of security and trust in the National DR System of the citizens, businesses and credit and financial institutions.

Computer systems (CS) security has become a very critical concern that needs the attention of researchers to ensure the information protection and cyber security. This article provides an overview of the state of the art in cyber security, challenges, and global trends of CS security. A promising direction in solving information security problems is the use of stochastic methods based on the use of pseudo-random number generators (PRNG), the result of which is the introduction of unpredictability into the operation of CS and their elements. Examples of using stochastic methods for protection and attack are considered. Examples of information security technologies based on the use of PRNG in the development of software and hardware are given. Attention is drawn to the emergence of new mechanisms for carrying out attacks on CS based on code reuse and, accordingly, new methods of protection against such attacks. The idea of creating a stochastic computer is substantiated, and presented the possible strategies and approaches.

In the process of developing and operating navigation systems, it is very important to reliably assess the accuracy of determining spatial characteristics. A methodology has been developed for assessing and confirming the accuracy of determining spatial characteristics by various software and hardware systems, such as coordinates, velocity, and orientation. The basis was taken from the foreign standard ASTM E3064-16, which describes coordinates and orientation accuracy confirmation of optical tracking systems. The developed approach is based on assessing the accuracy of measuring a certain fixed length (rod) in different positions and orientations. The speed accuracy assessment is based on the coordinate accuracy assessment and is based on the use of linear regression to calculate the speed. The error in determining the orientation angle in space is also calculated based on the coordinate measurement error and is given for small angles. The applicability limits of the described methodology are given. The technique makes it possible to assess the accuracy and reliability of navigation and measuring systems.

The article identifies the main problems associated with the inconsistency and incoordination of such concepts as “information protection”, “information security”, “security of information”, “cybersecurity” and “cyber resilience”, which has led to the absence of a unified system currently accepted by the professional community concepts of the subject area under consideration. To overcome this flaw, it is proposed to build a basic system of concepts for the “security of objects in the information sphere (ISF)” subject area, based on taking into account the characteristics of objects (which using information technologies and processing information), using the ISF concept (as a collection of space of such objects and the environment of their interaction) and on the asset concept (part of an object that has a certain value), which can be main and auxiliary. Taking into account these initial data, the selected subject area is compared with three separate systems of concepts: “ensuring the security of information of objects in the ISF”, “ensuring the resilience of objects in the ISF” and “ensuring the information and psychological security of a person as an object’s asset in the ISF”. A description of the proposed systems of concepts is given, which can be attributed to the development of a methodological basis for ensuring the objects’ security. These conceptual systems have minimal overlap with each other and correspond to three separate areas of practical and scientific activity that require professionals with unique professional competencies. The results of the work have practical significance for the educational field in the formation of students' modern, methodologically sound conceptual base.

The article is devoted to the problem of identifying deviant groups studying in educational institutions. The article substantiates the relevance of this problem. Recent incidents and possible reasons for their occurrence are analysed. The system for preventive detection of deviant groups of teenagers is offered. Categories of deviant groups of adolescents are identified: potential shooters; potential bullies; potential students capable of laying hands on themselves. It is suggested to measure anxiety and aggressiveness in adolescents in order to detect deviation of adolescents. The ways of measuring anxiety and aggressiveness are considered. It is suggested to use profiling as an objective method of assessment. Profiling by school psychologists is rather difficult to implement due to their limited number in educational institutions. To automate the process and exclude the subjective factor, it is suggested to use online profiling. Within the framework of online profiling, the objects of research are the pages of social networks used by students. Criteria for determining anxiety and aggressiveness based on information from social network pages are proposed. A toolkit for partial automation of the process of data collection from the pages of social networks of students of educational institutions is proposed. The use of the method of clustering k-means clustering method to identify deviant groups of students. An example of detection of teenagers with deviations using specially generated synthetic data is given.

The ultra-high frequency (UHF) tag IC’s main part of the power management unit (PMU) design technique is presented. The technique is a step-by-step algorithm for designing a PMU and consists of five interrelated stages. At the first stage, the requirements for the parameters of the PMU (output voltage, output DC power, efficiency, output capacitor capacity) and the Q-factor of the tag analog front-end are determinates. At the second stage, the design of an electrical circuit of a voltage multiplier (VM) is carried out. VM is required to convert the voltage of the input radio frequency (RF) signal into an DC voltage. During the third stage, the design of the electrical circuit of the DC voltage limiter is carried out, which is necessary to reduce the output voltage of VM to a safe level. The result of stage 4 is an electrical circuit of surge protection designed to provide the required level of immunity of the tag IC to the effects of electrostatic discharge and a high-power RF signal. As part of the final stage, the evaluation and alignment with the required Q-factor value of the tag IC analog front-end is carried out. The proposed technique can be used for the development of domestic UHF tag ICs (ISO 18000-6C, GJB 7377.1, etc.) based on CMOS technological processes, including ICs designed for radio frequency identification of critical infrastructure objects. Using the presented technique, the design of a PMU with an estimated efficiency value of 70%, an estimated Q-factor of the analog front-end of less than 15 at an RF input signal power of -12.7 dBm was performed.

The purpose of the article is to develop a technique that allows analyzing and quantifying the software protection level used in automated systems of internal affairs agencies in real time. To achieve this goal, the method of system analysis of existing approaches to assessing the protection level of automated systems software, the mathematical apparatus of queuing systems, methods of graph theory, probability theory and mathematical statistics, and the theory of semi-Markov processes were used. Quantitative static and dynamic indicators are proposed that make it possible to adequately assess the software protection in relation to current vulnerabilities in the dynamics of its functioning and taking into account the existing disadvantages of operation at the facilities of informatization of internal affairs bodies. Mathematical models and algorithms for analytical calculation of the proposed indicators in real time have been developed. The prospects for the practical implementation of the considered technique are related to the development of a software package for analyzing and evaluating the software protection in order to select its optimal version for increasing the protection level of official information of limited distribution circulating at specific informatization facilities of internal affairs bodies.

Various approaches to solving the problem of speech command recognition in real time using artificial neural networks (ANN) of several types are considered. A brief overview of deep fully-connected, convolutional and recurrent neural networks is given. It is shown that ANNs of convolutional and recurrent types are capable of providing the required level of performance and accuracy when performing inference in real time. A comparison is given of the performance of convolutional and recurrent algorithms when ported to the K1879VM6Ya hardware platform from the NeuroMatrix family of high-performance digital signal processors. When porting, the features of the microprocessor architecture were considered. All basic operations are performed on a vector matrix coprocessor. The advantage of convolutional ANN has been demonstrated. Considering the results of research into a neural network of this type on the K1879VM6Ya platform, it was transferred to a more productive hardware accelerator - the K1879VM8Ya system-on-chip. The prospects for creating a speech recognition system on the K1879VM8Ya platform are considered.

The article presents the main provisions of the theory of functional modeling in relation to solving an important and relevant problem for the methodology of information security managing – the development of mathematical models characterizing the dynamic capabilities of malware to implement destructive effects on critical information infrastructure objects. As a result of the analysis of the models that pose a threat to information security through the use of malicious codes, such as the "chain of cyber intrusions", the "unified chain of cyber intrusions", the basic and advanced models of Diamond intrusion analysis, the ATT&CK model, an up-to-date version of the functional model in the IDEF0 notation of the process of malware destructive impact on the operating environment of a special-purpose automated control system was built. The process of malware exposure is decomposed into individual stages, tactics, and techniques. The purpose of the research was to develop a variant of the malware impact on a special-purpose automated control system as a method of violating the state of information security and its processes of the system under consideration. The obtained results are a tool for the formalized presentation of the described processes in terms of the Markov processes and the development of analytical models, appropriate temporal and probabilistic characteristics for quantitative assessment of the intruder's ability to implement threats to the information security state in special-purpose automated control systems, through the malware impact.

Striking a balance between safety and performance remains a critical concern, despite advancements in the field. To address this issue, a versatile framework named Safety Goes Along with Performance (SGAWP) is proposed, centered on off-policy algorithms grounded in value function optimization. SGAWP utilizes reinforcement learning to navigate the data space, emphasizing high task performance while addressing risks (such as undesirable states) by incorporating safety costs into the value function. By integrating uncertainty management and task performance constraints, SGAWP aims to achieve improved safety performance alongside respectable task performance. Moreover, SGAWP leverages curiosity-driven exploration to expand the data space and employs task policies to enhance safety policy performance. As a result, SGAWP enhances safety performance with minimal loss in task performance. Beyond its success in reinforcement learning, SGAWP holds promise for applications like autonomous driving, where safety is paramount. Through rigorous experimentation across various off-policy algorithms, SGAWP demonstrates robust generalization and achieves its objectives effectively.

The article substantiates the key role anti-virus protection of automated control systems in ensuring the required protection level of information circulating and processed in these systems. A scientific hypothesis is formulated on ways to solve the problem adaptive control of the process ensure information protection in the automated control system from effects of impact of malware as a problem increasing the efficiency information support for these systems in the process of their functioning. The factors influencing the controllability of information security in the automated control system against threats from malware are formulated. The general form of expressions for characterizing the capabilities of an information protection violator, resident anti-virus protection technology in automated control systems and information processing technology in these systems is substantiated, as well as the general form of expression for the indicator of information protection controllability of in automated control systems from the effects of malware.

The article is focused on the development of a method for detecting and eliminating floating vulnerabilities in mobile applications, their nature is described, and existing methods of detecting and neutralizing floating vulnerabilities are investigated, their defects are noted. The developed method is based on analyzing the state of the application at different points in time and comparing it with a reference state. The proposed algorithm includes fixing the initial state, discrete analysis, detection and identification of vulnerabilities, their elimination, and prevention of additional risks. The scope of application of the results includes the developing and securing of mobile applications for Android operating system. The conclusions of the paper confirm the importance of detecting and preventing floating vulnerabilities to ensure a high level of information protection. The developed method allows to effectively detect and eliminate vulnerabilities, which contributes to the creation of secure and protected applications for users of mobile devices.

The article is devoted to the formalization of the process of unauthorized getting of computer information by intercepting informative signals of secondary electromagnetic radiation of the main technical means and systems by technical means of intelligence, as well as the removal informative guidance signals on the conductive lines of the main technical means by technical means of intelligence. Analyzing the completeness problem of the assessing information leakage threats due to the interception of informative signals of side electromagnetic radiation and leads, it must be stated that the procedure for identifying such threats is limited only to their detection by controlling only individual signs of manifestations of these threats. At the same time, the dynamics of the interception implementation process is not taken into account. This determines the need to solve the scientific problem of developing methodological foundations for the synthesis of algorithms for recognizing information leakage threats. The article presents the main stages of the procedure for formalizing the actions of the violator to intercept information. The basis for solving such problems is the procedure for forming the recognition feature space. In order to form such a space, functional modeling methods are used. The article presents a representation of the functional diagram in terms of the Markov process, as well as obtaining a mathematical expression to determine the average value of the time spent by the violator to achieve the target interception function.

Circuit solutions for physically unclonable functions (PUF) of a ring oscillator (RO) implementation for the purposes of digital devices identification, cryptographic keys and random numbers generation are considered. The effectiveness using configurable ROs (CROs) in PUF circuits is based not only on reducing of the hardware overhead of traditional RO PUFs, but also on the generation of output signals with unique frequencies, close in value in a case of the FPGA implementation. The proposed modification of the basic scheme of the CRO PUF, based on the XOR2 logic gates as controlled delay elements, allows to use a full set of input challenges instead of the basic scheme. It is shown that the delay value depends not only on the challenge, but also on the interconnect configuration of the structural elements of the CRO circuit. A time model of the modified CRO PUF is proposed, which analytically proves the influence of interconnects on the frequency of the generated signal, which was experimentally confirmed using the Xilinx Zynq-7000 FPGA. Based on this result, a new structure of PUF CRO with controlled interconnections is proposed.

This article discusses the development of recommendations for shielding individual parts of a technical means to reduce the energy of the signal emitted by the LVDS (Low Voltage Differential Signaling) interface. The LVDS interface is widely used in various electronic devices for transmitting low-voltage digital signals. In fact, LVDS became an interface for connecting laptops and monitor arrays, for this reason it is used in a large number of standard LCD panels. However, when signals are transmitted through the LVDS interface, side electromagnetic radiation occurs, which can be intercepted by intruders. To solve this problem, it is proposed to use the shielding recommendations described in this article. Shielding is the process of installing a metal shield that serves as a barrier to electromagnetic radiation around the cable, the technical means itself or its separate parts. This allows to reduce the level of signal emission and improve the quality of data transmission. The article describes methods for individual parts of a typical monitor with an LVDS interface shielding. Special attention is paid to evaluating the effectiveness of the proposed recommendation. Experiments are being carried out, during which the radiation level of the signal is measured before and after the refinement of the technical means. The results show a significant decrease in signal energy, which confirms the effectiveness of the proposed approach. Thus, this article is of interest to specialists in the field of electronics and engineers involved in the development and improvement of data transmission interfaces. The proposed recommendations can be used to reduce electromagnetic radiation in various electronic devices with LVDS interface.

Abstract In an era of increasing political polarization, its analysis becomes crucial for the understanding of democratic dynamics. This paper presents a comprehensive research on measuring political polarization on X (Twitter) during election cycles in Spain, from 2011 to 2019. A wide comparative analysis is performed on algorithms used to identify and measure polarization or controversy on microblogging platforms. This analysis is specifically tailored towards publications made by official political party accounts during pre-campaign, campaign, election day, and the week post-election. Guided by the findings of this comparative evaluation, we propose a novel algorithm better suited to capture polarization in the context of political events, which is validated with real data. As a consequence, our research contributes a significant advancement in the field of political science, social network analysis, and overall computational social science, by providing a realistic method to capture polarization from online political discourse.

Abstract Similarities and differences between the features related to the productivity of onshore and offshore wind energy are developed with the aid of information theory techniques complemented by normal statistics. The data comes from the 13‐year period between 2010 and 2022 for the registered turbines in Germany (practically all). The information content of the generated power is dynamically measured by the mutability of the files storing the information. Monthly statistics show that in spite of the Summer months being relatively unproductive, the corresponding mutability shows the possibility of making use of short periods of intermediate productivity in the case of offshore plants. Favorable conditions for wind energy generation in Wintertime are reached for both onshore and offshore production, although the latter is favored. More homogeneity and stability in the data are still necessary to generalize algorithms, protocols, and criteria. This general study shows the success of the information theory techniques in describing wind ramps. Applications to specific zones could improve the efficiency and capacity factor of particular wind turbines depending on their exposure to wind streams or the blocking of nearby mountains and forestry. The information theory techniques presented here allow for a different and novel viewpoint to detect favorable and unfavorable wind energy periods.

This study presents a methodological framework for optimal placement of pressure sensors in Water Distribution Networks (WDNs) for leakage monitoring under uncertainty. Monte Carlo simulation is utilized to simulate leakages of different magnitudes at various nodes in the WDN taking into consideration background noise and minimum resolution of pressure sensors. A novel sensor preselection algorithm based on community detection and maximum entropy computation to reduce the search space of the pressure Sensor Placement Problem (SPP) is presented. The pressure SPP is formulated as a multi-objective optimization problem that seeks to maximize Joint Entropy, Coverage, and minimize Total Correlation. NSGA-II is used to solve the SPP and the solutions in the optimal Pareto front are ranked using a hybrid Entropy TOPSIS to eliminate potential bias and subjective human judgement in optimal sensor configuration implementation. The sensor preselection algorithm achieved a 67% reduction in the search space (possible sensor positions) of the case study, C-TOWN WDN, with only 2.78% reduction in coverage. The result of the pressure SPP indicates only 21 pressure sensors are needed to cover 95.45% of the WDN under study. Finally, the overall performance of the proposed methodological framework is presented and compared with other related works.

Probabilistic prediction models exist to reduce surprise about future events. This paper explores the evaluation of such forecasts when the event of interest is rare. We review how the family of Brier-type scores may be ill-suited to evaluate predictions of rare events, and we offer an alternative to information-theoretical scores such as Ignorance. The reduction in surprise provided by a set of forecasts is represented as information gain, a frequent loss function in machine learning training, meaning the reduction in ignorance over a baseline having received a new forecast. We evaluate predictions of a synthetic dataset of rare events and demonstrate the differences in interpretation of the same datasets depending on whether the Brier or Ignorance score is used. While the two types of scores are broadly similar, there are substantial differences in interpretation at extreme probabilities. Information gain is measured in units of bits, an irreducible unit of information, that allows forecasts of different variables to be comparatively evaluated fairly. Further insight from information-based scores is gained via a similar reliability–discrimination decomposition as found in Brier-type scores. We conclude by crystallising multiple concepts to better equip forecast-system developers and decision-makers with tools to navigate complex trade-offs and uncertainties that characterise meteorological forecasting. To this end, we also provide computer code to reproduce data and figures herein.

This article dealt with further properties of the Renyi entropy and the residual Renyi entropy of $ k $-record values. First, we discussed the Renyi entropy order and its connection with the usual stochastic and dispersive orders. We then addressed the monotonicity properties of the residual Renyi entropy of $ k $-records, focusing on the aging properties of the component lifetimes. We also expressed the residual $ n $th upper $ k $-records in terms of Renyi entropy when the first dataset exceeded a certain threshold, and then studied various properties of the given formula. Finally, we conducted a parametric estimation of the Renyi entropy of the $ n $th upper $ k $-records. The estimation was performed using both real COVID-19 data and simulated data.

Research into digital platforms has become increasingly difficult. One way to overcome these difficulties is to build on data access rights in EU data protection law, which requires platforms to offer users a copy of their data. In data donation studies, researchers ask study participants to exercise this right and donate their data to science. However, there is increasing evidence that platforms do not comply with designated laws. We first discuss the obligations of data access from a legal perspective (with accessible, transparent, and complete data as key requirements). Next, we compile experiences from social scientists engaging in data donation projects as well as a study on data request/access. We identify 14 key challenges, most of which are a consequence of non-compliance by platforms. They include platforms’ insufficient adherence to (a) providing data in a concise and easily accessible form (e.g. the lack of information on when and how subjects can access their data); (b) being transparent about the content of their data (e.g. the lack of information on measures); and (c) providing complete data (e.g. the lack of all available information platforms process related to platform users). Finally, we formulate four central recommendations for improving the right to access.

Abstract Edgar Morin is more than 100 years old and has produced numerous original ideas. Complex Thinking is his approach to complexity and took almost thirty years to be written. He developed it based on many other thinkers but chiefly, we argue, on Wiener’s Cybernetics, von Bertalanffy’s General System Theory and Shannon’s Information Theory. This article describes and discusses how those latter theories have been incorporated into Morin’s thought, especially in La Méthode, his magnum opus, and presents, in a comparative fashion, his pros and contras on each of them. In our conclusion, we discuss how some of Morin’s criticisms of the founding theories might be unjust and also present a summary of some judgmental appraisals of Complex Thinking.

Human travelling behaviours are markedly regular, to a large extent predictable, and mostly driven by biological necessities and social constructs. Not surprisingly, such predictability is influenced by an array of factors ranging in scale from individual preferences and choices, through social groups and households, all the way to the global scale, such as mobility restrictions in response to external shocks such as pandemics. In this work, we explore how temporal, activity and location variations in individual-level mobility—referred to as predictability states—carry a large degree of information regarding the nature of mobility regularities at the population level. Our findings indicate the existence of contextual and activity signatures in predictability states, suggesting the potential for a more nuanced approach to estimating both short-term and higher-order mobility predictions. The existence of location contexts, in particular, serves as a parsimonious estimator for predictability patterns even in the case of low resolution and missing data.

Background: In the wake of Industry 4.0, libraries are integrating Fourth Industrial Revolution (4IR) technologies to enhance efficiency. However, this shift in practice raises ethical and privacy concerns, particularly regarding the Protection of Personal Information Act (PoPI Act). Objectives: This literature review explores the ethical and privacy challenges posed by 4IR technologies in delivering information services to library patrons including the impact on PoPI Act compliance in addressing data privacy concerns. Method: Adopting a systematic approach, this literature review employs the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart and inclusion criteria focussed on 4IR in libraries and its relation to the PoPI Act. Peer-reviewed articles in English from 2013 to 2023 were sourced from scholarly databases. Results: The review highlights the transformation of academic library services in the 4IR era and the consequent privacy challenges. Concerns arise from advanced library systems and extensive data retention. While libraries operate non-profitably, the adoption of 4IR technologies for data acquisition mirrors commercial practices, raising ethical questions. Patron privacy issues extend beyond traditional data collection to potential misuse and improper data handling as libraries often work with vendors. Conclusion: The integration of 4IR technologies in academic libraries necessitates a delicate balance between improved services and safeguarding user privacy and the PoPI Act serves as a crucial regulatory framework. Librarians must navigate the evolving landscape of data ethics, emphasising transparency, accountability and adherence to privacy legislation. Contribution: The introduction of artificial intelligence and 4IR technologies to library information services has unlimited possibilities including countering misinformation and disinformation, and the expansion of library services to tech-savvy users beyond the physical walls of the library building. However, the deployment of these technologies raises new questions about ethical concerns that the use of these technologies poses to information professionals in the rendition of library services. The results of this study will be useful for policy and professional practice in taking full advantage of 4IR technologies and services.

Background: Smart cities leverage advanced technologies such as the Internet of Things (IoT), fifth generation (5G) networks, and data analytics to enhance citizens’ quality of life, focussing on creating efficient, functional, and eco-friendly urban environments. While these initiatives offer significant benefits, there are ongoing concerns about data security and privacy. Objectives: This article investigates the data security and privacy risks and challenges in emerging South African smart cities. The objectives are to identify these risks, assess the effectiveness of current security measures, and contextualise these vulnerabilities within the South African and global contexts. Method: A qualitative approach was adopted, involving virtual interviews with 20 Subject Matter Experts (SMEs) through purposive and snowball sampling. The raw data were thematically analysed, revealing significant themes. Results: Emerging South African smart cities face several risks and challenges, including poor governance, a shortage of skills, a lack of awareness and training, insufficient funding, and a combination of these factors. Conclusion: The research highlights the importance of safeguarding individuals’ data and privacy in the context of smart cities, advocating the need for proactive measures to address these concerns. Contribution: This article promotes interdisciplinary dialogue, leading to more comprehensive solutions. In addition, exploring data security and privacy in emerging smart cities aids in understanding the implications of information management practices. Although the article focuses on emerging South African smart cities, the challenges discussed have global relevance.

Background: The impact of Digital Financial Services (DFS) on women’s economic empowerment (WEE) has aroused the attention of practitioners and scholars over the past decade. However, its influence on the WEE of women domestic workers has largely been overlooked, particularly in marginalised and vulnerable communities. Objectives: This study investigated the DFS that women domestic workers use and how they enhance the economic empowerment of women domestic workers. Method: The study utilised qualitative data from in-depth interviews with women domestic workers (n = 40) in Nigeria. Thematic analysis of qualitative data identified three themes, namely, financial security, privacy and agency, that constitute pathways to women domestic workers’ economic empowerment. Results: The findings indicate that the availability and user-friendliness of DFS play a significant role in promoting the extracted themes among women domestic workers, thereby enhancing their reputation, relevance in the affairs of the family and overall growth and development. The study indicated that ownership of a mobile phone is a foundational element that drives DFS, which powers WEE. Conclusion: Policymakers, employers and relevant stakeholders should acknowledge this importance and strive to establish mechanisms that enhance and safeguard the financial rights of domestic workers. Contribution: This study contributes to the ongoing endeavours of policymakers, governments and researchers in comprehending the expanding realm of women’s empowerment by exploring the potential of DFS as a viable means to empower all women and girls.

Background: With the rapid development of Internet technology and social media, a growing number of companies now not only transfer their traditional offline business interactions to online but also engage in online customer relationship management, market share expansion and brand building. Consumer interaction in the virtual brand community has become progressively more important in consumers’ purchase decision. Objectives: The purpose of establishing virtual brand community is to obtain brand loyalty, but the existing research rarely discusses the impact of member interaction on brand loyalty. To address this research gap, we explore the influence mechanism between virtual brand community member interaction and brand loyalty. Method: To verify the research hypothesis, we distributed and collected 393 valid questionnaires on wenjuan.com, one of the largest online questionnaire service companies in China. Results: Our results reveal that virtual brand community members’ interaction has a positive impact on brand loyalty. In addition, community identification also has a partial mediating effect. Moreover, media richness regulates the relationship between member interaction and community identification. Conclusion: This article mainly investigates the virtual brand community member interaction behaviours. We also explore the influences of different dimensions of virtual brand community interaction on community identification and member brand loyalty. Contribution: This article deepens our understanding of online platform members’ participance behaviours.

Background: South African universities are dealing with concerning socio-economic issues and budgetary limits that affect university operations negatively. It is no longer viable for most universities to purchase and maintain information technology (IT) infrastructure systems while also keeping up with the ever-changing technology across the world. Objectives: The aim of this article is to explore the benefits that come with infrastructure as a service (IaaS), as compared to the on-premises model that is currently used by most South African universities. Method: This article adopts both transaction cost theory (TCT) and diffusion of innovation theory (DOI) as the underpinning theories. The interpretivist paradigm was applied to gain a comprehensive understanding of how university management perceives IaaS adoption. Results: The results introduce three new and critical factors that need to be considered by university managers whenever they want to move their on-premises IT model to cloud IaaS: trust, security and attitude. Conclusion: The research finds that IaaS offers advantages in scalability, flexibility, accessibility and on-demand deployment. These findings underscore the importance of addressing barriers to IaaS adoption within the specific context of South African universities. Contribution: The findings of this article add to the cloud computing literature, by presenting a new model that IT decision-makers can utilise when considering moving their on-premises IT infrastructure to IaaS in South African universities. The article recommends that future research could expand the number of universities from which data are collected.

Background: Workarounds are creative human actions that bypass a known problem in a system or a policy. Workarounds serve as temporary ‘fixes’ when effective but will often compromise the integrity of information systems in the long term, mainly when they are ineffective. Objectives: Forming part of behavioural studies in information systems security, the study aimed to investigate how workarounds influence the integrity of information security systems across businesses. Method: A quantitative approach that followed the positivism paradigm was employed. A survey strategy was used, and data were collected using closed-ended questionnaires targeting employees working in the Gauteng province of South Africa. The survey elicited responses from 207 professional participants. Analysis was done using Statistical Package for Social Sciences (SPSS) v29 software. Results: The study suggests that Individuality and Job characteristics are crucial predictors of workarounds, with the most notable findings pointing to a significant positive association between Workaround and Information security integrity. Crucially, highly individualistic employees are more likely to initiate workarounds, and in turn, this influences information security integrity. Conclusion: The work shows that employees with highly individualistic personalities are more likely to initiate workarounds and should be trained and supervised to mitigate this attribute, as this might be detrimental to information security integrity. Contribution: The study contributes theoretically by showing how workaround activities influence information security integrity. This study will assist enterprises in fortifying their information security measures.

Background: Health system planning and monitoring rely on routine data collection, analysis and utilisation. However, underdeveloped countries need more data for decision-making. South Sudan’s data management framework only partially functions, with delayed data collection and inaccurate data. The study examined the factors affecting data quality in Maridi County, South Sudan, aiming to improve resource forecasting and equitable health service delivery. Objective: The study sought to identify the obstacles and opportunities for improving data quality in health information systems (HIS) in Maridi County, Western Equatoria State, South Sudan. Methods: A cross-sectional study involving 106 respondents was conducted on 12 healthcare facilities in Maridi County. Statistical Package for the Social Sciences (SPSS) version 25 was used for descriptive, factor and thematic analysis to understand data quality, focussing on behavioural, organisational and technical aspects. Result: The study revealed that insufficient motivation, negative staff attitudes, excessive workloads, a lack of cooperation, personnel insufficiency, inadequate supervision, feedback and training influenced data quality. These factors were interrelated, with over 50% of variables showing weak to strong correlations. Set of standard indicators correlated with the presence of standard data collection tools (r = 0.51). Regular feedback from the County Health Department linked with completeness (r = 0.63) and the training of personnel on health management information systems (HMIS) and completeness resulted in moderate association (r = 0.488). Conclusion: Staff motivation, optimal staffing, training, regular feedback, and continuous supervision are crucial for maintaining the appropriate skill set for data quality. Contribution: Data quality can be achieved when standard tools and human resources are maintained and are evenly distributed.

Background: While the Internet of things (IoT) has been praised for its potential to improve food security and combat climate change, it is unclear how agricultural entrepreneurs (especially farmers) in emerging contexts are harnessing this technology to leverage agricultural productivity. Objectives: Given the lack of documentation of novel-technology-supported farming approaches in relevant extant literature in emerging economies, this study sought to explore how South African farmers are harnessing the strength of IoT to leverage productivity in crop farming. Method: To address this research gap, a systematic literature review was conducted to establish how IoT was implemented in crop farming in resource-constrained contexts of South Africa. These databases, namely Google Scholar, Scopus, MDPI, IEEE Xplore, and Science Direct, were utilised to gather the relevant information. Results: The findings highlighted that IoT technology presented multiple opportunities for improving operational efficiency and connectivity and facilitating remote management of agricultural activities. Conversely, the findings suggested that the utilisation of IoT in crop farming poses serious challenges arising from software complexity, data security, lack of supporting infrastructure and technical skills. Conclusion: This article demonstrates how institutional voids, human capital and technological gaps in the South African farming industry undermine crop farming, food security in the communities and government efforts at promoting the latest technologies for leveraging agricultural productivity and the farming industry in general. Contribution: The study has contributed to filling the gap in the IoT literature in South Africa and worldwide. This study also contributed by aligning the theory to the study.

Background: Technological advancements have heightened the importance of safeguarding individual privacy and data. In response to these challenges, South Africa introduced the Protection of Personal Information (POPI) Act. This legislation established robust legal frameworks aimed at protecting confidential information and upholding individuals’ right to anonymity. However, there is a significant research gap regarding the POPI Act’s direct implications and effectiveness in the context of artificial intelligence (AI) adoption and utilisation. Understanding the interplay between the POPI Act and AI technologies is crucial for ensuring regulatory compliance, safeguarding personal data and fostering responsible AI deployment in South Africa. Objectives: This study investigates the POPI Act’s applicability in addressing privacy issues related to AI adoption in various sectors. Method: The research uses a document review methodology to analyse the documents and synthesise the results. This approach offers efficiency, accessibility, cost-effectiveness and non-intrusiveness benefits, making it a valuable tool for qualitative research across various disciplines. Results: Despite the POPI Act’s guiding principles aligning with key concepts of personal information protection, there are several gaps in its applicability to AI advancements across various sectors. Conclusion: The study emphasises the need for a dynamic legal framework that evolves with AI advancements, advocating for the incorporation of more stringent measures to address emerging privacy concerns. Contribution: The research contributes to the ongoing discourse on data protection and AI by highlighting the need for a forward-thinking legal framework that balances innovation and privacy, ensuring that the POPI Act remains effective in the face of evolving technologies.

Abstract In the domain of modern manufacturing, computer numerical control (CNC) milling machines have emerged as instrumental assets. However, the data they generate is of vast amount, but usually contains redundancies and displays consistent patterns, making it inefficient for deep learning training. This paper proposes a novel sampling algorithm tailored for CNC milling machine data, emphasizing both diversity and efficiency. The proposed method leverages the entropy concept from the information‐theoretic perspective to evaluate and enhance data diversity, aiming to achieve efficient learning with high accuracy. This in turn enables to not only facilitates a deeper understanding of CNC data characteristics but also contributes significantly to the optimization of deep learning training processes in the context of CNC milling data.

This article provides an initial analysis of the EU AI Act's (AIA) approach to regulating general-purpose artificial intelligence (AI) – such as OpenAI's ChatGPT – and argues that it marks a significant shift from reactive to proactive AI governance. While this may alleviate concerns that regulators are constantly lagging behind technological developments, complex questions remain about the enforceability, democratic legitimacy, and future-proofing of the AIA. We present an interdisciplinary analysis of the relevant technological and legislative developments that ultimately led to the hybrid regulation that the AIA has become: a framework largely focused on product safety and standardisation with some elements related to the protection of fundamental rights. We analyse and discuss the legal requirements and obligations for the development and use of general-purpose AI and present the envisaged enforcement and penalty structure for the (un)lawful use of general-purpose AI in the EU. In conclusion, we argue that the AIA has significant potential to become a global benchmark for governance and regulation in this area of strategic global importance. However, its success hinges on effective enforcement, fruitful intra-European and international cooperation, and the EU's ability to adapt to the rapidly evolving AI landscape.

Background: The Fourth Industrial Revolution (4IR) has transformed value chains across various industries. However, there is still a lack of knowledge on how to effectively utilise 4IR technologies in organisational value chains. Research must explore how organisations can use 4IR technologies to optimise their value chain performance. Objectives: The primary aim of this study is to explore the holistic impact of 4IR technologies on the structural transformation of value chains. Method: Applying the principles of the resource-based view and the VRIO (Valuable, Rare, Inimitable and Organisation) framework, a systematic literature review was conducted to map the intersection of 4IR technologies and value chain performance. It utilised resource-based view theory and the VRIO framework to assess the role of 4IR in transforming value chains. This study focused on the VRIO integration of 4IR resources, such as advanced data analytics, Internet of Things (IoT), proprietary technologies and skilled workforces. Results: The research shows that 4IR resources are valuable and rare assets that require meticulous organisational integration, adaptable organisational structures, innovation-driven cultures and cross-functional collaboration. Conclusion: The strategic integration of 4IR resources within value chains can lead to innovation, efficiency and enduring competitive advantage. Contribution: This study provides a strategic roadmap for integrating emerging 4IR technologies into business value chains, cultivating a deeper understanding and maximising the benefits of these technologies to achieve sustained value creation and competitive advantage.

Background: South African insurance companies are under pressure to adapt to the constantly changing environment and customer-changing requirements. Agile software development presents itself as a viable solution for swiftly meeting these demands. However, there is a lack of comprehensive understanding regarding the current utilisation of agile methodologies within the South African insurance sector; this article aims to bridge this gap. Objectives: The purpose of this theme is to fully understand the extensive level of the experience for the participants and the nature of projects the participants have been involved in and lastly time frames of the projects and how long have insurance been using agile methodology. Method: For this study, purposive sampling that involves the selection of the units to be observed based on your own judgement about which ones were the most useful or representative will be applied. The criteria were based on the participants having played a role as stakeholder in a project that has used agile methodology within the selected organisation within the past 3 years to remain relevant to this study purpose. Results: The identified pattens from the respondents showed that agile methodology is currently utilised for the following in the selected insurance company: software upgrades new product new function Conclusion: In summary, the current state of agile methodology utilisation in a South African insurance company is associated with application transformation to cloud computing, work transformation, onboarding of new applicants, environment enhancements, schema amendment, introduction of new product such as sales force, automating insurance claims documents, scheme enhancement, fund anniversary and renewal of people’s schemes. Contribution: This comprehensive research significantly contributes to the body of knowledge, shaping the strategic direction of agile methodologies within software development project environments.

Background: Patient records are essential to healthcare professionals access to health information, allow them to assess symptoms and signs across a wider temporal range and improve diagnosis and treatment. The study acknowledged the significance of healthcare informatics such as Smart Card Technology (SCT) in today’s dynamic health systems. Objectives: This study aimed to investigate factors that influence healthcare professionals’ intentions to use SCT in public healthcare. Method: The study adopted a quantitative research approach using questionnaire surveys as a means to collect data from a total of 406 healthcare professionals from hospitals in Tshwane. Results: The findings showed that all of the variables based on the diffusion of innovation (DOI) theory, including behavioural intention (BI), social influence (SI), service quality (SQ), user satisfaction (US), compatibility (C), system use (SU) and information quality (IQ), as well as the health unified theory of acceptance of user technology (HUTAUT), DeLone and McLean’s Information Systems Success (DM ISS) model, had a positive impact on the intention to use the SCT. Continued use of SCT was positively correlated with user satisfaction and found a favourable correlation between BI and all of the factors. Conclusion: The healthcare professionals’ intention to utilise SCT was notably impacted by various factors, including SI, SQ, US, C, SU and IQ. These factors collectively influence the intention to utilise the SCT. In addition, these findings show that BI has an impact on the intention to utilise SCT. Contribution: The results offer a more profound understanding of the variables that impact the use of SCT to improve patient outcomes. In developing countries, public hospitals can enhance their technology acceptance by utilising the SCT adoption framework. Furthermore, this study only included healthcare professionals who worked for public hospitals; to provide a more complete picture of both sectors, future research might concentrate on a target group of healthcare professionals who worked for both public and private hospitals. In addition, future studies should examine patient perceptions regarding the use of SCT in healthcare delivery and the characteristics that encourage patients to adopt and use the technology.

Background: About 1.3 billion people around the world are living with disabilities, facing challenges such as premature death, mental conditions and other diseases. In South Africa, over 3.5 million people live with disabilities, making up about 6.6% of the total population. People with disabilities face numerous challenges of prejudice, and increasingly, digital exclusion is also becoming a concern. Objectives: The objective of this study was to determine the extent and challenges that People with disabilities (PwD) have in accessing digital technology, assess the level of the digital divide, and propose measures to narrow this gap. Data were collected using survey questions, and the target population were people with disabilities located in various districts of KwaZulu-Natal province, South Africa. Method: The study utilised a quantitative approach and analysed the findings using the Statistical Package for the Social Sciences (SPSS). Results: The results indicated that people with disabilities are marginalised and have limited or no access to technology. The research concludes that there needs to be a targeted approach towards assisting people with disabilities, and stakeholders involved need to combat the digital divide for disadvantaged individuals to promote positive social change. Conclusion: More needs to be done to increase society’s sensibilities towards people living with disabilities. Technology penetration seems to be a challenge and individuals with disabilities are left with a significant gap that needs to be addressed. Contribution: This article contributes to bridging the technology inequality for people with disabilities in historically disadvantaged societies.