Advances in Systems Science and Applications
Advances in Systems Science and Applications (ASSA) is an international peer-reviewed open-source online academic journal. Its scope covers all major aspects of systems (and processes) analysis, modeling, simulation, and control, ranging from theoretical and methodological developments to a large variety of application areas. Survey articles and innovative results are also welcome. ASSA is aimed at the audience of scientists, engineers and researchers working in the framework of these problems. ASSA should be a platform on which researchers will be able to communicate and discuss both their specialized issues and interdisciplinary problems of systems analysis and its applications in science and industry, including data science, artificial intelligence, material science, manufacturing, transportation, power and energy, ecology, corporate management, public governance, finance, and many others.
International Institute for General Systems Studies, Pennsylvania, USA
Methods and Models of Clustering and Conceptual Aerodynamic Design of Aircraft under Uncertainty
Methods for coordinating and aggregating expert information on the uncertain parameters of aircraft components were developed. They were modified by using uncertainty theory methods, a mathematical model, and algorithms for generating aircraft configuration options. These methods use clustering into a fixed number of classes to aggregate the generated options and identify characteristic types of aircraft configurations. It reduces the dimensionality of the data during multivariate analysis of design solutions. Algorithms for constructing Pareto fronts and selecting optimal representatives for each cluster were developed based on weighted criteria aggregation. Based on the developed methods and models, a three-level architecture for transforming uncertainty into deterministic recommendations is proposed. There are a generation of non-deterministic component characteristics; a generation of configuration options; and an aggregation and clustering of options. Aircraft components are formalized as sets of uncertain parameters defined by corresponding distributions: a wing, a fuselage, an engine. The developed methods and models were validated based on a comparison of the obtained results with data about real aircraft. A formalized method and models for matching and aggregating expert information based on clustering methods for a fixed number of classes. Testing on real data, as a result of which 4 deterministic recommendations on optimal aircraft configurations were obtained. Implementation of the developed methods in the form of algorithms that can be integrated into an intelligent system, providing a choice of technologically feasible and cost-effective solutions. Clustering allows you to group aircraft configuration options, identifying characteristic types of design solutions. Verification based on real aircraft data has confirmed the adequacy and practical applicability of the method of matching and aggregating expert information in solving urgent aircraft engineering problems. At the same time, it is possible to reduce the design time by automating the processes of generation and evaluation of limited configuration options.
Clustering, conceptual aerodynamic design, aircraft, uncertainty, system reliability
Copyright (c) 2026 Advances in Systems Science and Applications
Bayesian Estimation of COVID-19 Under-Reporting with Time-Varying Rates: A Case Study of Morocco
Accurate estimation of COVID-19 cases remains challenging in many low and middle-income countries due to substantial under-reporting driven by limited testing capacity, asymptomatic infections, and surveillance system constraints. This study develops an advanced Bayesian hierarchical framework to estimate the true scale of the COVID-19 pandemic in Morocco while explicitly modeling time-varying case detection and seasonal effects. Using national surveillance data from March 2020 to June 2022, we estimate a time-varying reporting rate increasing from 10.7% to 11.5% throughout the pandemic, indicating significant improvements in surveillance capacity. The model reveals that the actual epidemic was substantially larger than official reports suggested, with a final attack rate of 30.6% (95% HDI: 24.9--37.3%) compared to the reported 3.2%.. Our methodological innovations include temporal reporting rate estimation and seasonal component integration, providing a more realistic framework for epidemic assessment in settings with evolving surveillance systems.
COVID-19, Under-reporting, Bayesian Inference, Time-varying Parameters, Epidemiological Surveillance
Dynamic Linearizing Feedback Design for a Single-Link Manipulator under Unmatched Disturbances
Using the output feedback linearization method, we consider the design of a servo system for a single-link manipulator, which is elastically coupled to a gearbox shaft and controlled by a sensorless DC motor. Unlike typical problem formulations, we assume significant parametric uncertainty in the controlled plant model and the presence of external, unmatched disturbances. The output (measured and controlled) variable is the angular position of the manipulator, which, during control, tracks the reference trajectory. There is no analytical description of the reference signal; only its current value is known. The design of a tracking system is based on the equivalent canonical form of the “input – output” relationship with respect to mixed variables, which are functions of state variables, external influences, and their derivatives. A combined control law has been formalized that linearizes a closed-loop virtual “input – output” system under conditions of an uncertain control multiplier. A reduced observer with piecewise linear corrective actions in the form of nested saturators has been developed. The observer is constructed on the basis of a canonical system with an uncertain input and, based on the tracking error measurements, estimates mixed variables and generalized disturbances with a given accuracy without dynamic generators of external influences and additional expansion of the state space. It is shown that observer gain coefficients tuning can be performed using a reference Hurwitz polynomial with a large stability margin. The actual gains will be many times smaller than those of a typical observer with linear correction without saturation, which generates large spikes in estimated signals and control action at the beginning of the transient process. Numerical simulation results are presented, demonstrating the performance of the tracking system and the advantages of the developed observer compared to a typical observer with linear correction without saturation.
tracking, uncertain parameters, unmatched disturbances, reduced-order state observer, piecewise linear function with saturation, single-link manipulator
On the Best Constant in the Jackson–Stechkin Inequality
In this article, we obtain an upper bound for the exact constant in the Jackson-Stechkin inequality in the space L^p(T), where T is one-dimensional torus, 1 \le p \le \infty. This inequality relates the best approximation of a function by trigonometric polynomials to its generalized modulus of smoothness of order r with non-constant steps depending on the parameters h and a in the space L^p(T). We consider the modulus of smoothness with a non-constant step depending on both the classical step h and the auxiliary parameter a. We obtain an upper bound for the exact constant in the Jackson-Stechkin inequality that depends only on the smoothness parameter r and is independent of the other parameters a and p. For r=2 and r=3, we derive more precise bounds than in the general case.
Jackson-Stechkin inequality, approximation by trigonometric polynomials
Firefly Optimization Analysis of Steel Manufacturing Plant under the Approach of RPGT
This study presents a reliability and cost‑based optimization framework for a steel manufacturing plant. It consists of four subsystems: "Grinding Machine," "Descaling Machine," "Hot Steckel Mill," and "Cutting Machine." A grinding machine is frequently utilized. If this machine malfunctions, it might lead to a serious system failure. Thus, we use a standby unit equipped with a grinding machine and a descaling machine that consists of two parallel machines operating simultaneously. This subsystem can operate with a single machine at a lower capacity. The failure in the hot steel mill and cutting machine leads to the complete breakdown of the system. The study's goal is to maximize manufacturing plant production by enhancing system dependability through better management, control, and maintenance. The analysis focuses on four key performance measures: Mean Time to System Failure (MTSF), steady‑state availability, busy period, and the expected number of server visits under the approach of RPGT. A Markov-based simulation system model has been developed for performance analysis and solved using the firefly algorithm (FA) to improve the outcomes. The main tenets of this approach are as follows: subsystem repair and failure rates vary; repaired units function as reliably as new ones over a certain length of time; repair and failure rates operate independently; and a single repair facility meets all demands. These simplifications make it possible to analyze system performance and dependability in a targeted manner. In order to maximize industrial advantages and maximize dependability, the optimal values of all parameters based on the exponential distribution are taken into consideration. To examine the findings and make inferences about the behavior of the system, tabular and graphical analyses are provided. The work that is being presented aims to provide the most favorable operating condition for the steel manufacturing plant, balancing high reliability, low maintenance burden, and maximum long‑run profit.
FA, RPGT, steady-state availability, server visits, standby unit
Reliability Assessment and Cost Optimization of a Fault-Tolerant Rice Processing System under Environmental Disturbances
Modern industries heavily depend on automated and semi-automated production units, where uninterrupted operation is crucial to meeting market demand and maintaining grain quality. However, such systems are exposed not only to internal component failures but also to environmental disturbances such as humidity, temperature fluctuations, dust, and power-quality variations. This paper develops a comprehensive reliability and cost optimization model for a four-unit rice industry system operating under a fault-tolerant framework with standby support. An additional environmental error stage is explicitly incorporated into the state transition diagram to capture real-world operating conditions. The system behaviour is modelled as a continuous-time Markov process with lacking fault exposure, restart mechanism, and repair capacity subject to service interruption. Transient state probabilities are derived using Laplace transform and matrix-analytical techniques. Key performance indicators, including Mean Time to Failure, system reliability, availability and Average number of component failures, are evaluated. A Cost-effective ratio (CER) is further formulated by combining operational, repair, environmental recovery, and downtime costs. Numerical illustrations demonstrate how environmental disturbance intensity and maintenance parameters influence system performance. The results show that integrating fault-tolerant design with environmental recovery strategies significantly improves operational reliability while reducing long-term system cost in rice processing industries.
Mathematical Modeling of Prostate Cancer Dynamics and Therapy
This study considers a mathematical model for selecting an optimal chemotherapybased treatment strategy for prostate cancer, with the goal of minimizing the integral of the squared deviation of the PSA tumor marker from its normal value over the entire course of treatment. The optimal strategy is obtained by solving a nonlinear programming problem using the method of local variations. It should be noted that mathematical modeling of biological processes is a complex and not always fully formalizable problem. Verifying the adequacy of such models requires the joint efforts of teams of biologists and physicians and constitutes a separate task. Undoubtedly, the main and decisive role in the fight against cancer belongs to advances in biology and medicine. On the other hand, the success of mathematical methods in many related scientific fields makes it reasonable to hope that the results of mathematical modeling of cancer dynamics, together with appropriate experimental validation, may suggest new ways to choose treatment protocols.
Mathematical model, prostate cancer, system of nonlinear differential equations, method of local variations
A Novel Identity-Based Digital Signature Scheme Compliant with GOST 34.10-2018 and Its Application in Digital Government Systems
GOST 34.10-2018 serves as the official standard for public key cryptography in the Russian Federation, constituting a vital pillar of the broader GOST regulatory framework. This standard specifies a digital signature algorithm characterized by high security and performance, predicated on Elliptic Curve Cryptography (ECC). Due to its robustness and alignment with national security requirements, it is officially mandated for use in governmental information systems, financial transactions, and diverse cryptographic applications. However, as digital ecosystems evolve toward complex architectures—such as digital transformation and Digital Government—the need for streamlined and efficient certificate management becomes increasingly paramount. This paper addresses that challenge by proposing a novel, secure, and efficient Identity-Based Signature (IBS) scheme based on the GOST 34.10-2018 standard. Unlike traditional Public Key Infrastructure (PKI), our identity-based approach allows a user’s public key to be derived from unique identifiers, significantly reducing the administrative burden of certificate revocation and storage. The security of the proposed scheme is rigorously evaluated within the Random Oracle Model (ROM), demonstrating existential unforgeability against sophisticated forgery attacks. Furthermore, we perform a comprehensive performance analysis, assessing the computational cost in comparison to existing publications and experimental efficacy. Results indicate that the signature process maintains high throughput and low latency. Consequently, the proposed scheme is both theoretically sound and highly viable for practical integration into modern digital infrastructures, ensuring alignment with established digital signature standards and operational efficiency.
On Sufficient Conditions for Optimality in the Minimum Frequency Maximization Problem for a Shell of Revolution at a Given Weight
We consider shallow elastic shells with a given circular boundary and seek an axisymmetric shell shape maximizing the fundamental shell vibration frequency at a given weight. The choice of functionals considered during optimal design is part of the formulation of optimization problems. The most typical problems in the theory of optimal design of compressed structures are the problems of maximizing the critical ω0 (ω0 is the minimum eigenvalue) for a given weight of the structure and the problems of minimizing the weight under the constraint ω0 ≥ μ, where μ is a given number. We study an optimal control problem described by an eigenvalue problem for a system of differential equations with variable coefficients some of which are nonintegrable near zero. To solve this problem, in this paper we derive sufficient optimality conditions under the assumption that the frequency domain functional is Fréchet differentiable and the necessary conditions in the optimization problem are satisfied. It is proved that if the necessary conditions are satisfied, then the sufficient conditions are realized as well. Using the sufficient conditions, as an application, we also determine the optimal shape f = f (r) for the case in which h(r) = h0.
second Fréchet differentiability, frequency functional, sufficient condition, optimality
Optimizing the Social Network in the SCARDO Model
This article examines an optimal control problem focused on optimizing the structure of a social network to achieve a desired opinion distribution in the population within a finite time horizon. The opinion dynamics adhere to the SCARDO model, and the network structure is operationalized using a stochastic block model whose parameters are subject to adjustment. We derive an analytical result demonstrating that the problem under consideration can be reduced to a control problem in which the structure of the network is fixed, but the parameters of the ranking algorithm—integrated into the model—are optimized. The latter problem is already solved in the scholarly literature. This allows us to introduce a numerical algorithm for solving the initial control problem. Our findings have potential applications in designing friend recommendation systems for real-world social platforms.
opinion dynamics models, SCARDO model, mean-field approximation, modular networks, network structure optimization
Derivations for a Special Case of Inverse Semigroup Algebras
This paper is aimed at studying the derivations of inverse semigroups algebras. We adress a special case of semigroups which are constructed as a disjoint union of two groups. We use a categorical method, constructing a category and expressing the derivations in terms of characters on said category. The resulting derivation algebra is proven to be divisible into direct sum of derivation algebras for two groups.
On Derived Equivalences of Exact Structures on the Category of Representations k[x]/(xn)
From the perspective of homological algebra, exact categories are interesting because they possess derived categories. Typically, an additive category admits many exact structures. If the original category is sufficiently nice (for example, quasi-abelian), a classification of exact structures can be given in terms of certain Serre subcategories in the category of contravariant functors. It turns out that the derived categories of different exact structures are functorially related. This work is concerned with sufficient conditions for the derived equivalence of different exact structures on certain categories.
homological algebra, exact categories, representation theory
Input of Medical Interventions, Medical Technologies, and Accessibility Factors in Lung Cancer Treatment Outcomes
Expert analysis reveals that outcomes in lung cancer treatment involving novel drugs depend less on the drugs themselves and more on systemic changes in disease management. These outcomes are tied to key acceptability factors: patient awareness and perceptions regarding early diagnosis and adherence, awareness and qualifications of healthcare providers (HCPs), and overall affordability and availability. Consequently, a rational model for disease control must consider medical technology as a multi-agent integrated system. This complex must include both the medical intervention (the drug) and the critical accessibility factors that ensure treatment success, ultimately transforming the underlying healthcare infrastructure, financing, and specialist expertise.
The Sturm–Liouville Operator with Rapidly Growing Potential and the Asymptotics of its Spectrum
In this paper, we study the asymptotic behavior of the discrete spectrum of the Sturm–Liouville operator given on the positive real semiline by the expression $-y′′ +q(x)y$ and the zero boundary condition $y(0) \cos{\alpha} + y'(0) \sin{\alpha} = 0$, for rapidly growing potentials $q(x)$. The asymptotics of the eigenvalues of the operator for the classes of potentials are obtained, which characterize the rate of their growth at infinity.
Copyright (c) 2025 Advances in Systems Science and Applications
Climate-Dependent Malaria Model with Delay in Mosquito Dynamics
Climate variability plays a crucial role in understanding malaria transmission dynamics, particularly through its influence on mosquito population and the parasite’s developmental processes. Although temperature and rainfall have long been recognized as major climatic drivers of malaria spread, and hence most of the malaria models often overlook the combined effects of temperature-dependent aquatic-stage development and variation in the extrinsic incubation period of the parasite. This study develops a new temperature-dependent malaria transmission model that incorporates mosquito maturation delays, short- and long-term EIP routes, and an explicit aquatic-stage compartment. The model extends earlier frameworks by integrating nonlinear temperature relationships for key mosquito life-history traits and by distinguishing between short and long incubation processes through probabilistic weighting. This structure provides a more realistic representation of how climatic fluctuations regulate mosquito abundance, survival, and infectiousness. The resulting model enhances predictive accuracy in understanding malaria seasonality and transmission potential across varying environmental conditions. Numerical simulations demonstrate how temperature shifts alter the timing and intensity of outbreaks, highlighting the importance of climate-sensitive modelling for malaria surveillance and guiding adaptive vector control strategies. The proposed framework contributes to the refinement of climate-based malaria prediction tools and supports evidence-driven public health decision-making in endemic regions.
Incubation period, Malaria transmission, Maturation delay, Mosquito dynamics, Sensitivity analysis, Temperature
Rothe Time-Semidiscretization for Doubly Nonlinear ParabolicProblems in Musielak–Orlicz–Sobolev Spaces
This paper establishes the existence of an entropy solution for a doubly nonlinear parabolic problem set within the framework of Musielak-Orlicz-Sobolev spaces, without imposing the $\Delta_2$ condition. The problem involves a Leray-Lions operator and a general Lipschitz, strictly increasing nonlinearity in the time derivative term, with $L^1$ source data. Our approach employs Rothe's time-semidiscretization method, reducing the evolution problem to a sequence of elliptic entropy subproblems at discrete time steps. We derive uniform a priori estimates in the modular topology associated with the Musielak-Orlicz function, which remain valid in the absence of the $\Delta_2$ assumption. Using these estimates, we prove compactness for the Rothe sequence in $W^{1,x}_0 L_\Psi(Q_T)$ and in $C([0,T]; L^1(\Omega))$. The limit is then identified via monotonicity techniques, confirming that it satisfies the entropy formulation of the original problem. This work unifies and extends previous existence results from standard Sobolev, variable-exponent, and Orlicz-Sobolev settings to the fully Musielak-Orlicz case with general nonlinearities and low-regularity data.
Assessing the Consistency of National Projects: How Target Achievement Could Transform Russia’s Quality of Life Ranking
This study assesses the potential impact of Russia’s National Projects on the country’s global standing by integrating S.A. Aivazyan’s Quality of Life Index (QLI) with State-Space dynamic modelling. Using a panel of 14 socioeconomic indicators (2000–2022), we simulate Russia’s quality of life trajectory through 2036 under baseline and target-achievement scenarios. The analysis demonstrates that achieving government targets for life expectancy, fertility, infant mortality, and income inequality is statistically consistent with structural trends and would raise Russia’s global rank by 11 positions. These findings validate the internal consistency of Russia’s strategic planning goals and confirm the QLI’s utility as a tool for public administration effectiveness.
A Method for Analyzing Causal Relationships to Ensure the Reliability and Safety of Complex Human-Machine Systems
The article presents a method for analyzing causal relationships aimed at ensuring the reliability and safety of complex human-machine systems (HMS). The developed approach combines system decomposition with modeling of dynamic interactions, considering the influence of human, technical, and organizational factors. A model based on Markov processes with variable transition intensities dependent on subsystem states is proposed, which allows for identifying cascade failures and reducing the dimensionality of tasks without loss of informativeness. In the literature review, we performed an analysis of modern methods, including dynamic Bayesian networks, fuzzy cognitive maps with genetic tuning, and system-theoretic process analysis. The effectiveness of hybrid algorithms in identifying critical risks is demonstrated. As a result, we have conducted numerical experiments on aviation systems, such as Airbus A-320, Bombardier CRJ-200, Boeing 747, and Sukhoi Superjet 100 (RRJ-95). These experiments illustrate the calculation of stationary state probabilities and risk dynamics. Conclusions are formulated regarding the methodological flexibility of the approach, its advantages in overcoming the “curse of dimensionality,” and prospects for application in other industries.
Sustainable Management in a Multipolar World as a Global Organizational System
This paper is devoted to the sustainable management problem of a multipolar world. The description of a multipolar world as a global organizational system is given. For the first time in the literature, all elements of the global organizational system mathematical model are specified in terms of a multipolar world order where civilizations act as agents. The peculiarities of viability conditions for such a global socio-economic-ecological system are indicated. The solvability conditions of the sustainable management problem under multipolarity are indicated.
game theory, global organizational system, mathematical modeling, multipolar world, sustainable management
Vector Fields with Non-Isolated Singular Points Viewed from the Inside and Outside
We present a brief survey of recent results about vector fields with non-isolated singular points and their applications. One of the most interesting and promising application is connected with quasi-linear differential equations of the second order, including the equation of geodesics in signature varying (pseudo-Riemannian) metrics.
Multiple Capture of Coordinated Evaders in the Linear GroupPursuit Problem with a Simple Matrix and Phase Restrictions
In a finite-dimensional Euclidean space, the pursuit problem of two evaders by a group of pursuers with equal opportunities for all players is considered. The motion of each participant is described by a linear system of differential equations with a simple matrix. It is assumed that the evaders use the same control and do not move out of a convex polyhedral set. The pursuers use counterstrategies based on information about the initial positions and the prehistory of the evaders' control. The set of admissible controls $V$ is a sphere of unit radius with its center at the origin, and the goal sets are the origin. The goal of the group of pursuers is the capture of at least one evader by a given number of pursuers. In terms of the initial positions and parameters of the game, a sufficient condition for capture is obtained. The method of resolving functions, which is used as a basis for analysis, provides sufficient conditions for solvability of the problem of pursuit in some guaranteed time.
differential games, pursuer, evader, capture, multiple capture, conflict-controlled processes
On Linear Differential Equations on the Torus and Non-Standard Analysis
In this paper, we consider periodic boundary value problems for differential equations whose coefficients are trigonometric polynomials. We construct the spaces of generalized functions, where such problems have solutions. In particular, the solvability space of a periodic analogue of the Mizohata equation is constructed. We build also a periodic analogue and a generalization of the construction of the nonstandard analysis, where infinitely small are not only functions, but also functional spaces. To show that not all constructions on the torus lead to a simplification in compare with the plane, we consider a periodic analogue of the hypoelliptic differential operator and show that its number-theoretic properties are significant. In particular, it turns out that if a polynomial with integer coefficients is irreducible in the rational field, then the corresponding differential operator is hypoelliptic on the torus.
differential operator on the torus, linear differential equation on the torus, Mizohata equation, nonstandard analysis, hypoellipticity
Legendre Transformation and Its Applications
We present the Legendre transformation in a geometric way based on the procedure of the Legendrian lift. This approach allows us to understand some interesting properties of it, in particular, the reason for the appearance of singularities of dual curves. Also we consider application of the Legendre transformation to the Clairaut differential equation. Finally, we say a few words class of contact transformations and present an infinite group of contact transformations different from the Legendre transformation.
Legendre transformation, duality, contact transformation, contact structure, pedal curve, singular point, Clairaut equation
A Word-Oriented Substitution–Permutation Network Cipher with Security Evaluation based on Active S-Box Bounds and a Dynamic Advanced Encryption Standard-Based Variant
The Substitution–Permutation Network (SPN) serves as a foundational structure in the design of modern block cipher algorithms due to its effective realization of two essential properties: confusion and diffusion. Currently, the security of SPNs is actively studied, with the S-box structure and the diffusion layer being key components analyzed to enhance resistance against attacks. In this paper, we propose a generalized SPN-based cipher model inspired by the AES structure. We then present a novel theoretical approach to evaluating the security of this SPN cipher, based on a lower bound of the number of active S-boxes. This forms the basis for identifying the roles and cryptographic properties required of the component transformations in this type of cipher. Next, we propose a dynamic block cipher algorithm based on the AES cipher, which not only ensures the required level of security but also inherits the implementation advantages of the original AES. The dynamic AES block cipher demonstrates higher security compared to the original AES, passes randomness evaluation standards, and is efficiently implementable. These results are significant in guiding the design of secure and flexible block cipher algorithms, while also providing a theoretical foundation for the selection and evaluation of secure cryptographic components in modern cryptosystems.
Multiple Capture of Coordinated Evaders in the Linear Group Pursuit Problemwith a Simple Matrix and Phase Restrictions
In finite-dimensional Euclidean space, an analysis is made of the problem of pursuit of two evaders by a group of pursuers, which is described by a system of the form $$ \dot z_{ij} = \alpha z_{ij}+ u_i - v,\ u_i, v \in V. $$ It is assumed that the evaders use the same control and do not move out of a convex polyhedral set. The pursuers use counterstrategies based on information about the initial positions and the prehistory of the evaders' control. The set of admissible controls $V$ is a sphere of unit radius with its center at the origin, and the goal sets are the origin. The goal of the group of pursuers is the capture of at least one evader by a given number of pursuers. In terms of the initial positions and parameters of the game, a sufficient condition for capture is obtained. The method of resolving functions, which is used as a basis for analysis, provides sufficient conditions for solvability of the problem of pursuit in some guaranteed time.
The Methods for Aviation Systems’ Safety Analysis during Combinations of Dangerous Heterogeneous Events Including Human Factor
This study presents a probabilistic method for assessing the safety and reliability of aviation systems based on modeling transitions between functional and failed elementary states. The analysis includes five core components of the aircraft system: crew, engines, avionics, power supply, and structural elements. Using failure and recovery flow intensities derived from realworld data for various aircraft types in 2022, the authors construct a system of differential equations to calculate dynamic safety indicators. The method applies state-transition graphs and formal mathematical models to describe the system’s behavior under different conditions. Particular attention is given to the non-technical elementary state representing crew condition, with a refined classification of critical human factor events such as specific headache types. The study performs calculations in MATLAB and provides comparative safety assessments for multiple aircraft models, such as Airbus (A-319 and A-320), Bombardier CRJ200, Boeing (737, 747 and 777), Sukhoi Superjet 100 (RRJ-95) and An-26B-100.
Optimization of Multi-Currency Deposit Structure by Two Indicators (Income and Risk) under Uncertainty
A two-criteria vector optimization problem – finding Pareto-optimal solutions in linear systems with interval uncertainty of coefficients – is considered. The problem of resource allocation to multiple activities is investigated. The uncertainty-adjusted income is a bilinear function, linear by strategy under fixed uncertainty and by uncertain parameters under fixed strategy. Guaranteed income is a linear function of variables and guaranteed risk is a piecewise linear function. Finding the optimal guaranteed risk is reduced to a linear programming problem by piecewise linear programming methods. To solve the two-criteria problem of the optimal allocation of financial resource on three currency deposits, the parameterization of the Pareto set by the value of the guaranteed income criterion is applied. Thus, the construction of a representative subset of Pareto-optimal solutions is reduced to solving a finite number of linear programming problems. The results can be used in analyzing the problems of financial management under conditions of incomplete information.
deposit diversification, bicriteria optimization, incomplete information, minimax regret solution
Grading Structure for Derivations of Group Algebras
In this paper we give a way of equipping the derivation algebra of a group algebra with the structure of a graded algebra. The derived group is used as the grading group. For the proof, the identification of the derivation with the characters of the adjoint action groupoid is used. These results also allow us to obtain the analogous structure of a graded algebra for outer derivations. A non-trivial graduation is obtained for all groups that are not perfect.
derivations, bimodule, outer derivations
Ensuring the Sustainability of Health Care Management Expert Support and Decision Making in Modern Conditions
Current technological and environmental changes requiring new approaches for healthcare data generation and assessment as well as decision-making support. The analysis performed using Delphi method indicated that sustainability of healthcare decision-making by using a number of approaches based on existing opportunities for proactive risk-based assessment of population health and healthcare interventions. Non-numerical qualitative expert opinions are of the same value as quantitive data while the balance between them and the methodology of mutual transformation form an integrated evidence-based support for the sustainable data generation and healthcare decision-making. Qualitative expert opinions make it also possible to decrease the asymmetry and lack of quantitative data between model studies on animals and the characteristics of the human body. The balance between qualitative expert assessment and the digital evidence changes during the lifecycle of the intervention or possibly process (like pandemic). Sustainability of healthcare decision-making in changing environment depends on availability and methods of qualitative expert support. Currently, there are no generally accepted methods for the final qualitative expert assessment, which makes it possible to reduce the diversity of interdisciplinary big data to a transparent and understandable assessment and these methodology and methods are to be developed. Automated systems for early detection of emergent cases based on medical statistics data are also of great importance and capable increasing sustainability of healthcare management and this information should be linked to pre-prepared action plans to avoid COVID-19 lessons in future.
sustainability, healthcare management, decision-making, expert support, public health emergencies, COVID-19 lessons, data generation, quantitative data, qualitative data, proactive, risk-based.
Stability Criteria for Periodic Selector-Linear Difference Inclusions
The paper considers periodic selector-linear difference inclusions. Lyapunov functions from a parametric class of homogeneous forms of even degree are constructed. These functions establish necessary and sufficient conditions of asymptotic stability and can be used in the development of numerical methods for investigating the stability of the systems equivalent to the considered difference inclusions. Using piecewise linear Lyapunov functions, an algebraic criterion of asymptotic stability of the considered inclusions is obtained. An example of a mechanical system leading to periodic selector-linear difference inclusion is considered.
algebraic criterion of asymptotic stability