This paper presents experimental measurement of neutron flux from an AmBe source using a stilbene organic scintillator and subsequent mathematical processing of the measured data. The neutron energy spectrum was reconstructed by solving a Fredholm integral equation of the first kind using maximum likelihood expectation maximization (MLEM) and a novel B-spline-based MLEM-BS method with regularization. Bootstrap resampling was applied to estimate confidence intervals. Results demonstrate successful neutron spectrum unfolding, reduced noise sensitivity of the spline approach, and good agreement of the reconstructed spectrum with the ISO reference standard.
This study evaluates the positioning performance of non‑survey‑grade GNSS devices (smartphones, sport watches, and IoT trackers) across open terrain, urban canyons, and forest environments. A spatio‑temporal synchronization framework with decomposition into along‑track and cross‑track error components is applied using a post‑processed geodetic reference. The results reveal pronounced generational differences among tracking devices, strong environment‑dependent performance degradation, and fundamental physical limits of low‑cost GNSS relevant to tactical and autonomous applications.
In this article, we investigate the problem of estimating the spectral characteristics of the intensity of moving objects under stochastic uncertainty based on the results of measuring the magnitudes of wave fields at separate points. We assume that the unknown spectral functions belong to known sets from the functional space, and certain restrictions are given for the unknown correlation matrices. For linear guaranteed estimates of the set of linear functionals from spectral functions, we prove that the guaranteed mean square estimates are expressed in terms of solutions of a certain system of linear algebraic equations.
The paper presents a hybrid methodological framework for resolving military capability gaps by integrating Multi-Criteria Decision-Making (MCDM) and constructive simulation. The purpose is to enhance defense planning transparency and objectivity. Using the Analytic Hierarchy Process (AHP), expert-driven criteria weights were established, focusing on force protection and operational effectiveness. These were validated via 200 stochastic simulation cycles in MASA SWORD, comparing conventional reconnaissance against UAV-integrated structures. Findings indicate that UAV integration (OCE = 0.7882) provides a 50.6% reduction in friendly fatalities compared to traditional methods (OCE = 0.6945). The framework offers a scalable, auditable tool for evidence-based strategic procurement.
This paper verifies mechanized battalion defensive capabilities using constructive simulation. The methodology employs the MASA SWORD environment with Monte Carlo replications, randomized A/B testing of Courses of Action, and standardized metrics (MoE, MoP, MoFP, MoS). The results show that ISR quality and C2 latency are decisive for defensive effectiveness, while obstacle system design and logistical throughput significantly influence enemy tempo and operational endurance. The findings support capability assessment, operational planning, and training design. The paper’s value lies in a reproducible, metrics-based framework for battalion-level capability verification.
The expanding significance of the information domain in today’s “information society” highlights the necessity of efficient information security and governance. The distribution of dangerous information has become more accessible due to the quick development of information dissemination technologies; therefore, a thorough understanding of information dissemination mechanisms is necessary to create effective countermeasures. An established and successful method for resolving these problems is modelling. This study aims to explore the information warfare paradigm further and how it relates to the idea of conflict, a topic covered in several related publications. The ultimate goal of this article is to develop a comprehensive system that uses software tools to assess the dynamics of internal conflict using the information warfare paradigm.
We construct and study a continuous evolutionary model describing the conflict interaction between automation and the labor market in strategic IT sectors. The system dynamics are based on the Lotka-Volterra framework, enhanced by Markov switching and Levy-type stochastic jumps. This allows for describing the impact of rare but critical events that abruptly change employment levels. By applying phase merging methods, we derive a reduced model that preserves key asymptotic behavior. The approach serves as a tool for analyzing market resilience and strategic risks under global uncertainty.
This paper presents a simulation-based decision support approach for artillery target engagement, focusing on the integration of stochastic modelling and reliability-based evaluation into fire planning. Traditional artillery methods rely on deterministic models and consumption norms, which provide limited insight into the variability of fire effectiveness. The proposed approach employs Monte Carlo simulation to model firing accuracy and munition effects, producing probabilistic distributions of target damage. These outputs are evaluated using reliability-based criteria, enabling comparison of firing methods in terms of effectiveness, probability of success, and ammunition consumption. Results demonstrate that optimized firing methods can achieve the required effect (≥30% target damage) with the desired reliability (84%) while significantly reducing ammunition expenditure and exposure time compared to traditional approaches. The study highlights the potential of simulation-based decision support to improve efficiency and decision-making in artillery fire planning.
Soil passability modelling depends on the quality and integration of soil data. This study evaluates the influence of soil database selection on passability assessment using soil datasets commonly used in the Czech Republic. Soil types and soil texture were harmonised, validated against field observations, and analysed with respect to spatial agreement. Results show that DSM50 provides the most consistent soil type information, while soil texture assessment relies on the dataset with the widest coverage, as no clear best dataset emerged. An attribute‑specific hierarchical integration framework is proposed to ensure robust and operationally applicable soil passability modelling.
Integrated Air and Missile Defence (IAMD) environments are increasingly characterized by high-density saturation attacks consisting of heterogeneous threats such as unmanned aerial systems, cruise missiles, and ballistic weapons. The core operational challenge is the Weapon-Target Assignment (WTA) problem, which involves determining the optimal allocation of defensive resources to incoming threats under strict time constraints. Traditional heuristic approaches implemented in legacy air defence systems rely on simplified rules such as Closest-Threat-First (CTF), which do not fully account for the multi-dimensional nature of modern engagements.
This paper proposes a Multi-Criteria Decision Analysis (MCDA) framework for optimizing WTA decisions in IAMD Command and Control (C2) systems. The model evaluates potential weapon-target engagements using three primary criteria: probability of interception, temporal urgency, and interceptor cost efficiency. A comparative simulation framework based on Monte Carlo methods evaluates the proposed approach against a baseline heuristic model. The results demonstrate that the MCDA-based approach significantly improves defensive efficiency while maintaining resource sustainability.
The presented Python-based simulation environment provides a scalable proof-of-concept for integrating decision-support algorithms into future automated IAMD architectures.