Search Results (112)

Satellite communications are pivotal to global Internet access, connectivity, and the advancement of information warfare. Despite these importance, the open nature of satellite channels makes them vulnerable to eavesdropping, making the enhancement of interception resistance in satellite communications a critical issue in both academic and industrial circles. Within the realm of satellite communications, polarization modulation and quadrature techniques are essential for information transmission and interference suppression. To boost electromagnetic countermeasures in complex battlefield scenarios, this paper integrates multi-parameter weighted-type fractional Fourier transform (MP-WFRFT) with directional modulation (DM) algorithms, building upon polarization techniques. Initially, the operational mechanisms of the polarization-amplitude-phase modulation (PAPM), MP-WFRFT, and DM algorithms are elucidated. Secondly, it introduces a novel variable polarization-amplitude-phase modulation (VPAPM) scheme that integrates variable polarization with amplitude-phase modulation. Subsequently, leveraging the VPAPM modulation scheme, an exploration of the anti-interception capabilities of MP-WFRFT through parameter adjustment is presented. Rooted in an in-depth analysis of simulation data, the anti-scanning capabilities of MP-WFRFT are assessed in terms of scale vectors in the horizontal and vertical direction. Finally, exploiting the potential of the robust anti-scanning capabilities of MP-WFRFT and the directional property of antenna arrays in DM, the paper proposes a secure transmission technique employing directional variable polarization modulation with MP-WFRFT. The performance simulation analysis demonstrates that the integration of MP-WFRFT and DM significantly outperforms individual secure transmission methods, improving anti-interception performance by at least an order of magnitude at signal-to-noise ratios above 10 dB. Consequently, this approach exhibits considerable potential and engineering significance for its application within satellite communication systems. Full article

Background and Objectives: Rumors, disinformation, and fake news are problems of contemporary society. We live in a world where the truth no longer holds much importance, and the line that divides the truth from lies, between real news and disinformation, becomes increasingly blurred and difficult to identify. The purpose of this study is to describe this concept, to draw attention to one of the “pandemics” of the 21st-century world, and to find methods by which we can defend ourselves against them. Materials and methods. A cross-sectional study was conducted based on a sample of 442 respondents. Results. For 77.8% of the people surveyed, the concept of “fake news” is important in Romania. Regarding trust in the mass media, a clear dominance (72.4%) was observed among participants who have little trust in the mass media. Although 98.2% of participants detect false information found on the internet, 78.5% are occasionally deceived by the information provided. Of the participants, 47.3% acknowledged their vulnerability to disinformation. The main source of disinformation is the internet, as 59% of the interviewed subjects believed. As the best measure against disinformation, the study group was divided almost equally according to the three possible answers, all of which were considered to be equally important: imposing legal restrictions and blocking the posting of certain news (35.4%), imposing stricter measures for authors (33.9%), and increasing vigilance among people (30.5%). Conclusions. According to the statistics based on the participants’ responses, the main purposes of disinformation are propaganda, manipulation, distracting attention from the truth, making money, and misleading the population. It can be observed that the main intention of disinformation, in the perception of the study participants, is manipulation. Full article

Russia’s invasion of Ukraine has profoundly altered the global geopolitical landscape. Owing to its geographical proximity, the conflict has had a considerable impact on Europe. Marked by the professionalisation and democratisation of technology, it has underscored the growing significance of hybrid warfare, in which disinformation and propaganda serve as additional instruments of war. Within this context, the aim of this article is to examine the characteristics of false information related to the war between Russia and Ukraine in four European countries between 2022 and 2023. To this end, a content analysis of 297 hoaxes was conducted across eight fact-checking platforms, complemented by ten in-depth interviews with specialised professionals. The findings indicate that disinformation is characterised by viral audiovisual hoaxes, particularly on Facebook and X (formerly Twitter), with a notable surge in disinformation flows at the onset of the invasion. In the early months, misleading content predominantly consisted of decontextualised images of the conflict, whereas a year later, the focus shifted to narratives concerning international support and alliances. The primary objective of this disinformation is to polarise public opinion against a perceived common enemy. The conclusions provide a broader and more nuanced understanding of wartime disinformation within the European context. Full article

We propose an amplitude encoding of the traveling salesperson problem along with a method for calculating the cost function using a probability distribution obtained on a quantum computer. Our encoding requires a number of qubits that grows logarithmically with the number of cities. We propose to calculate the cost function using a nonlinear function of expectation values of quantum operators. This is in contrast to the typical method of evaluating the cost function by summing expectation values of quantum operators. We demonstrate our method using a variational quantum eigensolver algorithm to find the shortest route for a given graph. We find that there is a broad range in the hyperparameters of the optimization procedure for which the best route is found. Full article

This study investigates the spatiotemporal distribution and evolution of traditional villages in southern Jiangsu Province, China. By integrating historical documents, remote sensing images, and socio-economic statistics, we have applied standard geographic information system (GIS) methods, including kernel density estimation, nearest neighbor analysis, and standard deviation ellipse analysis, to examine the patterns and driving forces behind village formation and transformation. The findings are as follows: (1) The spatial distribution of the villages exhibits a spatial pattern of “peripheral agglomeration and central decline,” with a nearest neighbor index value of 0.84 (z = −2.52, p < 0.05), indicating a significantly clustered distribution. Kernel density analysis revealed high-density zones along the southwestern coast of Taihu Lake and southeastern Dianshan Lake. (2) From the Song to the Qing Dynasty, village migration followed three sequential phases, “stabilizing near water → avoiding risks around water → adapting inland,” showing strong spatiotemporal linkages to climate change and warfare. (3) The density of the villages showed a significant negative correlation with the per capita GDP (Moran’s I = −0.69, p < 0.05; 0.69, p < 0.01) and was positively correlated with the proportion of primary industry. These findings highlight the spatial resilience characteristics of traditional villages under combined natural and socio-economic pressures and provide a theoretical foundation for regional heritage conservation and rural revitalization strategies. Full article

Russia’s conflict with Ukraine, which escalated into full-scale military confrontation in February 2022, originated in 2014 with the annexation of Crimea and the backing of pro-Russian separatists in Donetsk and Luhansk. However, this war extends beyond bilateral hostilities, reflecting a broader geopolitical confrontation with the West that aligns with Vladimir Putin’s strategic vision, as signalled in his 2007 Munich Security Conference speech. Russian security doctrines have consistently framed the West as an existential threat, a perception reinforced by state-controlled media. This study examines the role of Russian state media in shaping public perceptions of the West between 2014 and 2022. It explores how Russian media, particularly RIA Novosti, constructed adversarial narratives about Latvia, Poland, and Serbia within the framework of Russian security policy. Through qualitative content analysis, the research investigates the alignment of media narratives with official strategic objectives, the portrayal of Western nations as threats, and the intended audience of these narratives. The findings underscore the integral role of state-controlled media in Russia’s security strategy, highlighting an increasing consolidation of media control to sustain domestic legitimacy and justify external aggression. As Russia faces growing challenges, media restrictions are expected to intensify, reinforcing state-driven narratives and information isolation. Full article

It is essential that the state of health (SOH) for lithium-ion batteries is measured to ensure the safety and reliability of electric vehicles. However, an accurate prediction of SOH is still an art due to the complex degradation mechanisms. To address this challenge, a SOH prediction model based on Warfare Strategy Optimization-assisted hybrid mutual information in-former-Long Short-Term Memory neural network (IWSO-MILSTM) is proposed. First, both direct and virtual health indicators are derived from battery degradation curves. Building on this foundation, mutual information is applied to the correlation analysis of these health indicators, and the redundant health indicators can be filtered. Then, the selected health indicators are fed into the informer-LSTM to construct an interpretable predicted model for the health status of lithium-ion batteries. Notably, both redundancy of health indicators and the imprecision of model hyperparameters for LSTM affect the SOH prediction precision. IWSO is proposed to achieve co-optimization of filtering for health indicators and hyperparameters for the informer-LSTM based on developed initializing distribution methods and adaptive function so that the SOH prediction precision is ensured. Finally, the NASA dataset is used to validate the prediction precision of the IWSO-MILSTM, and the experimental results show that the IWSO-MILSTM can provide more competitive results, i.e., the R² value is improved by 25.68% and 3.63%, respectively, while the RMSE is reduced by 48.76% and 75.91% compared with XGBoost, LSTM, etc. Such results indicate the proposed method can predict SOH efficiently. Full article

The widespread deployment of unmanned aerial vehicles (UAVs) in modern warfare has profoundly increased the complexity and dynamic nature of aerial combat. To address the limitations of traditional UAV combat intention recognition methods, which rely on the “complete information” assumption and struggle to adapt effectively to dynamic adversarial environments, this paper proposes a deep learning-based UAV air combat intention recognition model (BLAC). The BLAC model establishes dynamic temporal feature mappings through a bidirectional long short-term memory network (BL) and innovatively incorporates a cross-attention mechanism (A) paired with contrastive learning (C) to improve model performance. To mitigate battlefield information uncertainty, the BLAC model implements cubic spline interpolation for numerical features and proximity-based imputation for non-numerical features, effectively resolving data loss challenges. The experimental results demonstrate that the BLAC model achieves superior intention recognition accuracy compared to mainstream models, maintaining over 91% accuracy even under 30% data loss conditions. These outcomes confirm the robustness and adaptability of the model in dynamic combat environments. This research not only provides an efficient framework for UAV combat intention recognition under information uncertainty but also offers valuable theoretical and practical insights for advancing intelligent command and control systems. Full article

To meet the multi-device integration requirements faced by electronic warfare systems in the current environment and to address the problem of conventional jamming-based imaging algorithms being unable to achieve a high range resolution under narrowband conditions, this paper proposes a broadband high-resolution synthetic aperture radar (SAR) imaging method based on narrowband dense false target jamming signals (DFTJSs). The characteristic of this signal is its ability to modulate large bandwidth phase information for each narrowband false target jamming signal (FTJS) so that the echo of the entire jamming signal has a secondary compression characteristic in the distance direction without affecting its jamming ability, thereby eliminating the influence of the first compression distance blur and obtaining a high resolution of the large bandwidth signal. Theoretical analysis and numerical simulations indicate that narrowband DFTJSs using phase modulation can achieve high-resolution imaging of specific target areas while causing interference to non-cooperative radar (NCR). Full article

The Russian invasion of Ukraine has also ignited a battleground in the domain of information. The conflict has been accompanied by a relentless disinformation offensive designed to manipulate public opinion and undermine democratic processes. This paper deals with the role of academia and scholars in focusing this information warfare. This study conducts a comprehensive analysis of scientific articles to examine how researchers and institutions have addressed fact-checking initiatives. To this end, performance analysis and literature review are combined to observe the state of academic investigations on fact-checking during the first thousand days of war in Ukraine (from 24 February 2022 to 19 November 2024). To do this, we identified 595 fact-checking articles in the Web of Science database within the “Social Sciences” category and narrowed the focus to 270 articles in the field of “Communication”. Finally, through an in-depth literature review of eight manuscripts, we seek to understand the specific strategies employed by academics to address the conflict between Russia and Ukraine through fact-checking. Our findings suggest that fact-checking research on the Russia–Ukraine war predominantly examines the impact of disinformation in conflict contexts, the role of media literacy in countering false narratives, and the contribution of citizen journalism to verification efforts. These conclusions can shed light on the crucial role of academia in safeguarding truth and fostering informed public debate in an era of information overload and manipulation. Full article

Cognitive warfare is a matter of concern due to its impact on people’s minds and decision-making. The manifestation of wars and the deliberate attempts of nations to use AI technologies to their advantage in outsmarting people’s minds cannot be ignored from a homiletical perspective. This article argues that AI (Artificial Intelligence), GAI (Generative Artificial Intelligence), and ChatGPT (Generative Pre-trained Transformer) offer tremendous possibilities to enhance interplay with humans. Viewed through the lenses of philosophy and ethics, it becomes evident that people providing AI technologies with data engage with technology from an intrinsic worldview. The provision of information and decision-making through AI technologies prompts us to consider people’s reasoning and responsibility. The harmful consequences of killer robots and the use of facial recognition to reach human targets raise deep ethical questions. The author contends that listeners to sermons are exposed to the age of homo digitalis and are tasked with making sense of what is happening in the world. When homiletical praxeology remains silent on the injustices and undignified practices of cognitive warfare and drone use, without proclaiming the values of the gospel and the Kingdom, listeners become reliant on alternative sources of information. In the normative section of this article, the importance of demolishing arguments and pretensions that oppose the knowledge of God and taking every thought captive to make it obedient to God’s will is emphasised. The article concludes with a call for homiletics to engage with AI technologies rather than ignore them. By utilising technological advantages without undermining the paramount value of preaching within the unique contexts of faith communities, listeners may become more open to the gospel and experience transformation in their minds, particularly regarding warfare. Full article

Mechanical exfoliation of two-dimensional (2D) materials using adhesive tape is a widely used method for producing high-quality single-layer graphene flakes. However, this technique is time-consuming, with low yields and inconsistent results due to process variations and human error. This paper introduces a modular system designed to rigorously test and optimize the conditions for 2D material deposition, with a focus on graphene. The system is adaptable to a range of inexpensive, commercially available linear stages and stepper motors, providing precise, independent control over key parameters such as peel speed and angle—both of which are critical in deposition yields. Tests confirmed the system’s accuracy within $\pm 0.7\%$ relative speed error across a range of speeds (1 $\mathsf{\mu }$m/s to 5000 $\mathsf{\mu }$m/s) and peel angle control from $0^{\circ }$ to ${120}^{\circ }$. Additionally, the system automates control of the key factors at the most demanding step of the exfoliation process while being affordable and easily assembled, making it accessible for laboratories and educational institutions to explore the optimal conditions for scaling 2D material production. This system offers the capability to gain critical insights into the exfoliation process, driving improved yields and scalability, which are essential for fabricating highly specialized devices that rely on 2D materials. Full article

As the scale of missions continues to expand, equipment support has emerged as a critical component of military combat effectiveness. Consequently, the supportability of a system of systems (SOS) for equipment has become as essential quality requirement alongside its performance metrics. This study systematically assessed the effectiveness of equipment SOS support through a task-driven methodology. Initially, a model for generating equipment support tasks was developed to translate the operational requirements into a sequence of support tasks. Subsequently, a simulation model was constructed to evaluate the equipment SOS support system, and solutions were derived for the corresponding SOS-level support effectiveness indexes. Finally, the feasibility and characteristics of the proposed models and simulation methodology were validated through a case study involving an emergency operational mission for an air combat group formation. The results indicate that the increased reliability of the equipment system correlates with a reduced failure rate and lower resource consumption for maintenance and support per device, thereby improving support efficiency. The methodology presented in this article provides a framework for evaluating the effectiveness of equipment SOS support while facilitating informed decision-making in information warfare conditions. Full article

Unmanned aerial vehicle (UAV) swarms have shown substantial potential to enhance operational efficiency and reduce strike costs, presenting extensive applications in modern urban warfare. However, achieving effective strike performance in complex urban environments remains challenging, particularly when considering three-dimensional obstacles and threat zones simultaneously, which can significantly degrade strike effectiveness. To address this challenge, this paper proposes a target strike strategy using the Electric Eel Foraging Optimization (EEFO) algorithm, a heuristic optimization method designed to ensure precise strikes in complex environments. The problem is formulated with specific constraints, modeling each UAV as an electric eel with random initial positions and velocities. This algorithm simulates the interaction, resting, hunting, and migrating behaviors of electric eels during their foraging process. During the interaction phase, UAVs engage in global exploration through communication and environmental sensing. The resting phase allows UAVs to temporarily hold their positions, preventing premature convergence to local optima. In the hunting phase, the swarm identifies and pursues optimal paths, while in the migration phase the UAVs transition to target areas, avoiding threats and obstacles while seeking safer routes. The algorithm enhances overall optimization capabilities by sharing information among surrounding individuals and promoting group cooperation, effectively planning flight paths and avoiding obstacles for precise strikes. The MATLAB(R2024b) simulation platform is used to compare the performance of five optimization algorithms—SO, SCA, WOA, MFO, and HHO—against the proposed Electric Eel Foraging Optimization (EEFO) algorithm for UAV swarm target strike missions. The experimental results demonstrate that in a sparse undefended environment, EEFO outperforms the other algorithms in terms of trajectory planning efficiency, stability, and minimal trajectory costs while also exhibiting faster convergence rates. In densely defended environments, EEFO not only achieves the optimal target strike trajectory but also shows superior performance in terms of convergence trends and trajectory cost reduction, along with the highest mission completion rate. These results highlight the effectiveness of EEFO in both sparse and complex defended scenarios, making it a promising approach for UAV swarm operations in dynamic urban environments. Full article

Air target intention recognition (ATIR) is critical for unmanned systems in modern air defense operations. Through the analysis of typical air defense combat scenarios, first, the paper defines the intention space and intention parameters of air units based on military experience and domain knowledge. Then, a rule-based agent for unmanned systems for online intention recognition is proposed, with no training, no tagging, and no big data support, which is not only for intention recognition and parameter prediction, but also for formation identification of air targets. The most critical point of the agent is the introduction and application of a thermal distribution grid graph (TDGG) and virtual grid dictionary (VGD), where the former is used to identify the formation information of air targets, and the latter is used to optimize the storage space and simplify the access process for the large-scale and real-time combat information. Finally, to have a performance evaluation and application analysis for the algorithm, we carried out a data instance analysis of ATIR for unmanned systems and an air defense warfare simulation experiment based on a Wargame platform; the comparative experiments with the classical k-means, FCNIRM, and the sector-based forward search method verified the effectiveness and feasibility of the proposed agent, which characterizes it as a promising tool or baseline model for the battlefield situational awareness tasks of unmanned systems. Full article