Search Results (550)

Unmanned Aerial Vehicles (UAVs) are increasingly being used in critical infrastructure, defense, and civilian applications, and face new cybersecurity threats. In this work, we present a novel hybrid deep learning architecture that combines Mamba, Kolmogorov-Arnold Networks (KAN), and Liquid Neural Networks for real-time cyberattack detection in UAV systems. The proposed Mamba-KAN-Liquid (MKL) model integrates Mamba’s selective state-space mechanism for temporal dependency modeling, KAN’s learnable activation functions for feature representation, and Liquid networks’ dynamic adaptation capabilities for real-time anomaly detection. Extensive evaluations on CIC-IDS2017, CSE-CIC-IDS2018, and synthetic UAV telemetry datasets demonstrate that our model achieves detection rates exceeding 95% across six different attack scenarios, including GPS spoofing (97.3%), network jamming (95.8%), man-in-the-middle attacks (96.2%), sensor manipulation (94.7%), DDoS (98.1%), and zero-day attacks (89.4%). The model meets real-time processing requirements with an average inference time of 47.3 ms for a sample batch size of 32, making it suitable for practical deployment on resource-constrained UAV platforms. Full article

This article examines Dag Solstad’s War Trilogy (1977–81) as a key work of realism and cultural memory in postwar Norwegian literature. Long dismissed as doctrinaire Marxist fiction, the trilogy is, in fact, one of the most ambitious literary engagements with World War II in Scandinavia. Drawing on Georg Lukács’s theory of the historical novel and Fredric Jameson’s account of realism’s “antinomies,” this article argues that Solstad’s realism is defined by contradiction: it is both a didactic mapping of social conflict and an aesthetic registration of lived sensation. The trilogy insists on the persistence of class antagonisms across civilian and military spheres; however, it also dwells on affective residues—hygiene, beauty, emotions, atmosphere—that resist narrative closure. This duality is framed through the concept of dual historicity: Solstad’s novels remember the 1930s and 1940s from the vantage point of the 1970s, while today they reach us as artifacts of that political and aesthetic moment. In light of this, the War Trilogy operates not only as historical fiction but as a medium of cultural memory, dramatizing the contradictions of remembrance itself. Realism here becomes neither transparency nor nostalgia, but a “battle of the senses” in which ideology and perception vie over the conditions of historical experience. Full article

Snow construction plays a crucial role in military operations in cold regions, providing tactical fortifications, thermal insulation, and emergency infrastructure in environments where conventional building materials are scarce or require extensive infrastructure for support. Current snow construction methods, including manual piling and compaction, are labor-intensive and inconsistent, limiting their use in large-scale or time-sensitive operations. This study explores the feasibility of adapting a compressed earth block (CEB) machine to produce compressed snow blocks (CSBs) as modular, uniform building units for cold-region applications. Using an AECT Impact 2001A hydraulic press, naturally occurring snow was processed with a snowblower and compacted at maximum operating pressure (i.e., 20,684 kPa) to evaluate block formation, dimensional consistency, and density. The machine successfully produced relatively consistent CSBs, but the initial 3–4 blocks following block height adjustment were generally unsuccessful (e.g., incorrect block height or collapsed/broke) while the machine reached its steady state cyclic condition. These blocks were discarded and excluded from the dataset. The successful CSBs had mean block heights of 7.76 ± 0.56 cm and densities comparable to ice (i.e., 0.83 g/cm³). Variations in block height and mass may be attributed to manual snow loading and minor material impurities. While the dataset is limited, the results warrant further investigation into this technology, particularly regarding CSB strength (i.e., hardness and compressive strength) and performance under variable snow and environmental conditions. Mechanized snow compaction using existing CEB technology is technically feasible and capable of producing uniform, structurally stable CSBs but requires further investigation and modifications to reach its full potential. With design improvements such as automated snow feeding, cold-resistant components, and system winterization, this approach could enable scalable CSB production for rapid, on-site construction of snow-based structures in Arctic environments, supporting the military and civilian needs. Full article

In the field of acoustic wave detection, optical sensors have significant potential applications in numerous civilian and military fields due to their high sensitivity and immunity to electromagnetic interference. This study designed an undercoupled silica optical waveguide resonator (OWR) with a 2% refractive index contrast. Mode spot converters were introduced at both ends of the straight waveguide to achieve efficient optical transmission between the fiber and the waveguide. The resonator was fabricated using plasma-enhanced chemical vapor deposition (PECVD) and inductively coupled plasma (ICP) etching technologies. The results show that the quality factor (Q-factor) of the resonator reached 2.75 × 10⁶. Compared with a resonator with a refractive index difference of 0.75%, the Q-factor remained at the same order of magnitude while the sensor size was significantly reduced. To achieve high-sensitivity acoustic wave detection, this study employed an intensity demodulation method to realize acoustic wave detection with the resonator. Test results demonstrate that the OWR can detect acoustic signals in the frequency range of 25 Hz to 20 kHz, with a minimum detectable sound pressure of 1.58 μPa/Hz^1/2 @20 kHz and a sensitivity of 1.492 V/Pa @20 kHz. The sensor exhibits a good signal-to-noise ratio and stability. The proposed method shows broad application prospects in the field of acoustic sensing and is expected to enable large-scale applications in scenarios such as communication, biomedical monitoring, and precision industrial sensing. Full article

Electromagnetic scattering analysis is inherently complex and plays a crucial role in both civilian and military applications. A primary objective in analyzing scattering problems is to achieve accurate results while minimizing computational cost. In this study, a novel high-frequency technique, called Triangular Ray Tube Tracing (TRTT), is proposed for calculating the Radar Cross-Section (RCS) of electrically large objects. Unlike conventional ray-based methods, TRTT employs triangular ray tubes (TRTs) with frequency-independent resolution, which significantly reduces the computational burden while maintaining accuracy. The method also accounts for multiple reflections and shadowing effects based on the geometry of the target. To validate the approach, computational steps and results obtained using TRTT are compared in detail with the classical Shooting and Bouncing Ray (SBR) method, which requires frequency-dependent ray density. The proposed method demonstrates substantial advantages in terms of efficiency, scalability, and frequency-independence, particularly for electrically large targets. Full article

Today, unmanned aerial vehicles (UAVs) are heavily dependent on Global Navigation Satellite Systems (GNSSs) for positioning and navigation. However, GNSS signals are vulnerable to jamming and spoofing attacks. This poses serious security risks, especially for military operations and critical civilian missions. In order to solve this problem, an image-based geolocation system has been developed that eliminates GNSS dependency. The proposed system estimates the geographical location of the UAV by matching the aerial images taken by the UAV with previously georeferenced high-resolution satellite images. For this purpose, common visual features were determined between satellite and UAV images and matching operations were carried out using methods based on the homography matrix. Thanks to image processing, a significant relationship has been established between the area where the UAV is located and the geographical coordinates, and reliable positioning is ensured even in cases where GNSS signals cannot be used. Within the scope of the study, traditional methods such as SIFT, AKAZE, and Multiple Template Matching were compared with learning-based methods including SuperPoint, SuperGlue, and LoFTR. The results showed that deep learning-based approaches can make successful matches, especially at high altitudes. Full article

Current research and development in understanding road users’ driving behaviors play a key role in improving traffic safety. Recently, several driving simulators have been employed as a suitable approach to investigate several drivers’ responses in challenging traffic scenarios. Although professional drivers represent a particular category among driving populations, the body of literature about their comparative behavioral and psychological characteristics remains limited. This study examined the differences in driving performance and visual and physiological responses between civilian and professional drivers in a simulated environment. A total of 30 drivers, with an equal split between professional and civilian categories, took part in a series of driving simulations. The simulations incorporated various infrastructure types, including four cone avoidance tasks and a high-speed motorway task. This study collected comprehensive data on performance metrics, hand usage, heart rate, and eye movements. Eye-tracking technology was used to measure visual attention. The findings revealed that during cone avoidance scenarios, civilian drivers exhibited a similar performance, visual behavior, and physiological response, except for the speed, experiment duration, and throttle, to professional drivers. In the motorway scenario, all metrics showed no significant difference between the two driver groups. These results highlight the need for cautious interpretation, particularly given the limitations of the sample. Revalidation is needed in larger studies, especially for understanding the differences between drivers’ metrics, which is crucial to elevate drivers’ safety, and assessing training programs in Hungary. Full article

Virtual reality (VR) creates immersive environments that allow users to interact with digital content, fostering a sense of presence and engagement comparable to real-world experiences. VR360 technology, combined with affordable head-mounted displays such as Google Cardboard, enhances accessibility and provides an intuitive learning experience. Drones, or unmanned aerial vehicles (UAVs), are operated through remote control systems and have diverse applications in civilian, commercial, and scientific domains. Taiwan’s Indigenous cultures emphasize environmental conservation, and integrating this knowledge into education supports both biodiversity and cultural preservation. The Amis people, who primarily reside along Taiwan’s eastern coast and central mountain regions, face educational challenges due to geographic isolation and socioeconomic disadvantage. This study integrates VR360 and drone technologies to develop a VR learning system for elementary science education that incorporates Amis culture and local environments. A teaching experiment was conducted to evaluate its impact on learning effectiveness and student responses. Results show that students using the VR system outperformed the control group in cultural and scientific knowledge, experienced reduced cognitive load, and reported greater learning motivation. These findings highlight the potential of VR and drone technologies to improve learning outcomes, promote environmental and cultural awareness, and reduce educational barriers for Indigenous students in remote or socioeconomically disadvantaged communities. Full article

This paper builds on findings from the first systematic study of military families in Slovenia (2019–2022) to critically examine how military families are perceived and constructed within broader sociocultural and institutional frameworks. Using perspectives from family studies, military sociology, defense studies, and critical military theory, the study investigates whether these perceptions continue to reproduce the traditional binary logic that positions the family as a feminized, private domain and the military as a masculinized, public domain, or whether late modern discourses have begun to disrupt these dichotomies. The analysis focuses on the intersection of gender roles, family practices, parental responsibilities, and the symbolic and practical meanings ascribed to the notion of the “military family.” We used a reflexive approach to thematic analysis, combining qualitative interviews with young adults (aged > 18) who grew up in military families (14 participants), interviews with military and civilian experts (41 participants), survey data from service members, their spouses, and civilian respondents (411 and 125 open-ended responses from separate surveys). Findings reveal significant differences in how military families are understood and experienced. More critically, the study highlights how military institutional power and its greediness extend into the familial realm, not only through logistical demands, but also through the normalization of military values, hierarchical gendered expectations, and parenting practices. Full article

LuTan-1 (LT-1) is China’s first L-band differential interferometric synthetic aperture radar system, comprising two multi-polarization SAR satellites, LT-1A and LT-1B. The satellite uses differential deformation measurement and interferometric altimetry technology to realize surface deformation monitoring and topographic mapping in designated areas. It has the characteristics of all-weather, all-time, and multi-polarization and can be applied to military and civilian fields. In order to further improve the accuracy of image geometric positioning, this paper analyzes the error sources of geometric positioning for the differential deformation measurement mode (strip 1) of the satellite service. The in-orbit data of three years since the launch (2022–2024) are selected to analyze the positioning accuracy and stability of the uncontrolled plane based on the corner reflector and active calibrator deployed in the calibration field. The experimental results show that the positioning accuracy of the satellite strip 1 image without a control plane meets the requirements of the in-orbit index and remains relatively stable. The geometric precision correction positioning accuracy after error source compensation is better than 3.0 m, providing a favorable support for the subsequent application. Full article

Background/Objectives: Military identity serves as a foundational lens through which service members navigate the events of everyday military and civilian life. However, the very process that cultivates a sense of unity and purpose can be a double-edged sword in civilian life. Although the prevalence and transition needs are known, few studies have explored how chronic pain specifically disrupts military identity in depth. This qualitative study explores three distinct trajectories through which Veterans with chronic pain experience identity change. Methods: This study used narrative inquiry involving two sets of in-depth interviews with 20 Veterans. Reflexive thematic analysis was employed to describe and differentiate three distinct trajectories of chronic pain. Results: Veterans with chronic pain experience identity change through three overlapping pain trajectories: (1) traumatic injury -> immediate discharge; (2) misdiagnosed/non-traumatic injury -> delayed discharge; and (3) cumulative wear and tear -> gradual discharge. Regardless of trajectory, chronic pain consistently disrupted military identity and forced Veterans to confront tensions between institutional expectations of stoicism and combat readiness and the physical realities of chronic pain during military service. Those interviewed described experiencing fragmented institutional support, uneven access to care, and the systemic invalidation of pain that did not conform to military ideals. Conclusions: These findings underscore the need for Veteran-centred approaches, including responsive services, comprehensive pain science education throughout military careers, early detection of conditions that can lead to chronic pain, and flexible care pathways tailored to the nuances of each pain trajectory and grounded in military culture and lifestyle. Full article

Ship detection in synthetic aperture radar (SAR) remote sensing imagery is of great significance in military and civilian applications. However, two factors limit detection performance: (1) a high prevalence of small-scale ship targets with limited information content and (2) interference affecting ship detection from speckle noise and land–sea clutter. To address these challenges, we propose a novel end-to-end (E2E) transformer-based SAR ship detection framework, called Flow-Aligned Nested Transformer for SAR Small Ship Detection (FANT-Det). Specifically, in the feature extraction stage, we introduce a Nested Swin Transformer Block (NSTB). The NSTB employs a two-level local self-attention mechanism to enhance fine-grained target representation, thereby enriching features of small ships. For multi-scale feature fusion, we design a Flow-Aligned Depthwise Efficient Channel Attention Network (FADEN). FADEN achieves precise alignment of features across different resolutions via semantic flow and filters background clutter through lightweight channel attention, further enhancing small-target feature quality. Moreover, we propose an Adaptive Multi-scale Contrastive Denoising (AM-CDN) training paradigm. AM-CDN constructs adaptive perturbation thresholds jointly determined by a target scale factor and a clutter factor, generating contrastive denoising samples that better match the physical characteristics of SAR ships. Finally, extensive experiments on three widely used open SAR ship datasets demonstrate that the proposed method achieves superior detection performance, outperforming current state-of-the-art (SOTA) benchmarks. Full article

Armed conflicts continue to severely impact human populations and essential infrastructure, particularly water supply systems. This study examines the Yechilla area, a high-intensity battle corridor during the Tigray (between 12°15′26″ 14°57′49″ N latitude; and 36°20′57″–39°58′54″ E longitude) war (2020–2022). Using Cochran’s formula, a representative sample of 89 water schemes was selected for onsite assessment. Additional data on damages to water offices, personnel, equipment, and related infrastructure were gathered through face-to-face interviews with local officials and water professionals, onsite visits, and reviews of governmental and non-governmental archives, and previous studies. The findings reveal that 48.3% of water schemes in the study area are non-functional (does not deliver water), which is a significant increase from pre-war non-functionality rates of approximately 7.1% regionally and 21.1% nationally. Despite the Pretoria peace agreement, non-functionality levels remain critically high two years after conflict. Damage includes partial impairments, lack of technical and spare part support, complete destruction, and looting of water scheme components. The widespread destruction of civilian water infrastructure during the Tigray conflict underscores the insufficiency of existing international legal frameworks, such as the International Humanitarian Law and International Water Law, which are inadequately protecting civilians and their property. Understanding the broader consequences of armed conflicts requires examining the indirect effects and the complex interactions within and between social, economic, and environmental systems. These interconnected impacts are essential to fully grasp how conflict affects livelihoods and human security on a wider scale. Full article

Background and Objectives: Hepatic steatosis is associated with an increased risk of liver-related morbidity and mortality. Although numerous studies have reported associations between depression, obesity, metabolic syndrome, and cardiovascular disease, the relationship between depression and hepatic steatosis has not yet been fully elucidated. Moreover, obesity is a shared risk factor for hepatic steatosis and depression; however, few studies have adequately adjusted for obesity as a potential confounder. In this study, we investigated the association between depression and hepatic steatosis stratified by obese and non-obese status. Materials and Methods: This study used data from the Korean National Health and Nutrition Examination Survey, conducted by the Korean Ministry of Health and Welfare between 2010 and 2019, which was a cross-sectional and nationally representative study of non-institutionalized civilians using a stratified, multistage, clustered probability sampling design. Multivariate logistic regression analyses were conducted to evaluate the association between depression and hepatic steatosis in the groups stratified by obese status. Results: Of 80,861 participants, data from 45,307 were included in the analysis. The prevalence of non-obese and obese hepatic steatosis was 3.1% and 19.3%, respectively, and the prevalence of diagnosed depression was 4.6%. Individuals with hepatic steatosis showed less favorable metabolic profiles, including higher rates of diabetes and elevated liver enzyme levels. Those with depression were older, predominantly female, and had lower socioeconomic status. After fully adjusting for confounding factors, multivariate logistic regression analysis showed that non-obese hepatic steatosis was significantly associated with an increased risk of depression, and obese hepatic steatosis was significantly associated with suicidal ideation and attempts. Conclusions: This study suggests a significant association between depression and hepatic steatosis with and without obese status. Given the significant impact of hepatic steatosis on depression outcomes, healthcare providers should screen patients with hepatic steatosis for depression and provide appropriate treatment as needed. Full article

Tiltrotor aircraft, due to their vertical takeoff and landing capability and efficient high-speed cruise performance, are increasingly valuable in both modern military and civilian applications. However, traditional calibration methods for blade pitch control often lack the precision required for large actuator strokes, which limits the control accuracy. This study aims to overcome these limitations by introducing an improved polynomial fitting algorithm to model the nonlinear relationship between the blade pitch control angles and actuator strokes. Using a specific rotor model, a coordinate system was established for the pitch control mechanism and spatial geometric relationships were derived. Experimental comparisons demonstrate that the proposed cubic polynomial fitting algorithm reduces the collective pitch error by approximately 57% and cyclic pitch error by 33%, markedly outperforming traditional linear fitting methods. These improvements significantly enhance the control precision and operational stability. The findings provide a reliable theoretical and practical basis for improving tiltrotor flight performance and safety. Full article