Defense and Security Studies

Design and analysis of a wideband split-ring integrated hybrid fractal-shaped patch antenna for WiFi, WiMAX, WLAN/5G midband applications

Rani Rudrama Kodali, Md. Shoaib, P. Anjali, T. Divya Sri Sivatmika — Mon, 12 Jan 2026 00:00:00 +0000

A split-ring integrated hybrid fractal antenna has been designed with improved bandwidth from 3 GHz to 9.56 GHz and is presented for WiFi/WiMAX/WLAN/5G midband applications. The proposed antenna is planned to deliver an extended bandwidth and is consists of split-ring resonators integrated with a fractal-shaped patch. The Fractal Shape in the antenna provides a compact size due to its self-similarity, space-filling property, and additional split-ring resonators to improve the bandwidth. The antenna, compact in size with dimensions of 31×37mm² and a thickness of 1.8mm, is constructed upon an FR4 epoxy substrate showing a dielectric constant of 4.4. The proposed antenna performance is presented with the help of reflection coefficient and VSWR plots, gain, field distribution, and radiation pattern. The comparison of simulated and measured analysis and results showed good agreement, indicating that the design antenna is suitable for WiFi, WiMAX, WLAN, and 5G applications.

Threat assessment model in air defense systems using Artificial Neural Networks

Salih Tasdemir, Murat Atan — Tue, 13 Jan 2026 00:00:00 +0000

This study aims to automate threat assessment and target assignment processes in air defense systems using a dynamic, learning artificial intelligence-based model. Unlike threat assessment studies in the literature that use different criteria and methods, this study integrates missing data completion, multi-criteria analysis, and artificial neural networks to dynamically update the threat score. Furthermore, unlike studies in the literature, the number of criteria used has been increased to enable the model to provide a broader perspective. Most studies are static and use a small number of criteria; this study presents a dynamic, multi-criteria model that can handle incomplete data. The developed Geometric Threat Score proposes an average perspective for threat assessment, which varies depending on individuals and geographical conditions. The model generates threat scores using criterion data obtained from radars and sensors and can respond adaptively to changing conditions. The results achieved demonstrated high performance with mean square errors (MSE) of 0.0005–0.0072 and a correlation coefficient (R) above 95%. This approach accelerates decision support processes in air defense systems, reducing human influence and increasing system effectiveness.

Artificial Intelligence reshaping United States of America’s National Defense strategy

Shakh e Nabat — Sun, 18 Jan 2026 00:00:00 +0000

Artificial Intelligence is an emerging, transforming, and revolutionizing technology of the 21st century. It has wide-ranging applications from education and healthcare to defense and security. It is rapidly transforming the modern defense system, making it faster, smarter, and more efficient. The ethics regarding the use of AI are in turmoil, but global powers would not wait for them to become established principles, as they find it imperative to maximize their power and capability in every sector, especially defense, where, from automated drones to real-time threat situations, AI is redefining warfare, national security, and defense strategies. National Defense strategy 2022 of the United States is one such strategy that entails within it the concept of integrated deterrence to use all means at disposal with the cooperation of allies and create a defense infrastructure with advanced and effective Artificial Intelligence. Followed by Data analytics and adoptive strategy 2023 that outlines the ways in which Artificial intelligence will be incorporated to answer the operational needs and prepare United States of America for the Future Advanced Warfare.

Next-Generation Black Box with IOT and Real Time Monitoring

Sat, 24 Jan 2026 00:00:00 +0000

The traditional black box, or Flight Data Recorder (FDR) and Cockpit Voice Recorder (CVR), has been instrumental in post-crash investigations. Its limitations, such as data loss, difficulty in retrieval from remote or underwater crash sites, and the inability to provide real-time insights, prompted the need for technological advancements. This paper aims to explore the integration of cutting-edge technologies such as the Internet of Things (IoT), Artificial Intelligence (AI), Satellite Communication, GPS, and advanced telemetry systems to revolutionize black box functionality and enhance aviation safety. Next-generation black boxes can leverage real-time encrypted data transmission through satellite connectivity, ensuring immediate access to crucial flight parameters, even before an accident occurs. The incorporation of GPS enables precise aircraft tracking, while telemetry techniques allow monitoring of critical flight parameters, engine health, and environmental conditions. Additionally, the use of underwater acoustic beacons and buoyant ejection modules can expedite black box recovery in case of oceanic crashes, reducing search and rescue operation time. AI-driven predictive analytics further strengthen aircraft monitoring by detecting anomalies and potential system failures, enabling preemptive measures to prevent disasters. The integration of IoT allows seamless connectivity between onboard sensors and ground control stations, ensuring that aviation authorities receive real-time alerts regarding abnormal flight behavior or malfunctions. Moreover, cloud-based data storage ensures redundancy, eliminating the risks of data loss due to hardware damage. By implementing IoT-enabled black boxes, the aviation industry can significantly reduce the risk of flight disappearance, improve accident investigations, and enhance proactive safety measures. The ability to access real-time flight data enhances situational awareness, minimizes investigation delays, and facilitates faster decision-making during in-flight emergencies. This technological evolution in flight data recording and transmission marks a significant step toward a safer, more efficient, and more transparent aviation ecosystem.

Analysis of Optical Telescope Element (OTE) used in James Webb Space Telescope (JWST)

Alan Catovic, Dzan Jasarevic — Thu, 12 Feb 2026 00:00:00 +0000

This paper presents an analysis of the James Webb Space Telescope (JWST) Optical Telescope Element (OTE) based on its published optical prescription and system architecture. Using modeling, key optical performance parameters were evaluated, including spot diagrams, footprint diagrams, wavefront error (WFE), point spread function (PSF), Strehl ratio, encircled energy (EE), and modulation transfer function (MTF). The segmented 6.6 m primary mirror was modeled using a User-Defined Aperture (UDA) approach to accurately reproduce the hexagonal pupil geometry and diffraction effects. Results confirm diffraction-limited performance across the evaluated field, with RMS wavefront error well below the Maréchal criterion, high Strehl ratios (≥0.87 off-axis and ≥0.97 on-axis at 1 µm), and encircled energy closely matching the diffraction limit. MTF curves demonstrate strong contrast transfer up to the cutoff spatial frequency with minimal field-dependent degradation.

Additional analyses were performed to assess the impact of individual segment piston and tilt misalignments. Controlled perturbations show that segment-level phase discontinuities significantly degrade WFE, emphasizing the importance of precise segment phasing and wavefront sensing and control (WFS&C).

The wargaming signalling paradox: when military publication precedes political miscalculation

Branko Ruzic — Wed, 18 Feb 2026 00:00:00 +0000

This article examines how publishing wargaming results or military planning timelines creates institutional commitment traps leading to strategic miscalculation. Analysing Russia's 2013 Gerasimov article and China's October 2025 15th Five-Year Plan, we identify three paradoxes: publication signals confidence while reflecting overconfidence; aims to deter but constrains flexibility; and demonstrates rigour while omitting critical behavioural factors. China's 2027 PLA centenary deadline is particularly concerning, as Xi Jinping's legitimacy becomes tied to published timelines despite acknowledged wargaming limitations - the same blind spots that contributed to Russia's Ukraine disaster. Contemporary Chinese simulation research exhibits identical problems while claiming 90% success probability.

A robust feature engineering approach for Arabic extremist content detection in social media

Ahmed Salman Ibraheem — Thu, 12 Mar 2026 00:00:00 +0000

In this paper, we propose an end-to-end machine learning system to analyze sentiment polarity in extremist (terrorism-related) Arabic content with novel designed features concentrating on linguistic discourse, properties and changes of such contents. We constructed three corpora (V1, V2 and V3) from Arabic tweets; which have been pre-processed by using various linguistic techniques: Normal stemmer, root pattern, Light Stemming. We have employed various machines' learning algorithms such as SVMs, NB and KNN with BOW and ngr am models to retrieve features. Our large scale comparative analysis based on a real-dataset benchmark chose linear SVM and Uni-gram model in conjunction with Term Frequency-inverse document Frequency (TF-IDF) as the preferable choice. Our approach achieved better accuracy for extremist sentiment detection and greater Recall in V1 (81.097%) and V2 (81.707%) compared to this setup. These ones were superior to other combination of SVM kernels along with the KNN algorithm that also was very competitive. Our findings outperformed the already established approach (Kanan & Fox) for classifying extremist Arabic texts (our BEA as an average achieved accuracy rate higher than their 78.00% but using P-Stemmer and SVM). The precision-recall and ROC AUC values for SVM settings also reinforced the performance, and high scores reflected its ability to handle complex features of Arabic like syllabic lengthening and diacritics. The present study demonstrates the potential applicability of this approach to enhanced supporting extremism detection analysis in Arabic textual data, and may offer a clearer perspective for those concerned on security, education and policy making domains.

Thermal protection strategies for hypersonic space vehicles: aerothermodynamics, TPS configurations, and performance effects

Fri, 13 Mar 2026 00:00:00 +0000

The Thermal Protection System (TPS) is one of the essential parts for visualizing the aerothermodynamic effect for a hypersonic moving body, i.e., M > 5. This detailed review paper deals with discussing the importance of aerothermodynamic effects, presents an overview of TPS, and highlights the key points on the influence of aerodynamic performance. The incorporation of TPS materials alters surface roughness, vehicle contour, mass distribution, and structural stiffness, thereby affecting drag, lift-to-drag ratio, boundary layer transition, and overall flight efficiency. The review aims to provide a cohesive understanding of the interdependence between aerothermodynamics, TPS material behavior, and aerodynamic performance, thereby supporting advanced design strategies for next-generation hypersonic space transportation systems.

Network-driven hybrid control for smart grids communications with renewable energy integration

Zeyid T. Ibraheem — Tue, 31 Mar 2026 00:00:00 +0000

This article presents a comprehensive simulation framework for performance analysis of hybrid monitoring and control systems in power grids. The model integrates the dynamics of the power grid and the communication network to deal with how these two interact and the effects that arise due to the interactions between them. The framework is demonstrated on a 15-node MATLAB-based simulation of generation stations, substations, industrial and residential loads, and renewable energy sources, with a real-world topology. The simulation incorporates profiles of daily loads, renewable generation profiles, and various forms of system disturbances, and a distributed control system that considers the delay of communication and the loss of packets. Verify the framework with simulations of voltage drops, load surges, generation losses, and cyber-attacks, and examine their impact on system performance based on the Voltage Quality Index, Frequency Quality Index, and Communication Reliability Index. Findings show that communication performance contributes greatly to control performance, particularly when there is a cyber event characterized by high voltage-quality degradation. The suggested framework will offer a guide that a smart grid planner will use to determine resilience and develop the respective strategies, optimize communication infrastructure, and continue to introduce renewable energy into future power systems.