Journal of Military Science and Technology

Improved MRAS with stator and rotor resistance estimation for vector control of induction motors

Tran Dinh Cuong, Phan Thanh Tai, Nguyen Thanh Quang, Phan Tran Dang Khoa — Wed, 25 Feb 2026 00:00:00 +0000

This research addresses the degradation of speed estimation accuracy in speed-sensorless induction motor drives that arises from temperature-dependent variations of stator and rotor resistances. These parameter changes significantly affect the Rotor Flux-Based Model Reference Adaptive System (RF-MRAS) observer, leading to reduced robustness and unstable operation under dynamic conditions. To mitigate this issue, an enhanced Field-Oriented Control (FOC) scheme is proposed, integrating an adaptive RF-MRAS observer with an online estimation mechanism for the stator resistance and a proportional inference approach for the rotor resistance. A complete induction motor model is formulated in the stationary α-β reference frame and subsequently transformed into the rotating d-q frame to facilitate the implementation of the vector control strategy. Simulation studies, conducted under both sudden step changes and gradual ramp variations of the motor resistances, verify that the proposed method significantly improves speed estimation accuracy and enhances overall system stability. Owing to its simple structure and low computational burden, the proposed approach is suitable for real-time embedded applications in modern sensorless motor drive systems.

Real-time long-term target tracking on an ARM platform with NPU acceleration and integration into UAV line-of-sight stabilization

Le Khanh Thanh, Vu Quoc Huy, Le Ba Tuan — Wed, 25 Feb 2026 00:00:00 +0000

This paper presents a real-time long-term target tracking algorithm optimized for ARM embedded platforms with integrated NPU acceleration. The system combines a pruned and quantized YOLOv10s detector with a NEON-optimized fDSST tracker. The two blocks are linked via an adaptive confidence index based on multi-feature fusion and a hysteresis mechanism to activate the detector only when necessary. Theoretical analysis demonstrates the boundedness of the correlation filter, the stability of the adaptive weight update process, and the exponential bounding of the probability of false state transitions. Experimental results on the Orange Pi 5 Max platform show that the system achieves an average speed of 19 FPS for detection and over 100 FPS for tracking, while maintaining stability in the presence of delay, noise, and transient occlusion. Monte-Carlo simulations and line-of-sight (LOS) stabilization simulations on a UAV rotating platform confirm a mean maximum angular error of approximately 0.006 rad and the ability to quickly re-track after target loss. The algorithm has potential applications in real-time optical surveillance, reconnaissance, and line-of-sight stabilization systems.

Real-time speech acquisition, compression and wireless transmission solution on resource-constrained embedded systems

Vuong Viet Thao, Pham The Anh, Phan Thi Lan, Nguyen Trung Hieu — Wed, 25 Feb 2026 00:00:00 +0000

Resource-constrained embedded systems are electronic systems designed to perform specific tasks with minimal hardware and software resources. They are very popular and essential to building a compact and efficient system at a low cost. This paper presents an embedded system architecture for real-time acquisition and compression, utilising wireless transmission, for intelligent embedded devices. The platform uses an STM32F411CEU6 (ARM Cortex–M4) microcontroller, paired with an INMP441 MEMS microphone, and employs the Codec2 encoder at a rate of 3.2 kbps. An optimised algorithm based on receiver-side data and sending voice frame processing on I2S and UART interfaces, respectively, has been applied using CMSIS-DSP acceleration and computational constrained STM32F4 series and NRF24L01 modules, with COBS encoding. System operation results in real-time execution with a latency of 2.31 ms/ frame and a low power consumption of 50.23-51.7 mW at 3.3 V operation, demonstrating a good model with performance characteristics that simultaneously achieve minimal real-time transmission and low power consumption. The proposed architecture system is well-suited and potentially suitable for next-generation speech-centric applications such as responsive speech-to-text, real-time command recognition, and a compact on-device language translation module.

Research and Design of a Low Phase-Noise Dielectric Resonator Oscillator for X-Band Radar Applications

Vu Minh Thanh, Luu Duc Tho, Pham The Quang — Wed, 25 Feb 2026 00:00:00 +0000

This paper presents the research, design, and implementation of a low phase-noise dielectric resonator oscillator (DRO) operating at 9.4 GHz for X-band radar applications. A high-quality-factor dielectric resonator operating in the mode was employed to enhance frequency stability and suppress phase noise. The oscillator was realized using a microstrip coupling structure, with a GaAs FET transistor serving as the active element in the feedback network. Comprehensive electromagnetic and circuit-level simulations were conducted in CST and ADS to optimize the resonator coupling and feedback configuration, ensuring stable oscillation and effectively mitigating spurious modes. Compared with conventional oscillator designs, the proposed DRO demonstrates superior frequency stability and reduced phase noise, while maintaining a compact form factor. These characteristics render the proposed design highly suitable for modern X-band radar front-ends as well as other advanced microwave communication systems requiring low-noise and high-stability local oscillators.

Building solutions and algorithms for water resource allocation for a river basin

Chu Hoa Lu, Dang Tien Trung, Vu Manh Tuan — Wed, 25 Feb 2026 00:00:00 +0000

In this study, the author proposes a water allocation model based on the linear programming (LP) method combined with the Simplex algorithm to maximize the overall economic benefits while ensuring social constraints and natural limits of the system. The model is built and applied to real data of two river basins. The calculation results demonstrate the effectiveness of the proposed method, with the ability to quickly determine the optimal solution and easily extend to large-scale water resource management systems.

The role of artificial intelligence and machine learning in mechanical engineering: A review

Nguyen Van Toan, Mai Xuan Hai, Doan Tat Khoa — Wed, 25 Feb 2026 00:00:00 +0000

This paper presents a review of the role of artificial intelligence (AI) and machine learning (ML) in advancing mechanical engineering, with an emphasis on domain-specific implementations that have driven recent technological progress. Applications such as predictive maintenance, structural integrity assessment, intelligent design optimization, automated quality inspection, and renewable energy system enhancement demonstrate the capacity of AI approaches, including deep neural networks and reinforcement learning, to improve performance efficiency, minimize operational costs, and foster sustainable engineering solutions. Beyond individual applications, the review discusses fundamental AI attributes, including model adaptability, interpretability, and the coupling of data-driven techniques with physics-informed frameworks, which collectively enable scalable adoption across mechanical engineering disciplines. Notwithstanding these advances, unresolved issues persist, particularly in terms of model reliability, computational overhead, and the availability of high-quality data. By consolidating recent research outcomes, highlighting existing limitations, and proposing prospective research pathways, this review aims to provide valuable insights for both academic researchers and industry.

Multifunctional electrospun CS/PVA/AgNPs nanofiber membranes for dye removal and antimicrobial water purification

Nguyen Thi Anh Huy, Tran Thanh Viet, Nguyen Khoi Nguyen, Le Anh Kien — Thu, 26 Feb 2026 00:00:00 +0000

There is an urgent need for sustainable methods to purify water contaminated with dyes and pathogenic microorganisms. Conventional treatment technologies often face limitations due to the use of toxic chemicals or complex fabrication processes. In this study, electrospun chitosan/poly(vinyl alcohol)/silver nanoparticle (CS/PVA/AgNPs) nanofiber membranes were fabricated and evaluated for their dual functionality in dye removal and antibacterial activity. SEM, XRD, and EDS analyses confirmed the formation of quasi-spherical AgNPs and their uniform distribution within the polymer matrix. Morphological analysis revealed that the incorporation of AgNPs into the CS/PVA matrix reduced the fiber diameter from 120-230 nm to 99-158 nm and significantly decreased bead formation. Congo Red adsorption reached equilibrium within 120-150 min, with capacities increasing with dye concentration. Maximum adsorption occurred at pH 4, and the membrane retained over 60% efficiency after two regeneration cycles. Additionally, the CS/PVA/AgNPs membrane exhibited strong antibacterial activity, achieving up to 99% inhibition against Escherichia coli and Staphylococcus aureus. Overall, these results highlight the potential of CS/PVA/AgNPs nanofiber membranes as multifunctional, eco-friendly materials for simultaneous dye adsorption and antimicrobial water purification.

Microwave-assisted synthesis of Co0.4Ni0.6Al2O4 - Evaluating the effect of practical parameters on material properties

Thu, 26 Feb 2026 00:00:00 +0000

In this study, microwave-assisted combustion synthesis (MACS) was used to prepare Co_0.4Ni_0.6Al₂O₄ spinel powders from respective metal nitrate salts and urea fuel using a domestic microwave oven. The study systematically varied the fuel-to-oxidizer (F/O) molar ratio and microwave output power to determine their influence on combustion behavior, phase formation, crystallinity, yield and morphology. Results show that the fuel content strongly controls combustion intensity and homogeneity, and a molar ratio Al³⁺:urea = 1:6 (F/O = 1.8) produced the most uniform, dark-blue spinel with sharper X-ray diffraction (XRD) peaks and fewer secondary phases compared with both fuel-rich and fuel-poor conditions. Furthermore, microwave power critically affected ignition, conversion and phase purity. The insufficient power (770 W) failed to trigger self-propagating combustion, while excessive power (1100 W) induced local overheating and more secondary phases (α-Al₂O₃ and NiO). The optimal condition identified in this work was 990 W at Al³⁺:urea = 1:6, which provided the highest mass conversion (91%) and well-crystallized Co_0.4Ni_0.6Al₂O₄ with porous morphology characteristic of combustion synthesis. The study demonstrates that control of F/O ratio and microwave power in MACS enables rapid, energy-efficient synthesis of Co–Ni aluminate spinels.

Fabrication of W-doped VO2 materials with low phase transition temperature for adaptive thermal camouflage application

Nguyen Duy Anh, Nguyen Huu Van, Do Thi Thuy, Nguyen Cong Thang, Khong Manh Hung — Wed, 25 Feb 2026 00:00:00 +0000

This paper reports on the synthesis of W-doped VO₂ materials and the characterization of their phase transition temperature (PTT). Utilizing a microwave-assisted combustion synthesis method, the materials were successfully prepared with high homogeneity in particle size, while the processing time was shortened. The phase composition of the materials was determined by X-ray diffraction (XRD), which revealed that at certain doping levels, the material exhibited a structural change from monoclinic to tetragonal at room temperature. The morphology of the synthesized VO₂ was evaluated by scanning electron microscopy (SEM), showing uniform particle sizes of less than 200 nm. Differential Scanning Calorimetry (DSC) analysis indicated that the PTT of pure VO₂ was 67.2 °C. In contrast, as the W-doping concentration was incrementally increased (from 1% to 2%), the PTT decreased (from 44.4 °C down to 22.3 °C). The effective control of the phase transition temperature is crucial for the material's application in the field of adaptive thermal camouflage.

Study on the fabrication of sulfuric acid-resistant butyl rubber for military battery linings

Wed, 25 Feb 2026 00:00:00 +0000

This study focuses on the development of a specialized butyl rubber (IIR) material with high resistance to sulfuric acid (40% H₂SO₄ at 70 °C) for use as military battery linings. The effects of the vulcanization system, N330 carbon black loading, P150 paraffin oil content, and the TMQ/6PPD antioxidant systems on the mechanical properties and chemical resistance were systematically investigated. Experimental results indicated that the use of an efficient vulcanization system comprising of 2.0 phr DTDM and 1.5 phr TMTD established a robust mono- and di-sulfidic crosslink network, effectively minimizing acid-induced chain scission. The optimal formulation was identified as containing of 50 phr of N330 carbon black, 10 phr of P150 paraffin oil, and a synergistic antioxidant system comprising of 2.0 phr TMQ and 1.5 phr 6PPD. The resulting material exhibited a tensile strength of 14.5 MPa, an elongation at break of 510%, and retained 92.4% of its mechanical properties after 168 hours of accelerated aging. SEM analysis confirmed that the surface of the optimized sample maintained its structural integrity without micro-cracks, fully satisfying the technical requirements for military equipment applications.

Biodegradable poly (lactic acid)/ZnO/Pluronic composite films: Mechanical properties, antibacterial performance, and fruit preservation

Nguyen Tien Manh — Wed, 25 Feb 2026 00:00:00 +0000

In this study, composite films based on Poly(lactic acid) (PLA), Zinc Oxide (NPs) and Pluronic P123 (0.5–1.5 wt% ZnO/Plu) were fabricated and characterized with respect to structure, mechanics, antibacterial behavior, and fruit‑preservation performance. An optimum was observed at 1.0 wt% ZnO/Plu, where tensile strength (15.7 MPa), elongation at break (~0.7%), and reduced 24‑h water solubility coincided with uniformly dispersed ZnO/Plu domains confirmed by SEM/EDX and FTIR. The films exhibited strong, dose‑dependent antibacterial activity against Escherichia coli and Bacillus subtilis, with maximal inhibition at 1.0 wt% and a slight decline at 1.5 wt% due to nanoparticle aggregation. When used as active packaging for bananas, the 1.0 wt% ZnO/Plu film most effectively limited weight loss, maintained titratable acidity and vitamin C, and preserved visual quality, indicating its potential as a biodegradable active packaging material for postharvest applications.

Formation and stability of Sc(III), La (III), Dy(III), Pr(III) and Y(III) complexes with hydroxypyridine-carboxylic acids in aqueous solution

Han Duy Linh — Wed, 25 Feb 2026 00:00:00 +0000

The complexation of three hydroxy-substituted pyridine carboxylic acids: 2-hydroxypicolinic acid (L¹), 3-hydroxynicotinic acid (L²), and 2-hydroxy-6-methylnicotinic acid (L³) - with Sc³⁺, Y³⁺, La³⁺, Pr³⁺, and Dy³⁺ was systematically studied using spectrophotometric and potentiometric titrations. Stepwise ligand deprotonation allowed determination of complex stoichiometries and formation constants (log β = 4.63 - 11.51), revealing a strong dependence on metal ionic radius, charge density, and donor atom type. Oxygen-donor ligands L¹ and L³ preferentially stabilize small, charge-dense cations (Sc³⁺, Dy³⁺), whereas the nitrogen-donor ligand L² favors larger ions (Y³⁺, La³⁺). The 6-methyl substituent in L³ introduces steric hindrance that reduces complex stability for larger cations. These results demonstrate the combined influence of donor atom identity, steric effects, and metal-ion properties on rare-earth complex stability, providing a quantitative basis for the rational design of selective ligands and functional coordination materials.

Harnessing bioinformatics to identify unique gene sequences tailored for the specific detection of Staphylococcus aureus by real-time PCR

Wed, 25 Feb 2026 00:00:00 +0000

Staphylococcus aureus is a major pathogen responsible for a wide range of foodborne illnesses. When the bacterial density of S. aureus reaches 10⁵ CFU/mL, the pathogen begins producing enterotoxin - the main agent responsible for illness. Previous studies have predominantly focused on detecting enterotoxin or anti-biotic resistance strains. In recent years, real-time PCR (qPCR) targeting a specific gene has proven to be an efficient and precise tool for the early detection of this pathogen, even at very low bacterial concentrations, before toxin production begins. This study aimed to identify the most specific and suitable genetic marker for qPCR-based detection of S. aureus, harnessing bioinformatics tools to evaluate six candidate genes – sa442, nuc, femA, mecA,mecC, spA and coa. Conserved genes and regions were analyzed using Geneious software and the NCBI BLAST tool to assess the coverage and similarity of the gene sequences across all bacterial S. aureus strains. The results demonstrated that the conserved DNA region of the nuc gene, positions 210 – 373, served as the most reliable marker for detection. Primers and probes designed from this sequence exhibited high specificity and optimal performance in qPCR assays. These findings underscore the effectiveness of bioinformatics in selecting robust targets for qPCR-based diagnostic applications in food safety monitoring.

Study on the development of an extraction process and evaluation of certain properties of the extract from perilla (Perilla frutescens var. crispa) leaves

Dang Duy Khanh, Le Ngoc Hoan, Tran Minh Anh, Nguyen Minh Tri, Vu Ngoc Toan — Wed, 25 Feb 2026 00:00:00 +0000

Perilla (Perilla frutescens var. crispa) leaves are widely used in traditional medicine and nutrition, and are known for their richness in polyphenols and bioactive compounds. This study aimed to optimize the extraction and enrichment of polyphenols from perilla leaves collected in Dong Anh commune, Hanoi city. The optimal extraction conditions were determined as 70° ethanol, a solvent-to-material ratio of 10:1 (v/w), at 35 °C for 65 minutes, yielding 5.74 mg GAE/g dry material. The crude extract contained a total polyphenol content of 114.83 mg GAE/g, which increased to 135.16 mg GAE/g after enrichment using activated X5 resin. In addition, the enriched extract gained a rosmarinic acid content of 62.8 mg/g. These findings demonstrate that the optimized extraction process combined with X5 resin enrichment produces a polyphenol-rich extract from perilla leaves, with promising applications in pharmaceuticals and functional foods.

An LLM-driven framework for strategic writing style transformation in cyber influence operations

Ngo Hoang Dang, Nguyen Huy Anh, Vu Viet Hoang, Nguyen Huy Hoang, Tran Lam — Wed, 25 Feb 2026 00:00:00 +0000

In the evolving landscape of cyber and cognitive warfare, language has emerged as a decisive instrument for shaping perception and influencing digital audiences. Effective communication on social media requires not only timely information delivery but also stylistic adaptability to maximize message reach and resonance. This paper introduces a Large Language Model (LLM)-based framework designed to optimize writing style transformation for strategic influence operations in online environments. Our system converts original textual content across three key styles - Humorous, Analytical, and Critical - spanning five thematic domains: Culture, Sports, Entertainment, Technology, and Politics. Through controlled style modulation, this method aims to enhance both information diffusion and positive engagement (“active dissemination”) while preserving message intent and factual coherence. We propose a multi-stage pipeline integrating stylistic control, semantic alignment, and evaluative feedback to select the optimal style for each context. Empirical evaluations, including pairwise statistical tests and diffusion analysis, demonstrate that style transformation significantly impacts audience interaction patterns and sentiment trajectories. The results can serve as a foundational tool for cyber influence strategists, enabling adaptive, ethically guided, and high-impact communication in the dynamic information battlespace.

Privacy-aware smart camera for abnormal event detection in home environments

Doan Huong Giang, Ho Anh Dung — Wed, 25 Feb 2026 00:00:00 +0000

Ensuring both effective monitoring and user privacy is essential in home surveillance applications. This study proposes a privacy-aware smart camera system integrating a servo-controlled mechanical housing with a dual-branch deep learning framework. That is a smart camera housing equipped with servo-controlled lids and dual operation modes, local button control and WiFi-based remote control, providing convenient usage while preventing unintended image capture. To detect hazardous household events, we constructed the EPUabInhouse dataset and proposed a dual-branch framework that integrates YOLOv8 for spatial analysis with RAFT optical flow for motion representation. Experimental results show that incorporating RAFT leads to a relative improvement of 2.02% to 4.15% in F1-score across different classes and significantly reduces background misclassification. These enhancements demonstrate the effectiveness and practical applicability of the proposed privacy-aware home surveillance system.

Building a mathematical model describing the dome profile of a solid fuel engine case made from composite materials using winding technology

Tran Ngoc Thanh, Dinh Van Hien, Bui Van Am — Wed, 25 Feb 2026 00:00:00 +0000

With the advantage of high specific strength, composite materials are the first choice for manufacturing a solid fuel engine case to increase the engine's stuffing coefficient. The main problem for designing an engine case from composite materials is the problem of determining the dome profile of the engine case. To determine the dome profile based on continuum theory, the article focuses on building a general mathematical model describing the dome profile of the case with an internal thermal protection layer under internal pressure p and axial force. Using this mathematical model, the influence of axial force and nozzle radius on the dome profile of the engine case is analyzed. The results of the article are the basis for designing the case of a solid fuel engine from composite materials.

Optimizing long-range UAV detection on YOLOv8: Breaking-point distance analysis and combining adaptive tiling with AdamW optimizer

Nguyen Van Ngon, Do Thi Nhan, Chu Hai Long, Pham Thanh Dong — Wed, 25 Feb 2026 00:00:00 +0000

The rapid proliferation of unmanned aerial vehicles (UAVs) has imposed stringent requirements on surveillance and early warning systems. In long-range detection scenarios, the apparent size of UAVs in images decreases significantly, leading to severe spatial information loss and degraded performance of convolutional neural network (CNN)-based detection models. This paper proposes a continuous quantitative analysis framework to model the relationship between observation distance and UAV detection performance by progressively reducing the input image resolution. Based on experimental regression analysis, a system-level breaking point is identified, representing a distance threshold at which detection performance begins to degrade sharply and exhibits nonlinear behavior. Furthermore, a solution integrating adaptive image tiling with the AdamW optimizer is proposed to ensure training stability and enhance performance in long-range scenarios. Experimental results on the YOLOv8s model show that the proposed approach improves mAP@0.5 in long-range detection by up to +24.9% while eliminating numerical instability during training on tiled data. Regression analysis identifies the system-level breaking point at D_c≈ 2.5, providing a quantitative basis for activating adaptive image processing in real-world deployments on resource-constrained platforms.

Influence of lower sheet material strength on joint quality in self-piercing riveting

Wed, 25 Feb 2026 00:00:00 +0000

Self-piercing riveting (SPR) has become a key joining technique for lightweight and high-strength joints, especially in the automotive and aerospace industries. This study investigates how the strength of the lower sheet affects the performance of SPR joints. While the upper sheet remains unchanged, the lower sheet varies using various alloys (AA7075-F, AA2019, BA0270, Mat A, and Mat B). A finite element model developed in Abaqus/Explicit was employed to simulate the SPR process and assess joint performance. Key joint evaluation criteria, such as interlock and remaining thickness, are also discussed. The results indicate that the strength of the lower sheet must reach a certain threshold to ensure proper joint formation. While increasing the lower sheet’s strength can enhance joint quality, excessive material strength may yield an insufficient interlock within the material or even generate a failure of the lower sheet.