In recent decades, there has been a growing demand for eco-friendly unmanned aerial vehicles (UAVs) in both civilian and military domains. This has created interest among scholars and industry experts who envision Flying Ad-hoc Networks (FANETs) supplanting conventional networks in contexts such as surveillance, disaster management, precision agriculture, and logistics. Despite the constraints of UAV resources, it is crucial to optimize UAV resource utilization to extend network lifespan and uphold a satisfactory quality of experience (QoE). This study examines the application of the Fisheye State Routing (FSR) protocol to facilitate communication among multiple UAVs within a dynamic network... More >

Vietnam's Electric Vehicle (EV) market is expanding rapidly, yet public charging infrastructure development lags significantly, exhibiting pronounced spatial imbalance in dense urban cores. This study addresses this gap through an integrated demand forecasting and location optimization framework for District 1, Ho Chi Minh City. We develop a log-linear regression model using Vietnam's macroeconomic data (2003–2023), identifying GDP and CPI as dominant determinants of vehicle ownership (R$^2$ = 0.962). Forecasted vehicle stocks for 2026–2030 are translated into public charging demand through vehicle-type disaggregation and service-capacity modeling. Spatially, we propose a four-stage opti... More >

The traditional approach of manually selecting the parameters for LCL filters employed in single-phase grid-tied inverters is often ineffective and challenging to optimize. This can result in the LCL filter being unable to adequately attenuate high-frequency harmonics, causing the grid-injected current to not fully comply with IEEE 519 standards. Furthermore, the filtering performance can degrade when the system is coupled to a weak grid due to the inherent resonance issue of the LCL filter. To address these problems, this paper thoroughly examines the total harmonic distortion (THD) and resonance frequency of an LCL-filtered grid-tied inverter. An optimization function with three different... More >

In today's technological landscape, recommender systems provide essential personalized suggestions by leveraging user preferences. This study evaluates User-Based (UBCF) and Model-Based Collaborative Filtering (MBCF) on the MovieLens 1M dataset, comparing performance on complete data versus partitions based on age and occupation. Using MAE and RMSE metrics, we assessed UBCF with Euclidean/Cosine similarity and MBCF with NMF/SVD. Results show MBCF with SVD achieved the best performance (MAE: 0.6909, RMSE: 0.8761), outperforming UBCF by approximately 5.2% in MAE and 5.4% in RMSE. This confirms model-based approaches, particularly SVD, excel with complete datasets, while demographic partitionin... More >

The growth of the Internet of Things (IoT) has connected a massive number of devices, but its common centralized design creates major security, privacy, and scalability problems that old security methods cannot properly fix. This review explores how Blockchain Technology (BCT) offers a new approach to create trust and strong security for IoT systems without a central authority. Following the PRISMA guidelines, this study analyzes 68 research papers and uses a Chi-square test to statistically confirm the link between IoT problems and the use of blockchain solutions. The results show a strong, statistically proven connection, with a Chi-square value of 34.772 (p<0.05) and a Cramer's V of 0.63.... More >

Gaze estimation plays a vital role in human-computer interaction, driver monitoring, and psychological analysis. While state-of-the-art appearance-based methods achieve high accuracy using deep learning, they often demand substantial computational resources, including GPU acceleration and extensive training, limiting their use in resource-constrained or real-time scenarios. This paper introduces GeoGaze, a novel, lightweight, training-free framework that infers categorical gaze direction (“Left”, “Center”, “Right”) solely from geometric analysis of facial landmarks. Leveraging the high-precision 478-point face mesh and iris landmarks provided by MediaPipe, GeoGaze computes a simp... More >

Text-based CAPTCHAs remain a widely deployed mechanism to distinguish humans from automated bots. The Telerik RadCaptcha, a component of the ASP.NET AJAX suite, generates distorted alphanumeric images with character overlap, intersecting lines, and dynamic background noise. This study introduces a novel, real-world dataset of 3,000 labeled Telerik RadCaptcha images and proposes a specialized multi-stage preprocessing pipeline featuring adaptive binarization and contour-based segmentation to robustly isolate overlapping and noisy characters—challenges where conventional methods frequently fail. The segmented characters are then classified using a lightweight Convolutional Neural Network (CN... More >

The escalating demand for efficient particle separation in microfluidic systems necessitates innovative design solutions. This study presents a simulation-based topology optimization method to passively separate particles within a 2D microfluidic channel, eliminating the need for external forces. Leveraging a coupled Navier-Stokes solver and particle advection simulation, the framework iteratively refines the channel's geometry by minimizing an objective function quantifying particle mis-sorting. Our approach computationally generated optimal, manufacturable topologies, demonstrating a peak sorting efficiency of 0.6667 (66.67%) achieved by the second iteration, which then stabilized in subse... More >