Articles
Ahmad Hamid A.,
Amirhassan Monadjemi S.,
Shoushtarian, B.,
Village, A.,
Khoee, S.,
Mahdavian, A.R. IEEE Access (21693536)pp. 74996-75015
Detecting abnormal crowd behavior in surveillance videos is a significant challenge due to the intricate and constantly evolving crowd dynamics. To solve this issue, we suggest a new method that combines data from various sources with different characteristics to enhance the precision of detecting human behavior in crowds. Our approach involves two separate pipelines that work simultaneously to produce scores for frames in a video segment. These scores are later modified for the individual level of the group, allowing for behavior recognition through the assessment of fuzzy logic functions. In the first pipeline, we utilize a depth-wise Separable Convolutional Neural Network (DWS-CNN) that provides reduced filtering compared to standard CNNs. The second pipeline combines the LiteFlowNet detector with the MOSSE tracker and a DSC-GRU network to generate high-level captions for objects in video frames. We implement the weighted average (WA) method to improve anomaly detection accuracy. Methods like weighted averages can mitigate the influence of outliers and noise in the outcomes or evaluations. Utilizing linguistic variables to represent scores and computing weighted averages of scores from two pipelines enhances the quality and reliability of these variables, creating fuzzy predicates that characterize people’s movements, presence, and responses at a microscopic scale. Our approach exceeds conventional visual and motion-centric methods, enabling a more comprehensive grasp of abnormal behaviors. Our suggested approach outperforms state-of-the-art methods in terms of effectiveness and performance based on tests done on well-known datasets. © 2013 IEEE.
Scientific Reports (20452322)15(1)
This study developed a self-healing, anti-corrosive coating based on a novel nanocomposite formulation of 8-hydroxyquinoline-5-sulfonic acid-zinc doped polyaniline (HQZn-PA) incorporated into an epoxy matrix. The chemical composition and surface morphology of the synthesized nanocomposite were thoroughly characterized using Fourier transform infrared spectroscopy, X-ray diffraction, nuclear magnetic resonance, and scanning electron microscopy. Electrochemical impedance spectroscopy and potentiodynamic polarization tests confirmed the outstanding corrosion resistance and self-healing efficiency of the coating. The synthesized HQZn-PA demonstrates enhanced anticorrosive properties through the synergistic effects of its constituents. Polyaniline (PA) contributes anodic protection and forms a barrier layer, while the chelation of zinc by 8-hydroxyquinoline-5-sulfonic acid (HQZn) improves PA compatibility within the polymer matrix and functions as an organic corrosion inhibitor. This dual action strengthens corrosion resistance through both anodic and cathodic protection mechanisms. The HQZn-PA nanocomposite reduced the corrosion rate of epoxy coating by 450× compared and maintained an impedance modulus of 1.03 × 1010 Ω cm2 after 40 days in a saline environment. The nanocomposite also demonstrated a self-healing efficiency of 99.28% in scratched coatings. These results highlight the potential of HQZn-PA as a highly effective corrosion inhibitor and self-healing agent for long-term metal protection in harsh environments. © The Author(s) 2025.
Polymers for Advanced Technologies (10427147)36(4)
The uncontrolled leaching of corrosion inhibitors from coatings into the environment, even when corrosion does not occur, causes environmental pollution and diminishes anticorrosion performance. To address these challenges, we developed an anticorrosive nanoscale additive based on 8-hydroxyquinoline-5-sulfonic acid-doped polyaniline (HQPA). The synthesized HQPA possesses synergistic anticorrosive properties due to the presence of PA, which provides anodic protection and creates a protective layer, and 8-hydroxyquinoline-5-sulfonic acid, which not only enhances compatibility between HQPA and the polymer matrix but also, as an organic corrosion inhibitor, further improves corrosion protection through cathodic protection. Electrochemical analysis substantiated that the HQPA anticorrosive pigment could provide significant corrosion protection to submerged bare steel in an aqueous saline solution by forming a passive layer and mixed cathodic/anodic protection. Additionally, it was revealed that steel coated with an epoxy coating containing only 1 wt% HQPA exhibits a corrosion rate approximately 10 times lower than that of coatings containing non-conjugated inhibitors. Furthermore, this coating possesses significant self-healing attributes, with a healing rate of 97.5%. This strategic approach paves the way for the development and commercialization of materials offering robust corrosion protection and self-healing features. © 2025 John Wiley & Sons Ltd.
Epoxy adhesives are widely used as structural adhesives distinguished by a significant degree of cross-linking, resulting in their brittle characteristics. Some specialized applications require improved thermal stability and adhesive strength. The incorporation of zinc oxide nanoparticles into a core–shell rubber (CSR) structure composed of poly(butyl acrylate-allyl methacrylate) core and poly(methyl methacrylate-glycidyl methacrylate) shell will enhance the adhesion, toughness, and thermal stability of epoxy adhesives. We synthesized CSR particles using a two-stage emulsion polymerization method, characterizing them through Fourier-transform infrared spectroscopy (FTIR), scanning electron microscopy (SEM), transmission electron microscopy (TEM), and differential scanning calorimetry (DSC) analyses. We synthesized epoxy adhesives with different CSR particles ratios (1.25, 2.5, and 3.75 phr) and zinc oxide nanoparticles (1, 2, and 5 phr) using mechanical stirring and ultrasonication (a two-step mixing process) to enhance dispersion. We cured the epoxy adhesive samples for 7 days for tensile tests and 2 days for lap shear tests at room temperature. We employed the tensile and lap shear tests to assess the mechanical properties of the samples. The samples underwent thermogravimetric analysis (TGA) to assess their thermal stability. We assessed the fracture surface of the optimum samples using field-emission scanning electron microscopy (FESEM). We utilized design-of-experiments (DOE) and artificial neural network (ANN) approaches to model the mechanical properties. The outcomes of FTIR, SEM, TEM and DCS analyses validated the successful synthesis of CSR particles. The tensile test findings on the dumbbell-shaped samples show a 51%, 30%, and 218% enhancement in tensile strength, modulus, and toughness for the samples containing 2.5 phr CSR particles and 2 phr zinc oxide nanoparticles, respectively. Furthermore, the lap shear tests revealed that the addition of 3.75 phr CSR particles and 5 phr zinc oxide nanoparticles increased the shear strength to 19.5 MPa. This is 127% higher than the pure epoxy. The TGA data indicated that both additions improved the thermal stability of the pure epoxy. Additionally, the predictions of shear strength, toughness, tensile modulus, and tensile strength by DOE and ANN were very close to the experimental results (R2adj > 0.95 for DOE and MREave < 3.2 for ANN). © The Author(s) 2025.
