Foggy road conditions present significant challenges for road monitoring systems and autonomous driving, as conventional defogging techniques often fail to accurately recover fine details of road structures, particularly under dense fog conditions, and may introduce undesirable artifacts. Furthermore, these methods typically lack the ability to dynamically adjust transmission maps, leading to imprecise differentiation between foggy and clear areas. To address these limitations, a novel approach to image dehazing is proposed, which combines an entropy-weighted Gaussian Mixture Model (EW-GMM) with Pythagorean fuzzy aggregation (PFA) and a level set refinement technique. The method enhances the performance of existing models by adaptively adjusting the influence of each Gaussian component based on entropy, with greater emphasis placed on regions exhibiting higher uncertainty, thereby enabling more accurate restoration of foggy images. The EW-GMM is further refined using PFA, which integrates fuzzy membership functions with entropy-based weights to improve the distinction between foggy and clear regions. A level set method is subsequently applied to smooth the transmission map, reducing noise and preserving critical image details. This process is guided by an energy functional that accounts for spatial smoothness, entropy-weighted components, and observed pixel intensities, ensuring a more robust and accurate dehazing effect. Experimental results demonstrate that the proposed model outperforms conventional methods in terms of feature similarity, image quality, and cross-correlation, while significantly reducing execution time. The results highlight the efficiency and robustness of the proposed approach, making it a promising solution for real-time image processing applications, particularly in the context of road monitoring and autonomous driving systems.

The impact of artificial hailstones on G300 steel sheets with varying thicknesses has been systematically investigated to evaluate the resulting dent depths. Two distinct methods for producing simulated hailstones were employed: one utilizing polyvinyl alcohol (PVA) adhesive and the other incorporating liquid nitrogen. Comparative analyses of these techniques revealed that the liquid nitrogen method, in conjunction with demineralized water, yielded more accurate results than the PVA adhesive-based method. Experimental findings were cross-referenced with theoretical predictions and finite element simulations, with model accuracy being validated against existing research in the field. The study focused on three hailstone diameters—38mm, 45mm, and 50mm—across various sheet thicknesses. Results indicate that dent depth is primarily influenced by the impact energy, sheet metal thickness, and hailstone diameter. Notably, the momentum of the hailstone plays a critical role, with smaller, higher-momentum hailstones inducing permanent deformations comparable to those of larger, lower-momentum hailstones, even when the impact energies are equivalent. The findings suggest that variations in hailstone momentum can lead to similar deformation patterns across different sizes, emphasizing the importance of momentum in the design of steel sheet materials for enhanced hailstone impact resistance. This study contributes valuable insights for the development of more resilient materials in industries subject to dynamic impact loading, such as automotive and aerospace engineering.

This study investigates the structural response of a hub steering knuckle from a Toyota Camry LE under typical in-service loading conditions, with a focus on material performance comparison. Aluminium alloy A356.0-T6 and grey cast iron were selected as candidate materials for the analysis. A three-dimensional (3D) model of the hub steering knuckle was generated using SolidWorks 2018, while static structural simulations were conducted with ANSYS Workbench R15.0 (2019 version). The factor of safety (FOS) was varied between 2.293 and 15 to account for the diverse operational scenarios. The applied loading conditions were derived from the cumulative forces acting on the four tyres of the vehicle, with a total force of 3938.715 N in the Z-direction. The steering moment was calculated to be 5400 N·mm at a perpendicular distance of 108 mm, while the braking force amounted to 3964.63 N·mm, with a corresponding braking moment of 277,524.73 N·mm, all determined using standard analytical formulas. A solid mesh type was employed for the finite element analysis (FEA), with a blended curvature-based meshing technique applied. The results of the analysis showed that, for A356.0-T6, the maximum equivalent Von Mises stress (VMS), maximum equivalent elastic strain, maximum principal stress, and maximum shear stress were 36.079 MPa, 0.00018393 mm/mm, 44.587 MPa, and 19.871 MPa, respectively. In comparison, grey cast iron exhibited values of 24.016 MPa, 0.00013104 mm/mm, 41.214 MPa, and 18.625 MPa, respectively. The maximum directional deformations along the Z-axis for A356.0-T6 and grey cast iron were 0.010135 mm and 0.007275 mm, respectively. The maximum total deformations were recorded at 0.069036 mm and 0.048725 mm for A356.0-T6 and grey cast iron, respectively. These findings suggest that both materials are suitable for use in hub steering knuckles, with grey cast iron being preferable when impact resistance is a priority, whereas A356.0-T6 is more suitable for applications requiring lightweight and corrosion resistance. The results contribute to the understanding of material selection for automotive components, considering both mechanical performance and operational demands.

The transformation of public services into electronic formats (e-services) has gained significant momentum with the advancement of information and communication technologies, particularly due to the widespread use of the Internet and increasing citizen expectations. This transition has not only enhanced the efficiency of traditional public services but also facilitated new forms of e-governance that promote greater interaction, transparency, accessibility, and accountability between citizens and the state. Within this context, this study seeks to address the question: What are the key factors influencing citizens' satisfaction with e-services? The case of student satisfaction with the e-services provided by Anadolu University in Eskişehir, Turkey, serves as the focal point for the investigation. A survey conducted among 1,000 students from eight faculties and one graduate school at Anadolu University assessed their satisfaction with a variety of e-services, including Anasis, Mergen, Anadolu Mobil, E-Mail, library services, cafeteria services, and others. The collected data were analyzed using a combined methodology that integrated the E-GovQual model and the Importance-Performance Analysis (IPA) method. The E-GovQual model provided a comprehensive framework for evaluating the quality of e-services, allowing for an in-depth understanding of students' perceptions. The IPA method, on the other hand, facilitated the identification of performance gaps in e-service delivery and highlighted areas in need of improvement, based on students' expectations. The findings of the analysis were used to formulate strategic recommendations for decision-makers, students, and researchers. This research contributes to the growing body of knowledge on e-governance and user satisfaction in educational institutions, offering practical insights for optimizing online platforms to better meet student needs and expectations.

This research examines customer relationship management (CRM) systems using multi-criteria decision-making (MCDM) methods, with the intention of selecting the most suitable solution for small companies. The main goal of this research is to make a decision when choosing a CRM system by applying an objective approach. For this purpose, objective criteria were used, and an objective evaluation of the observed CRM systems was conducted. By using the MEREC (MEthod based on the Removal Effects of Criteria) method, the importance of the criteria was determined, while the CORASO (COmpromise Ranking from Alternative SOlutions) method was applied to rank the CRM systems. These methods were combined using a methodology into a hybrid approach. The results of this approach indicate that CRM systems with a higher degree of integration and automation achieved a higher rank, while systems with limited functionalities and longer implementation times received a lower ranking. This analysis confirms the importance of CRM systems in optimizing business processes, improving customer satisfaction, and enhancing marketing activities in companies. The results of the research can assist small companies in making decisions when selecting a CRM system. The contribution of this research is to provide efficient decision-making in the selection of a CRM system, thereby strengthening the companies' operations and improving their performance.

This study investigates the effect of magnesium hydroxide Mg(OH)$_2$ flame retardant treatment on corn stalk fiber and its impact on the properties of fiber asphalt when mixed at a 3% concentration with asphalt. The study examines the changes in fiber aspect ratio and microscopic morphology before and after flame retardant treatment, and explores the underlying mechanisms that influence the basic performance of fiber asphalt. The effects of flame retardant-treated corn stalk fibers on the asphalt binder were assessed using tests such as softening point, penetration, elongation, temperature scanning, and bending beam rheometer. The results indicate that as the concentration of magnesium hydroxide increases, the three main indicators of the fiber asphalt binder first increase and then decrease. The highest softening point (49.8°C) occurred at a concentration of 2%, the highest penetration (7.6mm) at 1%, and the highest elongation (12.7cm) at 1%. The high and low-temperature performance tests show that the fiber asphalt binder made with 1% magnesium hydroxide-treated corn stalk fibers achieves the best balance of both high and low-temperature properties.