Artificial intelligence is gaining ground in several application areas, including biometric authentication. However, several limitations and shortcomings of the learning algorithms are applied to make such systems intelligent. One of the most prominent limitations is the need for more rationality and understanding of the decisions made by the algorithms, which makes these systems vulnerable to intruder attacks. In the case of fingerprint spoofing, it is crucial to understand the reasoning behind the classifier's decisions. To address this limitation, a robust convolutional neural network (CNN) with Gradient-Weighted Class Activation Mapping (GradCAM) is proposed for detecting fingerprint spoofing attacks. Visual explanations are generated by applying GradCAM on the fused CNN layers rather than the last layer, thus improving the interpretability of images. Additionally, softmax classifier scores are subjected to threshold optimization to compute evaluation metrics, including accuracy, False Acceptance Rate (FAR), and False Rejection Rate (FRR), across predefined splits and multiple folds. The explanations generated are subjected to verbal explanations using another popular explainable framework, i.e. Local Interpretable Model-Agnostic Explanations (LIME). The framework is further validated by comparing it with various deep CNN frameworks, such as ResNet-18 and EfficientNet-v2, on different benchmarks of the LivDet 2013 datasets, which indicate its superiority over state-of-the-art approaches.
Piezoelectric energy harvesters (PEHs) have significant potential to provide a sustainable solution for low-grade energy harvesting and battery-less powering systems from physiological monitoring to internet-of-things applications. To access the performance of devices and the suitability of the material, figure-of-merit (FOM) are investigated. From an application perspective, lead-free ferroelectric materials with high figures of merit require enhancements in their ferroic functionalities. In this study, a balanced combination of properties is realized in BiFeO3-BaTiO3 (BF-BT) ceramics through microwave sintering (MS) and precise La3+ doping. This approach leverages the synergistic effects of optimizing grain size to enhance the electrostrictive coefficient and stabilizing the domain orientation via polar nanoregions (PNRs), resulting in outstanding electrical properties, including a high TC = 502 degrees C, d33 = 191 pC/N, and FOM = 5888 x 10-15 m2/N. These findings highlight the potential of MSengineered BF-BT ceramics to meet the demands of advanced PEHs, opening new possibilities for creating wireless sensors which are self-powered and capable of operating in high-temperature surroundings.
This study investigates the modal characteristics of jointed plain concrete pavement (JPCP) systems resting on a two-parameter Pasternak foundation. The work addresses gaps in understanding the influence of joint stiffness and subgrade shear coupling on pavement vibration behaviour. A novel two-dimensional finite element framework is developed by incorporating discrete stiffness modelling of dowel and tie bars to realistically simulate inter-slab load transfer. The Pasternak foundation formulation accounts for both vertical stiffness and shear interaction within the subgrade, enabling improved representation of soil–structure interaction. The pavement slabs are modelled using Mindlin–Reissner plate theory with six degrees of freedom per node, allowing accurate capture of bending, shear, and rotational effects. Model accuracy is verified through mesh convergence analysis and validation against established analytical benchmarks. The numerical results identify three distinct vibration regimes. Low-frequency modes (< 1 Hz) are governed primarily by foundation properties. Intermediate bending-dominated modes (12–42 Hz) show a reduction of up to 37.9
In recent years, the exploration of magnesium (Mg) alloys has gained momentum in the pursuit of developing biodegradable implants. However, its rapid degradation in physiological environments poses significant challenges, leading to premature mechanical failure and tissue damage. While several chemical coating techniques have been attempted, in-situ mineralization of Ca-P rich apatite has shown potential to overcome the limitations of ex-situ coatings. This study investigated the influence of surface topography resulting from different wire electric discharge settings, Low Discharge Rate (LDR) and High Discharge Rate (HDR), towards in-situ apatite mineralization and anchoring on Mg alloys during in-vitro and in-vivo conditions. The observed apatite mineralization on the LDR-Mg sample demonstrated a dense microflower-shaped structure, closely resembling the ideal Hydroxyapatite (HA) configuration with a Ca/P ratio of 1.60. Notably, the apatite mineralization on the LDR-Mg sample significantly suppressed the corrosion current density (Icorr). This resulted in a 1.6 mm/year corrosion rate with corrosion inhibition efficiency (ηc) of 78 % after 7 days of immersion in SBF. During in vitro degradation, the LDR-Mg sample maintained the lowest hydrogen evolution rate, relative weight changes, and pH variations compared to Mg and HDR-Mg samples. After skin implantation up to 10 weeks, the LDR-Mg samples indicated enhanced implant-tissue integration followed by a marginal volume loss of 11 %. The H&E staining analysis and serum indices reveal that LDR-Mg samples exhibit the highest biocompatibility, with well-preserved tissue architecture and minimal organ damage. The findings highlight the potential of spark tuning on Mg alloys for stable in-situ apatite mineralization, enhancing anticorrosion performance and bioactivity for full-scale clinical applications.
In the present paper, we provide an explicit construction for generators of a λ-constacyclic code 𝒞 of arbitrary length ℓ over a finite chain ring(FCR) ℛ in terms of certain minimum degree polynomials of the ring ℛ[x]/ ⟨ x^ℓ-λ⟩. Moreover, the proposed construction achieves the minimum possible number of generators. We prove certain properties of this set of generators, using which we obtain a minimal spanning set of 𝒞. We also obtain that the rank of 𝒞 is ℓ-n_0, where n_0 is the degree of the minimal degree polynomial in 𝒞. Finally, we derive necessary and sufficient conditions under which an arbitrary length λ-constacyclic code 𝒞 over ℛ is Maximum Hamming Distance with respect to Rank(MHDR) as well as Maximum Distance Separable(MDS) in terms of a torsion code of 𝒞 over the residue field 𝔽_q of ℛ. We further determine the exact values for n_0 for which 𝒞 over ℛ is MHDR.
