Govindammal Aditanar College for Women

Uncertain mathematical systems frequently involve ambiguous graph relationships, incomplete connectivity structures, nonlinear uncertainty propagation, and dynamically evolving graph interactions that cannot be effectively represented using classical deterministic graph theory. To address these limitations, this research proposed a hybrid Fuzzy-Neuromorphic Graph Framework (FNGF) integrating fuzzy graph theory, adaptive neuromorphic spike propagation, entropy-aware graph optimization, and spectral graph stability analysis within a unified mathematical architecture. The proposed framework incorporates adaptive fuzzy membership modeling, spike-driven graph learning, synaptic graph optimization, and entropy-guided graph sparsification mechanisms for intelligent uncertainty-aware graph computation. Experimental evaluations were conducted using 5000 synthetically generated uncertain graph instances under varying graph perturbation levels and uncertainty densities. The proposed framework achieved uncertainty classification accuracies of 97.82%, 94.12%, and 90.37% under low, medium, and high graph noise environments, respectively. Furthermore, the framework demonstrated 95.84\% graph stability prediction accuracy, approximately 60.29% entropy reduction, and nearly 79\% reduction in graph computational energy consumption compared to conventional graph neural systems. The entropy-aware graph pruning mechanism significantly improved graph sparsification and graph robustness against topological perturbations, while sparse spike-driven graph propagation substantially enhanced adaptive convergence efficiency. The proposed framework establishes a mathematically rigorous, scalable, interpretable, and energy-efficient intelligent graph architecture suitable for future uncertain intelligent systems, adaptive optimization environments, neuromorphic communication systems, and large-scale uncertainty-aware computational networks.

The concepts of k-product cordial labeling and edge product cordial labeling were introduced in 2012 and further explored by various researchers. Building on these ideas, we define a new concept called ‘edge k-product cordial labeling’ as follows: For a graph G=(V(G),E(G)), which does not have isolated vertices, an edge labeling f:E(G)→0,1,…,k−1, where k≥2 is an integer, is said to be an edge k-product cordial labeling of G if it induces a vertex labeling f*:V(G)→0,1,…,k−1 defined by f*(v)=∏uv∈E(G)f(uv)(modk), which satisfies ef(i)−ef(j)≤1 and vf*(i)−vf*(j)≤1 for i,j∈0,1,…,k−1, where ef(i) and vf*(i) denote the number of edges and vertices, respectively, having label i for i=0,1,…,k−1. In this paper, we study the edge k-product cordial behavior of trees, a comet, and a double comet.

Data Hiding (DH) is a widely distributed method to conceal private data through the internet. Hiding data in a Moving Object (MO) in the video has sought attention due to the deficiency of human visual structure. The existing Exploiting Modification Direction (EMD) technology faces a large amount of distortion due to the even distribution of DH. This paper proposes a Generalized Exploiting Modification Direction (GEMD) by splitting a video into compressed frames and then the frames are separated into MO. Each MO is distinguished using Kalman technique by analyzing the first and next frames. The GEMD is applied separately in each MO by interpolating the image using matching algorithm. In order to reduce the mismatch problem out of boundary pixels and error rates are considered. The proposed DH algorithm is evaluated using PETS 2009 data set. Experimental results have demonstrated that the proposed GEMD algorithm hiding data in each MO improves the capacity and image quality over the existing methods.

IoT allows the devices to transfer data so as to provide domination for users to make the process easy. The fusion of IoT with VR and AR plays a predominant role in the invention over multiple areas. In this paper, a detailed survey of VR and AR technique with the recent existing technique with IoT is given. The VR existing work are sued the field of VR hardware faces the issues in the cross platform, kitchen aid module advancement using VR, VR broad casting, structure-from-motion (SFM) VR for motion analysis. While AR existing work concentrates in the area of game play, e-commers, robotics and automation systems (RAS) training tool, robot operation in the health care, tourism and education. Its application in IoT with system architecture in the real time scenario is discussed.

Abstract Marine algae possess abundant reserves of bioactive compounds that can host secondary metabolites exhibiting both structural and biological activity. In our present study, the aqueous, ethanol, methanol, and chloroform extract of seaweed such as Codium fragile and Turbinaria conoideswas employed to determine the phytochemical, GC-MS, antioxidant, and larvicidal activity. The phytochemical compounds showed C. fragile and T. conoides ethanolic extract revealed the existence of fourteen numbers of compounds compared to the others. The GC-MS analysis was performed on the ethanolic extract of C fragile and T. conoidesshowed the presence of each of twenty different compounds. C. fragile of Hexadecanoic Acid (27.79%), 4-Methanocycloocta[d]Pyridaz (7.39%), 1,1-Dimethoxy-2-Hepten-7-Al (7.04 %) and Octadecanoic Acid, (5.9%). The T. conaids of Dibutyl phthalate (69.56%), 1,2-Benzenedicarboxylic acid (14.01%) and Phthalic acid (2.58 %) were present as the major constituent with the highest area percentage. The antioxidant activity of different solvents the T. conoides ethanolic extract was found to have the highest DPPH (81.48 ± 1.0%), ABTS (88.29±1.0%) and Hydroxyl radical scavenging (86.51±1.0%) activity followed by other solvent extracts. The chloroform extract of C fragile and T. conoides showed effective Cx. quinquefasciatus larvicidal activity. Therefore, the bioactive substances derived from the ethanolic extracts could be used for the antioxidant and larvicidal activity of chloroform extract which will overcome the synthetic insecticides negative impact on the environment. The seaweed possesses the potential to serve as a promising alternative source for controlling mosquitoes due to its larvicidal properties.