Tootfinder

5G Core Fault Detection and Root Cause Analysis using Machine Learning and Generative AI
Joseph H. R. Isaac, Harish Saradagam, Nallamothu Pardhasaradhi
https://arxiv.org/abs/2508.09152

5G Core Fault Detection and Root Cause Analysis using Machine Learning and Generative AI
With the advent of 5G networks and technologies, ensuring the integrity and performance of packet core traffic is paramount. During network analysis, test files such as Packet Capture (PCAP) files and log files will contain errors if present in the system that must be resolved for better overall network performance, such as connectivity strength and handover quality. Current methods require numerous person-hours to sort out testing results and find the faults. This paper presents a novel AI/ML-…

Evaluation of in vitro antibacterial activity and phytochemical profile of aqueous leaf extract of Asystasia variabilis
R Wijerathna, NAV Asanthi, WD Ratnasooriya, RN Pathirana, NRM Nelumdeniya
https://arxiv.org/abs/2508.19049

Evaluation of in vitro antibacterial activity and phytochemical profile of aqueous leaf extract of Asystasia variabilis
This study evaluated the in vitro antibacterial effect and the phytochemical profile of aqueous extract of fresh mature leaves of Asystasia variabilis, a Sri Lankan indigenous plant, against four common wound infective bacteria (Staphylococcus aureus, Bacillus subtilis, Pseudomonas aeruginosa and Escherichia coli) using Kirby-Bauer disk diffusion test. Gentamicin 10 μg/ disk and distilled water was used as positive and negative controls respectively The study revealed, for the first time, that…