Ghani Khan Choudhury Institute of Engineering & Technology

This paper deals with Digital Learning and Training Methodology (DLTM) or Pedagogy (DLTP) in Study of Health Monitoring in RESCO. In a closed room teaching learning process its practically difficult to establish set up for grid connected power system and setup for condition monitoring in all academic institute which can be accessed for all time even from remote end. To overcome this limitation, RESCO model of solar power system connected with grid has been considered. Various health parameters of the system have been captured and stored in cloud from data capturing and transmission unit. Data are made accessible for study by remote end learners as well as data may be accessed from research laboratory. All information is made available for use at all time and can be accessed by computers and smart phone. If needed, researcher can interact with the system. This type of digital learning and training methodology is helpful to provide information, skill and knowledge to big number of learners of any age group as required.

We establish several numerical radius inequalities for bounded linear operators and the product of operators through Orlicz functions. Many inequalities are consequences of using specific Orlicz functions. In particular, it is shown that omega(T) <= n root log [1/2(n-1)e(w)(T-n)+ (1-1/2(n-1))e(parallel to T parallel to n)], <= parallel to T parallel to, for every positive integer n > 1.

We obtain several Berezin number inequalities for the Kronecker product A⊗ B , where A is an n× n complex matrix and B is a bounded linear operator on a reproducing kernel Hilbert space. These results generalize and improve some existing results.

This study aims to formulate effective maintenance strategies for urban roadways by integrating traditional approaches, advanced analytical tools, and contemporary technologies. Among the conventional methods utilized is the Maintenance Prioritization Index (MPI), while the Highway Development and Management Model (HDM-4) represents the modern analytical tool applied. HDM-4 uses comprehensive road network data to assist in route prioritization, particularly through economic assessments such as the Net Present Value to Cost (NPV/Cost) ratio for different pavement segments. Additionally, artificial intelligence (AI)-based techniques were employed using real-time pavement distress data to develop a heat map-based prioritization system for urban roads. The HDM-4 tool was also used to evaluate route conditions both in the present and projected future scenarios. Each method’s performance and applicability for prioritization were independently assessed. The research was conducted on selected urban corridors in Hyderabad, including Ayodhya Crossroad (DA), Ayodhya Crossroad to Dundigal (AD), Miyapur to VNR (MV), VNR to Miyapur (VM), VNR to Gandimaissama (VG), and Gandimaissama to VNR (GV). Furthermore, the relationship between the International Roughness Index (IRI) and the HDM-4 tool’s outputs was analyzed. Findings suggest that AI-based methods offer superior strategic insights for urban road maintenance compared to the MPI approach, while HDM-4 remains a valuable tool for prioritizing routes based on both current and anticipated pavement conditions.

The low lying excitations in odd-odd ^150Pm have been studied through proton induced reaction with an array of five Compton suppressed Clover HPGe and one segmented planar Ge detectors. The relative excitation functions for the observed γ rays have been studied using singles data at two beam energies of 8 MeV and 9 MeV. 16 new γ rays and 15 new levels have been placed in the level scheme of ^150Pm based on γ-γ coincidence data. The relative intensities for the observed γ rays have been determined using total and gated projections. Tentative spin-parity assignments were made to few low lying excitations of ^150Pm, using limited angular distribution data and other information. Lifetimes were estimated for two excited levels in this nucleus using using generalized centroid difference analysis, applied in the nanosecond range, with Ge detectors. Large basis shell model and projected shell model calculation were performed to interpret the experimentally observed levels. The present work indicates 1^- ground state, a 2^- state close to the ground state (∼50 keV) and a low lying 6^- isomeric state in this odd-odd nucleus along with emerging band structures developed with two quasiparticle configurations.