Konark Institute of Science and Technology (KIST) is a private engineering college in Bhubaneswar, Orissa in India. It was founded by the Vidya Sagar Charitable Trust in 2001. With the approval of the AICTE, KIST was affiliated with Utkal University, Vanivihar, Bhubaneshwar. Later it became affiliated with Biju Patnaik University of Technology in the year 2003–04.
UAV path planning in three-dimensional threat fields requires four conflicting objectives to be satisfied at once: path tortuosity, threat exposure, altitude deviation, and trajectory smoothness. Classical swarm optimizers converge prematurely under dense threats. Structured domain weighting is therefore required. Cross-domain Constraint Clustering with Reinforcement-Guided Multi-Objective Particle Swarm Optimization (XC-RL-MOPSO) is proposed. Q-learning pre-trains a feasible reference trajectory across 2000 episodes. This trajectory biases early swarm search toward low-exposure regions. Four objectives enter Pareto dominance. A fifth, reference adherence, is retained as a convergence diagnostic only. Objectives are clustered into three domains. Safety receives 0.40. Control receives 0.35. Efficiency receives 0.25. Weights remain static. A six-variant ablation is conducted across 15 replicates. Results indicate that domain-clustering removal degrades hypervolume by 21.0
Secure and efficient customer onboarding is paramount for sectors such as banking, insurance, and egovernance. This paper presents an intelligent web-based system for automated identity verification, specifically designed to facilitate the seamless transition from foundational identity (Aadhaar) to functional financial identifiers (Virtual PAN). The proposed framework minimizes manual data entry errors and identity fraud through a robust technology pipeline developed using Python. The system employs Open-Source Computer Vision Library (OpenCV) for image preprocessing, Deep Learning-based Face Recognition for biometric matching between live captures and document portraits, and Optical Character Recognition (OCR) for autonomous demographic data extraction. Simulation results indicate that this integrated approach significantly reduces human error, optimizes processing latency by enabling real-time issuance, and provides a scalable solution for high-security digital authentication environments. The research concludes that such an automated framework is a critical step toward achieving the “paperless and faceless” vision of modern digital governance.
Solid wastes produced from daily fish market is generally thrown in open air in developing countries like India which not only creates air pollution but also contaminates water sources and creates serious health issues. However, the fish scale from these solid wastes can be used as reinforcement to prepare polymeric composites characterized by their low cost, tailored strength, environmental-friendly, and easily availability. The novelty of this work is not only fish-scale powder along with glass-fibre in epoxy is used to prepare a hybrid composite from solid waste. But also, the microanalysis is conducted ANSYS ACP to evaluate the engineering constants along with theory of the proposed material combinations to determine buckling strength. Here, four kind of specimens such as Sample 1 with 100% epoxy, Sample 2 with 50% epoxy and glass fibre each, Sample 3 with 50% epoxy, 45% glass fibre, and 5% fish-scale, and Sample 4 with 95% epoxy and 5% fish-scale are made through hand layup process and fundamental material tests and thermal stability analysis were performed according to ASTM standards. It is witnessed that tensile, flexural and impact strength of samples (Sample 3) by addition of 5% of fish-scale powder is increased by 11.2%, 1.87% and 7.1% than glass-fibre and epoxy composite (Sample 2). However, the hardness is slightly decreased and samples becomes more hydroponic with negligible effect on thermal stability. Further, computational results show buckling strength is also affected by addition of fish-scale powder.
A power electronic device that is becoming more common in medium-voltage and high-power electric systems is the multilayer inverter. Because of their special construction, multilevel inverters can achieve high voltages with lower harmonic content and electromagnetic interference (EMI). By employing several semiconductor switches with the insertion of the lowest voltages in DC, the multi-level inverter produces alternating voltage that is higher power, smoother, and less distorted than the traditional two-level inverter. Multilevel inverter architectures offer the unique benefit of operating at high dc-bus voltages for greater power applications. Switching devices are connected in series to achieve this. As the number of output voltages grows the output voltage waveform's harmonic content decreases. Furthermore, alternating between different voltage levels reduces output voltage harmonics. These days, there are three distinct topologies that may be used: flying capacitor, diode clamped, and cascaded H-bridge. In this project, we will evaluate the THD of these multi-level inverters and examine the various multi-inverter topologies in MATLAB Simulink at a fixed level (i.e., at 11 levels) using various loads, such as a motor load and a series RLC load.
