Pressure drag is a mechanical force generated by a solid moving object in fluid. This work focuses on the reduction of pressure drag in aircraft. Pressure drag is an unavoidable force which forms as a reaction force to the motion of the aircraft and thereby decreasing its performance. So, the aircraft must put forth a huge extra force to pass through and needs more power to overcome the pressure drag which leads to more fuel consumption and decreasing the aircraft’s efficiency.

The widespread application of thermoplastic polymers in different aspects of industries has motivated researchers and companies to improve and upgrade their forming, joining and assembling processes to overcome their limitations. In this category, friction stir welding (FSW) proposed as an alternative for the traditional joining processes. In this paper, FSW with a threaded cylindrical tool was employed for dissimilar joining of the sheets polyethylene (PE) and polypropylene (PP).

The paper entails the design of an extremely area-efficient binary multiplier chiefly for use in Application Specific Integrated Circuits (ASICs) and embedded systems that rely on minimalistic area-constraints and expenses at the cost of speed. The design of the multiplier core has been based on the Urdhva-Tiryagbhyam (UT) theorem, an ancient simplification technique as described in the Vedic Scripts, for a simplified architecture

Objectives: To study the cost estimation using FFNN (Feed Forward Neural Network) and BPNN (Back Propagation Neural Network). Methods/Statistical Analysis: In proposed work, resource allocation has been done in which cost function has been estimated. The whole simulation is being done using MATLAB 2010a environment. Findings: From the simulation results, it is analysed that using FFNN, 95% of accuracy is achieved. Application/Improvements: With the advent of this technology, the cost of computation, application hosting, proper storage of content and delivery is abridged considerably.