Weldability of Friction Stir Welding using Aluminium Alloy with Pure Copper

Recently many reports on Friction Stir Welding (FSW) of various dissimilar systems such as Aluminium to Copper been reported.FSW of Aluminium, Copper has captured important attention from manufacturing industries, such as Shipbuilding, Automotive, Railway and Aircraft production. Copper and its alloys are widely used in industrial applications due to their excellent electrical & thermal conductivities, good strength, corrosion & fatigue resistance. The aim of present study was analogy of the microstructures and mechanical properties of friction stir welded joint of Aluminium to Copper plates in 4mm thickness

BEP Performance Analysis of Multi-Node Self Encoded Spread Spectrum - Cooperative Diversity in Rayleigh Fading Channel

Self - encoded spread spectrum (SESS) is a novel modulation technique th at acquires its spreading sequence from the random input data stream rather than through the use of the traditional pseudo - noise code generator. It has been incorporated with multi node cooperative diversity systems as a means to combat fading in wireless channels. In this paper we analyze the cooperative SESS for Amplify and Forward CD links ( M SESS - AFCD) and SESS for Decode and forward CD links ( M SESS - DFCD) in Rayleigh fading channels. The BE P expressions are derived in closed form, and the veracity of the analysis is confirmed by numerical calculations that demonstrate excellent agreement with simulation results

Multi User Diversity Evaluation in MIMO HSDPA Downlink Channels

A multiple transmit antenna, single receive antenna (per receiver) downlink channel with limited channel feedback is considered. Given a constraint on the total system-wide channel feedback, the following question is considered: is it preferable to get low-rate feedback from a large number of receivers or to receive high-rate/high-quality feedback from a smaller number of (randomly selected) receivers. Acquiring feedback from many users allows multi-user diversity to be exploited, while highrate feedback allows for very precise selection of beamforming directions. It is shown that systems in which a limited number of users feedback high-rate channel information significantly outperform low-rate/many user systems. The marginal benefit of channel feedback is very significant up to the point where the CSI is essentially perfect

WATER CARRIER

The main aim of our project is to develop a mechanism for easy transportation of more water at a time from water pond, rivers, etc. , to their respective places. Water place a vital role in our daily life. Water is the major requirement in our day to day life, without water we can't do anything. Locally water will be carrying by women's from miles of distances to therehomes. Women's are used to carry the water on their head, while carrying the water on their heads, it causes the major effect on their spinal cord. To overcome this problem for women's we re- implemented this project for easy to carry of water. If they are tired ,While carrying of water they can take the rest under the metal sheet which is placed on the top of the carrier. It is also used to protect the carrier from the sun ray's. The main aim to develop this is, to help the women's who are carrying the water on their heads and to protect them from the injuries and causes from carrying of water on their heads

Predictive Analysis of Tuberculosis Treatment Outcomes Using Machine Learning: A Karnataka TB Data Study at a Scale

Tuberculosis (TB) remains a global health threat, ranking among the leading causes of mortality worldwide. In this context, machine learning (ML) has emerged as a transformative force, providing innovative solutions to the complexities associated with TB treatment.This study explores how machine learning, especially with tabular data, can be used to predict Tuberculosis (TB) treatment outcomes more accurately. It transforms this prediction task into a binary classification problem, generating risk scores from patient data sourced from NIKSHAY, India's national TB control program, which includes over 500,000 patient records. Data preprocessing is a critical component of the study, and the model achieved an recall of 98% and an AUC-ROC score of 0.95 on the validation set, which includes 20,000 patient records.We also explore the use of Natural Language Processing (NLP) for improved model learning. Our results, corroborated by various metrics and ablation studies, validate the effectiveness of our approach. The study concludes by discussing the potential ramifications of our research on TB eradication efforts and proposing potential avenues for future work. This study marks a significant stride in the battle against TB, showcasing the potential of machine learning in healthcare

DMN2SC: Detecting Malicious Nodes with 2-hop Secure Channel Support in Wireless Sensor Networks

Security in wireless sensor networks is critical due to its way of open communication. In this paper we have considered suite of attacks and provided a solution to detect malicious nodes. In literature, many schemes have been proposed to mitigate such attacks but very few detect the malicious nodes effectively and also no single solution detects all attacks. In the proposed approach, each node chooses the parent node for forwarding the packet towards Sink. Each node adds its identity as a routing path marker and encrypts only the bytes added by a node in packet before forwarding to parent. Child node observes the parent, handles acknowledgement from 2-hop distance node and decides the trust on parent based on successful and unsuccessful transactions. Data transmission is divided into multiple rounds of equal time duration. Each node sends a trust value report via multiple paths to Sink at the end of each round. Sink identifies the malicious node based on the number of packets a node participates in forwarding and also based on the trust value report sent from each node for its parent. Each node chooses the parent node at the beginning of a round based on its own observation on parent to recover itself from malicious parent node. With the combination of trust factor, 2-hop acknowledgement and fixed path routing to detect malicious activity, simulation results show that proposed method detect malicious nodes efficiently and early, and also with low percentage of false detection, compared to other recently proposed approaches

One-pot synthesis of multifunctional ZnO nanomaterials: study of superhydrophobicity and UV photosensing property

ZnO nanomaterials are synthesized using one-pot synthesis method. Equimolar solution of Zinc Nitrate hexahydrate (Zn(NO3)(2).6H(2)O) and Hexamethylenetetramine (C6H12N4) is used as a precursor for ZnO formation. Different nanostructures of ZnO are achieved by controlling the pH of the growth solution in the range 2-12 (acidic to alkali). ZnO nanostructures are evaluated for hydrophobic property using static contact angle measurement setup and UV photosensing activity. Surface morphology, structural properties and compositional analysis of ZnO nanostructures are examined by field emission scanning electron microscope (FE-SEM), energy dispersive X-ray analysis (EDX), high-resolution transmission electron microscope (FEG-TEM) and X-ray diffraction (XRD) measurements. Existence of ZnO wurtzite structure is confirmed from XRD study and is analyzed by Rietveld refinement method. Nanomaterials are characterized using Raman spectroscopy which confirms highest oxygen deficiency in ZnO nanorods. The material shows remarkable superhydrophobic and UV photosensing property and hence the name multifunctional. Among all morphologies grown at different pH values, ZnO nanorods show superhydrophobic nature with contact angle more than 170 degrees. Total surface energy value of ZnO nanostructures is calculated using Wendt two-component theory. Different ZnO nanostructures (with variation of pH value) are used to study UV photosensing property. Responsivity and photocurrent show a strong dependence on the morphology of ZnO