Paper Title

ALCOHOL DETECTION AND ENGINE LOCKING SYSTEM TO PREVENT DRUNK DRIVING

Abstract

The Automatic Engine Locking System for Drivers project addresses the issue of drunk driving by implementing a robust and reliable solution. This project employs various hardware components, including Arduino, an alcohol sensor, a DC motor as the engine, GSM technology, a GPS module, and a display module. By combining these technologies, we have developed an automated system that detects alcohol levels in the driver\'s breath and disables the engine if alcohol is detected, ensuring safer roads and Preventing accidents caused by drunk driving.
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Paper Title

INNOVATIVE APPROACHES FOR RAPID IDENTIFICATION AND DETECTION OF IMPURITIES IN INACTIVE PHARMACEUTICAL INGREDIENTS

Abstract

Impurity is not a much-liked word by pharmaceutical and industry people, because they are concerned about quality. Here we discuss various impurities that might be present in API formulations. To fulfill our purpose we have compiled a variety of regulatory authorities’ guidelines (i.e., ICH, WHO, and pharmacopoeias), which serve in endlessly regulating the impurities by various means. As the impurity present in a drug can affect its quality and thus its efficiency, it is therefore crucial to know about impurities. The current article reveals the different terms, regulatory control, and basic techniques (e.g., HPLC, LC-MS, TLC) that will help novices to understand, identify, and quantitatively estimate impurities and that have the advantage of profiling. This article primarily focuses on identification and control of various impurities (i.e., organic, inorganic, and genotoxic). For any of the substances, quality is the prime objective. Because impurities can alter quality, understanding the various impurities will help in producing quality products.
KEYWORDS : analytical methods; genotoxic impurity; inorganic impurity; organic impurity; regulatory requirement in impurity profile

Paper Title

A COMPARATIVE STUDY OF MACHINE LEARNING ALGORITHMS

Abstract

The main objective of human evolution has always been to look for ways to mold the nature to satisfy our needs. A key milestone in this regard is the invention of a machine – called the computer that can complete a task given to it in fraction of time taken by an average human. While that sounds great, the only drawback is that the decision must still be taken by a man who is bound by limitations of the human body. The run to reap the complete benefits has given rise to what is called the Artificial Intelligence. Machine learning is a part of AI, which deals with imparting knowledge to the computer through various related examples. Throughout the years, various machine learning algorithms have been developed each with their own merits and demerits. This paper is a consolidated effort to bring together different ML algorithms like linear regression, KNN (k- nearest neighbours) etc. This research paper discusses the most recent developments in these areas of study and tries to define the best applications for each of those based on previous researches.
KEYWORDS : Machine Learning Algorithms, KNN, Linear Regression, Deep Learning, SVM, RF, Activation functions

Paper Title

IMPACT OF PROTONATION ON THE STRUCTURAL AND ELECTRONIC PROPERTIES OF SINGLE-WALLED CARBON NANOTUBES

Abstract

Strong tube-tube van der Waal attractions that hinder the dissolution of single walled carbon nanotubes (SWNTs) as individuals have been overcome by the direct protonation of the tubes by super acids. The removal of electrons from the SWNT, leading to a fractional positive charge on the carbons in the protonated state, is reversible upon deprotonation. With increasing concentration of the solubilized nanotubes, anion-mediated attractions at lower concentrations and spatial constraints at high concentrations guide the transformation of the SWNT-acid system into a nematic mesophase. Amine-terminated self-assembled monolayers (SAMs) have been shown to selectively adsorb semiconducting single-walled carbon nanotubes (sc-SWNTs). A dissolution model is proposed wherein the solubilized tubes exist as protonated polycarbocations, charge balanced by corresponding conjugate base anions. Previous studies have shown that when deposited by spin coating, the resulting nanotube networks (SWNTnts) can be strongly influenced by the charge state of the amine (primary, secondary, and tertiary). When the amine surfaces were exposed to varying pH solutions, the conductivity and overall quality of the resulting fabricated networks were altered. Finally, differing SWNT solution volumes were used to compensate for adsorption differences and yielded identical SWNTnt densities on the various pH-treated samples to eliminate the influence of network density.
KEYWORDS : single walled carbon nanotubes (SWNTs), nanotube networks, SWNT-acid system, self-assembled monolayers (SAMs).