This study explores the use of a natural colouring method on silk strands. Before and after dyeing, the chemical composition changes in silk yarn are inspected using a Fourier-Transform Infrared Spectroscopy (FTIR) study. The outcomes showed that colourants and fragrances could be introduced to silk yarns without compromising their basic assembly. ...

By M. Sharmila, R. Divya, A. Saniya, C. Prakash

This research analyses the bioactive Components of Grona Triflora, a medicinal plant that has potential health benefits, and its application in textile finishing to enhance fabric functionality and property. Grona Triflora was purified, dried, and ground into a powdered material for extraction using methanol, ethanol, and distilled water. The extra...

By A. Saniya, R. Divya, M. Sharmila, C. Prakash

This paper presents a comprehensive investigation into the seismic performance of a G+5 reinforced concrete spaceframe subjected to pushover analysis. The analysis incorporates the critical influence of soil-structure interaction on varying slope inclinations. A nonlinear static pushover method is utilized to examine the lateral loading streng...

By Tushar Golait, Neeraj Tiwari, Manjeet Singh Hora

With the rapid advancement in electric vehicle (EV) technology, efficient battery management has become crucial for enhancing performance, safety, and longevity. This research integrates Internet of Things (IoT) and artificial intelligence (AI) technology to provide a revolutionary solution to battery management in electric vehicles. Our suggested ...

By R. Ramya, V. Ramya, J. Jaganpradeep, M. Balamurugan, P. Murugesan

Arterial Blood Gas (ABG) analysis is an important diagnostic tool in intensive care unit (ICU) settings that provides valuable information about the patient's respiratory and metabolic status. However, in the absence of predictive information, when testing is over-utilized or not planned, it can cause discomfort to the patient, costs to the healthc...

By S. Ramadoss, A. Kumaravel

Accurate prediction of stock market trends remains a challenging task due to high volatility, non-linearity, and the dynamic nature of financial time series data. Conventional statistical and machine learning typically do not provide consistent performance due to the fixed hyperparameter settings and the inability to adapt to a shifting market situ...

By N. Subalakshmi, M. Jeyakarthic, V. Mohanaselvam

Emerging economies have a dynamic and challenging business environment, which requires entrepreneurial marketing and innovation capabilities of the high-tech startups. Such startups are usually faced with issues of lack of resources, regulation and lack of proper infrastructure. In this regard, it is important to combine entrepreneurial marketing p...

By Jainish Roy, Rajesh Sehgal

Nanomaterials have distinct physicochemical characteristics of high surface area, controllable surface chemistry, and size-dependent reactivity, which can be used to fine-tune industrial chemical reactions to maximize efficiency and sustainability. The paper examines the incorporation of the following nanomaterials, namely carbon nanotubes, graphen...

By Sandeep Soni, Rajvir Saini

Micro-expressions (MEs) are involuntary facial expressions, short-lived (usually between 1/5 and 1/25 seconds), and important in the application of security, psychological tests, and forensics. The MEs are however difficult to identify because it occur quickly and also involve little movement of the muscles. The paper presents an Enhanced Micro-Exp...

By P. Surekha, P. Vidya Sagar, G. Ramesh

To solve the problems of traditional Apriori algorithm in power marketing big data processing, such as candidate item set redundancy, low single-machine computing efficiency, and difficulty in adapting to multi-dimensional time series data, this study proposes an improved Apriori algorithm that integrates Resilient Distributed Dataset (RDD) distrib...

By Fan Pan, Lingen Zhou, Lu Gan, Wei Kang, Xiaolei Li