STUDY ON NATURAL DYEING OF SILK YARNS USING FERMENTED TURMERIC RHIZOMES WITH THEOBROMA CACAO FRAGRANCE
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
ANTI-DIABETIC AND ANTIMICROBIAL ACTIVITIES OF GRONA TRIFLORA MEDICINAL PLANT
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
NONLINEAR STATIC ANALYSIS OF RCC SPACE FRAME ON SLOPING GROUNDS INCORPORATING SSI
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
BATTERY MANAGEMENT SYSTEM FOR ELECTRIC VEHICLE USING ARTIFICIAL INTELLIGENCE AND IOT TECHNOLOGY
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
EXPLORING ABG IMBALANCES IN ICU PATIENTS USING MACHINE LEARNING SUPERVISED ALGORITHMS
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
PRECISION STOCK MARKET TREND ANALYSIS WITH HYBRID SMOOTH SVM AND WEIGHED VULTURE OPTIMIZATION
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
ENTREPRENEURIAL MARKETING AND INNOVATION CAPABILITIES IN HIGH TECHNOLOGY STARTUPS IN EMERGING ECONOMIES
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
LEVERAGING NANOMATERIALS IN CHEMICAL ENGINEERING TO OPTIMIZE EFFICIENCY AND SUSTAINABILITY ACROSS MODERN INDUSTRIAL PROCESSES
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
RULE-BASED ITERATIVE PREPROCESSING WITH DEEP SIAMESE GRU–BILSTM FOR EFFICIENT DOCUMENT STREAMING
Efficient document streaming requires robust preprocessing and semantic modeling to handle noise, redundancy, and morphological variations in large-scale text data. Existing stemming and document processing techniques often fail to preserve contextual relevance, leading to reduced classification and retrieval performance. In a bid to overcome this ...
By K. Ranjit Kumar, S. Thirumaran
MULTI-OBJECTIVE TOPOLOGY OPTIMIZATION OF 3D PRINTED LATTICE STRUCTURES FOR LIGHTWEIGHT AUTOMOTIVE COMPONENTS
The automotive industry is increasingly focused on developing lightweight, fuel-efficient, and structurally robust components to meet stringent performance and sustainability requirements. Additively manufactured lattice structures have emerged as a promising solution due to their high strength-to-weight ratio, energy absorption capability, and geo...
By Sapna Bawankar, Priya Vij