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
PREDICTION OF TOXIC-METABOLIC DISORDERS AT EMERGENCY CONDITIONS USING MULTI-LABEL CLASSIFICATION IN MACHINE LEARNING
Diagnosing critical conditions like Acute Liver Failure (ALF), Methanol Toxicity (MT), Alcohol Poisoning (AP), and Diabetic Ketoacidosis (DKA) is difficult due to similar symptoms and complex interdependent metabolism, often resulting in delayed and incorrect diagnoses in historic clinical practice. We present a hybrid machine learning framework in...
By S. Ramadoss, A. Kumaravel
INTEGRATING SUSTAINABLE PRACTICES AND AUTOMATION IN MINING ENGINEERING EDUCATION FOR THE MODERN ERA
Sustainable practice and automation in the field of mining engineering are becoming a fundamental component of educating the future engineers to respond to the challenges facing a changing mining industry. As mining operators are increasingly being pressured to utilize more environmentally sustainable practices and to adopt new automation technolog...
By Kamala Kodirova, Ozodbek Nematov, Anastasia Seitasmanova, Sarvinoz Qodirova, Feruza Sapaeva, Fotima Babajanova, Bakhtiyor Polvonov, Abduraim Adilov
A COMPARATIVE STRATIFICATION OF FISH SPECIES USING TRANSFER LEARNING ON PRE-TRAINED DEEP LEARNING NETWORKS JUXTAPOSED WITH SHUFFLERES – A HYBRID DEEP NETWORK CLASSIFIER
The marine ecoculture is an evolving realm that necessitates thorough scrutiny of the diverse species it comprises, along with the explicit identification of the species classes that form, to be crucial for aquaculture and the ecological conservation of fish diversity. The stratification through image classification is a well-studied area of resear...
By R.P. Selvam, R. Devi
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
AI FLEXIBLE WORK AND STRATEGIC HRM DRIVING ORGANIZATIONAL PERFORMANCE
The fast development of digital technologies has transformed the organization and work relations, and the process of the digitalization of Human Resource Management (HRM) has become significant in optimizing the performance of the organization. In this paper, I am going to examine how Artificial Intelligence (AI), flexible work environments, and st...
By E. Pavithra, K. Sathishkumar, G. Kowsalya, M. Ramalingam, Pardaev Jamshid, Jyoti Prasad Kalita, S.D. Vijayakumar
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