A Survey on Security and Privacy Challenges in State-of-the-Art Microfluidic Biochips
D Gountia, RR Behera, S Tripathy… - IETE Technical …, 2024 - Taylor & Francis
Microfluidic-based biochip is a prominent class of lab-on-a-chip systems for the healthcare,
biomedical, and biochemical industries, and was recently used for the detection of the Covid …
biomedical, and biochemical industries, and was recently used for the detection of the Covid …
An experimental approach to detect forest fire using machine learning mathematical models and IoT
Fire outbreak is a common issue which is occurring worldwide, causing significant damage
to both nature and human life. Recently, vision-based fire detection systems have gained …
to both nature and human life. Recently, vision-based fire detection systems have gained …
SMS Fraud detection using machine learning
SR Prusty, B Sainath, SK Jayasingh… - … Systems: Proceedings of …, 2022 - Springer
The term SMS stands for short message service. It is a message networking method that
uses smartphones and cell phones. It is a text messaging system that lets smart phones to …
uses smartphones and cell phones. It is a text messaging system that lets smart phones to …
Smart weather prediction using machine learning
SK Jayasingh, JK Mantri, S Pradhan - Intelligent Systems: Proceedings of …, 2022 - Springer
Prediction of weather is a challenging task for all researchers of weather and the
meteorological department. Many techniques are evolved in time for the prediction of …
meteorological department. Many techniques are evolved in time for the prediction of …
A secure fault detection for digital microfluidic biochips
R Ranjan Behera, D Gountia - The Computer Journal, 2024 - academic.oup.com
Among all the modern technological advances, digital microfluidic biochip has been
extending a salient solution to healthcare and bio-laboratories with the pledge of high …
extending a salient solution to healthcare and bio-laboratories with the pledge of high …
Ensemble classifier based predictive model for type-2 diabetes mellitus prediction
BS Ahamed, MS Arya… - Machine learning and …, 2023 - api.taylorfrancis.com
Type-2 Diabetes-Mellitus (T2DM) is a chronic disease that affects many people's day to day
lives [1]. There are various factors involved such as Age, Family History, Pregnancy, Body …
lives [1]. There are various factors involved such as Age, Family History, Pregnancy, Body …
Hybrid Crow Search and RBFNN: A Novel Approach to Medical Data Classification
Abstract The Radial Basis Function Neural Network (RBFNN) is frequently employed in
artificial neural networks for diverse classification tasks, yet it encounters certain limitations …
artificial neural networks for diverse classification tasks, yet it encounters certain limitations …
Advancements in Precision Agriculture: A Machine Learning-Based Approach for Crop Management Optimization
C Senapati, S Senapati, S Swain, KJ Patra… - Sustainable Farming …, 2024 - taylorfrancis.com
In the rapidly evolving landscape of intelligent farming, there has been a transformative shift
toward modernizing traditional agricultural practices by integrating cutting-edge …
toward modernizing traditional agricultural practices by integrating cutting-edge …
Machine Learning Techniques of Weather Forecasting–A Review
J Ghosh, A Bhattacharya - Asian Journal of Environment …, 2023 - public.paper4promo.com
Weather is a particular state of the atmosphere that describes the degrees to which it is hot
or cold, wet or dry, calm or stormy, clear or cloudy. On earth, most weather phenomena …
or cold, wet or dry, calm or stormy, clear or cloudy. On earth, most weather phenomena …
13 AdvancementsPrecision in
C Senapati, S Senapati, S Swain… - Sustainable Farming …, 2024 - books.google.com
Smart farming stands at the forefront of agricultural innovation as shown in Figure 13.1,
marking a transformative era where advanced technologies seamlessly integrate with …
marking a transformative era where advanced technologies seamlessly integrate with …