A5066605685- Cellular Automata and Applications
- DNA and Biological Computing
- Mineral Processing and Grinding
- Mathematical Dynamics and Fractals
- EEG and Brain-Computer Interfaces
- Artificial Intelligence in Healthcare
- Algorithms and Data Compression
- Non-Invasive Vital Sign Monitoring
- semigroups and automata theory
- Geochemistry and Geologic Mapping
- Soil Geostatistics and Mapping
- Image Processing and 3D Reconstruction
- Geoscience and Mining Technology
- Advanced Data Storage Technologies
- Geophysical Methods and Applications
- Parallel Computing and Optimization Techniques
- Quantum-Dot Cellular Automata
- Modular Robots and Swarm Intelligence
- Medical Image Segmentation Techniques
- Fire Detection and Safety Systems
- Face and Expression Recognition
- Neural Networks and Applications
- Coal Properties and Utilization
- Machine Learning and Data Classification
- Chaos control and synchronization
Birla Institute of Technology, Mesra
2022-2025
Indian Institute of Engineering Science and Technology, Shibpur
2016-2021
This paper presents a study of chaos in one-dimensional cellular automata (CAs). The communication information from one part the system to another has been taken into consideration this study. is formalized as binary relation over set cells. It shown that an equivalence and all cells form single class when automaton (CA) chaotic. However, between two sometimes blocked some CAs by subconfiguration which appears during evolution. blocking analyzed with help de Bruijn graph. We identify types —...
Cardiovascular diseases (CVDs) significantly impact global health, with differences in risk factors and outcomes observed between genders. This research paper aims to identify gender-based for cardiovascular by employing an integration of stratified random sampling statistical machine learning algorithm logistic regression employed on the Cleveland Heart Disease dataset. The dataset comprises various clinical attributes associated heart disease patients. Through feature analysis, sampling,...
Ensuring safety in the mining industry is a critical concern for nation's industrial advancement. Industry 4.0, characterized by integration of advanced technologies, at forefront efforts to enhance practices. Coal seams contain range hydrocarbon gases, predominantly methane, which released significant quantities during operations. Effectively mitigating methane emissions imperative. The inclusion forecasting allows early identification potential emissions, hence results significance...
A significant contribution to the economic growth of a nation comes from mineral industries. Therefore, concentration metallic or nonmetallic minerals in different regions Earth’s crust is important determine. The present paper studies grade and thickness estimation iron coal deposits, respectively, by applying two-dimensional cellular automata (CAs). Krigging popular method for resources. However, krigging results complex mathematical calculations if number sample points increases. Here,...
Abstract Nilpotent cellular automata have the simplest possible dynamics: all initial configurations lead in bounded time into unique fixed point of system. We investigate nilpotency setup one-dimensional non-uniform (NUCA) where different cells may use local rules. There are infinitely many NUCA but only a finite number Changing distribution rules system drastically change dynamics. prove that if available such every periodic leads to nilpotent behavior then so do also eventually...
This work reports realization of close to accurate data migration in Chip Multiprocessors (CMPs). The periodic boundary cellular automata (PBCA) is introduced accept the requests from processor cores competing for a block and perform density classification requesting processors. CA enables identification populated region thereby points area migration. design enriched favor isolation decide on avoid performance loss such
This work reports a unification technique that can form universal platform to emulate any cellular automata (CAs). The paper shows number of non-uniform CAs be mapped into one uniform CA. To show the effectiveness method, three well known applications, such as pseudo random pattern generation, cryptography and classification are chosen where different used for corresponding hardware implementations. Finally, is proposed all these existing use platforms, now implemented in platform.
In the current era of computation, machine learning is most commonly used technique to find out a pattern highly complex datasets. The present paper shows some existing applications, such as stock data mining, undergraduate admission, and breast lesion detection, where different supervised algorithms are classify various patterns. A performance analysis, in terms accuracy, precision, sensitivity, specificity given for all three applications. It observed that support vector (SVM) method good...