A Study on Multiresolution based Image Fusion Rules using Intuitionistic Fuzzy Sets

The purpose of image fusion is to create a single image that optimizes the amount of data also highlight the necessary information from two or more source images. There are various types of pixel based image fusion methods such as AVG, Principle Component Analysis (PCA), Intensity Hue Saturation (IHS), Brovey Transform (BT), Discrete Wavelet Transform (DWT) etc. But Stationary wavelet Transform (SWT) based fusion method provides better fusion result with less color distortion. On the other-hand, Intuitionistic Fuzzy Set (IFS) helps to remove the barrier of vagueness and uncertainties from the fused image. That is why; this paper focus several types of fusion methods using SWT with different IFS operations for find the better one that is helpful for human perception also for next generation image processing.

Efficient design in building construction with rubber bearing in medium risk seismicity: case study and assessment

Earthquakes pose tremendous threats to life, property and a country's economy, not least due to their capability of destroying buildings and causing enormous structural damage. The hazard from ground excitations should be properly assessed to mitigate their action on building structures. This study is concerned with medium risk seismic regions. Specifically, the heavily populated capital city Dhaka in Bangladesh has been considered. Recent earthquakes that occurred inside and very close to the city have manifested the city's earthquake sources and vulnerability. Micro-seismicity data supports the existence of at least four earthquake source points in and around Dhaka. The effects of the earthquakes on buildings are studied for this region. Rubber base isolation is selected as an innovative option to lessen seismic loads on buildings. Case studies have been carried out for fixed and isolated based multi-storey buildings. Lead rubber bearing and high damping rubber bearing have been designed and incorporated in building bases. Structural response behaviours have been evaluated through static and dynamic analyses. For the probable severe earthquake, rubber bearing isolation can be a suitable alternative as it mitigates seismic effects, reduces structural responses and provides structural and economic benefits

Web search engine misinformation notifier extension (SEMiNExt):a machine learning based approach during COVID-19 pandemic

Abstract Misinformation such as on coronavirus disease 2019 (COVID-19) drugs, vaccination or presentation of its treatment from untrusted sources have shown dramatic consequences on public health. Authorities have deployed several surveillance tools to detect and slow down the rapid misinformation spread online. Large quantities of unverified information are available online and at present there is no real-time tool available to alert a user about false information during online health inquiries over a web search engine. To bridge this gap, we propose a web search engine misinformation notifier extension (SEMiNExt). Natural language processing (NLP) and machine learning algorithm have been successfully integrated into the extension. This enables SEMiNExt to read the user query from the search bar, classify the veracity of the query and notify the authenticity of the query to the user, all in real-time to prevent the spread of misinformation. Our results show that SEMiNExt under artificial neural network (ANN) works best with an accuracy of 93%, F1-score of 92%, precision of 92% and a recall of 93% when 80% of the data is trained. Moreover, ANN is able to predict with a very high accuracy even for a small training data size. This is very important for an early detection of new misinformation from a small data sample available online that can significantly reduce the spread of misinformation and maximize public health safety. The SEMiNExt approach has introduced the possibility to improve online health management system by showing misinformation notifications in real-time, enabling safer web-based searching on health-related issues