Comparison and Evaluation of Dimensionality Reduction Techniques for Hyperspectral Data Analysis

Hyperspectral datasets provide explicit ground covers with hundreds of bands. Filtering contiguous hyperspectral datasets potentially discriminates surface features. Therefore, in this study, a number of spectral bands are minimized without losing original information through a process known as dimensionality reduction (DR). Redundant bands portray the fact that neighboring bands are highly correlated, sharing similar information. The benefits of utilizing dimensionality reduction include the ability to slacken the complexity of data during processing and transform original data to remove the correlation among bands. In this paper, two DR methods, principal component analysis (PCA) and minimum noise fraction (MNF), are applied to the Airborne Visible/Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) dataset of Kalaburagi for discussion

Assessment on the Potential of Multispectral and Hyperspectral Datasets for Land Use/Land Cover Classification

Land use/land cover (LULC) is a significant factor which plays a vital role in defining an urban ecosystem. Interpretations of LULC are eased in recent times by utilizing hyperspectral and multispectral datasets obtained from various platforms. An attempt is made to comparatively assess the potentiality of AVIRIS NG with Sentinel 2 data through applied classification techniques for Kalaburagi urban sphere. Spectral responses of both datasets were analyzed to derive reflectance spectra. A standard supervised classification algorithm associated with dimensionality reduction techniques is applied. For performance evaluation, results are validated to check which dataset outperforms well and provides better accuracy

Cloning, Soluble Expression and Purification of High Yield Recombinant hGMCSF in Escherichia coli

Expression of human granulocyte macrophage colony stimulating factor (hGMCSF), a cytokine of therapeutic importance, as a thioredoxin (TRX) fusion has been investigated in Escherichia coli BL21 (DE3) codon plus cells. The expression of this protein was low when cloned under the T7 promoter without any fusion tags. High yield of GMCSF was achieved (~88 mg/L of fermentation broth) in the shake flask when the gene was fused to the E. coli TRX gene. The protein was purified using a single step Ni2+-NTA affinity chromatography and the column bound fusion tag was removed by on-column cleavage with enterokinase. The recombinant hGMCSF was expressed as a soluble and biologically active protein in E. coli, and upon purification, the final yield was ~44 mg/L in shake flask with a specific activity of 2.3 × 108 U/mg. The results of Western blot and RP-HPLC analyses, along with biological activity using the TF-1 cell line, established the identity of the purified hGMCSF. In this paper, we report the highest yield of hGMCSF expressed in E. coli. The bioreactor study shows that the yield of hGMCSF could be easily scalable with a yield of ~400 mg/L, opening up new opportunities for large scale production hGMCSF in E. coli

Proceedings of the International Conference on Frontiers in Desalination, Energy, Environment and Material Sciences for Sustainable Development

This proceeding contains articles on the various ideas of the academic community presented at the International Conference on Frontiers in Desalination, Energy, Environment and Material Sciences for Sustainable Development (FEEMSSD-2023) & Annual Congress of InDA (InDACON-2023) jointly organized by the Madan Mohan Malaviya University of Technology Gorakhpur, KIPM-College of Engineering and Technology Gida Gorakhpur, and Indian Desalination Association, India on 16th-17th March 2023.  FEEMSSD-2023 & InDACON-2023 focuses on addressing issues and concerns related to sustainability in all domains of Energy, Environment, Desalination, and Material Science and attempts to present the research and innovative outputs in a global platform. The conference aims to bring together leading academicians, researchers, technocrats, practitioners, and students to exchange and share their experiences and research outputs in Energy, Environment, Desalination, and Material Science.  Conference Title: International Conference on Frontiers in Desalination, Energy, Environment and Material Sciences for Sustainable Development & Annual Congress of InDAConference Acronyms: FEEMSSD-2023 & InDACON-2023Conference Date: 16th-17th March 2023Conference Location: Madan Mohan Malaviya University of Technology, GorakhpurConference Organizers: Madan Mohan Malaviya University of Technology Gorakhpur, KIPM-College of Engineering and Technology Gida Gorakhpur, and Indian Desalination Association, Indi

Book of Abstracts of the 2nd International Conference on Applied Mathematics and Computational Sciences (ICAMCS-2022)

It is a great privilege for us to present the abstract book of ICAMCS-2022 to the authors and the delegates of the event. We hope that you will find it useful, valuable, aspiring, and inspiring. This book is a record of abstracts of the keynote talks, invited talks, and papers presented by the participants, which indicates the progress and state of development in research at the time of writing the research article. It is an invaluable asset to all researchers. The book provides a permanent record of this asset. Conference Title: 2nd International Conference on Applied Mathematics and Computational SciencesConference Acronym: ICAMCS-2022Conference Date: 12-14 October 2022Conference Organizers: DIT University, Dehradun, IndiaConference Mode: Online (Virtual