Browsing by Author "Singh, P"

Now showing 1 - 8 of 8
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    Advances in Optical Visual Information Security: A Comprehensive Review
    (2024-01) Sachin; Kumar, R; Sakshi; Yadav, R; Reddy, S; Yadav, A; Singh, P
    In the modern era, the secure transmission and storage of information are among the utmost priorities. Optical security protocols have demonstrated significant advantages over digital counterparts, i.e., a high speed, a complex degree of freedom, physical parameters as keys (i.e., phase, wavelength, polarization, quantum properties of photons, multiplexing, etc.) and multi-dimension processing capabilities. This paper provides a comprehensive overview of optical cryptosystems developed over the years. We have also analyzed the trend in the growth of optical image encryption methods since their inception in 1995 based on the data collected from various literature libraries such as Google Scholar, IEEE Library and Science Direct Database. The security algorithms developed in the literature are focused on two major aspects, i.e., symmetric and asymmetric cryptosystems. A summary of state-of-the-art works is described based on these two aspects. Current challenges and future perspectives of the field are also discussed.
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    Asymmetric double-image encryption using twin decomposition in fractional Hartley domain
    (2022) Kumar, J; Singh, P; Yadav, AK
    Twin decomposition, consisting of equal and random modulus decompositions, not only makes a cryptosystem asymmetric but also resists special attack. A new double-image asymmetric crypto system using twin decomposition in fractional Hartley domain is proposed. An input grayscale image, bonded with another grayscale image as its phase mask, is transformed via fractional Hartley transform. Equal modulus decomposition is applied on the resulting image, giving us two inter mediate images. One of them is subjected to another fractional Hartley transform followed by ran dom modulus decomposition, whereas the other serves as the first private key. The application of random modulus decomposition also results in two images: encrypted image and the second private key. During the process of decryption, firstly the encrypted image is combined with second private key and thereafter it is subjected to inverse fractional Hartley transform. The resulting image is then combined with the first private key, and followed by another inverse fractional Hartley trans form, thus recovering the two original images. The proposed cryptosystem is validated for pairs of grayscale images.
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    Covering assisted intuitionistic fuzzy bi‑selection technique for data reduction and its applications
    (2024) Saini, R; Tiwari, A; Nath, A; Singh, P; Maurya, S; Shah, M
    The dimension and size of data is growing rapidly with the extensive applications of computer science and lab based engineering in daily life. Due to availability of vagueness, later uncertainty, redundancy, irrelevancy, and noise, which imposes concerns in building efective learning models. Fuzzy rough set and its extensions have been applied to deal with these issues by various data reduction approaches. However, construction of a model that can cope with all these issues simultaneously is always a challenging task. None of the studies till date has addressed all these issues simultaneously. This paper investigates a method based on the notions of intuitionistic fuzzy (IF) and rough sets to avoid these obstacles simultaneously by putting forward an interesting data reduction technique. To accomplish this task, frstly, a novel IF similarity relation is addressed. Secondly, we establish an IF rough set model on the basis of this similarity relation. Thirdly, an IF granular structure is presented by using the established similarity relation and the lower approximation. Next, the mathematical theorems are used to validate the proposed notions. Then, the importance-degree of the IF granules is employed for redundant size elimination. Further, signifcance-degree-preserved dimensionality reduction is discussed. Hence, simultaneous instance and feature selection for large volume of high-dimensional datasets can be performed to eliminate redundancy and irrelevancy in both dimension and size, where vagueness and later uncertainty are handled with rough and IF sets respectively, whilst noise is tackled with IF granular structure. Thereafter, a comprehensive experiment is carried out over the benchmark datasets to demonstrate the efectiveness of simultaneous feature and data point selection methods. Finally, our proposed methodology aided framework is discussed to enhance the regression performance for IC50 of Antiviral Peptides.
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    Genome sequencing of SARS-CoV-2 omicron variants in Delhi reveals alterations in immunogenic regions in spike glycoprotein
    (2023-10) Shikha, S; Jogi, MK; Jha, R; Kumar, RA; Sah, T; Singh, P
    The SARS-CoV-2 omicron variants keep accumulating a large number of mutations in the spike (S) protein, which contributes to greater transmissibility and arapid rise to dominance within populations. The identification of mutations and their affinity to the cellular angiotensin-converting enzyme-2 (ACE-2) receptor and immune evasion in the Delhi NCR region was under acknowledged. The study identifies some mutations (Y505 reversion, G339H, and R346T/N) in genomes from Delhi, India, and their probable implications for altering the immune response and binding affinity for ACE-2. The spike mutations have influenced the neutralizing activity of antibodies against the omicron variant, which shows partial immune escape. However, researchers are currently exploring various mitigation strategies to tackle the potential decline in efficacy or effectiveness against existing and future variants of SARS-CoV-2. These strategies include modifying vaccines to target specific variants, such as the omicron variant, developing multivalent vaccine formulations, and exploring alternative delivery methods. To address this, it is also necessary to understand the impact of these mutations from a different perspective, especially in terms of alterations in antigenic determinants. In this study, we have done whole genome sequencing (WGS) of SARS-CoV-2 in COVID-19 samples from Delhi, NCR, and analyzed the spike’s mutation with an emphasis on antigenic alterations. The impact of mutation in terms of epitope formation, loss/gain of efficiency, and interaction of epitopes with antibodies has been studied. Some of the mutations or variant genomes seemtobetheprogenitors ofthe upcomingvariants in India. Our analyses suggested that weakening interactions with antibodies may lead to immune resistance in the circulating genomes.
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    Hybrid similarity relation based mutual information for feature selection in intuitionistic fuzzy rough framework and its applications
    (2024) Tiwari, A; Saini, R; Nath, A; Singh, P; Shah, M
    Fuzzy rough entropy established in the notion of fuzzy rough set theory, which has been efectively and efciently applied for feature selection to handle the uncertainty in real-valued datasets. Further, Fuzzy rough mutual information has been presented by integrating information entropy with fuzzy rough set to measure the importance of features. However, none of the methods till date can handle noise, uncertainty and vagueness simultaneously due to both judgement and identifcation, which lead to degrade the overall performances of the learning algorithms with the increment in the number of mixed valued conditional features. In the current study, these issues are tackled by presenting a novel intuitionistic fuzzy (IF) assisted mutual information concept along with IF granular structure. Initially, a hybrid IF similarity relation is introduced. Based on this relation, an IF granular structure is introduced. Then, IF rough conditional and joint entropies are established. Further, mutual information based on these concepts are discussed. Next, mathematical theorems are proved to demonstrate the validity of the given notions. Thereafter, signifcance of the features subset is computed by using this mutual information, and corresponding feature selection is suggested to delete the irrelevant and redundant features. The current approach efectively handles noise and subsequent uncertainty in both nominal and mixed data (including both nominal and category variables). Moreover, comprehensive experimental performances are evaluated on real-valued benchmark datasets to demonstrate the practical validation and efectiveness of the addressed technique. Finally, an application of the proposed method is exhibited to improve the prediction of phospholipidosis positive molecules. RF(h2o) produces the most efective results till date based on our proposed methodology with sensitivity, accuracy, specifcity, MCC, and AUC of 86.7%, 90.1%, 93.0% , 0.808, and 0.922 respectively.
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    Microbial World: Recent Developments in Health, Agriculture and Environmental Sciences
    (2021-03) Dhingra, G; Saxena, A; Nigam, A; Hira, P; Singhvi, N; Anand, S; Kaur, J; Kaur, J; Dua, A; Negi, N; Gupta, V; Sood, U; Kumar, R; Lal, S; Verma, H; Verma, M; Singh, P; Rawat, C; Tripathi, C; Talwar, C; Nagar, S; Mahato, N; Om Prakash; Singh, M; Kuhad, R.C.
    An Annual Conference Organized by Association of Microbiologists of India and Indian Network for Soil Contamination Research.
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    Recent Advancements in the Field of Chitosan/Cellulose-Based Nanocomposites for Maximizing Arsenic Removal from Aqueous Environment
    (2024-09) Chauhan, K; Singh, P; Sen, K; Singhal, R; Thakur, V
    Water remediation, acknowledged as a significant scientific topic, guarantees the safety of drinking water, considering the diverse range of pollutants that can contaminate it. Among these pollutants, arsenic stands out as a particularly severe threat to human health, significantly compromising the overall quality of life. Despite widespread awareness of the harmful effects of arsenic poisoning, there remains a scarcity of literature on the utilization of biobased polymers as sustainable alternatives for comprehensive arsenic removal in practical concern. Cellulose and chitosan, two of the most prevalent biopolymers in nature, provide a wide range of potential benefits in cutting-edge industries, including water remediation. Nanocomposites derived from cellulose and chitosan offer numerous advantages over their larger equivalents, including high chelating properties, cost-effective production, strength, integrity during usage, and the potential to close the recycling loop. Within the sphere of arsenic remediation, this Review outlines the selection criteria for novel cellulose/chitosan-nanocomposites, such as scalability in synthesis, complete arsenic removal, and recyclability for technical significance. Especially, it aims to give an overview of the historical development of research in cellulose and chitosan, techniques for enhancing their performance, the current state of the art of the field, and the mechanisms underlying the adsorption of arsenic using cellulose/chitosan nanocomposites. Additionally, it extensively discusses the impact of shape and size on adsorbent efficiency, highlighting the crucial role of physical characteristics in optimizing performance for practical applications. Furthermore, this Review addresses regeneration, reuse, and future prospects for chitosan/cellulose-nanocomposites, which bear practical relevance. Therefore, this Review underscores the significant research gap and offers insights into refining the structural features of adsorbents to improve total inorganic arsenic removal, thereby facilitating the transition of green-material-based technology into operational use.
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    Ydj1 interaction at nucleotide-binding-domain of yeast Ssa1 impacts Hsp90 collaboration andclient maturation
    (2022-11) Gaur, D; Kumar, N; Ghosh, A; Singh, P; Kumar, P; Guleria, J; Kaur, S; Malik, N
    Hsp90constitutes one of the major chaperone machinery in the cell. The Hsp70 assists Hsp90inits client maturation though the underlying basis of the Hsp70 role remains to be explored. In the present study, using S. cerevisiae strain expressing Ssa1 as sole Ssa Hsp70, weidentified novel mutations in the nucleotide-binding domain of yeast Ssa1 Hsp70 (Ssa1-T175N andSsa1-D158N)that adversely affect the maturation of Hsp90 clients v-Src andSte11. The identified Ssa1 amino acids critical for Hsp90 function were also found to be conserved across species such as in E.coli DnaK and the constitutive Hsp70 isoform (HspA8) in humans. These mutations are distal to the C-terminus of Hsp70, that primarily mediates Hsp90 interaction through the bridge protein Sti1, and proximal to Ydj1 (Hsp40 co chaperone of Hsp70 family) binding region. Intriguingly, we found that the bridge protein Sti1 is critical for cellular viability in cells expressing Ssa1-T175N (A1-T175N) or Ssa1 D158N(A1-D158N)assoleSsaHsp70.Thegrowthdefectwasspecific forsti1Δ,as deletion of none of the other Hsp90 co-chaperones showed lethality in A1-T175N or A1-D158N. Mass-spectrometry based whole proteome analysis of A1-T175N cells lacking Sti1 showed an altered abundance of various kinases and transcription factors suggesting compromised Hsp90activity. Further proteomic analysis showed that pathways involved in signaling, sig nal transduction, and protein phosphorylation are markedly downregulated in the A1-T175N upon repressing Sti1 expression using doxycycline regulatable promoter. In contrast to Ssa1, the homologous mutations in Ssa4 (Ssa4-T175N/D158N), the stress inducible Hsp70 isoform, supported cell growth even in the absence of Sti1. Overall, our data suggest that Ydj1 competes with Hsp90 for binding to Hsp70, and thus regulates Hsp90 interaction with the nucleotide-binding domain of Hsp70. The study thus provides new insight into the Hsp70-mediated regulation of Hsp90 and broadens our understanding of the intricate com plexities of the Hsp70-Hsp90 network.