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Improving service quality and customer engagement with marketing intelligence
To succeed, businesses must keep up with the ever-changing technological landscape and constantly introduce new advancements. The rise of digitalization has wholly transformed how companies interact with their customers, presenting both opportunities and challenges. Marketing professionals are inundated with data and need guidance on leveraging it effectively to craft successful marketing strategies. Additionally, the ethical and privacy concerns surrounding the collection and use of customer data make the marketing landscape even more complex. Improving Service Quality and Customer Engagement With Marketing Intelligence is a groundbreaking book that offers a comprehensive solution to these challenges. This book is a must-read for marketing professionals, business owners, and students, providing a practical guide to navigating the digital age. It explores the impact of digitalization on marketing practices. It offers insights into customer behavior, equipping readers with the knowledge and skills needed to thrive in today's competitive market. The book's interdisciplinary approach integrates insights from marketing, technology, data science, and ethics, giving readers a holistic understanding of marketing intelligence. With its timely and practical approach, Improving Service Quality and Customer Engagement With Marketing Intelligence is a valuable resource for anyone seeking to enhance their marketing efforts in the digital age. It features best practices, case studies, and step-by-step guides, empowering readers to make informed decisions prioritizing customer satisfaction and engagement. Reading this book will help you stay ahead of the curve and drive success in today's dynamic marketing landscape by bridging the gap between academia and industry. 2024 by IGI Global. All rights reserved. -
Improving Signal Coverage in Millimeter-Wave Massive MIMO via Efficient Predefined-Time Adaptive Neural NetworkBased Beam Training
This paper proposes an advanced deep learning framework for efficient beam training in millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) systems. To overcome the limitations of conventional beam training approaches such as high overhead, slow adaptation to dynamic environments, and poor scalability, an Improving Signal Coverage in Millimeter Wave Massive MIMO via Efficient Predefined Time Adaptive Neural Network based Beam Training (ISC-MMIMO-EPTANN-BT) model is proposed. The proposed model used deep neural network (DNN) to learn complicated nonlinearities in channel power leakage (CPL) and used an efficient predefined time adaptive neural network (EPTANN) to provide real-time responsiveness and temporal synchronism in beam training. The parameters of the model are also optimized using fire hawk optimization algorithm (FHOA) to get better convergence speed and signal coverage. The proposed technique is executed in MATLAB. The proposed approach attains better performance under successful rate by significantly less beam training overhead and also increases signal coverage based on simulation results. The proposed ISC-MMIMO-EPTANN-BT method attains 26.15%, 21.08%, and 33.75% higher successful rates and 16.32%, 28.94%, and 20.24% lower normalized mean square error compared with existing methods such as deep learning for beam training in millimeter wave massive MIMO schemes (BT-MMIMO-DNN), deep learning for combined feedback and channel prediction in large-scale MIMO systems (CNN-JCS-MMIMO), and triple-refined hybrid-field beam training in mmWave extremely large-scale MIMO (TR-FBT-MIMO), respectively. The ISC-MMIMO-EPTANN-BT technique reduced beam training overhead, enhanced signal coverage, and identified a promising candidate for successful beam training in mmWave massive MIMO schemes. 2025 John Wiley & Sons Ltd. -
Improving Speaker Gender Detection by Combining Pitch and SDC
Gender detection is helpful in various applications, such as speaker and emotion recognition, which helps with online learning, telecom caller identification, etc. This process is also used in speech analysis and initiating human-machine interaction. Gender detection is a complex process but an essential part of the digital world dealing with voice. The proposed approach is to detect gender from a speech by combining acoustic features like shifted delta cepstral (SDC) and pitch. The first step is preprocessing the speech sample to retrieve valid speech data. The second step is to calculate the pitch and SDC for each frame. The multifeature fusion method combines the speech features, and the XGBoost model is applied to detect gender. This approach results in accuracy rates of 99.44 and 99.37% with the help of RAVDESS and TIMIT datasets compared to the pre-defined methods. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024. -
Improving the Accuracy of Cardiovascular Disease Classification Using CardioAugmentNet Technique
Cardiovascular disease is the leading cause of death and mortality worldwide. Thus, early diagnosis of CVDs is crucial since the disease can be managed with optimal care. In the current study, we consider CardioAugmentNet, which is a CNN model augmented with data augmentation strategies for the classification of several cardiovascular pathologies in ECG images. A proposed method was designed to provide a robust algorithm for the detection of irregular heart rhythms, myocardial infarction and other cardiac diseases. The model is trained and tested on the dataset of ECG images from individuals with various prevalent cardiovascular diseases as well as normal hearts. Therefore, the CardioAugmentNet state-of-the-art model classifies different cardiac abnormalities with high accuracy, suggesting that it can be used in clinical practice. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2026. -
Improving the Security of Video Embedding Using the CFP-SPE Method
With the amount of data being transferred on a daily basis, it is becoming increasingly dangerous to save data on the Internet in the face of intruders or hackers. This study paper is one of the most effective ways to transmit information in a secure and confidential manner. The authors previously disclosed a way for embedding a secret video inside a cover video in their prior work. The writers have implemented a number of techniques to incorporate the secret video. The current work improves on the existing approach by including encryption and decryption concepts into the video embedding process. The secret data for either a large or little amount of information is put on the cover video utilising the embedding technique. Our proposed method combines compression, encryption, decryption, and secret information embedding to provide a more secure data transfer. 2022 Karthick Panneerselvam et al. -
Improving Voltage Regulation in High-Power Solar Applications
This paper presents an advanced solar-powered isolated DC-DC converter optimized for high-power applications, with a focus on precise voltage regulation at the output stage. To mitigate high-voltage stresses typically encountered in single-stage DC-DC converters, a Lossless Active Clamp Flyback circuit is integrated, offering soft switching capabilities and regenerative energy features. The proposed topology is designed using low-voltage devices, enhancing overall system efficiency. A hardware prototype rated at 2 kW has been developed to empirically validate the circuit's performance. Additionally, a novel control algorithm is introduced to further optimize the converter's operational characteristics. The proposed converter is benchmarked against existing solutions, highlighting significant improvements in terms of component count, voltage handling, and energy regeneration. The results demonstrate superior efficiency and robustness, making the system highly suitable for high-power renewable energy applications. Through this innovative approach, the converter offers substantial gains in performance and operational feasibility, especially in scenarios demanding high power density and stringent efficiency standards. 2025 IEEE. -
Improvised hand layup fabrication of alkali treated jute epoxy composites: A comparative study of positive and vacuum-assisted compaction
There lie several benefits of using fiber composites which have increased the desire for using these materials in various higher-level applications. They have been widely used in automobile sector, aerospace, sports industry, medical field, and so on. This has created a demand for better manufacturing techniques with cost-effectiveness. This work has been focused on improvising the hand layup procedure. To enhance the properties of the samples prepared by this conventional method, surface treatment was incorporated. Woven jute fiber was chemically treated with KOH under various sizing conditions. Hand layup was carried out for the samples followed by applying pressure considering two different methods; vacuum- assisted compaction and positive compaction. The jute composites prepared by the positive compaction hand layup technique were found to be better than the vacuum-assisted or negative compaction composites for the same set of sizing samples. There is a maximum increase of 32.4% in the tensile strength of treated composites prepared by positive compaction in comparison to untreated samples. On the other hand, the values of all the treated samples showed a reduction in tensile strength with a maximum decrease of 50% than the untreated sample for the negative compaction technique. The Authors, published by EDP Sciences, 2026. -
Improvised Model for Estimation of Cable Bending Stiffness Under Various Slip Regimes
It is well known that the bending response of a stranded cable varies between two extremes, known as a monolithic stickslip state and a completely frictionless loose wire state. While the monolithic state offers the maximum stiffness for the cable, the latter loose wire assembly results in minimum stiffness. The estimation of the actual behavior of the cable under any loading scenario demands a proper modeling that accounts for the interaction of the constituent wires in the intermittent slip stages. During loading, the wires are not only subjected to forces along their axes but are considerably acted upon with radial forces that cause clenching effect. Major research works have focused on the frictional resistance of these radial forces from the Coulomb hypothesis, which contributes to the macro slip phenomenon. As the effect of these radial clenching forces are also significant in causing high contact stresses between wires at the adjacent layers, the need for considering the micro slip at these locations is also vital in the evaluation of the net cable stiffness. In this paper, a novel model is proposed that considers the slip caused by the Coulomb friction hypothesis and the micro slip caused by the Hertzian contact friction for the evaluation of bending stiffness. The variation of the bending stiffness has been evaluated for a single-layered cable as a function of bending curvature at various locations by studying their slip regimes. The predicted results are compared with the published results to establish the refined combined slip hypothesis suggested in this paper. The suggested slip model in this paper has also been accounted with the improvised kinematic relations that consider the wire stretch effect, a parameter that has been neglected in this cable research till date. 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. -
Improvising data security measures using rajan transform
Data security has always been a concern with the use of a large amount of data in our day-to-day life. There are many methods suggested and presented to secure data during the stages of its preprocessing and post-processing. However, many of them are not following the process of Homomorphism. During the study of Fast Fourier transform (FFT), Hadamard transform (HT) and Rajan transform (RT), this research work encountered a method that uses the cyclic, dyadic and graphical inverse properties of data and encrypts them which makes them homomorphic. This paper is targeting to improvise the data security measures using Homomorphism-based Rajan Transform, a method, which can help in securing data while data processing. The proposed methodology works in such a way that the encrypted data is available for processing without decrypting data into the original form. The performance of the proposed method is described by the efficiency of the algorithm, key size, Block size, and no of rounds required to complete the encryption. It has been found, if we take 512 bits of input data to get 512-bit ciphertext, it takes 9 rounds and generates a 4608-bit key. 2021 Taylor's University. All rights reserved. -
Improvized machine learning model for extracting building footprints from collapsed images using high-resolution remote sensing images
We propose the development of a robust Enhanced U-Net framework for detecting building objects in images compromised by collapse. Traditional approaches often struggle to identify smaller buildings obstructed by taller structures, trees, or cloud coverage. However, recent advancements in machine learning algorithms present promising opportunities to address these challenges and improve the accuracy of building object detection and damage assessment. The proposed method employs the Siamese U-Net framework, enhanced with novel machine learning algorithms to overcome limitations in existing methodologies and increase the accuracy and reliability of damage assessment, even in complex scenarios. By using augmented satellite images during testing and lowering the building threshold value, our model can accurately predict damaged buildings and retrieve the footprints of smaller structures. The results of this research will advance image analysis techniques, especially in scenarios where collapsed structures pose significant identification and damage assessment challenges. This will be invaluable for government disaster management agencies, insurance companies, and other related organizations. 2025 World Scientific Publishing Company. -
Impulse noise recuperation from grayscale and medical images using supervised curve fitting linear regression and mean filter
Acquisition of images from electronic devices or Transmission of the image through any medium will cause an additional commotion. This study aims to investigate a framework for eliminating impulse noise from grayscale and medical images by utilizing linear regression and a mean filter. Linear regression is a supervised machine learning algorithm that computes the value of a dependent variable based on an independent variable. The value of the recuperating pixel is measured using a curve-fitting, direction-based linear regression approach or applying a mean filter to the noise-free pixels. The efficiency of the proposed technique experiments with benchmark test images and the images of the USC-SIPI and TESTIMAGES data sets. Peak signal-to-noise ratio (PSNR) and structural similarity index metrics (SSIM) are determined to prove the performance of the proposed method. The results, when compared with the seven recent state-of-the-art techniques, show the superiority of the proposed method in terms of visual quality and accuracy. The proposed model achieves an average PSNR value of 65.21dB and an SSIM value of 0.999 for the reconstruction of medical images, proving its accuracy and efficiency. The impulse noise restoration process helps the radiologist get a clear visual clarity of the medical image for diagnosis purposes. 2022 Institute of Advanced Engineering and Science. All rights reserved. -
In search for FPI trail in blue-chip Indian bourse during a phase of rehabilitation- An investigative study /
Asian Journal of Management, Vol.8, Issue 1, pp.107-111, ISSN: 0976-495X (Print), 2321-5763 (Online). -
In search of radio emission from exoplanets: GMRT observations of the binary system HD 41004
This paper reports Giant Metrewave Radio Telescope (GMRT) observations of the binary system HD 41004 that are among the deepest images ever obtained at 150 and 400 MHz in the search for radio emission from exoplanets. The HD 41004 binary system consists of a K1 V primary star and an M2 V secondary; both stars are host to a massive planet or brown dwarf. Analogous to planets in our Solar system that emit at radio wavelengths due to their strong magnetic fields, one or both of the planet or brown dwarf in the HD 41004 binary system are also thought to be sources of radio emission. Various models predict HD 41004Bb to have one of the largest expected flux densities at 150 MHz. The observations at 150 MHz cover almost the entire orbital period of HD 41004Bb, and about 20percent of the orbit is covered at 400 MHz. We do not detect radio emission, setting 3? limits of 1.8 mJy at 150 MHz and 0.12 mJy at 400 MHz. We also discuss some of the possible reasons why no radio emission was detected from the HD 41004 binary system. 2020 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society. -
IN SEMICONDUCTOR MEDIA CAUSED BY DYNAMIC LOADING THROUGH MEMORY EFFECTS AND NONLOCAL FRAMEWORKS
We investigate a novel meticulous heat transfer model to capture the photo-thermal-elastic interactions efficiently inside a nonlocalized semiconductor material affected from a dynamic thermal loading. For the purpose of apprehending memory and nonlocal effects during complex diffusion processes inside the semiconductor, the Atangana-Baleanu fractional derivative is established on the linearized coupled thermoelastic theory which involves thermal displacement gradient and temperature gradient among the constitutive variables. Laplace transform methodology is acquired for solving the problem. Later on, a suitable algorithm of numerical inversion of the Laplace transform is employed for achieving the computational results in physical domain. As per the graphical results, conclusions about the influences of significant parameters such as fractional parameter, photo-generated carrier life-span and the velocity of dynamic heat source on the dimensionless physical fields like temperature, displacement, stress and carrier density are constructed. Further, the utility of the current advanced heat transfer model is established by comparing the graphical results of physical fields under the current heat transfer theory with the old developed theories of heat transfer models having two phase lags and single phase lag parameter. All the graphical results are evaluated against distinct values of depth of the semiconductor media. We believe that this fine study will support researchers for obtaining promising and optimum results of real world problems where the photo-thermal effects inside the semiconductor are taken into account. 2026 The Authors, under license to MSP (Mathematical Sciences Publishers). -
In silico analysis of NHP2 membrane protein, a novel vaccine candidate present in the RD7 region of Mycobacterium tuberculosis
Mycobacterium tuberculosis, the etiological agent of tuberculosis, is one of the trickiest pathogens. We have only a few protective shields, like the BCG vaccine against the pathogen, which itself has poor efficacy in preventing adult tuberculosis. Even though different vaccine trials for an alternative vaccine have been conducted, those studies have not shown much promising results. In the current study, advanced computational technology was used to study the potential of a novel hypothetical mycobacterial protein, identified by subtractive hybridization, to be a vaccine candidate. NHP2 (Novel Hypothetical Protein 2), housed in the RD7 region of the clinical strains of M. tuberculosis, was studied for its physical, chemical, immunological and structural properties using different computational tools. PFAM studies and Gene ontology studies depicted NHP2 protein to be functionally active with a possible antibiotic binding domain too. Different computational tools used to assess the toxicity, allergenicity and antigenicity of the protein indicated its antigenic nature. Immune Epitope Database (IEDB) tools were used to study the T and B cell determinants of the protein. The 3D structure of the protein was designed, refined and authenticated using bioinformatics tools. The validated tertiary structure of theprotein was docked against the TLR3 immune receptor to study the binding affinity and docking scores. Molecular dynamic simulation of the protein-protein complex formed were studied. NHP2 was found to activate host immune response against tubercle bacillus and could be explored as a potential vaccine in the fight against tuberculosis. 2023, The Author(s), under exclusive licence to Plant Science and Biodiversity Centre, Slovak Academy of Sciences (SAS), Institute of Zoology, Slovak Academy of Sciences (SAS), Institute of Molecular Biology, Slovak Academy of Sciences (SAS). -
In Silico Analysis of the Apoptotic and HPV Inhibitory Roles of Some Selected Phytochemicals Detected from the Rhizomes of Greater Cardamom
Occurrence of cervical cancer, caused due to persistent human papilloma virus (HPV) infection, is common in women of developing countries. As the conventional treatments are expensive and associated with severe side effects, there is a need to find safer alternatives, which is affordable and less toxic to the healthy human cells. Present study aimed to evaluate the anti-HPV and apoptotic potential of four compounds from the greater cardamom (Amomum subulatum Roxb. var. Golsey), namely rhein, phytosphingosine, n-hexadecenoic acid and coronarin E. Their anti-HPV and apoptotic potential were studied against viral E6, E7 and few anti-apoptotic proteins of host cell (BCL2, XIAP, LIVIN) by in silico docking technique. Phytochemicals from the plant extract were analysed and identified by LC/MS and GC/MS. Involvement of the target proteins in various biological pathways was determined through KEGG. Structural optimization of the three-dimensional structures of the ligands (four phytochemicals and control drug) was done by Avogadro1.1. Receptor protein models were built using ProMod3 and other advanced tools. Pharmacophore modelling of the selected phytochemicals was performed in ZINCPharmer. Swiss ADME studies were undertaken to determine drug likeness. The ligands and proteins were digitally docked in DockThor docking program. Protein flexibility-molecular dynamic simulation helped to study proteinligand stability in real time. Finally, the correlation of evaluated molecules was studied by the use of principal component analysis (PCA) based on the docking scores. All the ligands were found to possess apoptotic and anti-cancer activities and did not violate Lipinsky criteria. n-Hexadecanoic acid and its analogues showed maximum efficacy against the target proteins. All the proteinligand interactions were found to be stable. The uncommon phytochemicals identified from rhizomes of greater cardamom have anti-cancer, apoptotic and HPV inhibitory potentials as analysed by docking and other in silico studies, which can be utilized in drug development after proper experimental validation. 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature. -
In Silico Identification of 1-DTP Inhibitors of Corynebacterium diphtheriae Using Phytochemicals from Andrographis paniculata
A number of phytochemicals have been identified as promising drug molecules against a variety of diseases using an in-silico approach. The current research uses this approach to identify the phyto-derived drugs from Andrographis paniculata (Burm. f.) Wall. ex Nees (AP) for the treatment of diphtheria. In the present study, 18 bioactive molecules from Andrographis paniculata (obtained from the PubChem database) were docked against the diphtheria toxin using the AutoDock vina tool. Visualization of the top four molecules with the best dockscore, namely bisandrographolide (?10.4), andrographiside (?9.5), isoandrographolide (?9.4), and neoandrographolide (?9.1), helps gain a better understanding of the molecular interactions. Further screening using molecular dynamics simulation studies led to the identification of bisandrographolide and andrographiside as hit compounds. Investigation of pharmacokinetic properties, mainly ADMET, along with Lipinskis rule and binding affinity considerations, narrowed down the search for a potent drug to bisandrographolide, which was the only molecule to be negative for AMES toxicity. Thus, further modification of this compound followed by in vitro and in vivo studies can be used to examine itseffectiveness against diphtheria. 2023 by the authors. -
In silico molecular docking study of Andrographis paniculata phytochemicals against TNF-? as a potent anti-rheumatoid drug
Tumor necrosis factor-? (TNF-?) is a proinflammatory cytokine which plays a crucial role in controlling inflammatory responses. The pathway of Rheumatoid arthritis (RA) leading to TNF-alpha is activated by macrophages and quite often by natural killer cells and lymphocytes. In the inflammatory phase, it is believed to be the main mediator and to be anchored with the progression of different diseases such as ankylosing spondylitis, Crohn's disease, and Rheumatoid arthritis (RA). The major goal of this study is to use in silico docking studies to investigate the anti-inflammatory potential of a bioactive molecule from the medicinal plant Andrographis paniculata. The three-dimensional structures of different phytochemicals of A. paniculata were obtained from PubChem database, and the receptor protein was derived from PDB database. Docking analysis was executed using AutoDock vina, and the binding energies were compared. Bisandrographolide A and Andrographidine C revealed the highest score of ?8.6 Kcal/mol, followed by, Neoandrographolide (?8.5 Kcal/mol). ADME and toxicity parameters were evaluated for these high scoring ligands and results showed that Andrographidine C could be a potent drug, whereas Neoandrographolide and Bisandrographolide A can be modified in invitro and can lead to a promising drug. Further, the top scorer (Andrographidine C) and control drug (Leflunomide) were subjected to 100 ns MD Simulation. The protein complex with Andrographidine C had more stable confirmation with lower RMSD (0.28 nm) and higher binding energy (?133.927 +/? 13.866 kJ/mol). In conclusion, Andrographidine C may be a potent surrogate to the disease-modifying anti-rheumatic drugs (DMARDs) & Non-steroidal anti-inflammatory drugs (NSAIDs) that has fewer or minor adverse effects and can aid in RA management. 2022 Informa UK Limited, trading as Taylor & Francis Group. -
In Silico Screening of Medicinal Plant-Derived Compounds Against Spodoptera litura
Spodoptera litura (Lepidoptera: Noctuidae) is a major agricultural pest in the Asia-Pacific region, causing significant crop damage. Current pest control strategies heav-ily rely on chemical pesticides, leading to environmental concerns and rapid resistance development. Molecular docking and molecular dynamics studies were used to investigate bio-compounds from three medicinal plants-Vitex negundo, Artemisia nilagirica, and Portulaca oleraceaas potential eco-friendly pest management al-ternatives. Gas chromatography-mass spectrometry (GC-MS) analysis identified 28 phytochemicals, of which 14 conformed to Lipinskis Rule of Five, which were selected as ligands. Molecular docking simulations were conducted to evaluate ligand interactions with four key target proteins in Spodoptera litura: acetylcholinesterase (AChE), carboxylesterase (CES), ecdysone receptor (EcR) and juvenile hormone (JH). Among the tested compounds, oxalic acid, 6-ethyloct-3-yl hexyl ester, and (11Z)-13-methyl-11-tetradecenyl acetate exhibited the highest binding affinities (-8.4 to-6.5 kcal/mol), suggesting their potential as inhibitory agents. Normal mode analysis (NMA) revealed low eigenvalues of the complexes, ranging from 9.6992260-5 to 3.0715890-4, indicating flexibility and requiring minimal energy for conformational changes. Deformability was highest in hinge regions, while var-iance analysis confirmed inverse proportionality across the complexes. The B-factor graph highlighted stable mobility and the root mean square (RMS) of the 3D con-former structures. Elastic network graphs displayed residue interactions as dots, with darker grey areas signifying greater stiffness. ADME/T analysis showed that these compounds possess favorable pharmacokinetic properties, including efficient ab-sorption and metabolism, while exhibiting no significant risks of mutagenicity or cardiotoxicity. These findings further support the suitability of Oxalic acid, 6-ethyloct-3-yl hexyl ester, and (11Z)-13-Methyl-11-tetradecenyl acetate as promising candidates for advancing sustainable and eco-friendly pest management approaches. Furthermore, the potential of identified plant-derived compounds as novel biopesti-cides contributes to sustainable and environmentally responsible pest management strategies. 2025, Brawijaya University. All rights reserved. -
In silico studies of viral protein inhibitors of Marburg virus using phytochemicals from Andrographis paniculata
The Marburg virus is a causative agent of Marburg hemorrhagic fever, which was discovered in Marburg, Germany, in 1967. It is a highly contagious and fatal disease transmitted by body fluids. The reservoir host is African fruit bats. Currently, there is no vaccine available to control this disease. Medicinal plants possess many phytochemicals of great therapeutic value. Many have antiviral properties and have been identified as promising drug molecules against various viral diseases proven with an in silico approach. The current research uses the in silico approach to identify the phyto-derived drugs from Andrographis paniculata to treat the Marburg virus. Twenty-four bioactive molecules from the A. paniculata plant were investigated against the targets VP35 and VP40 of Marburg viral proteins using the AutoDock Vina 1.1.2 tool. Out of 24 compounds, Andrographidine C, Andrographidine A, Andrographolactone, and 7-O-methylwogonin showed best docking scores for the target VP40 dimer while Bisandrographolide A, Luteolin Andrographolide, and Andrographiside showed best docking scores with VP35 protein. To determine the druglikeness, pharmacokinetic and pharmacodynamic properties and toxicity for each targets highest docking score compound was assessed using the Swiss absorption, distribution, metabolism, and excretion (ADME) and pkCSM tool. Andrographidine C and Andrographolide performed well in all the parameters of ADME and toxicity. These compounds are recommended as effective inhibitors of VP35 and VP40 of Marburg virus and potential antiviral drugs to treat the hemorrhagic disease. Furthermore, in vitro and in vivo studies can be used to examine the effectiveness and mode of action against the proteins of the Marburg virus. 2023 R. Hariprasath et al