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Quadratic convective flow of radiated nano-Jeffrey liquid subject to multiple convective conditions and Cattaneo-Christov double diffusion
A nonlinear flow of Jeffrey liquid with Cattaneo-Christov heat flux is investigated in the presence of nanoparticles. The features of thermophoretic and Brownian movement are retained. The effects of nonlinear radiation, magnetohydrodynamic (MHD), and convective conditions are accounted. The conversion of governing equations into ordinary differential equations is prepared via stretching transformations. The consequent equations are solved using the Runge-Kutta-Fehlberg (RKF) method. Impacts of physical constraints on the liquid velocity, the temperature, and the nanoparticle volume fraction are analyzed through graphical illustrations. It is established that the velocity of the liquid and its associated boundary layer width increase with the mixed convection parameter and the Deborah number. 2018, Shanghai University and Springer-Verlag GmbH Germany, part of Springer Nature. -
A comparative study of magnetite and MnZn ferrite nanoliquids flow inspired by nonlinear thermal radiation
The characteristics of the magnetohydrodynamic (MHD) stagnation point flow of ferrofluids are investigated. The effects of nonlinear thermal radiation, heat generation and viscous dissipation are considered. Two different nanoparticles (Fe3O4 and MnZnFe2O4) are comprised in the base fluid (water). The ordinary differential equations are formed using suitable similarity transformations from the governing partial differential equations. The subsequent nonlinear ordinary differential equations are solved numerically using RKF-45 method. The influence of governing parameters on the results are analysed. It is found that the thermal boundary layer thickens due to the influence of nonlinear radiation and heat generation for both the fluids. The rate of heat transfer is higher for MnZn ferrite-nanofluid in comparison with magnetite nanofluid. 2017 by American Scientific Publishers All rights reserved. -
Celebrity Endorsements in Fashion Purchases
This study investigates the impact of celebrity endorsements on consumer purchase intentions in the fashion apparel sector, focusing on three key variables: celebrity likeability, which is often aligned to cultural norms, and the celebrity familiarity. Information was obtained from 100 participants across India, and chi-square analysis was applied to the hypotheses. The analysis shows that all of these factors are significantly related to attitudes toward purchasing at a less than 0.05 level of significance. Four factors were determined to have significant impact with celebrity likeability coming out strongly to support the notion that consumers buy endorsed products to emulate the celebrity. Cultural fit adds consistency to trust and identity, and familiarity enhances recall, and confidence on the brands. In view of these observations, marketers ought to look at strategic celebrity selection more intensely. The endorser choice is highly recommended to be selected in accordance with the values and preferences of the target market to have the most influence on the buying decision. This paper reveals the need to adopt targeted and culturally appropriate appeals in influencing purchase behaviour in the Indian fashion domain. 2026 selection and editorial matter, Dr. Harold Andrew Patrick and Dr. Ravichandran Krishnamoorthy; individual chapters, the contributors. -
Synergizing digital learning with customer engagement in digital era
Specifically concentrating on the junction of digital learning and customer engagement, this research investigates the dynamic interplay between technology, education, and consumer relationships. The research demonstrates a symbiotic link between advances in one field and their favourable influence on the other through a thorough literature review and case studies. The findings show that increasing learning outcomes and fostering meaningful customer involvement may be achieved by combining customer engagement tactics with digital learning methodologies. According to the study's conclusion, firms must take advantage of this convergence to gain a competitive advantage. It highlights that digital learning and consumer involvement offer a substantial channel for innovation and growth. According to the report, for a complete user experience, customer engagement tactics should include digital learning tools. By illuminating this creative amalgamation, this chapter provides a novel outlook on the dynamic digital terrain, providing discernments into restructuring pedagogical approaches and augmenting customer engagements. 2025 Samriddha D. P., Thirupathi Manickam, Devarajanayaka Kalenahalli and Ravi V.. All rights reserved. -
Hybrid botnet detection using ensemble approach
Botnets are one of the most threatening cyber-attacks available today. This paper proposes a hybrid system which can effectively detect the presence of C&C, P2P and hybrid botnets in the network. The powerful machine learning algorithms like BayesNet, IBk, KStar, J48 and Random Tree have been deployed for detecting these malwares. The performance and accuracy of the individual classifiers are compared with the ensemble approach. Labelled dataset of botnet logs were collected from the Malware Facility. Secured data was collected from Christ university network and the combined dataset is tested using virtual test bed. The performance of the algorithms is studied in this paper. Ensemble approach out performed individual classifiers. 2005 ongoing JATIT & LLS. -
Differential Approach of Bioremediation by Sclerotium rolfsii Towards Textile Dye
Synthetic dyes are extensively used in various industries and are one of the major contaminants of industrial effluents. Dyes being xenobiotic, carcinogenic, and toxic there is need for their effective removal and detoxification to conserve water resources. Tremendous research has been carried out to identify potent microorganisms that facilitate bioremediation of these harmful dyes. A static batch culture has proved white rot fungi Sclerotium.rolfsii as an efficient catalyst in bioremediation of textile dyes and to compare their efficiency in decolourisation of two different azo dyes. Studies revealed the organism employ different remedial approach to cationic dye (Malachite green) and anionic dyes (Rose Bengal). Decolourisation of malachite green was a gradual with degradation and bio-transformation to colourless, non-toxic by products while Decolourisation of rose Bengal was quick process of biosorption. S.rolfsii exhibited 89% of decolourisation of malachite green dyes at higher concentration of 900mg/L while 96% for rose Bengal at 900mg/L. The mechanism of dye decolourisation was proposed using the UV Vis spectrophotometry, FTIR, XRD, HPLC and SEM. Microbial toxicity studies confirmed the dye metabolites of degraded malachite green was less toxic compared to original dye. Com- prehensively studies illustrate the sustained application of S. rolfsii as model organism for bioremediation of complex industrial effluents due to its differential bio remedial approach can potentially decolourise or remove various dyes. 2023, Association of Biotechnology and Pharmacy. All rights reserved. -
An algorithm for IoT based vehicle verification system using RFID
The verification of vehicle documents is an important role of transport department which is rising day by day due to the mass registration of the vehicles. An automated vehicle verification system can improve the efficiency of this process. In this paper, we propose an IOT based vehicle verification system using RFID technology. As a result, the vehicle checking which is done now manually can be replaced by automation. There is a loss of a significant amount of time when the normal vehicle checking is done manually. The proposed system will make this process automated. The present verification process is using inductive loops that are placed in a roadbed for detecting vehicles as they pass through the loop of the magnetic field. Similarly, the sensing devices spread along the road can detect passing vehicles through the Bluetooth mechanism. The fixed audio detection devices that can be used to identify the type of vehicles on the road. Other measurements are fixed cameras installed in specific points of roads for categorising the vehicles. But all these mechanisms cannot verify the documents and certificates of the vehicles. In our work, we have suggested an algorithm using RFID technology to automate the documentation verification process of the vehicles like Pollution, Insurance, Rc book etc with the help of RFID reader placed at road checking areas. This documents will be updated by the motor vehicle department at specific periods. Copyright 2019 Institute of Advanced Engineering and Science. All rights reserved. -
An Analysis of Grimms' Transmedia Storytelling in the Age of Technology
This research paper delves into an intersection of traditional literature and transmedia storytelling, with particular emphasis on Grimms' tales and its television series adaptation. Providing young audiences with engaging and dynamic experiences, transmedia storytelling involves delivering a single story across numerous platforms. Utilizing narrative analysis, this research seeks to uncover hidden themes, character growth, and story dynamics by breaking down the complex presentation and structure of stories in diverse media. Natural Language Processing (NLP) techniques like thematic analysis, sentiment analysis, keyword sentiment analysis have been employed to examine the differences between the presentation of these stories in varied formats as well as evaluating audience reception. It also assesses the degree to which transmedia adaptations support the resuscitation of beloved children's books in popular culture. By incorporating digital surrealism and aspects of technology, this paper enhances our understanding of how traditional stories captivate audiences across various media forms while maintaining their timeless quality. 2024 IEEE. -
A Textual Analysis of Panchatantra, Enhanced by Technology from the Psychological Perspective
This research paper offers a textual analysis of the portrayal of animals in the Panchatantra tales, leveraging technology, Natural Language Processing (NLP) for enhanced insights. The study focuses on the interplay of anthropomorphism and stereotypes within these narratives, delving into the diverse stereotypes associated with specific animals in the stories. This analysis enhances our understanding of animal portrayal in children's literature. Natural Language Processing (NLP) techniques like textual classification and thematic analysis have been employed to examine the underlying archetypes embedded within the tales to comprehend stereotypes. Through a close examination of literary examples employing AntConc, a corpus analysis software, this paper provides readers with a nuanced understanding of how anthropomorphism and stereotypes influence human perceptions of animals and contribute to our understanding of the natural world. 2024 IEEE. -
The total upper domatic number of a graph
Let G = (V, E) be a graph with no isolated vertices. For two disjoint subsets A and B of V , if every vertex in B is adjacent to at least one vertex in A, then the set A is said to dominate set B. A partition ? = {V1, V2, . . ., Vk} of the vertex set V is a total upper domatic partition of G if Vi dominates Vj or Vj dominates Vi or both, for any Vi, Vj ? ? and G[Vi], 1 ? i ? k, has no isolated vertices. The total upper domatic number Dt(G) of G is the maximum order of a total upper domatic partition of G. In this paper, we initiate a study on the concept of total upper domatic number and determine the bounds of Dt(G) and exact values of the same for some classes of graphs. World Scientific Publishing Company. -
Transitivity of trees
For a graph G = (V,E), a partition ? = (V1,V2,..,Vk) of the vertex set V is a transitive partition if Vi dominates Vj whenever i < j. The transitivity Tr(G) of a graph G is the maximum order of a transitive partition of V. For any positive integer k, we characterize the smallest tree with transitivity k and obtain an algorithm to determine the transitivity of any tree of finite order. 2022 World Scientific Publishing Company. -
Upper domatic number of regular graphs
A partition ? = {V1, V2, , Vk } of the vertex set V (G) of a graph G = (V, E) is an upper domatic partition if Vi dominates Vj or Vj dominates Vi or both for all Vi, Vj ? ?. The maximum order of an upper domatic partition of G is called the upper domatic number D(G) of G. In this article, we determine the upper domatic number of 4-regular graphs. We also find the upper domatic number of 5-regular graphs with girth at least five and determine the upper domatic number of the complements of cycles. 2021 the authors. -
The upper domatic number of powers of graphs
Let A and B be two disjoint subsets of the vertex set V of a graph G. The set A is said to dominate B, denoted by A ? B, if for every vertex u ? B there exists a vertex v ? A such that uv ? E(G). For any graph G, a partition ? = fV1; V2; : : : ; Vpg of the vertex set V is an upper domatic partition if Vi ? Vj or Vj ? Vi or both for every Vi; Vj ? ?, whenever i ? j. The upper domatic number D(G) is the maximum order of an upper domatic partition. In this paper, we study the upper domatic number of powers of graphs and examine the special case when power is 2. We also show that the upper domatic number of kth power of a graph can be viewed as its k-upper domatic number. 2021 Azarbaijan Shahid Madani University. -
New results on upper domatic number of graphs
For a graph G = (V, E), a partition ? = {V1, V2,..., Vk} of the vertex set V is an upper domatic partition if Vi dominates Vj or Vj dominates Vi or both for every Vi, Vj ? ?, whenever i 6= j. The upper domatic number D(G) is the maximum order of an upper domatic partition of G. We study the properties of upper domatic number and propose an upper bound in terms of clique number. Further, we discuss the upper domatic number of certain graph classes including unicyclic graphs and power graphs of paths and cycles. 2020 Azarbaijan Shahid Madani University -
Formulation and Characterization of Plant, Animal, and Probiotic Based Fish Meals and Evaluating their Efficacy on Growth and Performance in zebrafish (Danio rerio)
A comparative analysis on the effects of plant based (PD), animal based (AD) and probiotic based (PrD) diets on growth performance in Danio rerio was investigated. Different diets were administered as either single or combination diet (CD) containing PD, AD and PrD exhibited varying effects on growth and development. The probiotic bacteria isolated from Indian prawn (Penaeus indicus) was identified as Bacillus sp using 16s rRNA sequencing and phylogenetic analysis. The isolate was characterized by evaluating its ability to survive at different pH, temperature and simulated artificial gastric environment and was further subjected to varying concentrations of salt and organic solvents. Antibiofilm activity of the isolate was evaluated against fish pathogens; Vibrio harveyi (96.12.7%), Escherichia coli (96.21.5 %,), Pseudomonas aeruginosa (95.33.0%) and Staphylococcus aureus (96.72.8%). After the end of trail period, growth parameters were evaluated. Weight gain percentage was significantly higher in PrD (15.70.08 %) compared to other treatments. (p<0.05). Feed conversion ratio was least in CD (0.350.09) and feed efficiency (2.70.08) in CD was numerically high compared to other treatments. (p>0.05).The study promotes sustainable aquaculture by the use of alternative aqua feeds derived from plant or animal based sources. The study also highlights the usage of probiotics in improving growth performance, disease resistance in aquatic animals. 2021. Paari et al. -
Bacillus cereus-mediated biofermentation of Sardine offal waste: A novel approach to enhance nutritional value by Response Surface Methodology optimization
The rising protein demand in the aquaculture sector has significantly impacted fishmeal supply and pricing. Excessive use of fishmeal can lead to environmental issues and negatively impact marine biodiversity and human food security. Consequently, finding alternative fishmeal in aquaculture is crucial for economic and environmental sustainability. The present study aimed to determine how Bacillus cereus (MT355408) could enhance nutritional value of Sardine fish waste, which could replace fish meal in the market. Solid-state fermentation (SSF) represents a biotechnological method that utilizes microbes to convert discarded fish byproducts into valuable products. The bacterial ability to produce enzymes was studied and optimised for its maximum production to be used as an inoculum for the SSF technique. Different prebiotic sources were also studied for better upliftment of bacteria in the solid-state surface. A single-factor analysis was conducted to investigate the influence of varying prebiotic concentrations, inoculum quantity, and fermentation duration on protein breakdown. After studying the single-factor tests, a further response surface model was employed for better yield. The results indicated that the highest protein yield could be achieved with a fermentation time of 132.893 hours, a prebiotic quantity of 25%, and an inoculum quantity of 5.3%. The study's findings also affirmed that the model was vital in enhancing the crude protein content during fermentation. In conclusion, the model's results contribute valuable insights into fermentation processes, offering practical implications for enhancing protein content and digestibility in similar contexts. 2024, Applied and Natural Science Foundation. All rights reserved. -
The total upper domatic number of a graph
Let G = (V,E) be a graph with no isolated vertices. For two disjoint subsets A and B of V, if every vertex in B is adjacent to at least one vertex in A, then the set A is said to dominate set B. A partition ? = {V1,V2,,Vk} of the vertex set V is a total upper domatic partition of G if Vi dominates Vj or Vj dominates Vi or both, for any Vi,Vj ? ? and G[Vi], 1 ? i ? k, has no isolated vertices. The total upper domatic number Dt(G) of G is the maximum order of a total upper domatic partition of G. In this paper, we initiate a study on the concept of total upper domatic number and determine the bounds of Dt(G) and exact values of the same for some classes of graphs. 2025 World Scientific Publishing Company. -
AI Driven Air Quality Analysis for Health: An Experimental Review
Air pollution, both indoor and outdoor, was linked to 6.7 million premature deaths in 2020, including over 237,000 children under the age of 5, according to WHO. Indoor Air Pollution (IAP) is a crisis of public health that affects billions of people by exposing them to IAP pollutants like particulate matter (PM2.5), volatile organic compounds(VOCs), polycyclic aromatic hydrocarbons (PAHs), and carbon monoxide (CO). The most common cause of IAP varies from incense burning and biomass fuel to ventilation, leading to a horrific human health effect by causing respiratory disease, cardiovascular disease, sick building syndrome, and mental impairment. This review brings together evidence from various studies on the effects of indoor air quality on the environment, health, and productivity. Apart from pollutant exposure, determinants of well-being, i.e., thermal, acoustic, and visual comfort, are the subject of this article. Developments in artificial intelligence (AI), the Internet of Things (IoT), and computational modeling have revolutionized Indoor Air Quality monitoring to detect pollutants and exposures in real-time. All these technologies have the potential to intervene effectively but are intimidating through the prism of high cost, sensor calibration, and the need for large-scale epidemiological studies. To restrict indoor air pollution risks, inter-disciplinary studies need to be adopted to combine effective ventilation technologies and advanced pollutant control systems. Large-scale applications of clean fuel like solar, biogas, electricity, liquefied petroleum gas (LPG), and efficient biomass stoves need to be employed to restrict home air pollution. The present review calls for an emergent public campaign and policy intervention to enhance indoor air quality, health, and well-being. 2025 IEEE. -
An Accurate Multiple Data Based Stock Prediction and Sentiment Analysis Using Synergic Deep Info Convolutional Neural Network
Sentiment analysis is one of the most widely used methods for forecasting stock market action from consumer feedback. Most of the methods associated with sentiment analysis are limited due to low accuracy and enhanced error rate. This is addressed by proposing a synergic squeeze deep info convolutional neural network-advanced variable capsule equilibrium auto encoder (SSDCNN-AVCEAE) for sentiment analysis and accurate multiple data-based stock prediction. Stock market data from NSE Nifty 50 (Mar 2, 2020May 10, 2021) and real-time twitter sentiment analysis are pre-processed through data cleaning and sentiment analyzer lexicon processes. Merging features using SSDCNN, optimized with random search algorithm, mitigates overfitting. SSDCNN eliminates redundant features. Selected features undergo classification by AVCEAE, a fusion of advanced capsule auto encoder (ACAE) and variable equilibrium optimization algorithm, enhancing prediction accuracy for rising or falling stock market movements while minimizing errors. Variable equilibrium optimization refines ACAE parameters. The proposed framework demonstrates exceptional performance with F1-Score, accuracy, false alarm rate, sensitivity, precision, specificity, and error rate reaching 98%, 99%, 0.1%, 99%, 99%, and 0.2%, respectively. The measurements highlight the model's ability to handle a variety of issues, making it a reliable option for precise stock prediction. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.