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Study of magnetoconvection with maxwell cattaneo law
This thesis deals with the study of Rayleigh-Bard-convection in a Newtonian fluid and micropolar fluid by replacing the classical Fourier law by non-classical Maxwell-Cattaneo heat flux law. The effects of second sound, non-uniform basic temperature gradients, suctioninjection-combination, temperature modulation and gravity modulation in newlinepresence of external constraints like magnetic field and rotation are studied. newlineThe problems investigated in this thesis throw light on externally controlled convection in Newtonian and micropolar fluids in the presence of Maxwell-Cattaneo law. The problems investigated in this thesis deal newlinewith practical problems with very large heat fluxes and/or short time duration. With this motivation, we investigate in this thesis five problems and their summary is given below. (i) Effects of Coriolis force and non-uniform basic temperature gradients on the onset of Rayleigh-Bard-Chandrasekhar newlineconvection with Maxwell-Cattaneo law The effect of non-uniform temperature gradient on RayleighBard-Chandrasekhar convection in a rotating Newtonian fluid with Maxwell-Cattaneo law is studied using the Galerkin technique. The eigenvalues is obtained for free-free, rigid-free and rigid-rigid velocity boundary combinations with isothermal and adiabatic boundaries. A linear stability analysis is performed. The influence of various parameters on the onset of convection has been analyzed. One linear and five non-linear temperature profiles are considered and their comparative influence on onset is discussed. It is found that the results are noteworthy at short times and the critical eigenvalues are less than the classical ones. It is shown that the system having magnetic field will delay in the onset newlineof instability. In general, it is observed that step function and inverted parabolic temperature profile are the most destabilizing and stabilizing profiles. -
Influence of advertisements controversial element and emotional appeal on customer intention to buy
This paper studies the influence of an advertisements controversial element and emotional appeal on the customer intention to buy. The research paper is both exploratory and conclusive. S-O-R model was used for the study. Convenience sampling was used to draw a sample of 264 respondents. The data were tested for reliability, correlation and regression. The advertisements controversial element and emotional appeal significantly influence the customers intention to buy. The controversial element and the emotional appeal are positively correlated with the customer intention to buy. The research was done within a limited time and resources. The future research paper can include more moderators in the research model. The research paper provides a better understanding of the emotional appeal and the controversial element of an advertisement on customer intention to buy. 2025 Inderscience Enterprises Ltd. -
Maximised bioethanol extraction from bamboo biomass through alkali pretreatment and enzymatic saccharification by application of ANN-NSGA-II-based optimisation method
The demand for alternative fuels is growing due to the depletion of fossil fuel resources. Non-edible resources are explored as alternatives, and a bamboo is an up-and-coming option for producing ethanol. The extraction process for bioethanol from bamboo involves alkali pretreatment, enzymatic saccharification, and ethanol production. The bamboo biomass is treated with alkali at high temperatures and pressure. This treatment helps break the lignin bonds that hinder the reaction between cellulose and enzymes. As a result, the pretreated biomass contains 40% less lignin than its raw form. Next, the air-dried pretreated biomass undergoes saccharification using Supercut Acid Cellulose. The saccharification process is optimised to achieve the shortest possible time, determined through prediction models based on artificial neural networks and optimisation techniques like Non-dominated Sorting Genetic Algorithm-II. The optimised process involves specific biomass and enzyme loading, producing reducing sugars estimated using the DNS method. Following enzymatic Saccharification, the hydrolysate is fermented using Saccharomyces cerevisiae, a type of yeast. This fermentation process yields ethanol with a 1614.26mg/kg concentration. The Author(s), under exclusive licence to Springer Nature B.V. 2023. -
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Evaluating forces associated with sentient drivers over the purchase intention of organic food products
The study proposes to find out the factors which influence awareness among the consumers towards purchasing organic food product. The study is based on primary data by using tools Chi-square test, Cronbach alpha, KMO, and Bartlett's test, ANOVA, regression, correlation, and cross-tabulation. The study found that awareness driver's nutritional information, price, certification, brand name, and logos have an essential influence on the purchase intention of the product of organic food. However, labeling and food standards do not show a noteworthy rapport between labeling and organic food products' purchase plans. The core commitment and flow to explore are to analyze purchasers with respect to organic guarantee systems (accreditation, guidelines, logo, imprints, and confirmation) so we can distinguish the genuine organic products. The independent factors of awareness like organic buying preference and buying frequency, have a significant influence on the purchase intention of organic food. The research provided evidence of consumer awareness and purchase intention of organic food that would help the organic food industry to promote their products according to the attribute of customers. 2020 Asian Economic and Social Society. All rights reserved. -
Value co-creation through search efforts and customer involvement impacting purchase intention of smart phones
A marketing strategy which successfully involves its customer helps in stimulating purchase intentions. Understanding the behavioral aspects of customers become pertinent in formulating such strategies. The aim of this paper is to explore the underlying factors of customer involvement in value co-creation and discover how it affects the purchase intention of the customers towards smartphones. The study also tries to understand the contribution of search efforts towards customer involvement and how it affects purchase intention. The data for the study has been collected through a validated questionnaire from 233 respondents. Extensive literatures are reviewed to identify research gap and identify the variables for the study. The study can help marketers to identify the factors of customer involvement so that they can understand the customer purchase behaviour better and hence forecast on customer purchase intention to improve their sales of smartphones. BEIESP. -
Verification and validation of Parallel Support Vector Machine algorithm based on MapReduce Program model on Hadoop cluster
From the recent years the large volume of data is growing bigger and bigger. It is difficult to measure the total volume of structured and unstructured data that require machine-based systems and technologies in order to be fully analyzed. Efficient implementation techniques are the key to meeting the scalability and performance requirements entailed in such scientific data analysis. So for the same in this paper the Sequential Support Vector Machine in WEKA and various MapReduce Programs including Parallel Support Vector Machine on Hadoop cluster is analyzed and thus, in this way Algorithms are Verified and Validated on Hadoop Cluster using the Concept of MapReduce. In this paper, the performance of above applications has been shown with respect to execution time/training time and number of nodes. Experimental Results shows that as the number of nodes increases the execution time decreases. This experiment is basically a research study of above MapReduce applications. 2013 IEEE. -
Maximised bioethanol extraction from bamboo biomass through alkali pretreatment and enzymatic saccharification by application of ANN-NSGA-II-based optimisation method
The demand for alternative fuels is growing due to the depletion of fossil fuel resources. Non-edible resources are explored as alternatives, and a bamboo is an up-and-coming option for producing ethanol. The extraction process for bioethanol from bamboo involves alkali pretreatment, enzymatic saccharification, and ethanol production. The bamboo biomass is treated with alkali at high temperatures and pressure. This treatment helps break the lignin bonds that hinder the reaction between cellulose and enzymes. As a result, the pretreated biomass contains 40% less lignin than its raw form. Next, the air-dried pretreated biomass undergoes saccharification using Supercut Acid Cellulose. The saccharification process is optimised to achieve the shortest possible time, determined through prediction models based on artificial neural networks and optimisation techniques like Non-dominated Sorting Genetic Algorithm-II. The optimised process involves specific biomass and enzyme loading, producing reducing sugars estimated using the DNS method. Following enzymatic Saccharification, the hydrolysate is fermented using Saccharomyces cerevisiae, a type of yeast. This fermentation process yields ethanol with a 1614.26mg/kg concentration. 2023, The Author(s), under exclusive licence to Springer Nature B.V. -
Optimization of Biodiesel Production from Waste Cooking Oil by Box Behnken Design Using Response Surface Methodology
Interest in Biodiesel production has grown over the years due to concerns related to the environment, and the solutions include deriving energy from waste as the replacement for diesel, a petroleum-derived fuel. Biodiesel has been accepted as a "green fuel" as it is a renewable, non-toxic, safe and biodegradable energy material. The utilisation of waste cooking oil (WCO) by converting it into biodiesel is one of the promising alternatives to diesel. An attempt to optimise the biodiesel production from WCO (a waste material) has been made via this study. The process adopted was Trans-esterification of pretreated WCO, and the optimization of biodiesel production was carried out by Box-Behnken method using a response surface methodology. The variations between the analytical and experimental results were within acceptable limits. The response surface methodology resulted in an optimum yield of 96.88% (analytical), which was validated through an experiment within an acceptable error of 0.58%. 2021,International Journal Of Renewable Energy Research.All rights reserved. -
Effectiveness of information and communication technologies on the learning outcomes of management graduates in public and private sector institutes
In most of the countries, information and communication technology (ICT) has a made a strong impact on the development of educational sector and it is considered to be the strongest pedagogy in delivering the communication effectively. This is the era of Information and Communication and to increase the efficiency and effectiveness of Education sector the role of ICT is indispensable. The performance of the students can be made better with the help of information and communication technology (ICT). ICT will help the students to gather the information very effectively and help in in developing their knowledge skills as well as to improve their learning skills. To understand the effectiveness and also the impact of ICT in Education sector especially in management education, for the current study the data is been collected from 158 respondents who are MBA graduates from 15 B-schools from Bangalore city, the study is being conducted with the help of convenient sampling from various B-schools from Bangalore city. The study has shown that the learning and teaching through ICT improves the knowledge and learning skills of students. This indicates that existence of ICT is improving the educational efficiency among the management graduates in Bangalore city. 2019, Institute of Advanced Scientific Research, Inc. All rights reserved. -
The role of business development management consultants in construction industry in India
The Indian construction industry is in boom in terms of the growth and development taking place in the field of infrastructure and the service sector and subsequently many public owned design, architecture, construction and engineering companies were set up in India. The current study emphasises on the role of business development management consultants in the overall performance of construction companies and the existing review of literature focuses on the various factors which affects the overall business performance of the construction companies which includes different variables considering all the existing studies this study identified the gap in terms of intervention of BDMC in the construction field. The methodology adopted for the study is quantitative exploratory research and the results of the study was very positive that the promoters believe that the business development management consultants contribute a lot in the overall performance of the construction company with their expertise in the field and professional way of dealing with the other stake holders of the company helps them to perform very effectively and efficiently. This study helped in getting the practical exposure to the working of construction companies and understanding the role of business development management consultants. The Author(s) 2019. -
Customers satisfaction towards online banking services of public sector banks
At present the banking industry around the world has been undergoing a rapid transformation. The deepening of information technology has facilitated better tracking and fulfillment of commitments, multiple delivery channels for online customers and faster resolution of issues. Customer satisfaction is important criteria for banks sustenance, now banks are offers online banking services according to the customer needs and requirements. This study analysed customers satisfactions towards online banking services of public sector banks in Tiruchirappalli district. It is understand from the present study that bank websites and technology platforms has to offer various knowledge features on financial services. To retain the existing customers, banks has to conduct regular surveys on the customer satisfaction. The results of the study shows that variables like prompt response, security and Website design and ease of use are top three factors affected customer satisfaction. IJSTR 2020. -
High-speed portrait video segmentation using the hybrid combination of deep-learning models and boundary movement adjustment
As global warming intensifies, the development of energy-efficient Artificial Intelligence (AI) technologies has become crucial. Additionally, the growing demand for on-device AI in smartphones, extended reality devices, and autonomous vehicles necessitates AI systems that can function effectively on low-performance hardware. To address these needs, this study proposes hybrid methods in the field of Portrait Video Segmentation (PVS). Our proposed hybrid models leverage Deep-learning based Segmentation Models (DSMs) and a novel Boundary Movement Adjustment (BMA) process to achieve speed and accuracy balance. The Hybrid Serial Model (HSM) not only accelerates PVS but also improves energy efficiency while maintaining a similar level of accuracy. On the other hand, the Hybrid Parallel Model (HPM) enables high-performance PVS even on low-performance devices, ensuring no video frames are lost during high-speed segmentation processing. Tests conducted on Jetson Nano, Raspberry Pi, and a desktop PC demonstrate the effectiveness of these models, showing improvements in PVS speed while maintaining accuracy close to that of traditional DSMs. HSM increased PVS speed from 15.2 Frames Per Second (FPS) to 25.1 FPS on a desktop PC with a 0.5 % accuracy loss, and from 6.3 FPS to 16.5 FPS on a Jetson Nano with a 1 % loss. HPM reached 30 FPS on a desktop PC with a 0.05 % loss, and 29.7 FPS on a Jetson Nano with a 1 % loss. On the Raspberry Pi, the HPM method improved speed from 2.9 FPS to 29.8 FPS, demonstrating its adaptability for low-performance devices. 2025 Elsevier Ltd -
An in vitro slow-growth callus conservation strategy for several medicinal plants using response surface methodology and machine learning
Background: In vitro culture of callus is an effective method for conserving the genetic resources of economically important crops. However, continuous subculturing is a costly and labor-intensive process. Therefore, establishing an efficient in vitro long-term conservation system applicable to various plant species is required. In this study, calli derived from five medicinal plant species, Camellia japonica (Cj), Centella asiatica (Ca), Ligusticum afficinale (Lo), Panax ginseng (Pg), and Sageratia thea (St) were used to optimize storage conditions and establish a suitable in vitro conservation strategy. Calli cultures were maintained on the appropriate culture medium at 5C for 120 days. Cell viability and regrowth rate were assessed during the storage period, and correlations between growth and antioxidant traits were examined. Subsequently, pretreatment optimization using sucrose (39%), MeJA (0-200 M), and CTR (020mg/L) was performed using RSM, and the effects of pretreatment and storage temperature on callus conservation were evaluated. In addition, machine learning models such as GRNN, MLP, RF, SVR, and XGBoost were applied to the experimental data. Results: The findings demonstrated that, in comparison to Ca and St, Lo, Pg, and Cj exhibited noticeably higher antioxidant capacity while maintaining high cell viability and regrowth rates. Interestingly, Ca and St drastically decreased viability and regrowth after 60 days, whereas Lo, Pg, and Cj maintained viability and regeneration for up to 90 days. Both TPC and AC (measured by FRAP assay) showed a high positive correlation with cell viability and growth rate, according to correlation analysis. RSM predicted that the optimal pretreatment medium for enhancing antioxidant capacity was the species-specific proliferation medium supplemented with 3% sucrose, 135 M MeJA, and 20mg/L CTR, while the highest TSSC was achieved using the species-specific proliferation medium supplemented with 9% sucrose and 200 M MeJA. When the storage temperature was set to 15C following the antioxidant-enhancing pretreatment derived from the RSM optimization, all five species showed improved cell viability and regrowth rates, among the storage methods. Among the ML models tested, XGBoost demonstrated the most stable and accurate predictive performance for both viability and regrowth during in vitro conservation. SHAP-based analysis of the XGBoost model, focusing on regrowth rate, revealed that storage duration was the most influential factor affecting regrowth prediction, followed by storage temperature, while pretreatment conditions showed secondary but meaningful contributions. Conclusions: This study demonstrates that long-term callus conservation is closely associated with AC and TPC. Medium supplemented with sucrose 3%, 135 M MeJA, and 20mg/L CTR, followed by storage at 15C, significantly improved viability and regrowth, and calli could be maintained up to 120 days without subculturing. This approach provides an efficient and broadly applicable in vitro strategy for the conservation of diverse plant genetic resources. The Author(s) 2026. -
In vitro storage under slow growth, plant regeneration, and ex vitro acclimatization of Ligusticum officinale (Makino) Kitag
Ligusticum officinale is an important medicinal plant belonging to Apiaceae. It does not set seeds and is propagated by rhizome division. However, its sensitivity to high summer temperatures makes field cultivation and genetic resource conservation challenging. To conserve L. officinale germplasm, we employed an in vitro slow-growth storage (SGS) method. Shoot cultures of L. officinale were established on Murashige and Skoog medium supplemented with 1.0 mg/L benzyl adenine, 30 g/L sucrose, and 2.4 g/L gelrite. Cultures were kept for one, three, five, and seven months. The effects of storage temperatures of 25 C (control) versus 15 C, medium supplementation with or without mannitol (3%), and abscisic acid (ABA), 0.5 mg/L, were examined. At the conclusion of the conservation period, survival was measured right away. Four weeks later, the shoot proliferation medium was used to measure the regrowth rate and recovery features. Subsequently, the regenerated shoots were transferred to MS medium supplemented with 1.0 mg/L indole-3-butyric acid for rooting of shoots for 4 weeks. The findings showed that even after seven months, shoot cultures kept at 15 C with medium supplemented with 3% mannitol and 0.5 mg/L ABA maintained a good survival rate of 83.3%. When compared to the control, most growth indices, including shoot length, fresh weight, number of shoots, and number of leaves, were significantly suppressed by mannitol and ABA combined treatment. A regrowth rate of 71% was achieved after transfer to proliferation medium. All the shoots that were cultured on rooting medium involved in rooting and plantlets were successfully acclimatized in controlled conditions. 2026 SAAB. Published by Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies. -
Moral Identity, Moral Emotions and Maladaptive Personality Traits Among Adolescents in South Korea by Doo Jong Kim
The rule of survival of the fittest often thwarted the leap towards holistic development. How does morality associate with personality in adolescent development? Drawing on the theories of Augusto Blasi and Gordon Allport, the present study took a morality-personality integrative approach to adolescent development and viewed moral identity centrality as an agentic drive for their holistic growth. It aimed to determine whether moral identity centrality, other-praising moral emotion, and personality dysfunction of maladaptive personality traits are coherent in predicting antisocial behaviour in a sample of 436 Korean adolescents (M = 15.71 years, SD = .70; female 48.4%). The present study set up three hypotheses in the structural relationship of research variables (i.e., moral identity centrality, other-praising moral emotion, personality dysfunction of maladaptive personality traits and antisocial behaviour). Hypothesis 1: Personality dysfunction of multiple maladaptive personality traits predicts antisocial behaviour. Hypothesis 2: Other-praising moral emotion and personality dysfunction mediate moral identity centrality and antisocial behaviour. Hypothesis 3: Sex does not make notable differences in the structural relationship of research variables. The study analyzed the data mainly through structural equation modelling (SEM). As a result, all hypotheses were accepted. First, four multiple maladaptive traits, i.e., negative affectivity, antagonism, disinhibition, and psychoticism, significantly predicted adolescents antisocial behaviour (and#946; = .791, p lt .001) (Hypothesis 1). Second, the modified structural model showed a serial multiple mediation effect of other-praising moral emotion and personality dysfunction between moral identity centrality and antisocial behaviour (Hypothesis 2). Third, multi-group analyses showed apparent coherence among research variables regardless of sex (Hypothesis 3). -
Analyzing the Performance of Canny Edge Detection on Interpolated Images
Surveillance cameras are extensively used nowadays in many commercial and domestic places to monitor theft, intrusion and other illegal activities. Typically, the cameras are placed at a high position to monitor a large area. Therefore, the captured images include background area in addition to the target objects. Under such situation, the image can be zoomed to focus on the target objects using various interpolation techniques. For further processing of the image, many techniques like edge detection, image sampling and image thresholding etc. are available. Considering edge detection to be a basic step for many application such as Object detection, Object recognition etc, in this work, we analyze the performance of the Canny Edge Detection algorithm on images interpolated using Nearest Neighbour, Bilinear and Bicubic interpolation methods. Canny Edge Detection is applied to the input image and the resultant image is saved for later comparison. The same image is upscaled using interpolation and the Canny Edge Detection algorithm is used on this upscaled image. This image is then resized to the original image size. Both the images are compared to check for their similarity using the Structural Similarity Index Method (SSIM). 2019 IEEE. -
Accuracy Enhancement of Portrait Segmentation by Ensembling Deep Learning Models
Portrait segmentation is widely used as a preprocessing step in multiple applications. The accuracy of portrait segmentation models indicates its reliability. In recent times, portrait segmentation using deep learning models have achieved significant success in performance and accuracy. However, these portrait segmentation models are limited to a single model. In this paper, we propose ensemble approach using multiple portrait segmentation models to improve the segmentation accuracy. The result of experiment shows that the proposed ensemble approach produces better accuracy than individual models. Accuracy of single models and proposed ensemble approach were compared with Intersection over Union (IoU) metric and false prediction rate to evaluate the accuracy performance. The result shows reduced false negative rate and false discovery rate, this reduction in false prediction has enabled ensemble approach to produce segmented images with optimized error and improved result of segmentation in portrait area of human body than individual portrait segmentation models 2020 IEEE. -
A Study on the Effect of Canny Edge Detection on Downscaled Images
Abstract: Nowadays user devices such as phones, tablets etc. allows processing the images with help of high-end applications and softwares developed. Most of the times, the images are downscaled to make them compatible with these end devices. This leads to the loss of image quality. This loss of information on downscaling an image results in distortion of edges and while zoomed in results into a blurred image. As the edge detection is a basic step for many image processing applications such as object detection, object segmentation, object recognition, etc. It is necessary to know the impact of edge detection on downscaled image. In this paper, we are using Canny Edge detection method to detect the edges. The original images are downscaled using different interpolation methods. Canny Edge detection is applied on original images and downscaled images to compare the distortion in the edges. We used Structural Similarity Index Method for comparison. We are also comparing execution time taken by Canny Edge Detection on different interpolation methods to check for optimal interpolation method. We observed that the distortion in edges and time efficiency differ for different interpolation methods which are detailed below in the result section. As blurring is also a disadvantage of downscaling, we are applying Gaussian Blur on the images to compare the blurring due to Gaussian blur technique and blurring due to downscaling. 2020, Pleiades Publishing, Ltd. -
Selfie Segmentation in Video Using N-Frames Ensemble
Many camera apps and online video conference solutions support instant selfie segmentation or virtual background function for entertainment, aesthetic, privacy, and security reasons. A good number of studies show that Deep-Learning based segmentation model (DSM) is a reasonable choice for selfie segmentation, and the ensemble of multiple DSMs can improve the precision of the segmentation result. However, it is not fit well when we apply these approaches directly to the image segmentation in a video. This paper proposes an N-Frames (NF) ensemble approach for a selfie segmentation in a video using an ensemble of multiple DSMs to achieve a high-performance automatic segmentation. Unlike the N-Models (NM) ensemble which executes multiple DSMs at once for every single video frame, the proposed NF ensemble executes only one DSM upon a current video frame and combines segmentation results of previous frames to produce the final result. For the experiment, we use four state-of-the-art image segmentation models to make an ensemble. We evaluated the proposed approach using 81 videos dataset with a single-person view collected from publicly available websites. To measure the performance of segmentation models, Intersection over Union (IoU), IoU standard deviation, false prediction rate, Memory Efficiency Rate and Computing power Efficiency Rate parameters were considered. The average IoU values of the Two-Models NM ensemble, Two-Frames NF ensemble, Three-Models NM ensemble and Three-Frames NF ensemble were 95.1868%, 95.1253%, 95.3667% and 95.1734% each, whereas the average IoU value of single models was 92.9653%. The result shows that the proposed NF ensemble approach improves the accuracy of selfie segmentation by more than 2% on average. The result of cost efficiency measurement shows that the proposed method consumes less computing power like single models. 2021 IEEE.